DATA ASSESSMENT AND UTILIZATION FOR IMPRO VING ASSET MAN A GEMENT OF SMALL AND MEDIUM SIZE WATER UTILITIES b y A N D R E W W O O D B . A . S c , The U n i v e r s i t y o f B r i t i s h C o l u m b i a , 1987 M . E n g . , The U n i v e r s i t y o f B r i t i s h C o l u m b i a , 1998 A T H E S I S S U B M I T T E D I N P A R T I A L F U L F I L L M E N T O F T H E R E Q U I R E M E N T F O R T H E D E G R E E O F D O C T O R O F P H I L O S O P H Y i n T H E F A C U L T Y O F G R A D U A T E S T U D I E S ( C i v i l Engineer ing) T H E U N I V E R S I T Y O F B R I T I S H C O L U M B I A January 2007 © A n d r e w W o o d , 2007 A B S T R A C T D a t a regarding water m a i n breaks are essential for undertaking informed and effective infrastructure asset management. Th i s thesis reports o n the f indings o f a survey regarding water m a i n break data co l lec t ion practices across N o r t h A m e r i c a and develops an approach for constructing databases and integrating the data w i t h break predic t ion models to improve the asset management practices o f a ut i l i ty . The survey determines the amount and type o f data col lected b y water ut i l i t ies , the leve l o f comfort w i t h the amount o f data col lected and the ava i lab i l i ty o f alternate sources o f data. The responses p rov ide insight into the strategies and data co l l ec t ion practices o f sma l l to mid- s i ze uti l i t ies and show that the amount o f data col lected b y uti l i t ies can be class i f ied b y the degree o f data richness and defined as either an expanded, intermediate, l imi t ed or m i n i m a l data set. U t i l i t i e s can implement recommended practices to increase the amount o f data they col lect , increase effectiveness o f data co l l ec t ion and processing and consider addi t ional sources o f data for water m a i n breaks to improve their data sets. The thesis also introduces an approach for constructing a water m a i n break and general ne twork database that relates data from mul t ip le sources to augment the amount o f data avai lable for asset management analysis w h i l e main ta in ing exis t ing data warehousing practices. W h e n used, managers m a y gain insight into current and future performance o f the dis t r ibut ion network and develop future asset management strategies. The approach is f lexib le , uses c o m m o n l y avai lable software tools and anticipates the evolu t ion o f data co l lec t ion , ver i f ica t ion and storage capabil i t ies w i t h i n the ut i l i ty . F i n a l l y , a f ramework is presented that guides sma l l to m e d i u m water ut i l i t ies i n ident i fy ing k e y data to be used i n asset management and pipe break predic t ion m o d e l i n g i i and i n selecting appropriate water m a i n break predic t ion models . The framework m a y be used to identify the magni tude o f a uti l i ty 's pipe burst problems today and i n the future, enhance the development o f pipe replacement priori t ies based on forecasted breaks and identify k e y data to col lect i n future data acquis i t ion programs. Water ut i l i t ies w i t h va ry ing amounts o f data can easi ly implement it w i t h their exis t ing data management and analysis tools. i i i TABLE OF CONTENTS Abstract i i Table of contents i v List of tables . . . . . . . . v i i List of figures v i i i Acknowledgements x Co-authorship statement x i i 1 Introduction 1 1.1 B a c k g r o u n d 2 1.2 Thesis objectives and organizat ion 7 1.3 Asse t management 9 1.4 Pred ic t ing water m a i n breaks 13 1.5 Research methods 18 1.5 References 29 2 Assessment of water main break data for asset management 37 Preface 38 2.1 Introduction '. 40 2.2 D e s i g n o f the survey '• 42 2.3 Survey results 43 2.4 D i s c u s s i o n and recommendat ions 51 2.5 Conc lu s ions 56 2.6 Acknowledgemen t s 58 iv 2.7 References 59 3 Constructing water main break databases for asset management 75 Preface 76 3.1 Introduction 78 3.2 State o f data i n uti l i t ies .' 80 3.3 Water m a i n break data for asset management 81 3.4 Const ruc t ing water m a i n databases 84 3.5 A water m a i n break database for M a p l e R i d g e , B C 92 3.6 D i s c u s s i o n 98 3.7 Conc lu s ions 100 3.8 Acknowledgemen t s 102 3.9 References 103 4 Using water main break data to improve asset management for small and medium utilities 119 Preface , 120 4.1 Introduction 122 4.2 Water m a i n breaks 123 4.3 A framework for us ing predic t ion models to improve asset management 128 4.4 Break predic t ion models for L a i t y V i e w , M a p l e R i d g e , B C 132 4.5 Conc lus ions 139 4.6 A c k n o w ledgem ents 140 v 4.7 R e f e r e n c e s . . . 141 5 Conclusions and recommendations 153 5.1 S u m m a r y o f research goals . .154 5.2 Conc lus ions 155 5.3 Observations 157 5.4 C l o s i n g remarks 165 References 167 Appendices 179 A p p e n d i x A C o m p a r i s o n o f survey questions for D e b et al. (2002) and W o o d and Lence (2006) '. 179 A p p e n d i x B Statistical analysis for guiding the interpretation o f survey results 183 A p p e n d i x C Desc r ip t ion o f M a p l e R i d g e water system 187 A p p e n d i x D Water m a i n break survey form 193 A p p e n d i x E L i s t o f organizations that were sent a c o p y o f the water m a i n break survey 203 A p p e n d i x F Survey responses 215 A p p e n d i x G Water m a i n break and system data and statistics o f models 393 A p p e n d i x H Degree o f accuracy o f predict ions for p ipe groups 437 v i LIST OF TABLES i Table 2.1 Service popula t ion o f respondents 62 Table 2.2 Percentage o f respondents that record loca t ion data 63_ Table 2.3 A d d i t i o n a l sources o f break-related phys ica l data for respondents .64 Table 2.4 Suggested sources and approaches for co l lec t ing phys i ca l data on water m a i n breaks 66 Table 3.1 Water m a i n break data ava i lab i l i ty for M a p l e R i d g e 107 Table 3.2 Water m a i n breaks for a g iven year o f instal la t ion 109 Tab le 3.3 P ipe breaks for pipes o f a g iven diameter (1983-1999) 110 Table 4.1 T y p i c a l data used i n models and factors for w h i c h they are a surrogate 146 v i i LIST O F FIGURES Figure 1.1 Twenty-year total per household infrastructure cost estimates for different s ized water systems 36 F igure 2.1 Percentage o f respondents that col lect general informat ion ..68 F igure 2.2 Percentage o f respondents that record phys i ca l data 69 F igure 2.3 Percentage o f respondents that record failure causes 70 F igure 2.4 Percentage o f respondents that record repair activit ies 71 F igure 2.5 Percentage o f respondents that col lect different types o f environmental data : 72 F igure 2.6 Percentage o f respondents that expressed confidence i n data col lec ted 73 F igure 2.7 Classes o f data richness among water ut i l i t ies 74 F igure 3.1 A schematic for constructing and us ing water m a i n break data for knowledge d iscovery I l l F igure 3.2 A process for d ig i t i z ing and creating data f rom arch iva l geographical data 112 F igure 3.3 L i n k i n g hydrau l ic m o d e l data w i t h network data 113 F igure 3.4 Buf fe r ing data to create data relationships us ing G I S 114 F igure 3.5 M a p l e R i d g e water m a i n break analysis data web 115 F igure 3.6 C u m u l a t i v e breaks i n L a i t y v i e w area: 1983-1999 116 F igure 3.7 N u m b e r o f years i n service w h e n break occurred i n pipes (1983-1999) 117 F igure 3.8 N u m b e r o f breaks for pipes i n a g iven so i l type instal la t ion (1983-1999) 118 v i i i Figure 4.1 Improv ing asset management us ing pipe break predic t ion models 147 F igure 4.2 Degree o f accuracy o f t ime-l inear and t ime-exponent ia l predict ions for mater ial groups 148 F igure 4.3 Degree o f accuracy o f t ime-l inear and t ime-exponent ia l predict ions for material and diameter groups 149 F igure 4.4 Degree o f accuracy o f t ime-l inear and t ime-exponent ia l predict ions for material , diameter and age groups 150 F igure 4.5 Degree o f accuracy o f t ime-l inear and t ime-exponent ia l predict ions for material , diameter, so i l and age groups 151 F igure 4.6 Degree o f accuracy o f t ime-l inear and t ime-exponent ial predict ions for material , diameter, age and surface mater ial groups 152 i x A C K N O W L E D G E M E N T S I be l ieve that beh ind any w o r k are people and events that supported, inf luenced and shaped it and this is indeed true for m y thesis adventure and journey. ' I a m grateful to Barbara Lence , m y academic supervisor w h o encouraged and supported m y ideas and work , gave me important advice and was patient throughout m y program. Y o u demonstrated b y many long hours, a dedicat ion to mentor ing and I thank y o u for that and for ign i t ing m y passion for research, academia and success. M y other commit tee members w h o mentored and gave me t imely , succinct, gracious and k i n d advice and guidance were A l a n R u s s e l l and J i m Atwater . M y journey was successful because y o u pointed out or ro l l ed stones for me to step on as I crossed the doctoral r iver . Thank y o u for insp i r ing me to connect work , research and c o m m u n i t y service. I can say o f m y supervisory committee, as Isaac N e w t o n penned, " I f I have seen further it is b y standing o n the shoulders o f giants." M y f a m i l y has been instrumental , b y caring, p ray ing and encouraging throughout the journey. Cla re , I c o u l d not have done this without your endless support, patience and be l i e f i n me. I love you . Y o u shared the weight o f the studies i n so many ways and also freed m e to journey through un imagined waters. M a r k and Ju l i a , w h o have o n l y k n o w n their father as a graduate student, hav ing y o u both a long w i t h me has been a j o y , and I a m truly blessed. I have also been supported b y m y mother, Be t ty b y her steadfast prayers and confident and patient hope. I am grateful for the support o f m y employers , M a p l e R i d g e and C o q u i t l a m w h o tasked and then entrusted me w i t h the quest o f i m p r o v i n g their asset management practices. x I trust that this w o r k w i l l support their efforts to sustain their water infrastructure, protect pub l i c health and support their loca l economy. F i n a l l y , I have had the pleasure o f w o r k i n g w i t h m a n y colleagues and fe l low practitioners. O f these, I w i s h to spec i f ica l ly acknowledge W i l s o n L i u . x i CO-AUTHORSHIP S T A T E M E N T Andrew Wood was the lead and principal researcher of the work contained in the thesis titled "Data Assessment and Utilization for Improving Asset Management of Small and Medium Size Water Utilities". Dr. Barbara Lence, the Research Supervisor of the thesis, provided inspiration and supported the writing of the papers and Wilson Liu assisted with the preparation of figures used in the paper submitted as Chapter 3. xii C H A P T E R 1 INTRODUCTION 1.1 B A C K G R O U N D Rel i ab le , efficient and effective water dis t r ibut ion systems are c ruc ia l to pub l i c health and safety. These systems are also essential to the economic we l l -be ing o f m a n y munic ipa l i t i es since manufacturing, industry and commerce re ly to a large degree on obta ining rel iable and economica l ly -p r iced water del ivered through a network o f water pipe l ines, more c o m m o n l y referred to as Water mains . M a n y o f these water mains instal led over the decades i n N o r t h A m e r i c a are n o w beg inn ing to break and fa i l . The tradit ional pub l i c works emphasis on managing water m a i n breaks has been directed toward m i n i m i z i n g the loss o f water to k e y businesses and cr i t ica l facil i t ies and the damage to bui l t and natural infrastructure. H o w e v e r , breaks are also potential gateways to contaminat ion o f the water dis t r ibut ion system ( A W W A and E E S , 2002) and are identif ied as a h igh pr ior i ty i n the assessment o f water supply health r isks b y the N a t i o n a l Research C o u n c i l o f A c a d e m y Sciences (2005). B y replac ing the pipes just before they fa i l , ut i l i t ies reduce their r isks and costs o f water m a i n breaks. T h i s thesis is focused on he lp ing smal l and m e d i u m size uti l i t ies b y p r o v i d i n g informat ion o n water m a i n break data co l lec t ion , construct ion, compi la t ion , and management i n support o f asset management. The research presented includes an approach for these uti l i t ies to use water m a i n break predic t ion models o n a p ipe b y pipe basis for p r io r i t i z ing the replac ing o f water mains. The w o r k is presented as a series o f three manuscripts that are publ i shed i n peer-reviewed journals or are i n the process o f be ing peer-reviewed. W h e n I embarked on this research program m y goal was to assist sma l l and m e d i u m size uti l i t ies w i t h managing their pipe networks to address the r isks arid costs associated w i t h replac ing water mains . Spec i f i ca l ly , I wanted to assist them w i t h ident i fying, 2 . co l lec t ing and construct ing relevant pipe break data to analyze their p ipe network, p r io r i t i z ing their water m a i n replacements b y us ing break predict ions and gu id ing their data acquis i t ion and analysis programs. D u r i n g m y almost twenty years o f experience as a professional engineer i n pub l i c ut i l i t ies I observed that m y colleagues i n other ut i l i t ies were not us ing break predic t ion models i n their practice. W i t h i n the organizations w i t h w h i c h I was famil iar , co l l ec t ion o f water m a i n break data was undertaken o n an ad-hoc basis and storage o f such informat ion was not t yp i ca l ly comprehensive. A m o n g those uti l i t ies, there were no c o m m o n practices or standards for data co l l ec t ion and ve ry few uti l i t ies , i f any, were aware o f the data col lected b y other uti l i t ies. Bes t practices for Canad ian water uti l i t ies regarding w h i c h data to col lect were introduced i n 2002 ( N S G M I , 2002). A s a manager, I also wanted to compare the informat ion I was co l l ec t ing w i t h that o f other ut i l i t ies , to understand h o w data were in fo rming us and to share this knowledge w i t h m y colleagues. D u r i n g this t ime, I also became aware o f the general b e l i e f he ld b y m a n y u t i l i ty managers that asset management is a panacea for s o l v i n g our ag ing water system problems. W e needed to k n o w when , where and h o w m a n y pipes to replace; but w e were focusing on the entire network, not on specific pipes, to obtain funding for programs. I found that among m y colleagues, once funding was obtained, decisions o n p r io r i t i z ing pipe replacements were based o n his tor ica l data, experiences and management po l ic ies rather than o n the expected performance o f specif ic pipes though there are models for predic t ing water m a i n breaks. In fact, many o f m y colleagues were not aware o f these models and none, i f any, were us ing them. Thus , I was conv inced that w e needed an approach that appl ied pipe break models to in fo rm our decisions regarding the pr ior i t iza t ion and schedul ing o f specif ic pipe replacements. 3 A s a result o f m y observations, m y thesis identifies data that are col lected and avai lable for analysis across uti l i t ies i n N o r t h A m e r i c a , develops a methodology for creating and l i n k i n g data across various data sources and develops a f ramework for assisting i n the pr ior i t i za t ion o f water m a i n replacements and data acquis i t ion based on predict ions o f future water m a i n breaks w i t h i n a g iven water dis t r ibut ion system. The framework m a y be appl ied across the range o f data avai lable i n typ ica l water ut i l i t ies, acknowledges exis t ing industry needs and practices and W i l l help managers identify and use k e y avai lable break data. Our water mains are aging and failing. The water mains o f m a n y munic ipa l i t i es are predominant ly o f the 1960s to 1990s vintage because o f extensive urban development dur ing those years, w i t h some smaller amounts pr ior to that per iod. H o w e v e r , the replacement needs o f aging pub l i c works infrastructure has become the focus o f governmental and academic attention i n recent years. Because few water ut i l i t ies have ac t ive ly pursued aggressive water m a i n rehabil i ta t ion or replacement programs, they are n o w facing the p rob lem o f replac ing or rehabil i tat ing their aging systems (Deb et al., 2002). The U n i t e d States Env i ronmen ta l Protect ion A g e n c y ( U S E P A ) identifies that w h i l e U n i t e d States ( U S ) communi t ies spent one t r i l l i o n U S dollars i n 2001 o n d r ink ing water treatment, supply and waste water treatment and disposal , this expenditure l eve l m a y not be sufficient to keep pace w i t h future infrastructure needs ( U S E P A , 2002). T h e y also identify i n a 2003 survey that the 53,000 c o m m u n i t y water systems and 21,400 not-for-profit non-communi ty water systems i n the U S w i l l need an estimated $276.8 b i l l i o n to continue to p rov ide their services ( U S E P A , 2005). S i m i l a r l y , the Ontar io M i n i s t r y o f P u b l i c Infrastructure R e n e w a l (PIR) identifies that over the next 15 years, $25 b i l l i o n w i l l be needed for capital renewal o f Ontario 's $72 b i l l i o n water and waste water assets (Ontario P I R , 2005). The Federat ion o f 4 Canadian M u n i c i p a l i t i e s ( F C M ) state that k e y investments must be made i n core pub l i c infrastructure to manage waste and water systems, to meet pressing environmental and air qual i ty needs and to main ta in the economic health o f Canada's communi t ies ( F C M , 2001). G i v e n the current l eve l o f expenditures and the increasing age o f systems, ut i l i t ies need to predict breaks and use this informat ion to pr ior i t ize and p lan w h e n pipes should be replaced. The ab i l i ty to respond to the challenge o f k n o w i n g w h e n to replace a p ipe varies among water ut i l i t ies . S m a l l to m e d i u m size uti l i t ies m a y f ind it par t icular ly cha l lenging due to their l imi t ed resources and technical capaci ty and there are m a n y o f these ut i l i t ies across N o r t h A m e r i c a . In the U S , smal l water systems make up 90 percent o f those 53,000 c o m m u n i t y water systems ( A m e r i c a n Socie ty o f C i v i l Engineers , A S C E , 1999). N o analogous data exist for Canada, al though the Canad ian N a t i o n a l Research C o u n c i l ( C N R C ) identifies that there are 3500 munic ipa l i t ies serving fewer than 5000 people and that there are o n l y 63 munic ipa l i t i es serving populat ions greater than 100,000 (Van ie r and R a h m a n , 2004). M o s t sma l l to m e d i u m size water uti l i t ies and munic ipa l i t i es share s imi la r characteristics. T h e y purchase bu lk water f rom a regional or larger supplier and require some treatment. The treatment processes are s imple processes such as ozonat ion, ultra-viole t ( U V ) or chlor ine dis infect ion. S m a l l u t i l i ty systems are t yp i ca l l y compr ised o f smal l diameter pipes and.as noted b y Ket t le r and Goul te r (1985), smal ler pipes break have been observed to break more frequently than larger ones. T h i s m a y be because their beam strength and w a l l thickness are general ly less than those o f larger pipes. 5 Smal le r ut i l i t ies have scarce resources and technical expertise is t yp i ca l l y riot avai lable because staff are general ly expected to undertake a number o f different functions and do not have the luxury o f deve lop ing in-house expertise. C o m p o u n d i n g this is the fact that w i t h i n these systems, there is lit t le or no rel iable documentat ion o f the locat ion, capacity, cond i t ion and adequacy o f p ipe network elements for meet ing present or future needs ( M y e r s , 2001). These uti l i t ies m a y also lack the resources, f inanc ia l ly and organizat ional ly , to implement a complex informat ion management system program, nor the h is tor ica l data or tools to fu l ly analyze their system. T h e y require capital to rehabilitate, upgrade and instal l infrastructure, but face an economic challenge i n pay ing for these costs g iven a smal l revenue base. F o r example, al though the costs o f a sma l l water system m a y be modest compared w i t h those o f large systems, the per household costs are s igni f icant ly higher than those o f larger systems ( U S E P A , 2001). The data shown i n F igure 1.1 are the per household costs for different s ized water systems for meet ing anticipated needs. These data show that households i n smal l systems face costs that are over three and one h a l f t imes those o f households serviced b y large systems. Ut i l i t i e s are v i e w i n g asset management as an approach for addressing this d i l e m m a o f p lann ing pipe replacements b y understanding h o w m u c h rehabil i ta t ion w i l l cost, what to do first and w h e n to rehabilitate their systems. Asse t management is a business administrat ion approach to dec i s ion-making that covers an extended t ime hor i zon , draws from economics as w e l l as engineering science and considers a broad range o f assets. The approach incorporates the economic assessment o f alternative investment options and uses this information, to help make cost-effective investment decisions (Uni ted States Federal H i g h w a y Admin i s t r a t ion , U S F H W A , 1999). The benefits o f app ly ing an asset management 6 approach inc lude the ab i l i ty to l i n k user expectations and needs and to identify the means o f assessing value, system condi t ion , performance, service l ife and management and investment strategies. H o w e v e r , for smaller uti l i t ies to adopt asset management, they need portable, read i ly useable approaches that require l i t t le modi f ica t ion , are l i k e l y to be met w i t h litt le organizat ional resistance and serve to incrementa l ly improve water m a i n replacement analysis and planning. The need for p lann ing is urgent and the need to improve the p lann ing approaches w i l l o n l y increase w i t h t ime. 1.2 THESIS O B J E C T I V E S AND O R G A N I Z A T I O N T h i s thesis: • assesses the state o f data avai lable to smal l arid m e d i u m size water ut i l i t ies , • develops an approach for constructing and c o m p i l i n g water m a i n break data for analysis and • develops a f ramework that guides the ident i f icat ion o f k e y data for asset management and the select ion o f the most appropriate data and models for predic t ing water m a i n breaks. Organization of thesis. The thesis is presented as a series o f three manuscripts that are publ i shed i n peer-reviewed journals or are i n the process o f be ing publ i shed or peer-reviewed. E a c h o f the three manuscript chapters (Chapters 2 to 4) contains a preface, introduct ion, ove rv i ew o f the literature, body, conc lus ion and references. Tables and figures referenced i n each chapter are inc luded at the end o f that chapter and a l l appendices are p rov ided at the end o f the thesis. F i n a l l y , Chapter 5 summarizes the major conclus ions o f this work . 7 There are m a n y benefits o f a manuscript-based thesis over the tradit ional thesis and the p r imary benefit is that research f indings are publ i shed and shared w i t h the research commun i ty m u c h earlier than i n the product ion o f a tradit ional thesis. H o w e v e r , there are also significant disadvantages. Literature reviews are often repeated, some cont inui ty is lost and m u c h o f the data, results, and observations that w o u l d be i n a t radit ional thesis are condensed or e l iminated. T h i s results i n an abbreviated thesis and a percept ion b y the reader o f a lesser effort than was the case i n the research. T h i s thesis attempts to address these l imita t ions b y i nc lud ing a section i n this chapter on the approach, methodology and context o f the research. E a c h chapter preface provides the context for the w o r k presented i n that chapter (paper) w i t h respect to the overa l l research and thesis and the preceding chapter. D a t a not p rov ided i n the papers are also inc luded i n the appendices. Chapter 2 provides the results o f a survey that investigates the state o f data co l lec t ion practices, the c o m m o n l y avai lable water m a i n break data and the data sources w i t h i n N o r t h A m e r i c a n water uti l i t ies. The paper was publ i shed i n the J u l y 2006 issue o f the Journal o f the A W W A . A compar ison o f the survey questions and those o f D e b et al. (2002) is presented i n A p p e n d i x A . Chapter 3 presents an approach for b u i l d i n g and relat ing data from various sources for analysis, based on observations d rawn from the survey responses reported i n Chapter 2. Th i s w o r k demonstrates h o w to construct water m a i n data and databases w h i c h are based on l i n k i n g , relat ing, extracting and c o m p i l i n g data f rom sources internal and external to a u t i l i ty for the purpose o f analysis, or i n other words relating relational databases. Issues related to creating, l i n k i n g , t ransforming, cleansing, scrubbing and integrating data are identif ied and approaches for addressing them are presented. A number o f databases were created i n this por t ion o f the research. These are summar ized i n A p p e n d i x G . T h i s paper 8 was submitted to the Journal o f the A W W A i n February 2006, revised i n October 2006 and is scheduled for pub l ica t ion i n January 2007. Chapter 4 develops a framework that guides uti l i t ies i n ident i fy ing k e y data to be used i n asset management i n general and spec i f ica l ly i n pipe break predic t ion mode l ing and i n selecting the most appropriate mode l for predic t ing water m a i n breaks. It provides the u t i l i ty w i t h a method for consider ing future p ipe breaks i n the analysis o f p ipe pr ior i t iza t ion strategies. It incorporates exis t ing tools for data management and analysis that are w i d e l y avai lable and easy to implement b y smal l to m e d i u m size uti l i t ies w i t h va ry ing amounts o f data. T h i s paper was submitted to the A S C E Journal o f Infrastructure Systems i n Ju ly , 2006. The fifth and f inal chapter summarizes the conclus ions o f and discussions ar is ing from the research. A d iscuss ion o f future research is also presented. 1.3 ASSET M A N A G E M E N T S i x components o f an asset management p rogram have been suggested (Vanie r , 2001). These are inventory, asset value, deferred maintenance, condi t ion , service l ife predic t ion, and pr ior i t iza t ion o f rehabil i tat ion, replacement and renewal . Inventory. The first b u i l d i n g b l o c k o f asset management is to determine the type, compos i t ion , quantity and extent o f the assets. The p r imary capi tal assets that typ ica l water ut i l i t ies o w n inc lude water supply reservoirs, dams and support ing hydrau l ic structures, water treatment plants, water dis t r ibut ion systems inc lud ing pipes, valves , fire hydrants, d is t r ibut ion reservoirs, pump stations, pressure reducing valves and meters to measure distributed and purchased water. U t i l i t i e s are t yp i ca l ly main ta in ing inventories us ing tools such as Geographic Information Systems (GISs) , Compute r A i d e d Draf t ing ( C A D ) systems and relat ional databases. These systems require significant effort and resources to P implement and mainta in but for smal l systems, a s imple spreadsheet m a y be a l l that is required. W o o d and Lence (2G06) found that a rchiva l records are s t i l l the predominant sources o f data for ut i l i t ies that serve populat ions fewer than 50,000. In recent years, the use o f Compute r i zed Main tenance Management Systems ( C M M S s ) has also g r o w n i n popular i ty and these systems usua l ly interface w i t h or use G I S data. These systems are expensive to implement and require significant resources to mainta in . M a n y uti l i t ies s t i l l do not have C M M S s . Asset value. T o p lan for replacement, water u t i l i ty managers must k n o w the total value o f their assets. Managers must have a basic understanding o f system wor th and h o w m u c h is required to replace it. A c c o r d i n g to V a n i e r (2001), the s ix c o m m o n l y used terms to describe asset value are his tor ical , appreciated his tor ical , capital replacement, performance-in-use, depr iva l cost and market value. H i s t o r i c a l value is defined as the or ig ina l or book value, appreciated h is tor ica l value is the his tor ica l value calculated i n current dollars and capital replacement value is the cost o f the asset i n current dol lars . The performance-in-use value is the prescribed value o f the actual asset to the user. D e p r i v a l cost is the cost that w o u l d be incurred i f depr ived o f the asset but s t i l l required to de l iver the service. F i n a l l y , market value is the value i f the asset is so ld on the open market. U t i l i t i e s m a y not use a l l o f these values. F e w munic ipa l i t i es have specific asset values. In most cases, ut i l i t ies inherit their new infrastructure from developers who instal l it as part o f a hous ing subd iv i s ion and then transfer the ownership and maintenance o f the assets to the munic ipa l i ty . O n l y the book value o f the assets constructed di rect ly b y the mun ic ipa l i t y is t yp i ca l ly recorded. F o r many uti l i t ies , the value o f their assets are s i m p l y calculated b y m u l t i p l y i n g an average cost o f construct ion per metre o f p ipe b y the total length o f the network. Condition. Asse t management requires knowledge o f the cond i t ion o f the assets. In the past, a significant amount o f data were captured for evaluat ing operational values and objectives and a s imple spreadsheet was used to record these data. In recent years, C M M S have been used to warehouse and process informat ion and the management o f maintenance act iv i ty p lanning . H o w e v e r , asset managers face the p rob lem o f determining h o w and what to evaluate, o f def in ing what constitutes condi t ion and indices , o f p r o v i d i n g for data storage and o f determining h o w to use condi t ion data. N o t o n l y are there are no standard cond i t ion indices for water mains ( G r i g g , 2004) , but the challenge for m a n y water ut i l i t ies is that condi t ion assessments have to be on-going. T h e y can be cost ly and o n l y p rov ide informat ion for that asset at a specific t ime. There is also a need for a significant improvement i n the level o f accuracy i n p ipe l ine condi t ion assessment and accurate predic t ion o f p ipe l ine failures ( D e S i l v a et al, 2002). Deferred maintenance. Deferred maintenance is maintenance that has not been performed or has been deferred. F o r ut i l i t ies , managing deferred u t i l i ty maintenance requires ident i fy ing and managing the maintenance that is to be deferred and the compound ing effect o f maintenance that has not been performed such as not c leaning or repair ing water mains. The challenge for water u t i l i ty asset management l ies i n managing and integrating the amount o f deferred maintenance between the various components that make up a system w i t h the subjective nature o f h o w a maintenance b a c k l o g is calculated. F o r example, most pipe networks are segmented and o f differ ing age, condi t ion , value and consequence o f failure. De te rmin ing quanti tat ively the maintenance b a c k l o g o f that 11 network is ve ry dif f icul t wi thout accounting for reservoirs, pump stations and other assets. Thus there is ve ry litt le informat ion regarding deferred maintenance o f water dis t r ibut ion systems and few i f any munic ipa l i t ies can determine their deferred maintenance. Remaining service life. M a n a g i n g water u t i l i ty assets and p lann ing replacement requires estimates o f technical and economic service l i fe . Asse t managers face funding constraints and compet ing needs, thus op t im iz ing the expenditures f rom technical and economic perspectives is important. W h i l e technical l i fe m a y be diff icul t to predict, determining economic service l ife is m u c h s impler since it compares the immediate costs o f repairs w i t h the costs o f renewal . So the question that is often raised as part o f the understanding and analysis o f p ipe deterioration is w h e n does a p ipe reach the end o f its useful l ife? One def ini t ion o f w h e n a pipe reaches the end o f its useful l i fe is w h e n the pipe is replaced b y a ut i l i ty . T h i s can be mis lead ing since a u t i l i ty ' s dec i s ion to replace a p ipe m a y be based o n other factors such as po l i t i ca l choice , perception o f the re l i ab i l i ty o f the p ipe or the need to increase the hydraul ic capacity o f the pipe. Rajan i and M a k a r (2000) define the t ime o f death o f a pipe as the t ime at w h i c h its mechanica l factor o f safety falls b e l o w an acceptable value set b y the ut i l i ty . K l e i n e r and Rajani (1999) propose that the useful l i fe o f a p ipe is a function o f the economic costs o f deterioration rate and replacement and suggest that p ipe death coincides w i t h the op t imal t ime o f replacement. Statistics Canada defines the service l ife o f an asset as its useful l i fe at the t ime o f its acquis i t ion w h i c h general ly ends at demol i t ion (Statistics Canada, 2006). A c c o r d i n g to D e b et al. (1998), there are no standardized methods for predic t ing the l ife o f dis tr ibut ion systems. 12 Prioritizing. F i n a l l y , effective management o f water u t i l i ty assets requires the pr ior i t i za t ion o f replacement needs. That is , managers must be able to determine what to replace and w h e n to replace it. T h i s issue is c lose ly t ied to r e so lv ing f inancia l and technical challenges as to whether to mainta in , repair or renew an asset or to choose an alternative ) such as t w i n n i n g a water ma in . Because u t i l i ty managers are usua l ly required to p lan annual capital projects, this component o f asset management is usua l ly performed. In do ing so, they have to overcome obstacles to effective pr ior i t i za t ion such as h o w to address uncertainty w h e n longer-term p lann ing hor izons are considered or h o w to balance the various needs among an organizat ion. Tradi t iona l ly , ut i l i t ies have pr io r i t i zed p ipe replacements based on a combina t ion o f current management practices and his tor ical pipe breakage data. Management practices include directives based on general guidel ines, consequence assessments, legislat ive requirements and other u t i l i ty priori t ies . Rudimenta ry analyses that interpret h is tor ica l pipe break data, i nc lud ing locat ion, t ime and date o f break and pipe diameter and material have p rov ided informat ion regarding where and h o w m a n y breaks are occur r ing and what pipes are exper iencing breaks (K le ine r and Rajan i , 1999). 1.4 PREDICTING W A T E R M A I N B R E A K S A p r imary goal o f p r io r i t i z ing pipe replacements is to identify investment strategies that, o n one hand, avo id premature replacement o f pipes (i.e., unnecessary pre-investment o f funds), and o n the Other hand, avo id water m a i n breaks, interruptions i n service, potential contaminat ion o f water and the costs o f damage. I f ut i l i t ies can predict when and where water mains m a y break, this informat ion is also useful for assisting w i t h op t im iz ing 13 crew efforts and m i n i m i z i n g the results o f loss o f water to k e y businesses and cr i t ica l facil i t ies. Thus asset management decisions can be i m p r o v e d b y an abi l i ty to determine the future performance o f water mains b y predic t ing water m a i n breaks and poss ib ly ident i fy ing h o w such breaks m a y occur. Causes of breaks. A number o f authors have analyzed the causes o f breaks, * i nc lud ing O ' D a y (1982), M a l e et al. (1990), Sav ic and Wal ters (1999), Rajan i and M a k a r (2000), Rajan i and K l e i n e r (2001) and D i n g u s et al. (2002). A c c o r d i n g to Rajani and Tesfamar iam (2005), a combina t ion o f circumstances leads to pipe failure i n most cases and different factors cause failure i n different pipe networks. The causes o f breaks inc lude deterioration as a result o f use (e.g., internal corrosion) , phys i ca l loads appl ied to the pipe (e.g., traffic, frost), l im i t ed structural resistance o f the p ipe because o f construct ion practices dur ing instal la t ion and dec l in ing resistance over t ime (e.g., cor ros ion , aging factors). D ingus et al. (2002) surveyed the 46 largest A m e r i c a n Water W o r k s A s s o c i a t i o n Research Founda t ion ( A W W A R F ) member uti l i t ies i n 1997 and noted mul t ip le c o m m o n failure modes for cast i r o n p i p i n g systems. Cor ros ion , improper instal la t ion and ground movement were the three most c o m m o n causes o f pipe failure. Break prediction models. B reak predic t ion models have been developed to help the water industry understand h o w pipes deteriorate and w h e n pipes w i l l break i n the future. These models are typ ica l ly grouped into two classes - statistical and phys ica l -mechanica l models (K le ine r and Rajani , 2001). Statist ical models use his tor ica l p ipe break data to identify break patterns and extrapolation o f these patterns to predict future pipe breaks, or degrees o f deterioration. Phys ica l -mechan ica l models predict failure b y 14 s imula t ing the phys i ca l effects and loads o n pipes and the capaci ty o f the p ipe to resist failure over t ime. Statist ical models have been used to analyze large dis t r ibut ion systems (e.g., K l e i n e r and Rajan i , 1999) and are t yp i ca l ly characterized as either statistical determinist ic or statistical probabi l i s t ic equations (Kle ine r and Rajani , 2001). U n d e r the statistical determinist ic models , the p ipe breakage is estimated based o n a fit o f pipe breakage data to various time-dependent equations, w h i c h m a y represent the cumula t ive pipe breaks as a function o f t ime from date o f instal la t ion or f rom the earliest date o f avai lable break data, and most c o m m o n l y are t ime-l inear (Ket t ler and Goul ter , 1985) or t ime-exponent ial functions (Shamir and H o w a r d , 1979; W a l s k i , 1982 and K l e i n e r and Rajan i , 1999). Determinis t ic models were developed as early as 1979. Statist ical probabi l is t ic models predict not o n l y the failure potential , but the dis t r ibut ion o f failure. These models are more complex than determinist ic models and require more data. E x a m p l e s o f these include cohort su rv iva l , such as K A N E W (Deb et al, 2002), B a y e s i a n diagnost ic , break clustering, s e m i - M a r k o v C h a i n and data f i l ter ing methods. S u r v i v a l analysis has been demonstrated b y M a i l h o t et al (2000) as useful i f there are adequate histories o f pipe failures. Statist ical models can use avai lable h i s to r i ca l ' data on past failures to identify breakage patterns and are useful i f the data are l imi ted . Statist ical methods require some technical expertise i n deve lop ing the models and interpreting results, but not to the degree o f expertise required o f staff i f phys i ca l -mechanica l models are used. K l e i n e r and Rajani (2001) suggest that statistical models based on fewer data m a y be used to gain insights for future performance. 15 Phys ica l -mechan ica l models t yp i ca l ly fa l l into one o f two classes: determinist ic models w h i c h estimate pipe failure based o n s imula t ion o f the phys i ca l condi t ions affecting the p ipe (Doleac et al., 1980 and Rajani and M a k a r , 2000), and probabi l i s t ic models that use a dis t r ibut ion o f input condi t ions, such as rate o f corros ion, to predict the l i k e l i h o o d and dis t r ibut ion o f p ipe failure ( A h a m m e d and Me lche r s , 1994). P h y s i c a l models have been developed p r i m a r i l y for cast i ron and cement pipes and have significant data needs. K l e i n e r and Rajani (2001) suggest that o n l y larger diameter mains w i t h cos t ly consequences o f failure m a y jus t i fy the required data co l lec t ion efforts for these models . r Other developments i n recent years inc lude the use o f A r t i f i c i a l N e u r a l N e t w o r k s ( A N N s ) b y Sac lu t i (1999) and fuzzy-based techniques b y K l e i n e r et al. (2004). The A N N m o d e l predicts the number o f water m a i n breaks based o n a seven day weather forecast and is appl ied o n l y to homogeneous groups o f water mains for short-term maintenance work . The fuzzy-based techniques are appl ied to large t ransmiss ion water mains . In addi t ion, an agent-based system for predic t ing water m a i n breaks is proposed b y D a v i s (2000). W h i l e m u c h w o r k has been undertaken toward deve lop ing deterioration models , the use o f these models is not c o m m o n among uti l i t ies. U t i l i t i e s face obstacles such as a lack o f k e y data, l imi t ed inst i tut ional capaci ty w i t h i n their organizat ion to understand and use models and the complex i ty i n managing w o r k that i n v o l v e s a number o f groups. There is no c o m m o n m o d e l that m a y be appl ied to every water system. Because the literature suggests that breaks and causes o f breaks for any part icular water dis t r ibut ion system are system-specific (Rajani and Tesfamar iam, 2005), a u t i l i ty must create its system-specific mode l based o n factors o f deterioration that are relevant for the ut i l i ty . 16 S m a l l and m e d i u m size uti l i t ies typ ica l ly have the capaci ty to use statistical determinist ic models , but the implementa t ion o f more sophisticated models is not pract ical due to the data co l l ec t ion efforts and m o d e l maintenance required. A s this research demonstrates, statistical determinist ic models show promise for use b y these uti l i t ies because they can be appl ied us ing c o m m o n l y used software, they do not require specia l ized tools or expertise to operate, and m a y b y their degree o f accuracy prov ide managers w i t h insights into their system o n future pipe breaks. U l t ima te ly , predic t ion models need data and i n particular, data that are relevant for the models and are explanatory for accurate predict ions. Da ta co l l ec t ion regarding water m a i n breaks is not a s imple exercise nor is the practice consistent across ut i l i t ies . F o r a l l ut i l i t ies data co l lec t ion can have significant costs i f performed at a comprehensive leve l . These costs inc lude not o n l y out o f pocket costs but also organizat ional effort and human resources. W h i l e a co l l ec t ion o f best practices have been recommended b y the N a t i o n a l G u i d e to Sustainable M u n i c i p a l Infrastructure ( N G S M I , 2002) and A W W A R F (Deb at al., 2002), the current state o f knowledge o f data col lected b y sma l l and m e d i u m size uti l i t ies is l imi ted . Recent water u t i l i ty surveys include those init iated b y the N a t i o n a l Water and Wastewater B e n c h m a r k i n g Initiative (Earth Tech , 2004), the A m e r i c a n Water W o r k s Assoc i a t i on , ( A W W A , 2004) and A W W A R F (Deb at al., 2002). The N a t i o n a l Water and Wastewater B e n c h m a r k i n g Initiative, a partnership o f a number o f Canad ian uti l i t ies, examines water m a i n breaks as a performance measure but does not examine water m a i n break data i n detail . The A W W A database ( A W W A , 2004), c o m p i l e d as a jo in t effort between A W W A and A W W A R F , focuses on general ized data for dis t r ibut ion systems, 17 ut i l i ty revenue, treatment practices and finances and does not inc lude data o n water m a i n breaks except the number o f breaks. The survey b y D e b et al. (2002) reports on responses f rom five ut i l i t ies serving populat ions fewer than 100,000 and 32 w i t h populat ions greater than 100,000. Thus knowledge o f what smal l and m e d i u m size uti l i t ies have is needed. ( S m a l l and m e d i u m size uti l i t ies need help w i t h m a k i n g predict ions o f the remain ing service l ife o f water mains and guidance for integrating data acquis i t ion and analysis programs to improve the pr ior i t i za t ion o f their water m a i n replacements. T h e y lack knowledge regarding h o w to develop databases that support their efforts i n predic t ing future breaks and what to do w i t h break predict ions. In particular, research is needed to determine the extent o f data col lected, h o w the data should be c o m p i l e d and what can be done to support the use o f models w i t h i n these uti l i t ies. 1.5 R E S E A R C H M E T H O D S Institutional factors affecting asset management. The research goals were in i t i a l l y focused o n des igning and conduct ing experiments to determine k e y data avai lable i n smal l and m e d i u m size uti l i t ies and to assist these data w i t h us ing break predic t ion models that are appl ied o n a pipe b y pipe basis. A s the research progressed, it became apparent that an understanding o f u t i l i ty organizat ional structures, behaviors and practices, as w e l l as a wi l l ingness o n the part o f organizat ion was needed i f this research is to influence practice. T h i s is because water ut i l i t ies are complex organizations w i t h many staff that have var ious roles, responsibi l i t ies and accountabil i t ies. In addi t ion, these organizations face a significant amount o f staff retirements and "insti tutional m e m o r y loss" 18 i n the c o m i n g years. Pract ices that are easi ly taught and documented w i l l be important for business continuity. Furthermore, ut i l i t ies also cannot re ly so le ly on ora l corporate knowledge and need data that are shared among the organizat ion as w e l l as systems that facilitate data sharing. M o s t ut i l i t ies are t yp i ca l ly compr ised o f operations, f inancial , informat ion technology and engineering departments. Operations departments are responsible for operation and maintenance activit ies, f inancial departments manage the f inancia l aspects o f the u t i l i ty business, informat ion technology departments main ta in and manage data systems, w h i l e engineering departments are responsible for the expansion or construct ion o f new network assets. In m a n y uti l i t ies, operating departments are responsible for determining w h i c h pipes should be replaced. C o m m o n l y activit ies, roles and responsibi l i t ies evolve to fit a part icular person, their strengths and interests, though these m a y be inconsistent w i t h the general organizat ional structure. Da ta are usual ly col lected and managed o n an ad-hoc basis throughout the organizat ion b y those w h o are i n v o l v e d i n a specific ac t iv i ty or w h o have specific interest i n the data. N o one single person t yp i ca l l y coordinates or manages a l l the data ( typ ica l ly asset management ini t iat ives stall i n m a n y organizat ions due to the inab i l i ty to dedicate or create a pos i t ion for this role). Furthermore, w i t h i n any u t i l i ty , data m a y be ora l or documented and the format and storage o f such data m a y differ throughout that ut i l i ty . In addi t ion, budgets constrain activities i n these organizations. Dec i s ions and changes i n these organizations are usua l ly based o n dialogue among and acceptance b y those affected. W h i l e practices require approval b y senior managers, pub l i c p o l i c y decisions are referred to m u n i c i p a l counci ls . The pr ior i t iza t ion and schedul ing o f asset replacement projects are usua l ly performed b y groups o f ind iv idua l s or i n some cases b y 19 one i n d i v i d u a l and submitted to their m u n i c i p a l c o u n c i l for approval . These factors required deve lop ing research methods that cou ld be appl ied to a variety o f organizat ional structure, technical d i sc ip l ine , knowledge , s k i l l , ab i l i ty and size. N The District o f Maple Ridge. The Dis t r ic t o f M a p l e R i d g e , the case study for the research is a typ ica l water ut i l i ty . M a p l e R i d g e was incorporated as a mun ic ipa l i t y i n 1874 and experienced significant urban development over the past three decades. It was used to test the practicali t ies o f app ly ing the framework and approaches developed herein. M a p l e R i d g e was interested i n learning and i m p r o v i n g its practices. B u t it was a challenge as a researcher to k n o w , not o n l y for M a p l e R i d g e but for uti l i t ies i n general, what data were avai lable, to ident ify potential sources o f data, to determine h o w to access the data, to develop approaches to create useful data from various sources, and to develop a framework for associating, accessing, and managing the data across a l l functional l ines respecting responsibi l i ty , management and territorial issues. F o r example, i n M a p l e R i d g e , data are "owned" and managed b y various departments. Water m a i n break data are col lected, stored and managed b y those operating crews that respond to breaks. Other p ipe related data such as p ipe mater ial , diameter and age are stored i n the Eng inee r ing department. The operations department manager w h o oversees the superintendents and operating crews prepares and submits a list o f replacement projects to the ind iv idua l tasked as the corporate capital p rogram coordinator who then schedules those projects a long w i t h a l l other capital projects (that are submitted b y a l l other departments). The schedul ing respects the avai lable annual funding and is based o n the submitted informat ion and the coordinator's v i e w o f the future needs o f the organizat ion. The scheduled projects are then rev iewed b y the senior managers and the C h i e f Admin i s t r a t ive Off icer (more c o m m o n l y k n o w n as " C i t y Manage r " i n many munic ipa l i t ies ) 20 pr ior to submiss ion to m u n i c i p a l counc i l for approval . Thus the l i se o f M a p l e R i d g e as a case study required the research methods that c o u l d identify data i n mul t ip le sources, val idate his tor ic projected and estimated data, determine the basis o f col laborated decisions and dis t inguish p o l i c y and practice. Research time frame and tools. The research i n M a p l e R i d g e began i n early 2002 and was completed b y mid-year 2006. It is based o n three components: f irst ly, on conduct ing a survey o f N o r t h A m e r i c a n water ut i l i t ies, secondly, o n creating, l i n k i n g and m i n i n g data and f inal ly , o n developing the framework for us ing predic t ion models . The data used i n the experiments are actual water system data from the Dis t r i c t o f M a p l e R i d g e . A n a l y t i c a l software used i n the research include M i c r o s o f t Acces s® and Exce l®, (Mic rosof t Off ice 2000 versions) , A d o b e Acroba t Reader v 6 , K A N E W b y W e s t o n Solut ions (based on Mic roso f t A c c e s s ® Off ice 97 version), S-Plus v6 and V7 (Insightful Corporat ion) and A r c v i e w G I S 3 . 2 A and A r c m a p v 9 b y E S R I . Survey of North American utilities. There were a number o f challenges i n v o l v e d i n determining the data co l l ec t ion practices o f N o r t h A m e r i c a n water ut i l i t ies . The best practices indicated b y D e b et al. (2002) and N S G M I (2002) are fa i r ly recent observations and there are no publ i shed reports regarding industry awareness or use o f the recommended best practices. Because the best practices recommended i n these documents are not exact ly the same, it was necessary to reconci le the differences and develop the questions i n the survey questionnaire to reflect both sets o f best practices. Ano the r challenge i n developing the survey was the need to balance the degree o f detail i n w h i c h I was interested w i t h the effort required o f the respondent to vo lun ta r i ly provide such informat ion. I soon recognized that i n order for the survey to fu l f i l l m y research goal o f ident i fy ing the data avai lable to mid- s i ze ut i l i t ies , the questionnaire w o u l d 21' have to be detailed and that the informat ion w o u l d not be readi ly avai lable i n one place or w i t h any one person w i t h i n any organizat ion except w i t h i n very sma l l organizations. The survey w o u l d have to be easy to read, and not discourage uti l i t ies f rom responding to it. It w o u l d have to create interest and encourage persistence w i t h i n those organizations attempting to complete it. The survey w o u l d need a layout and format that was easy to read and complete (regardless o f the ab i l i ty o f the person comple t ing it), and yet easy for me to compi l e the responses. W h i l e a few electronic formats were examined, it became apparent that the survey w o u l d be most eas i ly completed i f the forms were sent out as a spreadsheet w o r k b o o k i n order that they cou ld be printed, completed b y hand and faxed back or that they cou ld be completed and sent back e lect ronical ly to me b y users (because spreadsheet software is c o m m o n l y used b y uti l i t ies) . A draft vers ion o f the survey was sent to four colleagues, two i n M a p l e R i d g e , one i n the C i t y o f Wes t V a n c o u v e r and one i n the C i t y o f B u r n a b y for their comments and this a l l owed me to test methods o f e lect ronical ly c o m p i l i n g the results. M i n o r edi torial and c lar i f ica t ion changes were made and incorporated i n the f inal vers ion. The f inal vers ion inc luded text control (for c o m p i l i n g and ana lyz ing the data) us ing drop d o w n boxes w h i c h also made the survey easier for users to complete. Ano the r challenge was h o w to distribute the survey and h o w to encourage people to complete the survey. I considered g i v i n g honorar ia but decided against that due to costs. T o encourage responses, I noted i n the dis tr ibut ion that, the results w o u l d be shared. I selected emai l dis t r ibut ion to m i n i m i z e the dis tr ibut ion costs and de l ivery t ime. N o t a l l professional associations I approached to help me distribute the survey were helpful , though most were. O v e r 400 surveys were di rect ly sent out and about thirty personal requests and specific f o l l o w up telephone cal ls were made. In a l l , three mai l ings o f the same survey were sent out. The first m a i l i n g was sent to members o f the Canad ian Water and Waste A s s o c i a t i o n 22 ( C W W A ) . The second to the members o f the A m e r i c a n P u b l i c W o r k s A s s o c i a t i o n ( A P W A ) and th i rd to the C i t y Engineers i n the Greater V a n c o u v e r R e g i o n a l Dis t r ic t . The responses were received gradual ly and the in i t i a l deadline for rece iv ing surveys was extended because o f a l o w number o f t i m e l y responses. The first set o f responses was from the C W W A members. The A P W A distr ibut ion was made through the A P W A to its members w h o were water resources professionals and this m a i l i n g generated a large response f rom a number o f U . S . ut i l i t ies. The C W W A dis t r ibut ion inc luded the spreadsheet fi le w h i l e the A P W A emai l dis t r ibut ion contained a l i n k to the fi le. The l i n k affected the submiss ion o f some uti l i t ies as it added another step to the response process and it created confusion on the part o f the respondents. In many A P W A cases, o n l y a por t ion o f the survey was returned in i t i a l l y and the uti l i t ies had to re-send the survey. W h i l e a majori ty o f surveys were completed and sent back electronical ly , a number o f responses were returned b y fax. The faxed responses were then inputted manua l ly into spreadsheets for processing. W h e n the responses were received, they were rev iewed for errors and text control . The raw data were exported into a M i c r o s o f t A c c e s s ® database. The database was queried and then inputted to a M i c r o s o f t Exce l® fi le for data manipula t ion , analysis and graphing. M o s t respondents spent about 45 minutes comple t ing the survey. O f the 70 responses received, 11 responses were rejected as incomplete . These usua l ly had o n l y one or more o f the seven spread sheets completed due to the confusion caused b y the l i n k i n g requirement or d i d not real ize that the fi le contained several spreadsheets. Those surveys were sent back and f o l l o w up telephone cal ls were made where appropriate. The design and development o f the survey began i n 2003 and the surveys were f ina l ly distributed, c o m p i l e d and analyzed i n 2004. A manuscript report ing on the survey, Chapter 2, was submitted to Journal A W W A i n 2005 and was publ i shed i n J u l y 2006. 23 Data creation. The creation o f data described i n Chapter 3 was inspired b y the survey results that showed a gap between data presently col lected and those avai lable (see F igure 2.2 o f Chapter 2), as w e l l as b y the fact that ut i l i t ies noted the locations o f different data w i t h i n their various departments. It was also d r iven b y the d i scovery that the data set purchased f rom the C i t y o f Seattle w h i c h was thought to have breadth and his tory was actual ly quite incomplete . Af te r repeated correspondences and a site v is i t to Seattle, it was determined that the data f rom Seattle c o u l d not be used for the experiments. I then contacted four munic ipa l i t i es i n the Greater V a n c o u v e r R e g i o n a l Dis t r ic t (Burnaby, R i c h m o n d , Wes t V a n c o u v e r and C o q u i t l a m and rev iewed the breadth and his tory o f their data. Y e t again I determined that the data p rov ided b y these munic ipa l i t ies was insufficient. Thus I decided to use M a p l e R i d g e data, though l imi ted , for input for the experiments because o f m y ab i l i ty to access these data, and to col lect data f rom other internal and external sources for this w o r k and for other m u n i c i p a l projects beyond the focus o f m y research. Because o f its l imi t ed data, M a p l e R i d g e is representative o f m a n y uti l i t ies and is ideal for demonstrating the concepts o f f inding and gathering data w i t h i n and external to an organizat ion and o f constructing and l i n k i n g data for asset management. The L a i t y V i e w area o f M a p l e R i d g e was selected to be a case study area because it represents an urban area and experienced construct ion practices typ ica l for the munic ipa l i ty . It comprises 13 percent o f the uti l i ty 's p ipe network. De te rmin ing i f data were avai lable required meet ing w i t h and exp lor ing activit ies o f various w o r k units throughout the organizat ion. The research effort o f creating data was significant and the approach and techniques used i n do ing so are presented i n this thesis. These tools are general and m a y be used b y a l l ut i l i t ies. N e w data constructed for M a p l e R i d g e i n this research include so i l , surface 24 material , water pressure and f low i n pipes, bedding and b a c k f i l l mater ial and traffic loading. A d d i t i o n a l activit ies were carr ied out to ver i fy data i n c l u d i n g f ie ld surveys o f so i l and p re l imina ry p ipe sampl ing and analysis. W i t h different departments co l lec t ing and storing data, the process o f scrubbing data was not a straightforward exercise. D u r i n g the process o f l i n k i n g the data, inconsistencies and m i s s i n g data i n the various databases were d iscovered (e.g., m i s s i n g material or diameter data or discrepancies between the hydraul ic m o d e l and G I S data). T y p i c a l l y , I had to delve into the details o f those databases to see w h i c h data were more current or i n some cases, to ver i fy those data us ing another source. F o r example , i f a pipe had different ages i n the different databases (e.g., the hydraul ic m o d e l and the G I S ) , I . checked the age i n each database to ensure that an input error had not been made, and checked the capital works program to see i f the p ipe had been replaced but that the age o f the new pipe had not been updated i n one o f the databases. I also rev iewed the data for consis tency w i t h the knowledge I have about M a p l e Ridge ' s practices (e.g., po l ic ies such as that there should not be asbestos cement pipes instal led after 1985). Where discrepancies existed, as-built drawings were rev iewed to determine i f data were correct. It was unfortunate that data were sometimes lost or deleted (e.g., at M a p l e R i d g e when a pipe is replaced, a l l records pertaining to that pipe are t yp i ca l ly el iminated). In some cases, I was able to ver i fy some data for these pipes, but I was not successful i n most cases. A s w e l l , the research required the development o f a technique to facilitate creating on-demand databases for analysis and updating. T h i s was required to address the need to obtain data for experiments and to be able to update the o r ig ina l database but also to respect the ownership o f the data and the organizat ional structure. 25 An example of how creating data. H o w pipe break records were created for this research and h o w they are planned to be managed i n the future b y M a p l e R i d g e is an example o f the activities and efforts described above. The break records for M a p l e R i d g e are not stored i n any one locat ion but i n var ious files and phys i ca l locat ions and w i t h different staff o f the operations department i n the operations b u i l d i n g ( w h i c h is separate f rom C i t y H a l l and the engineering department). Because o f m y experiences w i t h other uti l i t ies, I was certain that M a p l e R i d g e had some records o n water m a i n breaks. In the course o f conversations w i t h various staff over a number o f months, I made m a n y inquir ies and requests o f var ious operations and engineering staff (wi th suggestions o f w h o m a y have the data or where they m a y be stored, e.g., the archive files, i n someone's previous files or i i n w o r k request logs) , I was able to obtain a l l water m a i n break data for the per iod 1983-2004. Information regarding water m a i n breaks for certain years was o n l y avai lable f rom f ie ld staff break forms, i n paper form, and for other years, it was avai lable o n printed computer reports stored i n separate files. O n c e a l l the records were obtained, the data were rev iewed and scrubbed to separate out records o f service connect ion failures (e.g. saddle failures, l eak ing copper service lines) from those o f pipe breaks. Subsequently, an electronic database o f the breaks was then created b y input t ing the data b y hand into spreadsheets, ident i fy ing the specific ident i f icat ion number (see Chapter 3) o f the pipes that broke b y locat ing those pipes on maps us ing the loca t ion data recorded, and adding the G I S pipe ident i f icat ion number as a p ipe attribute. The spreadsheets were then exported to a M i c r o s o f t Acces s® database where a new input fo rm was created to a l l ow the addi t ion o f future break data from revised f ie ld record forms (as discussed i n Chapter 3). The storage locat ion o f the new water m a i n break database was ident i f ied and mapped b y those responsible i n the engineering department for data warehousing. T h e database is avai lable 26 to the operations department staff for searching, f ind ing and sharing the raw data. The break data for the L a i t y V i e w case study was then extracted f rom the new water m a i n break database for the experiments described i n Chapter 4. W h i l e the creation o f the database became more mechan ica l once the paper records were obtained, creating the database required d iscuss ion and resolut ion regarding i ) future data co l lec t ion resources, efforts, qual i ty control and training, and i i ) database b u i l d i n g , ownership , management and maintenance. A number o f discussions and negotiations transpired between the engineering, operations and informat ion technology departments regarding the goals and potential results resul t ing from pipe break data co l lec t ion and analysis, the roles and responsibi l i t ies for data co l lec t ion , storage, management and access, and the contr ibut ion b y each department o f staff t ime and finances. These discussions and m y desire to improve data warehousing practices, yet respecting data ownership issues w i t h i n M a p l e R i d g e , inspi red the development o f the distributed but related databases for on-demand analysis described i n Chapter 3. Th i s por t ion o f the research took f rom early 2004 un t i l summer 2005. Framework for using prediction models. Th i s por t ion o f the research experiments was in i t i a l l y based o n ana lyz ing the created data to determine i f there were k e y data that are current ly avai lable to most smal l and m e d i u m size uti l i t ies that c o u l d be used i n predic t ion models for i m p r o v i n g asset management. The L a i t y V i e w data set w i t h break his tory from 1983 to 2004 was used for the experiments and is described i n Chapter 4. ^ The experiments were designed to use statistical determinist ic t ime-exponent ial and t ime-l inear regression models , su rv iva l analysis models and K A N E W (Deb et al., 1998). T ime- l inea r and t ime-exponent ia l models can be used b y smal l to m e d i u m size uti l i t ies because these uti l i t ies t yp i ca l ly have the inst i tut ional capaci ty to use spreadsheets or s imple 27 statistical software packages. The surv iva l analysis and K A N E W (Deb et al, 1998) techniques were appl ied to determine the sui tabi l i ty o f those applications for more adept ut i l i t ies , even though most uti l i t ies m a y not have the ab i l i ty to use these more sophisticated techniques or operate the more complex software required. W h i l e not reported i n Chapter 4, the appl ica t ion o f su rv iva l analysis was not successful due to the l o w number o f breaks i n the L a i t y V i e w case w h i c h is a young system, the l imi t ed breaks i n older pipes and the loss o f data regarding pipes that were replaced. S u r v i v a l functions were der ived for a l l the p ipe groups described i n Chapter 4 but were incomplete for the most part because surv iva l analysis is dependent i n k n o w i n g the failure his tory across a large range o f pipe ages. There were not enough failures i n the older pipes to determine a complete surv iva l function for any type o f pipe. A s such, it was conc luded that su rv iva l functions cannot be expected to be c o m m o n l y used b y smal l and m e d i u m size uti l i t ies w i t h l imi t ed data. S i m i l a r l y , the use o f K A N E W is constrained by ; the l im i t ed break his tory to derive cohort specif ic survivals . K A N E W , a Mic roso f t Acces s® 97-based program was developed based on interviews w i t h u t i l i ty staff regarding their experience and can be ve ry conservative. I had a number o f discussions w i t h the developers o f K A N E W regarding the program, its development, use, l imitat ions and applicat ion. A g a i n , because o f the incomplete failure his tory o f pipes i n M a p l e R i d g e , K A N E W c o u l d not be appl ied w i t h success and was not reported o n i n Chapter 4. The strength o f K A N E W is i n a l l o w i n g a u t i l i ty to develop replacement budgets. U s i n g expected pipe l ives f rom the experiences o f other ut i l i t ies has some value for deve lop ing network replacement budgets but is not useful for pipe b y pipe replacements. 28 The experiments reported o n i n Chapter 4 were conducted dur ing summer and fa l l 2005 , and the analysis was completed i n 2006. Contribution of research. Th i s thesis offers a number contributions for sma l l and m e d i u m size uti l i t ies and future researchers. It assesses the data col lected b y uti l i t ies, it develops and demonstrates h o w to create and l i n k data for asset management i n general and it explores the under ly ing causes o f water m a i n breaks. F i n a l l y , the research develops a framework for uti l i t ies to use break predic t ion models on a pipe b y pipe basis to improve their method o f p r io r i t i z ing the replacing o f water mains for asset management and to in fo rm their future data acquis i t ion and storage programs. Managers m a y gain insights from the lessons learned from conduct ing this research o n organizat ional considerations such as inst i tut ional memory , staff t raining, engineering and operations responsibi l i t ies and strategic th ink ing for asset management. In particular, researchers w i l l benefit from this thesis because it identifies w h i c h data are avai lable for deve lop ing future asset management tools and h o w to access and construct water m a i n break data. 29 1.6 R E F E R E N C E S A h a m m e d , M . and M e l c h e r s , R . E . , 1994. R e l i a b i l i t y o f underground pipel ines subjected to corrosion. Journal of Transportation Engineering, 120:6: 989-1003. . A S C E ( A m e r i c a n Socie ty o f C i v i l Engineers) , 1999. A m e r i c a n Soc ie ty o f C i v i l Engineers report card and issue briefs. Public Works Management and Policy, 4 :1 : 58-76. A W W A ( A m e r i c a n Wate r W o r k s Assoc ia t ion) , 2004. 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D r i n k i n g Water Infrastructure Needs Survey. Second Repor t to Congress. U n i t e d States. Env i ronmen ta l Protect ion A g e n c y , Off ice o f Water , D r i n k i n g Water D i v i s i o n , Wash ing ton , D C . U S E P A , 1999. D r i n k i n g Water Infrastructure Needs Survey. U n i t e d States Env i ronmen ta l Protect ion A g e n c y , Of f ice o f Water , D r i n k i n g Wate r D i v i s i o n , Wash ing ton , D C . t J S F H W A , 1999. Asse t Management Pr imer , Federal H i g h w a y Admin i s t r a t ion , U S Department o f Transportat ion, Off ice o f Asse t Management , 400 7th Street, S . W . Wash ing ton D . C . 20590. Van ie r , D . J . , 2001 . Asse t Management : " A " to " Z " , American Public Works Association Annual Congress and Exposition - Innovations in Urban Infrastructure Seminar, Phi lade lph ia , U . S . September, 2001 . 1-16. Van ie r , D . J . and R a h m a n , S., 2004. M u n i c i p a l Infrastructure Investment P l a n n i n g ( M I I P ) M l f P Report : A P r imer o n M u n i c i p a l Infrastructure Asse t Management . Report B-5123.3, N a t i o n a l Research C o u n c i l Canada, Ottawa, O N . W a l s k i , T . M . , 1982. E c o n o m i c A n a l y s i s o f Water M a i n Breaks . Journal of Water Resources Planning Management Division, 108:3: 296-308. W o o d , A . and Lence , B . J . , 2006. Assessment o f Water M a i n Break D a t a for Asse t Management . Journal AWWA, 98:07. 35 Figure 1.1 Twenty-year total per household infrastructure cost estimates for different sized water systems $ 3 , 0 0 0 L a r g e M e d i u m S m a l l s y s t e m s s y s t e m s s y s t e m s Source: USEPA 1999 Drinking Water Infrastructure Needs Survey 36 C H A P T E R 2 ASSESSMENT OF W A T E R M A I N B R E A K D A T A F O R ASSET M A N A G E M E N T A version of this paper was published in the July 2006 issue of Journal A WW A. The paper is titled as Assessment of Water Main Break Data for Asset Management by A. Wood and B.J. hence. 37 P R E F A C E M u c h research has been conducted over the years regarding the development o f water m a i n break models . B u t as a manager, I found that none o f the m e d i u m size uti l i t ies w i t h w h o m I was famil iar , used break predic t ion models to pr ior i t ize their pipe replacements. Instead o f developing more models , I wanted to f ind a w a y to use break predic t ion models and exis t ing data i n asset management and i n p r io r i t i z ing specif ic pipes and to help other ut i l i t ies to do l ikewise . A s a manager, I k n e w that the u t i l i ty that I w o r k e d for d i d not have a large amount o f data w h i c h w o u l d l imi t their ab i l i ty to use models and I wanted to k n o w i f the amount o f data available was also a hindrance for other s imi la r s ize ut i l i t ies . In addi t ion, as a manager, I was interested i n compar ing our data co l lec t ion performance w i t h other ut i l i t ies and i n i m p r o v i n g our co l l ec t ion practices. T h o u g h best practices for water m a i n break data co l lec t ion were recommended i n 2002 (see N a t i o n a l G u i d e T o Sustainable M u n i c i p a l Infrastructure ( N G S M I , 2002) and A W W A R F (Deb et al, 2002), I c o u l d not f ind reports regarding the use o f the best practices, a l though D e b et al. (2002) had surveyed some large uti l i t ies (see A p p e n d i x A for a summary o f the size o f ut i l i t ies surveyed and the questions posed). Therefore, I developed a survey, the results o f w h i c h w o u l d serve as a foundation for m y research and distributed it to smal l and m e d i u m size uti l i t ies i n order that I might use it to guide m y research i n deve lop ing tools and techniques for i m p r o v i n g u t i l i ty asset management. I have received feedback on the results such as it is t i m e l y and provides managers w i t h a benchmark o f what is currently be ing done b y uti l i t ies against best practices. Some o f the results were presented at the 2006 B r i t i s h C o l u m b i a P u b l i c W o r k s A s s o c i a t i o n Conference, Q u a l i c u m Beach , B C and questions b y attendees inc lude: w h i c h data are most 38 important to col lect , what methods should uti l i t ies emp loy to col lec t data and h o w should data be stored and analyzed for asset management? The raw data regarding survey responses are appended to this thesis. 39 2.1 I N T R O D U C T I O N Water m a i n breaks can result i n loss o f water to key businesses and cr i t ica l faci l i t ies, and lead to damage o f infrastructure. Such events highl ight the deterioration, o f aging infrastructure, w h i c h is at the forefront o f p o l i c y and program discussions between nat ional and p rov inc i a l or state governments. The need for aging water m a i n rehabil i ta t ion is increasing, the costs o f repairs and replacement can be h igh , and the impact to customers potent ia l ly significant ( U S E P A 2001). F o r u t i l i ty managers, co l lec t ing , recording and mon i to r ing water m a i n breaks is important, not o n l y because such events m a y result i n significant pub l i c impact and destruction o f private property, but also because the data obtained f rom breaks m a y provide insights for management o f the system as a whole . T h i s informat ion is important i n developing the tradeoffs between expenditures and the leve l o f service p rov ided , and i n managing rehabil i tat ion programs to achieve a desired leve l o f service. T h i s paper reports o n the results o f a 2004 survey o f water ut i l i t ies i n the U . S . and Canada that determines the degree and types o f field informat ion that are currently col lected and other data avai lable w i t h i n different departments o f the u t i l i ty regarding water m a i n breaks. Queries were posed w i t h reference to the best practices recommended b y the Na t iona l G u i d e to Sustainable M u n i c i p a l Infrastructure ( N G S M I , 2002) and A W W A R F (Deb et al, 2002). The survey results identify the data that are deemed important and the approach undertaken for recording and storing these data b y different sizes o f ut i l i t ies . The leve l o f confidence that respondents have i n some o f the data be ing col lected and their l eve l o f comfort w i t h the amount and types o f data col lected, is also identif ied. The survey p rov ided the u t i l i ty managers w i t h a l ist o f data recommended as best practices against w h i c h they cou ld assess their o w n data co l lec t ion practices. The survey 40 f indings are important for the broader infrastructure management communi ty , because knowledge o f the data avai lable underpins the development o f relevant data acquis i t ion and storage strategies and the advancement o f asset management approaches. T h e y also prov ide u t i l i ty managers w i t h a basis for gauging their practices relat ive to those o f other ut i l i t ies . The survey was developed consider ing other recent water u t i l i ty surveys, i nc lud ing those ini t iated b y the N a t i o n a l Water and Wastewater B e n c h m a r k i n g Init iat ive (Earth Tech , 2004), the A m e r i c a n Water W o r k s Assoc i a t i on , ( A W W A , 2004), and A W W A R F (Deb et al, 2002). The N a t i o n a l Water and Wastewater B e n c h m a r k i n g Init iat ive (Earth Tech , 2004), a partnership o f Canad ian uti l i t ies, considers water m a i n breaks as a benchmark ing measure but does not examine water m a i n break data i n detail . The A W W A ( A W W A , 2004) database, c o m p i l e d as a jo in t effort between A W W A and A W W A R F , is based o n a 2002 and 2003 survey o f 337 smal l , m e d i u m , and large U . S . and Canad ian uti l i t ies and focuses o n a broad range o f potable water dis t r ibut ion characteristics i nc lud ing general informat ion regarding service popula t ion, pipe material , valves , fire hydrants and f lushing, f inished water storage faci l i t ies , corros ion control , customer metering, water, supply audit ing, and leakage management. It includes the reported number o f water m a i n breaks o f the uti l i t ies surveyed but does not inc lude data recorded o n water m a i n breaks. The survey reported on i n this paper bu i lds on previous A W W A w o r k (Deb et al, 2002), but queried i n greater detail the data that are col lected b y uti l i t ies, such as failure causes and the general phys i ca l characteristics o f the p ipe and so i l , and had more responses f rom sma l l to m e d i u m size uti l i t ies. In this survey, 37 uti l i t ies serving populat ions be low 100,000 and 22 uti l i t ies serving populat ions greater than 100,000 responded, compared 41 w i t h five ut i l i t ies serving populat ions be low 100,000 and 32 uti l i t ies serving populat ions greater than 100,000 that responded to the 2002 survey. 2 . 2 DESIGN O F T H E S U R V E Y The survey was designed for ease o f comple t ion and compi l a t i on into a data base for analysis. Users were able to print the survey and complete it b y hand, or complete it e lec t ronical ly us ing personal d ig i ta l assistants and laptops. M i c r o s o f t Exce l® w o r k sheets were chosen due to their c o m m o n use. Design of the questionnaire. Based on a rev iew o f the literature ( N G S M I , 2002; and D e b et al, 2002), the questions posed i n the survey were grouped into the f o l l o w i n g s ix Categories: • Genera l informat ion such as t ime o f break, customers affected, response personnel and equipment, and cost o f repairs; • L o c a t i o n data such as nearest property address and geographical coordinates; • P h y s i c a l data such as pipe mater ial and depth o f cover; • Env i ronmen ta l data such as depth o f frost and s o i l and air temperature; • Fa i lu re informat ion such as type and cause o f failure; and • Repa i r informat ion such as components replaced, repaired or instal led. The survey respondents were queried regarding h o w they current ly store data related to water m a i n breaks, their estimated level o f confidence i n selected data, their comfort w i t h the amount o f data and the percentage o f events for w h i c h data are recorded. T h e y were also g iven the opportuni ty to list the addi t ional data elements that they collect . 42 Survey distribution. The survey was distributed b y direct ema i l to members o f the Canad ian Water and Waste A s s o c i a t i o n ( C W W A ) , and members o f the A m e r i c a n P u b l i c W o r k s A s s o c i a t i o n ( A P W A ) w h o identif ied in,their member prof i le that they were either di rect ly responsible for, or interested i n , water dis t r ibut ion and treatment. 2.3 S U R V E Y R E S U L T S Seventy responses were received and after a rev iew o f each response for completeness, 59 surveys were deemed complete and analyzed herein as respondents. The general feedback f rom the respondents was that, w h i l e water m a i n break data co l lec t ion has been ident i f ied as important and a strategic ini t ia t ive ( G r i g g , 2004), ut i l i t ies are just beg inn ing to col lect data comprehensively , co l l ec t ion practices va ry w i d e l y , and most uti l i t ies v i e w their efforts as evo lv ing . The sizes o f the respondents range from one u t i l i ty serving 2,600 people to two uti l i t ies serving a popula t ion o f over one m i l l i o n . M o s t o f the respondents serve populat ions o f between 50,000 and 500,000. The service populat ions o f the respondents are shown i n Table 2 .1 . General water main break information. Genera l water m a i n break informat ion includes the date and t ime that a break is reported, the response t ime and resources used to address the break, and the impact on customers. The percentages o f a l l respondents that col lect different general informat ion are also shown i n F igure 2 .1 . A l l the respondents indicated that they record the date and t ime w h e n a break was reported. The data related to resources expended on the repair are general ly reported i n terms o f the amount o f crew hours spent responding to a reported break. H o w e v e r , o n l y about 70 percent o f respondents 43 record labor, materials, and equipment costs and less than 30 percent record the cost o f property damage or the effect o f the break o n customers. F r o m a management perspective, water m a i n breaks are a l i ab i l i t y and thus clear documentat ion o f a report o f the break or the request for assistance, and the u t i l i ty response to the informat ion, are required should c la ims be f i led against the ut i l i ty . L e n g t h y break response t imes m a y result i n significant private or pub l i c property damage and can be cos t ly and embarrassing for u t i l i ty managers. O n l y 70 percent o f respondents record costs. W h i l e this is surpris ing, it m a y be due to the d i f f icul ty associated w i t h recording some costs (e.g., some costs m a y o n l y be determined at a later t ime, such as costs from a c l a i m or for re-paving a road). Some costs m a y be determined us ing other sources o f data such as through pay ro l l or w o r k order systems. In addi t ion, w h i l e managers need to track expenditures for cost contro l , accountabi l i ty o f resources and p lann ing for future management decisions, they m a y use different report ing systems and m a y be required to report the costs for responding to water m a i n breaks o n l y on an aggregate basis. The survey responses show that few respondents record the effect o f the breaks o n customers i n terms o f damages incurred and the number or type o f customers that experience a water stoppage as a result o f the break or repair. H o w e v e r , the data m a y be avai lable or calculated i f necessary b y determining i f and where valves were operated to shut o f f water to sections o f a water m a i n and i f services were turned off, h o w long it took to restore the water service. T h i s w o u l d a l l o w a u t i l i ty to calculate the number o f customers affected and the length o f the interruption as a surrogate for the direct impact on customers. In addi t ion, c la ims data were also referenced as a potential source o f informat ion. 44 L o c a t i o n d a t a . L o c a t i o n data include the nearest property address, cross street, and geospatial coordinates. The percentage o f respondents that record var ious locat ion data is shown i n Table 2.2. L o c a t i o n data a long w i t h maps can a id response crews i n determining the t ime and effort o f response, the size o f m a i n to be repaired, the supplies needed to repair the break and the loca t ion o f valves that need to be c losed i n order to facilitate repairs. In addi t ion, recording the loca t ion o f the break a l lows future managers to determine i f there are repeated breaks i n a part icular section o f water m a i n and m a y help to assess i f rehabil i ta t ion or replacement o f the m a i n is required. M o s t respondents record the nearest property address and cross street name, but few record addi t ional informat ion that can identify the exact locat ion o f the break. The survey responses suggest that address and cross street data come f rom the in i t i a l report o f the break (i.e., the customer) but are not revised w h e n the actual break loca t ion is determined. The fact that data are col lected suggests that dispatching a response is the p r imary mot iva t ion for the co l lec t ion , but that co l lec t ing loca t ion details that w o u l d assist future break analyses is not as h igh a pr ior i ty . The lack o f actual break locat ion data m a y suggest that either respondents f ind it diff icul t to record and store spatial data or do not consider the specif ic locat ion o f a break important. The fact that few respondents record whether i so la t ion valves are operated can . make it diff icul t for u t i l i ty managers to determine the number o f customers affected b y a break and a repair. T h e use o f Geographic Information Systems (GISs ) for storing informat ion and v i s u a l i z i n g break data, and the l o w cost o f G l o b a l Pos i t i on ing Sys tem ( G P S ) survey equipment, m a y change this practice i n the future. GIS-s tored locat ion informat ion m a y u l t imate ly enhance dec i s ion-making regarding rehabi l i ta t ion and replacement. 45 Physical data. The data typ i ca l ly classif ied as phys i ca l include: the age, mater ial and characteristics o f the pipe, and surrounding so i l . The results reported i n F igure 2.2 show that most respondents col lect a narrow variety o f phys i ca l data. M o s t respondents record data that inc lude p ipe diameter, pipe mater ial , water service type, cover depth, and whether the surface is a roadway or other surface. The lack o f phys i ca l data col lected b y respondents m a y be attributed to the fact that -water m a i n breaks are typ ica l ly treated as emergency situations i n w h i c h the goals are to contain damage, repair the break, and restore lost water service to customers or that some informat ion on the phys ica l characteristics o f water mains m a y be avai lable elsewhere i n the data warehouse o f the ut i l i ty , such as i n as-built records, or i n G I S form. W h e n other data sources are accounted for, the percentage o f respondents that possess the various data elements increases. A n a l y s i s o f the survey results suggests respondents and uti l i t ies can be classif ied, according to the richness o f the data recorded, into four groups. These groups include uti l i t ies possessing: i . basic data consis t ing o f p ipe size and material ; i i . basic mater ial and diameter data plus l im i t ed informat ion such as age o f the pipe, use o f the surface at ground leve l , operating pressure, and type o f pipe jo int . I f pipes i n a network are fa i l ing at jo ints , details about jo in ts can be used to develop a strategy to anticipate, prevent, and repair breaks; i i i . i n addi t ion to the data described i n (i) and ( i i ) , data o n construct ion o f the water m a i n ; and i v . i n addi t ion to data described i n (i), ( i i ) , and ( i i i ) , detai led pipe informat ion such as pipe w a l l thickness and pipe fracture toughness ( typ ica l ly as a result o f pipe testing). 46 Failure causes and modes. A n important aspect o f water m a i n break data is the nature o f the failure. T h o u g h the mode o f failure cannot be def in i t ive ly correlated w i t h specif ic causes o f the failure, they m a y indicate a failure mechan i sm and suggest a cause o f failure for analysis b y asset managers. T h e survey queried the respondents regarding eleven c o m m o n failure modes and the responses to the survey show that 85 percent o f respondents record leak ing jo ints , valves , hydrants and service connections and between 7Q and 83 percent record the remain ing seven failure modes. These failures modes are: l eak ing jo in t , l eak ing service connect ion, l eak ing va lve , l eak ing hydrant, longi tudinal break, b low-out , split b e l l , corros ion pit hole, curb stop failure, tap failure and fai led b l o w -o f f (i.e., air release va lve) . Respondents cou ld also select an "other failure modes" category i n the event that the failure is different from the list o f failure modes provided . N o other modes were reported. W h i l e ut i l i t ies are able to determine and record the failure mode, o n l y 25 percent o f respondents record the cause i n 100 percent o f their records, 37 percent o f the respondents record the cause i n 75 percent o f their records, and o n l y 40 percent o f respondents record a cause i n at least 50 percent o f their records. Th i s suggests that few respondents have a consistently h i g h l eve l o f informat ion on the causes o f breaks to their water mains. The different causes o f failure and the percentage o f respondents that record a specific cause o f failure are shown o n F igure 2.3. The analysis o f data shown i n F igure 2.3 suggests that it is diff icul t for respondents to determine the cause o f failure. Managers m a y f ind that in ' their organizat ion, breaks are treated as emergency situations and the u t i l i ty staff at the scene o f the break focus o n cont ro l l ing the extent o f col lateral damage from the break. A l s o , some specia l ized 47 engineering background is required to confident ly determine the cause o f breaks under response situations. Repair activities. W h i l e it m a y be diff icul t to determine and record the cause o f breaks, the response regarding the recording o f repair activit ies is h igh . The data i n F igure 2.4 show the percentage o f respondents that record a specif ic repair act ivi ty. Repa i r activit ies t yp i ca l ly inc lude repair ing clamps and jo in ts or replac ing sections o f pipes, valves , hydrants, and connections. T h i s cou ld be expla ined b y the fact that ut i l i t ies can more readi ly record response actions i n the f ie ld than determine the cause o f a water m a i n break. Environmental data. Env i ronmen ta l data related to water m a i n breaks inc lude informat ion such as air temperature, so i l acidi ty , and moisture, and other antecedent condi t ions. The environment is important for water mains as the N a t i o n a l Research C o u n c i l o f the N a t i o n a l A c a d e m i e s (2005) identifies that water m a i n breaks and their repairs are also potential gateways to contaminat ion o f the water dis t r ibut ion system. The survey responses show that ve ry litt le environmental informat ion is col lected b y respondents. O n l y 12 percent o f the respondents record environmental data for a l l o f their water m a i n breaks and o n l y 27 percent record any environmental data at a l l . In fact, environmental data is the least recorded group o f informat ion for a l l o f the respondents. I f a respondent col lects environmental informat ion, most l i k e l y it is informat ion on the depth o f frost (27 percent o f respondents). Less than 10 percent o f the respondents take so i l samples. T h i s is surprising as it is w e l l pub l i c i zed that there is a significant relationship between external cor ros ion o f water mains and s o i l condi t ions. F igure 2.5 shows the percentage o f the respondents that record a g iven type o f environmental data, or can obtain the data elsewhere either w i t h i n the ut i l i ty or f rom sources external to the u t i l i ty such as 48 other agencies. In some cases, a s ignif icant ly greater percentage o f respondents indicated that more data are avai lable from other sources than are recorded. Hydraulic models. W h e n asked whether the u t i l i ty has a water m o d e l and whether it is used, 78 percent o f the respondents report hav ing a hydrau l ic mode l . O n l y 71 percent o f the respondents use these models for some purpose. The most popular uses o f models i n descending order o f popular i ty (i.e., based on the percentage o f respondents) are for capital p lann ing (69 percent), development p lanning (61 percent), operations (56 percent), and maintenance purposes (42 percent ). Confidence in data. A k e y survey question regards the leve l o f confidence that a u t i l i ty places o n the phys i ca l data that it collects. U t i l i t i e s were asked i f their confidence i n the data col lected is h igh . The intent was to determine not o n l y the l eve l o f confidence but also i f this l eve l varies b y data type. The confidence o f the respondents i n selected parameters is summar ized i n F igure 2.6. A s shown i n F igure 2.6, at least 72 percent o f uti l i t ies have h igh confidence i n pipe diameter and material , but o n l y 48 percent are h i g h l y confident about the year o f instal lat ion. Level of comfort with the amount of data collected. U t i l i t i e s were asked to indicate their l eve l o f comfort w i t h the amount o f data col lected. S ix ty- four percent o f the respondents were comfortable w i t h the amount o f data col lected. H o w e v e r , 22 percent were not comfortable and 14 percent had no op in ion regarding their l eve l o f confidence i n the data col lected. The leve l o f comfort w i t h the amount o f data col lec ted varies w i t h u t i l i ty size. Be tween 50 and 60 percent o f respondents w i t h service populat ions between 10,000 and 100,000 and approximate ly 70 percent o f those serving between 100,000 and 500,000 are comfortable w i t h the amount o f data col lected. B o t h respondents w i t h service populat ions greater than one m i l l i o n were also comfortable w i t h their data. 49 Sources of data available to utilities. The addi t ional sources o f phys i ca l data for the respondents are summar ized i n Table 2.3. The number o f respondents that indicated that data were avai lable from the other sources is also listed. F o r example , 46 percent o f respondents ident i f ied other sources for obtaining normal operating pressures. Managers m a y use this table to consider s imi la r data sources w i t h i n their organizat ion. T h e y m a y also be encouraged to determine i f this informat ion is avai lable f rom other sources that are not as yet identif ied. Storage of data. Different sizes o f uti l i t ies have different means o f data storage. The use o f a G I S as a data management system is greatest for respondents that serve a popula t ion o f between 50,000 and 100,000 (four o f these ten communi t ies use G I S s ) , and archiva l records are the predominant source o f data for ut i l i t ies that serve a popula t ion o f between 10,000 and 50,000 (eight o f these fourteen communi t ies use archiva l records). O f the fifteen respondents that serve a popula t ion o f between 100,000.and 500,000, seven use archiva l records (such as as-builts and other paper-based h is tor ica l records) as a source o f water m a i n break data, and four use G I S s . S t a t i s t i ca l conf idence of the survey results. A l t h o u g h the number o f respondents is l o w , the survey results can be used to draw some inferences regarding the practices o f water uti l i t ies i n general. A statistical analysis o f the s ignif icance o f the survey sample for p r o v i d i n g observations for the general C a n a d i a n - U . S . u t i l i ty popula t ion was undertaken. The accepted measure range o f confidence l imi t s is calculated us ing W i l d and Seber (2000), to be between 11 percent and 13 percent for this survey. T h i s is to say that i f 63 percent o f the respondents indicate that they record w h e n water service is restored, w e m a y expect that more than 50 percent ( i . e . , the lower confidence l imi t ) but less than 75 percent 50 (i.e., the higher confidence l imi t ) o f a l l water ut i l i t ies i n the general popula t ion w o u l d record the same. A p p e n d i x B summarizes the statistical confidence o f these results. 2.4 DISCUSSION AND R E C O M M E N D A T I O N S W h i l e a l l respondents are co l lec t ing data, they c lear ly do not col lect a l l data suggested b y best practices recommended b y the Na t iona l G u i d e to Sustainable M u n i c i p a l Infrastructure ( N G S M I , 2002) and A W W A R F (Deb at al, 2002). H o w e v e r , based on the responses it is apparent that data acquis i t ion is evo lv ing and that there is a strong interest i n compar ing their practices w i t h others and w i t h best practices. Feedback f rom the respondents indicates that the average respondent spent about 30 to 45 minutes comple t ing the survey. Th i s is i n addi t ion to the t ime that respondents spent determining the appropriate people w i t h i n the organizat ion to complete the survey. S u c h decis ions are c o m m o n among larger organizations where responsibi l i t ies for data co l lec t ion , management and analysis are shared. The amount o f data that respondents and uti l i t ies i n general have can be categorized into general classes o f data richness. Based o n the survey results, it is suggested that four classes exist. These are: expanded, intermediate, l imi t ed and m i n i m a l data set classes. A s shown i n F igure 2.7, the proposed data set classes are based on the breadth and record length o f data irrespective o f the tradit ional data categories such as break, pipe inventory, and operational data because the survey results indicate that m a n y respondents col lect data i n va ry ing amounts i n each o f the tradit ional data categories. Expanded data sets are compr ised o f informat ion, and records over a long per iod o f t ime. These m a y include: an inventory o f pipes that is correlated to pipe informat ion such as diameter, material , year o f instal lat ion, type o f jo in t , surface cover, type o f failures, probable cause o f failure, type o f 51 repair, pipe testing informat ion such as pipe w a l l thickness at t ime o f break, type o f p ipe l i n ing , so i l testing informat ion such as corros iv i ty , and p H . Intermediate data sets are compr i sed o f informat ion on inventory and pressure zones, a break his tory o f some length o f t ime, and some amount o f informat ion regarding pipe diameter, mater ial , age, exterior surface condi t ion , and instal lat ion, surface cover, and pipe protection. A u t i l i ty possessing informat ion w i t h this degree o f data richness has general ized descriptions regarding the type o f failures encountered and probable cause o f those failures. T h i s case is s imi la r to the expanded data case but does not include pipe and so i l testing data al though instal lat ion details m a y be avai lable . Limited data sets have o n l y l imi t ed informat ion o n the pipe network, surface uses and loads. Th i s w o u l d be an inventory, informat ion regarding pressure zones and general ized p rob lem areas, a break his tory o f a m i n i m a l length o f t ime, and a n o m i n a l amount o f informat ion regarding pipe diameter, pipe mater ial , year o f instal lat ion, and surface.cover. U n d e r this case, the informat ion compr i s ing the intermediate data set is s ignif icant ly reduced. Minimal data sets are compr i sed o f p ipe lengths, ident i f icat ion o f pressure zones, general ized p rob lem areas, and n o m i n a l informat ion regarding pipe diameters. G i v e n that asset management is becoming important for u t i l i ty managers, more attention and effort should be g iven to i m p r o v i n g data co l lec t ion i n the f o l l o w i n g areas: Collect for the future. Managers need to consider the long v i e w w h e n assessing their data co l l ec t ion strategy. Water m a i n break data w i l l be useful for future asset managers w h o w i l l have to make diff icul t investment decis ions regarding w h i c h pipes to replace. Estimates for the U . S . ( U S E P A , 2002) suggest that the capi tal needs for d r ink ing water i n the U . S . for the per iod between 2000 and 2019 range f rom 154 to 446 b i l l i o n U . S . dollars. There are no s imi l a r estimates for Canada. Future managers w i l l need to make wise 52 decisions to take into account not o n l y the ab i l i ty o f the pub l i c to afford replac ing these pipes but also the scarcity o f human resources and capital to actual ly perform the work . Because the practice o f infrastructure asset management w i l l evolve , data requirements for m a k i n g c r i t i ca l decisions are important but can also be expected to grow. Thus , the data co l l ec t ion strategy for ut i l i t ies should be to gather the data recommended as best practices keeping i n m i n d that m u c h o f the data w i l l be useful for future management decisions rather than for today 's decisions. It w i l l l i k e l y take some t ime to establish a data record o f sufficient length to support such decisions. M a n y managers m a y resist this approach because they m a y prefer to k n o w what is needed and w h y before embark ing o n data co l lec t ion programs. In some cases, such a strategy m a y be undertaken w i t h l i t t le addi t ional effort. F o r example , a u t i l i ty m a y be able to accumulate more informat ion b y co l lec t ing addi t ional informat ion as part o f exis t ing tasks, such as a descr ipt ion o f the failure mode, bedding, b a c k f i l l and depth o f cover. T o facilitate asset management, data co l lec t ion efforts should also inc lude , where possible , the types and causes o f breaks, and the phys ica l data o f a l l mains so as to provide a deeper understanding o f the failure modes and mechanisms. R e c o r d d a t a effect ively. F o r co l l ec t ion practices to be effective, ut i l i t ies need to record data cont inuously , consistently, and accurately. D a t a should be col lected on a l l -breaks to ensure that the records portray the state o f the w h o l e system. M i s s i n g records m a y create a l eve l o f uncertainty regarding the records that are col lected and undermine the confidence i n conclus ions d rawn from technical analyses and lead to organizat ional frustration. In order to record data i n a consistent manner, the use o f standard operating practices, procedures, and forms as w e l l as t ra ining for those w h o col lect data are important. I f a 53 ut i l i ty is already co l lec t ing data, a r ev iew o f a l l data co l lec t ion forms is useful to ensure consis tency i n methods as w e l l as to expand the data col lected i f appropriate. A n audit o f the records for qual i ty and accuracy should be undertaken per iod ica l ly . A suggested m o d e l for an audit exercise is the formation o f a qual i ty control group w i t h i n the u t i l i ty to audit the data and ensure qual i ty across the organizat ion. Th i s group cou ld also develop guidelines o f practice for educating staff. The most efficient approach for recording data w i l l vary among uti l i t ies and should reflect business and w o r k f low processes and organizat ional structure o f the ut i l i ty . M a n y uti l i t ies m a y have different departments, such as laboratory, maintenance, technical , and f inancia l departments, and response teams that col lect or generate informat ion. In such cases, it m a y be benef ic ia l to bundle or group data based on organizat ional departments and develop a process for ensuring that the data are col lected, assessed for relat ional l inks related to other data, recorded and stored i n an effective manner. F o r example , data forms cou ld be circulated among selected departments w i t h i n the organizat ion to col lect input data comprehens ive ly and to improve the sharing o f informat ion among departments, or depending o n the data and organizat ion, the data co l l ec t ion process between departments c o u l d be independent but l i nked or related v i a an asset index. The storage o f data can be undertaken i n various ways (see Table 2.3), or i n a comprehensive data warehouse. Some uti l i t ies prefer a comprehensive data warehouse to facilitate the synthesis and v i sua l representation o f data and v i e w G I S technology as the ideal tool for this purpose. Alternate sources of data and relating data. The survey results c lear ly show that alternate sources o f data related to water m a i n breaks exist i n many organizations. Table 2.4 summarizes the potential range o f informat ion sources identif ied i n this w o r k for different 54 data elements. F o r example , current and future capi tal project designs, as-builts, or asset pro-formas can be used to capture informat ion such as specifications, test pit logs, and inspect ion records. U t i l i t i e s m a y w i s h to consider the concept o f a data web, w h i c h m a y be thought o f as a relat ional structure o f the u t i l i ty ' s data sources, i nc lud ing break records, maintenance reports, pipe and so i l samples, customer informat ion, a rchiva l systems, hydraul ic m o d e l output, capital rehabil i ta t ion p lann ing data, G I S s , and maintenance management systems. The l inks between these data sources, support the web, and are keyed to some index o f the asset, for example , a pipe ident if icat ion number. The use o f the l inks reduces the need to convert data when a new informat ion management system is developed and implemented and facilitates the synthesis o f exis t ing corporate data for specif ic analyses. A data web is not a data storage appl ica t ion nor software, but a concept o f relat ing or l i n k i n g data and separate data sources i n an organizat ion to each other. W h i l e the development o f a data web for a u t i l i ty reduces the need to convert and store data, the addi t ion o f data elements i n each data system, such as the asset index (e.g., corresponding to a p ipe ident i f icat ion number) m a y be required. A wel l -des igned data web w o u l d enhance u t i l i ty management, par t icular ly for sma l l communi t ies w h o cannot afford wholesa le data management system implementat ion, conversions and upgrades. D e s i g n considerations m a y include ident i f icat ion o f the architecture o f the web, the characteristics and number o f required l inks , and the appropriate connections between the elements to be "webbed" . Taci t informat ion or knowledge that is currently not recorded can also be l i nked w i t h i n the web. Decision support tools. In deve lop ing dec is ion tools for support ing asset management, ut i l i t ies should consider a range o f systems that are f lex ib le and easi ly accessible for both present and future uses. The systems should be rel iable and mainta ined 55 over t ime. D a t a that have been col lected are useless i f the dec i s ion makers w i t h i n the organizat ion cannot access them or are unaware o f their existence. A n a l y s i s o f the survey results suggests that dec i s ion support tools for p r io r i t i z ing the replacement or rehabi l i ta t ion o f water mains should be tai lored to the degree o f richness o f the data avai lable to a ut i l i ty . U t i l i t i e s that have a m i n i m a l amount o f data cannot use sophisticated tools such as phys ica l (Rajani and M a k a r , 2000) or statistical pipe deterioration models (Shamir and H o w a r d , 1979; Jacobs and Karney , 1994; A n d r e o u et al, 1987; K l e i n e r and Rajan i , 1999), or l i fe cyc le cost ing. These tools, and most recent research i n water dis t r ibut ion asset management have focused o n uti l i t ies that possess large amounts o f data and more research is required to develop robust approaches for uti l i t ies w i t h l imi ted or m i n i m a l data records. These tools should also be f lexible enough to adapt as uti l i t ies increase the amount and types o f data col lected. 2.5 CONCLUSIONS Studies, even as recent as i n 2004, have identif ied the need for standardized m a i n break databases and te rminology and continued research regarding database development as strategic for informed infrastructure management (e.g., G r i g g , 2004; O ' D a y et al, 1986). The results o f the survey reported herein indicate that water m a i n break data co l lec t ion is evo lv ing , that industry practices do not match best practices recommended b y the Na t iona l G u i d e to Sustainable M u n i c i p a l Infrastructure ( N G S M I , 2002) and A W W A R F (Deb et al, 2002) at this t ime, and that most respondents recognize the need for a strategy for data qual i ty improvement . The data-related challenges that a l l ut i l i t ies face inc lude di f f icul ty i n m o b i l i z i n g f inancia l and human resources, absence o f h is tor ica l data, lack o f knowledge o f 56 current organizat ional practices, l o w re l iab i l i ty o f p rev ious ly col lected data, d i f f icu l ty i n p r io r i t i z ing data co l lec t ion , and the need to develop effective data storage programs. W h i l e it is generally accepted that the use o f re l iable data regarding asset inventory and cond i t ion w i l l enhance the management o f m u n i c i p a l infrastructure (Vanie r , 2001), the feedback from the respondents is that data co l l ec t ion practices regarding both inventory and cond i t ion vary w i d e l y . Genera l data regarding customer locat ion, t ime o f break, and emergency response actions are t yp i ca l l y avai lable, but informat ion regarding specif ic pipe loca t ion and phys ica l attributes is inconsistent. M o s t respondents do not have a consistently h i g h l eve l o f informat ion regarding causes o f failure and so i l and pipe sampl ing are general ly not undertaken. Conf idence i n and comfort w i t h the amount o f data col lected varies; mid - s i ze respondents expressed the least l eve l o f comfort w i t h the amount o f data col lected. M a n y respondents identif ied addi t ional sources o f informat ion inc lud ing archival , operation and maintenance and G I S informat ion, and hydraul ic models . M o r e o v e r , hav ing a.hydraulic mode l does not guarantee that it is used. T h i s m a y depend o n the staffs' ab i l i ty to operate and main ta in the mode l and on the re l i ab i l i ty and currency o f the input data. W h i l e both phys i ca l and statistical models have been developed for predic t ing p ipe deterioration and for deve lop ing water m a i n rehabil i ta t ion plans, it is evident that the choice and appl ica t ion o f these models are l imi ted b y the data that ut i l i t ies have regarding water m a i n breaks (Rajani and K l e i n e r , 2001 ; K l e i n e r and Rajan i , 2001). In general, uti l i t ies can be classif ied as those possessing expanded, intermediate, l im i t ed or m i n i m a l data. Character izat ion o f these classes m a y be used to in form the development o f new asset management techniques such as condi t ion models or heuristics and new ways o f effectively 57 col lec t ing , storing, combin ing , and representing water m a i n break data. T h i s is a subject o f a for thcoming paper b y the authors. 2 . 6 A C K N O W L E D G E M E N T S The authors gratefully acknowledge those uti l i t ies w h o invested their t ime and effort i n comple t ing the survey and Professors A . D . R u s s e l l and J . A twa te r at the U n i v e r s i t y o f B r i t i s h C o l u m b i a and D r . D . V a n i e r at the N a t i o n a l Research C o u n c i l Canada, w h o guided the development o f the survey. M r . s G . P h i l l i p s (ret.), W . L i u and G . I r w i n o f the Dis t r i c t o f M a p l e R i d g e assisted i n survey development, d is t r ibut ion and compi la t ion ; M s . K . Feh rman o f the Canad ian Water and Waste A s s o c i a t i o n and M r . A . G a l l o f the A m e r i c a n P u b l i c W o r k s A s s o c i a t i o n promoted and distributed the survey to their respective organizations. W e are also grateful to D r . N . G r i g g at the Co lo rado State U n i v e r s i t y for his thoughtful r ev iew o f this manuscript . c 58 2.7 R E F E R E N C E S A n d r e o u , S., M a r k s , D . and C l a r k , R . , 1987. A new M e t h o d o l o g y for M o d e l i n g Break Fa i lure Patterns i n Deter iorat ing Water Di s t r ibu t ion Systems: Theory . Advances in Water Resources, 10:1:2-10. E l sev ie r Science, B . V . A S C E ( A m e r i c a n Socie ty o f C i v i l Engineers) , 1999. A m e r i c a n Soc ie ty o f C i v i l Engineers report card and issue briefs. Public Works Management and Policy, 4 :1 : 58-76. A W W A ( A m e r i c a n Wate r W o r k s Assoc ia t ion) , 2004. WA TER: \STA TS - The Water Utility Database. 2002 version [CD-ROM]. A m e r i c a n Water W o r k s Assoc i a t i on , Denver , C O . 80235. D e b , A . R . , Grab lu tz , F . M . , Has i t , Y . J . , Synder, J . K . , Longanathan, G . V . and A g b e n o w s k i , N . , 2002. P r i o r i t i z i n g Water m a i n Replacement and Rehabi l i ta t ion . A W W A Research Foundat ion , 6666 W e s t Q u i n c y A v e n u e , Denver , C O . 80235. Ear th Tech , 2004. N a t i o n a l Water and Wastewater B e n c h m a r k i n g Init iat ive F i n a l Results -June 2004. Ear th T e c h , Burnaby , B C . Ear th Tech , 2003 . N a t i o n a l Water and Wastewater B e n c h m a r k i n g Init iat ive- Water U t i l i t y Def in i t ions 2003 Release B . , Ear th Tech , Burnaby , B C . G r i g g , N . S., 2004. Assessment and renewal o f water dis t r ibut ion systems. A W W A Research Foundat ion , 6666 Wes t Q u i n c y A v e n u e , Denver , C O . 80235. 59 Jacobs, P . and K a m e y , B . , 1994. G I S development w i t h appl icat ion to cast i ron water m a i n breakage rates. 2nd International Conference on Water Pipeline Systems, Ed inburgh , Scot land, B H R Group . 53-62. K l e i n e r , Y . and Rajan i , B . B . , 2001 . 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A W W A Research Founda t ion ( A W W A R F ) and U S Env i ronmen ta l Protect ion A g e n c y ( U S E P A ) , A W W A Research Foundat ion , 6666 Wes t Q u i n c y A v e n u e , Denver , C O . 80235. 60 Rajani , B . B . and K l e i n e r , Y . , 2001 . Comprehens ive rev iew o f structural deterioration o f water mains: p h y s i c a l l y based models . Urban Water, 3:3: 151-164. Rajan i , B . B . and M a k a r , J . , 2000. A methodology to estimate remain ing service l ife o f grey cast i ron water mains. Canadian Journal of Civil Engineering, 27:6: 1259-1272. Shamir , U . and H o w a r d , C , 1979. A n analytic approach to schedul ing pipe replacement. Journal AWWA, 71:5: 248-258. U S E P A , 2002. C l e a n Water and D r i n k i n g Water Infrastructure G a p A n a l y s i s , Env i ronmen ta l Protect ion A g e n c y , Off ice o f Water , D r i n k i n g Water D i v i s i o n , Wash ing ton , D C . U S E P A , 2001 . D r i n k i n g Water Infrastructure Needs Survey. 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Y . 61 Table 2.1 Service population of respondents Service Population >1,000 but <5,000 <10,000 <50,000 <100,000 <500,000 <1 million >1 million Total Canadian utilities a l b 2 8 9 6 3 1 30 U.S. Utilitiesc 1 13 3 11 1 29 Total responses 1 3 21 12 17 3 2 , 59 a) Canad ian respondents were from A l b e r t a (5), B r i t i s h C o l u m b i a (9), M a n i t o b a (2), N e w B r u n s w i c k (2), N e w f o u n d l a n d (1), N o v a Scot ia (1), Ontar io (6) and Saskatchewan (4). A n incomplete survey was received f rom one Quebec mun ic ipa l i t y so its response was not inc luded i n the analysis. A d m i t t e d l y , the survey was i n E n g l i s h and m a y be a reason for the l o w number o f responses from Quebec. b) Popu la t ion served is approximate ly 2600. c) U . S . respondents were from A l a s k a (1), A r i z o n a (1), C a l i f o r n i a (3), Co lo rado (1), F l o r i d a (1), I l l ino is (1), Kansas (2), Massachusetts (1), M a r y l a n d (1), M i c h i g a n (1), M i n n e s o t a (1), M i s s i s s i p p i (1), N o r t h C a r o l i n a (1), N e v a d a (1), Pennsy lvan ia (1), South D a k o t a (1), Tennessee (1), Texas (3), U t a h (1), Wash ing ton (4) and W i s c o n s i n (1). 62 Table 2.2 Percentage of respondents that record location data Location Data Percentage of respondents that record location data Nearest property address 9 3 % Cross street name 7 8 % Dis tance f rom cross street 4 4 % Isolat ion va lve operated 3 6 % Dis tance from nearest property l ine 3 4 % Coordinates (northing and easting) 10% 63 Table 2.3 Additional sources of break-related physical data for respondents Number of respondents having additional sources Archival O & M 7 GISs2 Other Normal operating pressure 27 X X X Models , . f i r e f low tests Traffic classification or type of road usage 23 X X X Exte rna l sources and traffic management systems Year of installation 22 X X X Typical flow in area of break 21 X X X M o d e l s Pipe wall thickness / classification 19 X X X Externa l sources Type of pipe lining 16 X X X Exte rna l sources Length of pipe segment containing the repair 14 X X X3 Pipe protection (wrapped / anodes) 13 X X X Under boulevard or roadway 12 X X Exte rna l sources Surface material 11 ' X X Pavement management systems Depth of cover 9 X X Type of joint 8 X X X Bedding material 8 X X Type of water service 7 X X Category of native soil 7 X X X Pipe fracture toughness 4 X X Externa l sources Backfill material 4 X X Pipe modulus or rupture 3 X Externa l sources Pipe sample collected 2 X M a i n tappings 64 Condition of cement lined pipe interior 2 X4 1 M o d e l s Pipe material 1 X Pipe diameter 1 X Condition of unlined pipe interior 1 X Condition of bedding 1 X Condition of pipe exterior 1 X 1 Operation and Maintenance records (O&M) 2 Geographic Information Systems (GISs) 3 GISs are the most popular source of length ofpipe segment containing repair data. 4 Evaluated with swabbing. 65 Table 2.4 Suggested sources and approaches for collecting physical data on water main breaks i Physical data Suggested sources of information P i p e diameter Bes t captured i n the f ie ld dur ing break repairs and avai lable f rom as-builts D e p t h o f cover Best captured i n the f ie ld dur ing break repairs and avai lable f rom as-builts P ipe mater ial C o u l d be captured i n the f ie ld dur ing break repairs, avai lable f rom as-builts and analyzed off-site, e.g., i n a laboratory for determining the different types o f cast i r on pipes C o n d i t i o n o f bedding C o u l d be captured i n the f ie ld dur ing break repairs and also obtained w i t h extra f ie ld w o r k Category o f native s o i l C o u l d be captured i n the f ie ld dur ing break repairs, determined from other records and also c o u l d be analyzed i n a laboratory C o n d i t i o n o f un l ined pipe interior C o u l d be captured i n the f ie ld dur ing break repairs, and also cou ld be analyzed i n a laboratory C o n d i t i o n o f p ipe exterior C o u l d be captured i n the f ie ld dur ing break repairs and slo cou ld be analyzed i n a laboratory T y p e o f water service C o u l d be captured i n the f ie ld dur ing break repairs or f rom other sources o f informat ion (e.g. l and use plans) Surface mater ial C o u l d be captured i n the f ie ld dur ing break repairs or from other sources o f informat ion (e.g. models) Surface use (under boulevard or roadway) C o u l d be captured i n the f ie ld dur ing break repairs or from other sources o f informat ion (e.g. mode l ) Traff ic c lass i f icat ion or type o f road usage C o u l d be captured i n the f ie ld dur ing break repairs or from other sources o f informat ion (e.g. transportation p lan , traffic models) " 1 L e n g t h o f p ipe segment conta ining the repair C o u l d be captured i n the f ie ld dur ing break repairs Or obtained w i t h addi t ional f ie ld work , or f rom as-builts or G I S B e d d i n g mater ial C o u l d be captured i n the f ie ld dur ing break repairs, m a y be avai lable f rom as-builts and other sources and/or bundled w i t h informat ion gained through addi t ional f ie ld w o r k P ipe protect ion (wrapped/ anodes) C o u l d be captured i n the f ie ld dur ing break repairs, m a y be available f rom as-builts and other sources and/or bundled w i t h informat ion gained through addi t ional f ie ld w o r k 66 Physical data Suggested sources of information T y p e o f jo in t C o u l d be captured i n the f ie ld (bundled w i t h informat ion gained through addi t ional f ie ld w o r k or from other sources o f informat ion (e.g., archives or construct ion inspect ion records) Y e a r o f instal lat ion M a y be avai lable f rom as-builts or other a rchiva l records such as construct ion inspect ion reports B a c k f i l l material M a y be avai lable f rom as-builts or other a rchiva l records such as construct ion inspect ion reports T y p i c a l f l ow i n area o f break Techn ica l tools (e.g., models) N o r m a l operating pressure Techn ica l tools (e.g., models) C o n d i t i o n o f cement l ined pipe interior M a y be avai lable from as-builts and better analyzed i n a laboratory for current condi t ion P ipe modulus o f rupture M a y be avai lable f rom as-builts and better analyzed i n a laboratory for current cond i t ion T y p e o f p ipe l i n i n g M a y be avai lable from as-builts and better analyzed i n a laboratory for current condi t ion P ipe w a l l thickness/classif icat ion M a y be avai lable from as-builts and better analyzed i n a laboratory for current cond i t ion P ipe fracture toughness M a y be avai lable from as-builts and better analyzed i n a laboratory for current condi t ion 67 Figure 2.1 Percentage of respondents that collect general information X X Mfy. fc \ \ \ \ s0 'fc «&. ^ v i>3 °o- % \ •\ x So <5-w ft ^ V '-fc x . %3 ^p ^ p ^p ^ p s O ^p cv*" o"^ cf^ cT^ cr^ cf^ D O O O O O O O O O O : O ) O O N ( D I T ) ^ C O C M T -So 68 Figure 23 Percentage of respondents that record failure causes s 70 Figure 2.4 Percentage of respondents that record repair activities 1 0 0 % 9 0 % 8 0 % 7 0 % 6 0 % 5 0 % 4 0 % 3 0 % 2 0 % 1 0 % 0 % i 4 # ^ y / 71 Figure 2.5 Percentage of respondents that collect different types of environmental data 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% • Data recorded • • Data recorded and/or available from other sources <0* , 0 s I I 72 Figure 2.6 Percentage of respondents that expressed confidence in data collected Figure 2.7 Classes of data richness among water utilities Increasing data collected or available for analysis (regardless of data categories, e.g., pipe inventory, break data, operational data) 74 CHAPTER 3 CONSTRUCTING WATER MAIN BREAK DATABASES FOR ASSET MANAGEMENT A version of this paper has been accepted and scheduled for publication in the January 2007 issue of Journal AWWA. The paper is titled as Constructing Water Main Break Databases for Asset Management by A. Wood, B. J. Lence and W. Liu. 75 P R E F A C E The survey results as reported i n Chapter 2 conf i rm that a number o f sources o f data exist for use i n ana lyz ing water m a i n breaks. In fact, the figure shown b e l o w (reference Figure 2.2) inspi red m y interest i n deve lop ing an approach for obta in ing and m a x i m i z i n g data from different sources internal and external to the ut i l i ty . I f ut i l i t ies can obtain and integrate data from a wide variety o f sources for analysis, they should be able to improve the breadth and richness o f their water m a i n break data for asset management. Getting data from other sources can help utilities ggo/ o _ JLg^B^^ • Data available from break records ( I n n H Data available from break records and other sources 8 0 % " ~ ~ H ~ ~ 6 0 % - J J - | -50% - J 40%- I I I I I n n 0 A k e y considerat ion for uti l i t ies is storage and management once the data are created. The focus o f h o w to manage data i n the Asse t Management Systems current ly being marketed is on consol idat ing a l l data into one large database (e.g., M A X I M O and 76 Hansen) . Conve r t i ng and consol idat ing data into one database is expensive, resource intensive^ and creates data ownership confl icts . It is unrealist ic to expect sma l l and m e d i u m water ut i l i t ies to make the f inancia l and organizat ional investment to achieve such as database artd thus this is a significant barrier to i m p r o v i n g asset management. The research presented i n this chapter describes an approach for accompl i sh ing the acquis i t ion and integration o f data f rom other sources for analysis and m a y be used to foster d iscuss ion between var ious departments on h o w asset management data can be managed and coordinated w i t h i n an organizat ion. The research provides techniques and approaches for creating data, constructing databases and relat ing those databases to each Other. M o s t important ly, this w o r k can be appl ied to practice, and has been the case o f the L a i t y V i e w area o f M a p l e R i d g e . F o r M a p l e R i d g e , the research resulted i n the construct ion o f a water m a i n break database, the compi l a t i on o f so i l type data w i t h w h i c h to analyze the relat ionship between s o i l and water m a i n breaks, a r ev iew o f the current water m a i n replacement p o l i c y (o f so le ly replac ing asbestos cement pipes), a survey o f s o i l and cor ros ion potential and a renewed staff interest i n i m p r o v i n g the process and framework o f dec id ing w h y , w h i c h and w h e n pipes should be replaced. In addi t ion, the approach o f constructing databases from different sources and relat ing databases has been adopted b y staff for deal ing w i t h a l l water system data and is be ing explored for use w i t h M a p l e Ridge ' s sewer system. 77 3.1 I N T R O D U C T I O N The tradit ional pub l i c w o r k s emphasis o n managing water m a i n breaks has been directed toward m i n i m i z i n g the loss o f water to k e y businesses and cr i t i ca l facil i t ies (such as hospitals and industr ial plants) and m i n i m i z i n g the damage to bui l t and natural infrastructure. H o w e v e r , breaks are also potential gateways to contaminat ion o f the water dis t r ibut ion system and have been identif ied as a h i g h pr ior i ty i n the assessment o f water supply health r isks b y the Na t iona l Research C o u n c i l o f A c a d e m y Sciences (2005). Pred ic t ing water m a i n breaks to reduce such r isks and op t imize the investment i n aging infrastructure requires rel iable p ipe data. These data include age, diameter and material for the subject dis t r ibut ion system and the number and nature o f breaks that occur i n the water mains. A recent study identifies a need for standardized m a i n break databases and cont inued research regarding database development ( G r i g g , 2004). B a s e d o n a 2004 survey o f N o r t h A m e r i c a n uti l i t ies, W o o d and Lence (2006) observe that water m a i n break data co l l ec t ion is e v o l v i n g and industry practices do not match best practices recommended b y the N a t i o n a l G u i d e to Sustainable M u n i c i p a l Infrastructure ( N G S M I , 2002) and A W W A R F (Deb et al, 2002). F o r u t i l i ty managers, co l lec t ing , recording and mon i to r ing water m a i n breaks is also important because such events m a y be used to ga in insights for the management o f the entire network. T h i s informat ion is important i n developing the tradeoffs between expenditures and leve l o f service provided , and i n managing rehabil i ta t ion programs to achieve a desired leve l o f service. F o r example, many ut i l i t ies focus their water m a i n replacement program on tolerating a certain leve l o f breaks i n the water dis t r ibut ion system, or perhaps through targeting replacement o f water mains o f a part icular vintage, or o f a mater ial that is prone to breaks. 78 W o o d and Lence (2006) suggest a number o f sources o f data that m a y be used for i m p r o v i n g a uti l i ty 's data breadth and richness for ana lyz ing water m a i n breaks. Th i s paper introduces an approach for constructing a water m a i n database w h i c h is based o n l i n k i n g or " re la t ing" data f rom sources internal and external to a u t i l i ty for the purpose o f knowledge discovery , or i n other words relating relational databases. Issues related to creating, l i n k i n g , t ransforming, c leansing, scrubbing and integrating data are ident i f ied and approaches for addressing them are presented. T h i s approach m a y assist ut i l i t ies i n deve lop ing data acquis i t ion and management strategies and gu id ing knowledge discovery . R e c o g n i z i n g that data co l l ec t ion and storage is organizat ional ly dr iven , the approach is designed to be easi ly adapted. The approach l inks informat ion among mul t ip le databases and respects decentral ized data input i n order to mainta in ease o f data storage and management. T h i s reduces the need for wholesale convers ion o f data to a central database and is l i k e l y to be cost effective for sma l l to mid- s i ze uti l i t ies. The decentral ized approach to database construct ion requires coordinat ion o f data acquis i t ion, personnel and a clear strategy for encouraging departmental cooperation. T o demonstrate the eff icacy o f this approach for use i n ana lyz ing and predic t ing breaks i n a water dis t r ibut ion system, a data schematic is created for ana lyz ing water mains and predic t ing future breaks for the L a i t y V i e w area o f the Dis t r i c t o f M a p l e R i d g e , B C . The development o f a data schematic is not mere ly a data storage exercise. Rather it is the creation o f l inkages that can be used to aggregate informat ion for analysis and that a l l ow data to be updated over t ime. The l inkages are created among p r imary and secondary data sources. F o r example, a mun ic ipa l i t y m a y not have a transportation p lan that specifies traffic vo lumes , but i f knowledge o f the v o l u m e o f vehic le traffic over a water m a i n is 79 desired, it m a y be able to use v o l u m e data f rom a traffic management system database. The use o f data f rom different sources provides f l ex ib i l i t y for ut i l i t ies to focus o n co l lec t ing data for future analyses without hav ing to commi t to specific appl ica t ion software. 3.2 S T A T E O F D A T A IN UTILITIES Water m a i n break data co l lec t ion practices va ry across ut i l i t ies and for many uti l i t ies , data co l lec t ion can have significant costs i f performed at a comprehensive leve l . These costs inc lude direct f inancia l costs as w e l l as organizat ional effort and human resources. The challenges o f co l lec t ing data include d i f f icu l ty i n m o b i l i z i n g f inancia l and human resources, absence o f h is tor ica l data, lack o f knowledge o f current organizat ional practices, poor re l i ab i l i ty o f p rev ious ly col lected data, compl ica t ions due to the emergency-oriented co l l ec t ion condi t ions w h e n breaks occur, d i f f icul ty i n p r io r i t i z ing co l l ec t ion efforts, and the need to develop effective data storage programs ( W o o d and Lence , 2006). In recent years, m a n y uti l i t ies have been deve lop ing improved data acquis i t ion and management strategies for water m a i n breaks and i n some cases us ing third parties for analyt ical tasks for obta ining specia l ized data such as so i l conduct iv i ty . M o s t munic ipa l i t i es do have some informat ion regarding their water pipes and condi t ions, but few have been main ta in ing records o f pipe breaks for longer than a decade, and ve ry li t t le informat ion is available regarding i n d i v i d u a l pipes i n a g iven network (Pellet ier et al, 2003). In a case study o f three munic ipa l i t i es i n Quebec, they found that o n l y s ix parameters (diameter, length, type o f material , year o f instal lat ion, type o f s o i l and land use above the pipe) were available for analysis. In recent years, best practices have been identif ied for water m a i n break data co l lec t ion (Deb et al, 2002; N S G M I , 2002). W o o d and Lence (2006) surveyed N o r t h A m e r i c a n uti l i t ies and conducted detailed 80 interviews to determine the richness o f data avai lable to uti l i t ies for ana lyz ing water m a i n breaks. T h e y found that ut i l i t ies i n general can be categorized into general classes o f data richness. These are the: expanded, intermediate, l imi t ed and m i n i m a l data set class. The data set classes are based o n the breadth and record length o f data irrespective o f the tradit ional data categories such as break, p ipe inventory, and operational data because the survey results indicate that m a n y respondents col lect data i n va ry ing amounts i n each o f the tradit ional data categories. The results o f the survey also showed that w h i l e m a n y uti l i t ies do not t yp i ca l ly have a c o m m o n break and water m a i n database or the appropriate data, they m a y f ind relevant informat ion avai lable elsewhere i n their organizat ion and use this informat ion to expand their database. 3 . 3 W A T E R M A I N B R E A K D A T A F O R ASSET M A N A G E M E N T T w o cha l lenging asset management issues are the determination o f remain ing service l ife and the pr ior i t i za t ion o f rehabil i tat ion efforts. B o t h o f these issues re ly o n knowledge discovery . T o determine remain ing service l i fe , one must be able to assess the cond i t ion o f a pipe and the expected remain ing l ife or some measure o f h o w long a g iven p ipe can be expected to last f rom the date o f instal lat ion. It is diff icul t to determine the exact c o n d i t i o n e d bur ied pipes because they are diff icul t to comprehens ive ly inspect. A s a m i n i m u m , uti l i t ies should have a database o f water m a i n breaks because the occurrence o f breaks m a y reflect the condi t ion o f a pipe and typ ica l ly the number o f annual water m a i n breaks is used as a surrogate for the condi t ion o f the network. H o w e v e r , breaks do not necessari ly reflect pipe condi t ion as there are many causes o f breaks such as damage from adjacent construct ion and frost heave. 81 Once pipe condi t ion is determined, the ca lcula t ion o f remain ing service l ife can be made us ing deterioration models that predict when failure or future breaks w i l l occur. These models m a y be either statistically or p h y s i c a l l y based. The concept o f remain ing service l ife is that, g iven use and t ime, a l l pipes w i l l reach a point w h e n they are replaced for reasons such as poor condi t ion , perception o f poor re l i ab i l i ty or the need to increase hydrau l ic capacity. Rajan i and M a k a r (2000) define the t ime o f death o f a p ipe as the t ime at w h i c h its mechanica l factor o f safety falls b e l o w an acceptable value. K l e i n e r and Rajani (1999) propose that the useful l i fe o f a p ipe is a function o f the economic costs o f deterioration and replacement and suggest that pipe death coincides w i t h the op t imal t ime o f replacement. P r io r i t i za t ion o f rehabil i tat ion efforts i nvo lve the t i m i n g and schedul ing o f repairs or replacement o f pipes. T h i s is c lose ly t ied to reso lv ing f inancia l and technical challenges as to whether to mainta in , repair or renew an asset or to choose an alternative such as tw inn ing a water m a i n or constructing an alternative water ma in . P r io r i t i za t ion is compounded b y uncertainty regarding avai lable funds and organizat ional trends w h e n longer-term p lann ing hor izons are considered. M a n y engineers have faced circumstances where short-term solutions m a y not be the most economica l i n the long term but are the most expedient, for instance w h e n a m a i n is repeatedly repaired instead o f replaced because capital replacement funds are di f f icul t to obtain, but emergency operating funds are avai lable . D e b et al. (2002) describe four general approaches for p r io r i t i z ing pipes for replacement: the Deter iora t ion Poin t Ass ignment method ( D P A ) , break-even analysis, failure p robabi l i ty and regression methods, and mechanis t ic methods. K l e i n e r and Rajani (2001) suggest that o n l y larger diameter mains w i t h cos t ly consequences o f failure m a y jus t i fy the data co l lec t ion efforts and costs required to calibrate mechanis t ic models . D e b et 82 al. (2002) suggests that break-even analyses be augmented w i t h predic t ive techniques for pipe breaks, such as failure probabi l i ty , regression and mechanis t ic methods. Other considerations for p r io r i t i z ing water m a i n replacements also include re l i ab i l i ty ( X u and Goul ter , 1998), consequence o f failure (Cooper et al, 2000), considerat ion o f other assets ( G r i g g , 2004; V a n i e r , 2001) , and on-going engineering and management processes. D a v i s (2000) suggests that for ana lyz ing the impact o f changes i n a water m a i n rehabil i ta t ion strategy, an agent-based approach is p romis ing . Agents are defined as information-processing systems and are based on ar t i f ic ial intel l igence approaches. D a v i s proposes a loose ly coupled generic agent-based dec i s ion support f ramework for water uti l i t ies. In this framework, agents are used to extract data from infrastructure, Geographic Information Systems ( G I S ) and strategic databases. Agents are also used to cleanse data, interface w i t h other databases, predict pipe deterioration and assist i n deve lop ing rehabil i ta t ion strategies. S m a l l to m e d i u m size uti l i t ies often do not have staff w i t h the sk i l l s to implement agent-based approaches. F o r these ut i l i t ies , an approach that employs engineering expertise and c o m m o n data processing systems is l i k e l y to be more feasible. K n o w l e d g e d i scovery is the process o f ident i fying v a l i d , useful and ul t imate ly understandable patterns i n data (Torra et al, 2004). The analysis o f water m a i n breaks is l imi t ed b y the challenges faced i n constructing databases such as l im i t ed personnel and resources, m i s s ing and conf l ic t ing data, and non-computer ized informat ion (Pellet ier et al, 2003; H a b i b i a n , 1992; and O ' D a y , 1982). Furthermore, baby-boomer staff o f many uti l i t ies w i l l retire over the c o m i n g years and data m i n i n g w i l l be overshadowed b y the issue o f data creat ion and storage because m u c h water dis t r ibut ion data are ora l ly recorded or are stored i n discrete departmentally managed databases rather than i n a central database. 83 3.4 C O N S T R U C T I N G W A T E R M A I N D A T A B A S E S The approach for sourcing, constructing and l i n k i n g water m a i n break data proposed herein is to create a connected data schematic and undertake knowledge d i scovery based o n these data as s h o w n as F igure 3.1. Identifiers that are shared among databases are used to loose ly associate and relate data across databases, as represented b y the w a v y l ines i n the figure. D a t a f rom different databases such as p ipe break data files, s o i l characteristics maps, ortho-photographs, as-builts and o ra l ly recorded informat ion are l i n k e d b y creating identifiers i n each data source that are c o m m o n to one or more sources. F o r example, specific p ipe segments, surface mater ial and break data can each be assigned a c o m m o n pipe ident i f icat ion number (pipe ID) . Information that are o n l y o ra l ly recorded and transmitted between staff or no longer documented w i t h i n an organizat ion m a y be used to "create" data that can be ver i f ied and integrated for analysis. Cons t ruc t ion standards and practices and manufacturer data can be identif ied through interviews. Da ta from external sources such as the U S Department o f Agr i cu l tu re ( U S D A ) and Canad ian S o i l Survey ( C S C ) can also be related. The database is created us ing processed and b lended data. The process ing and b lend ing o f data is performed b y technical specialists us ing tools such as G I S , spreadsheets and databases. A n a l y s i s o f the data can then be performed to ident ify ne twork performance inc lud ing the occurrence o f water m a i n breaks, complaints and pressure deficiencies. These can be accompl i shed w i t h var ious approaches such as statistical, phys i ca l and neural network mode l ing and r i sk analysis. F r o m the analysis and knowledge discovery , uti l i t ies can develop strategies to predict the remain ing service l ife and pr ior i t i ze rehabil i tat ion efforts. 84 Identifying the Purpose of Analysis. The first step is to identify the purpose for w h i c h the data are to be analyzed. In addi t ion to asset management, objectives such as , performance measurement and improvement , research and development, cost recovery o f services, transparency and pub l i c accountabi l i ty m a y be identif ied. Af t e r the purpose is established, the data required m a y be determined, i.e., i f the purpose o f the analysis is to determine factors associated w i t h breaks that lead to service l ife estimates, the data should include p ipe material , age and diameter. Asse t management analyses o f pump stations require horsepower rating, pump run times, v ibra t ion levels and maintenance details. Pavement asset management requires data o n pavement thickness, sub-base material , A n n u a l Ave rage D a i l y Traff ic ( A A D T ) and type o f axle loading . The purpose o f the analysis affects the design o f the schematic, the re l i ab i l i ty o f the relat ionships between the elements and the degree o f informat ion transferred across a l ink . Developing a data schematic. A data schematic identifies the data required, their potential sources and i f and h o w they are related. The schematic should be constructed cons ider ing the characteristics o f the data elements i nc lud ing the ava i lab i l i ty o f data, whether sources are p r imary or secondary or require interpretation, whether data can be obtained f rom para l le l or through a series o f sources, the confidence i n and explici tness o f the data, and h o w data m a y be l inked . In addi t ion, data can be obtained f rom mul t ip le sources and some sources m a y be more read i ly avai lable than others. Pa ra l l e l sources contain the same or related data and data can be d rawn i n para l le l , w h i l e sources that are i n series contain data that i n some w a y can be related to each other and are d rawn i n series. Once sourced, data can be l i nked across var ious databases us ing identifiers that are unique for specif ic databases or are c o m m o n across a number o f databases (e.g., a c o m m o n pipe I D number). L i n k i n g data f rom various sources also a l lows for the updat ing o f the various 85 . sources o f data as a result o f analysis, knowledge d iscovery or further research. F o r instance, i f the purpose o f the analysis is to determine i f water mains under heav i ly traveled roads experience higher rates o f water m a i n breaks, data o f interest inc lude the surface material , road function and traffic vo lumes . I f current network pipe data do not inc lude these attributes, surface ortho-photographs m a y be used to determine the surface mater ial . The road funct ion o n the surface over a water m a i n m a y be determined us ing a transportation p lan . Al te rna t ive ly , i f the transportation p lan does not contain road use data, but traffic counts or a traffic network p lan exist, this informat ion m a y be used to determine traffic loading . I d e n t i f y i n g Sources o f da ta . W o o d and Lence (2006) provide a l ist o f alternate secondary sources for break-related data based o n survey respondents ' wri t ten observations and personal interviews. O n their o w n , these data are not ve ry useful for ana lyz ing breaks, but w h e n combined , they can provide useful informat ion for deve lop ing rehabi l i ta t ion and operation and maintenance strategies. The f o l l o w i n g is a detai led d iscuss ion o f the alternative sources that ut i l i t ies should consider i n b u i l d i n g a water m a i n break database. N e t w o r k data. N e t w o r k data m a y be available f rom G I S s , Asse t Management ( A M ) / Fac i l i t i es Management ( F M ) systems, databases, spreadsheet systems and other analyt ical models , e.g., hydrau l ic models . Other sources o f data inc lude Superv isory C o n t r o l and D a t a A c q u i s i t i o n ( S C A D A ) systems and moni to r ing systems. A M / F M and S C A D A systems typ i ca l l y are enterprise systems, used b y m a n y departments throughout an organizat ion, store large amounts o f data on large server databases and operate o n a client-server environment. A M / F M systems col lect and store maintenance, repair and f inancial informat ion w h i l e S C A D A systems col lect and store operating data such as pump-run times, pressure and hydrau l ic data. 86 I f G I S s are be ing used for network mapping , each pipe i n the system is g iven an i nd iv idua l p ipe I D and m a y have corresponding informat ion such as year o f instal lat ion, length o f pipe segments, diameter and material . The length o f p ipe segment is typ ica l ly obtained f rom the geometry o f the spatial f i le and are usua l ly col lec ted f rom as-builts as part o f the construct ion o f the G I S . M a n y uti l i t ies use hydraul ic models for their water, sewer and drainage infrastructure. H y d r a u l i c models contain informat ion such as f low, pressure and pipe layout that can be useful for analysis o f water m a i n breaks and asset management. F o r example, roughness, mass balance discrepancies and hydrau l ic losses calculated i n a m o d e l can be indicat ions o f pipe condi t ion . A s - b u i l t drawings, previous construct ion standards, staff experience, purchasing records, manufacturer specifications, inspector and surveyor f ie ld notes, m a i n tappings, f lushing records, swabbing , laboratory, hydrant fire f l ow testing, inspections, water qual i ty testing results, and customer complaints m a y be used to indicate informat ion such as the bedding and b a c k f i l l material , depth o f cover, type o f jo ints , p ipe protection, o r ig ina l p ipe w a l l thickness, current w a l l thickness, cond i t ion o f pipe interior and leve l o f internal corros ion. Surface data. Sources for surface material , land use and traffic load ing data include h igh resolut ion (e.g., 0.15 metre / 6 inches) ortho-photographs and as-built drawings. L a n d use and transportation plans, G I S maps o f roads and o ra l ly recorded knowledge o f types and ratios o f road users, and traffic patterns provide informat ion about surface use, traffic loading, and potential sources o f damage from surface activit ies. Ortho-photographs m a y be loaded into G I S as a "background theme" and over la in w i t h the p ipe network to generate drawings to determine surface mater ial data for each pipe. T h i s m a y reduce the need for f ie ld surveys. V 87 S o i l data. S o i l data are avai lable from both p rov inc i a l and federal government databases i n Canada and analogous sources i n the U S . The C S C N a t i o n a l S o i l Database contains the s o i l types for a l l o f Canada and is the national reposi tory for survey informat ion f rom the broad (1:1 m i l l i o n scale) to the detailed leve l (1:10,000 to 1:250,000 scale). The U S D A Na tu ra l Resources Conserva t ion Service is responsible for the N a t i o n a l Coopera t ive S o i l Survey w h i c h includes the efforts o f federal, state, and academic institutions (Rossiter, 2005). The Wash ing ton Suburban Sanitary C o m m i s s i o n has developed so i l cor ros iv i ty maps based o n U S D A so i l survey results (Habibian,1992) . W h i l e agricul tural surveys m a y be l imi t ed i n terms o f their usefulness i n cor ros ion analysis, w h e n combined w i t h a so i l sampl ing or survey program, they m a y be used to p rov ide a general understanding o f the so i l condi t ions. U t i l i t i e s should also r ev iew boreholes and logs f rom previous studies, w e l l d r i l l i n g data and informat ion gathered on construct ion projects. S o i l permeabi l i ty data and water table informat ion can be useful for drainage and sanitary sewer i n f l o w and inf i l t ra t ion analysis. Other sources o f data. U t i l i t i e s should explore the data col lected b y others or used w i t h i n the organizat ion such as mapp ing o f envi ronmenta l ly sensitive areas, pavement management systems and infrastructure plans. Env i ronmenta l informat ion such as water and ambient temperature and the frequency o f frost, m a y be avai lable f rom water qual i ty testing, weather and environment agencies. Gas p ipel ine , electr ical , t e lecommunica t ion or other ut i l i t ies operating i n the area m a y have informat ion o n s o i l data, stray currents and the cor ros iv i ty o f soi ls . Information that are not recorded but avai lable o ra l ly from staff can be obtained b y us ing interviews o f staff to determine, for example, the type o f bedding and b a c k f i l l material , p ipe l i n i n g and pipe protection. Whenever possible , ver i f ica t ion o f observations 88 is recommended. B r o a d surveys and spot testing are other techniques to consider w h e n obta ining data. F o r example, a program that samples s o i l for cor ros iv i ty and relates the agricul tural classif icat ions to soi ls can y i e l d insights into potential corros ion hot spots and focus moni to r ing efforts. L i n k i n g da ta . The objective o f connect ing or l i n k i n g data is b y relat ing relat ional databases to support on-demand data analysis. Da ta from mul t ip le sources m a y be l i nked i n series, or para l le l or remain un l inked . Th i s approach can facilitate the updating o f the analysis data set as data sources are updated and thereby support future knowledge discovery . Information processing tools, such as G I S s , spreadsheets and databases can be used to create electronic records, manipulate and analyze data. Output f rom these tools is also easi ly exported to other, comprehensive databases. G I S shape files can conta in a m y r i a d o f informat ion that m a y be v i e w e d and exported for analysis us ing other analyt ical software such as spreadsheets and databases. Depend ing o n the expertise and sk i l l s o f those ana lyz ing the data for knowledge discovery , ut i l i t ies m a y choose to use a spreadsheet fi le as the m a i n data analysis f i le . A n example o f w h i c h is described i n the case study presented i n this paper. J I f break records are stored o n l y o n paper, an electronic break database should be created. Spreadsheets are easy to use and the data can be easi ly transferred to G I S format for v i e w i n g w h i l e be ing retained as the k e y database. P i p e I D numbers that are assigned for G I S ne twork maps can be used as the connect ion between the break records and pipe characteristic data. I f records do not specify the exact loca t ion o f the break a long a pipe segment, some extrapolat ion m a y be required to identify the damaged pipe. F o r example , a house number m a y need to be used to define the locat ion a long a p ipe where the break occurred. . •• 89 A process for conver t ing geographical a rchiva l informat ion into electronic data for relat ing data is shown i n F igure 3.2. In the first step, informat ion i n the fo rm o f paper maps is scanned to create T a g Image F i l e Format ( T I F F ) images. T h e n the images are d ig i t i zed to create p o l y l i n e drawings and G I S are used to b u i l d p o l y g o n coverage. Attr ibutes are attached for each p o l y g o n and then related to a c o m m o n identifier, such as a pipe I D . U s i n g the intersect funct ion o f the G I S , the attributes o f the ne twork pipes and the attributes o f the po lygons are combined and exported as a spreadsheet f i le . A l l the files fo rm a por t ion o f the data warehouse that is used to create the m a i n analysis f i le . F o r example , s o i l image maps m a y be d ig i t i zed to create a c losed p o l y l i n e d rawing o f so i l types, fitted to the cadastral drawings o f the water network i n A u t o D e s k M a p ® us ing the 2 D transformation process, and then used to b u i l d p o l y g o n coverage o f the so i l condi t ions w i t h A r c M a p ® . I f each p o l y g o n is assigned a so i l type ident i f icat ion number that corresponds to a so i l type, then us ing the intersect funct ion o f A r c M a p ® , the pipe and corresponding s o i l attributes can be generated and exported to a shape f i le , and u l t imate ly exported as a spreadsheet fi le o f pipe IDs and corresponding so i l type. H y d r a u l i c models m a y be used to calculate the f l o w through m o d e l l inks , and the pressure and heads at nodes w i t h i n the water dis t r ibut ion system. A process for est imating pressure data a long each l i n k w i t h i n the network is shown i n F igure 3.3. H y d r a u l i c mode l outputs (e.g., f l ow and fr ic t ion coefficient estimates i n l inks and pressure estimates at nodes) are determined for the corresponding pipe I D . The pipe l i n k and node shape files are combined us ing G I S tools, exported to a spreadsheet f i le , and thereafter combined w i t h the other pipe network data, such as pipe material , diameter, date o f instal lat ion, and length. Often, the hydrau l ic m o d e l and the pipe network do not have a one to one relat ionship, and c o m m o n l y the hydraul ic m o d e l is a skeleton o f the network where a l i n k 90 i n the m o d e l m a y actual ly represent a number o f pipes i n the real system. F o r example , the C i t y o f Toronto recently skeletonized their 307,956 pipe network to a 76,989 l i n k hydraul ic m o d e l (Sch ick , 2005). In this case, the pressure and f low m a y be related b y buffering the hydraul ic m o d e l output to the pipe network data. Buf f e r ing creates a relat ionship between the l inks i n the m o d e l and the w e l l documented pipes i n the p ipe network; a process shown i n F igure 3.4. Here , the pipe network data (a . D W G file) is converted to a shape fi le w i t h ident i f icat ion numbers (usual ly the pipe ID) and the hydraul ic m o d e l data are prepared as a shape fi le . The two shape files are buffered us ing G I S analysis tools. Buf fe r ing the two shape files creates a relat ionship between each pipe and the m o d e l pressure and f low i n the l inks . U s i n g this process, a l l pipes can be associated w i t h corresponding f lows and pressures. T h i s approach m a y also be used for c o m b i n i n g sewer or drainage hydrau l ic models or other spatial data. P r o c e s s i n g D a t a . P r io r to the analysis stage, data should be processed to reduce errors and inconsistencies and to produce a coherent data set. D a t a process ing activit ies inc lude s imple transformations (e.g., detecting and r emov ing outliers), c leaning and scrubbing, b l end ing data f rom the various sources and summar i z ing the data to reduce the number o f records (Torra et al, 2004). In the process o f relat ing the data, analysts m a y d iscover inconsistencies i n the databases and m a y have to determine the re l i ab i l i ty o f the data and h o w to treat incomplete data, e.g., pipes that do not have an instal lat ion date. Ana lys t s m a y also f ind pipes that are mi s s ing material or diameter data or that hydrau l ic m o d e l output and G I S data differ. It falls o n the analyst and data schematic bui lder to careful ly consider the impacts o f data use approaches and h o w these approaches affect the ab i l i ty to achieve the purpose o f the analysis. 91 Knowledge discovery. Once data processing is complete , u t i l i ty managers m a y analyze and extract knowledge and gain insights regarding their system. T y p i c a l knowledge d i scovery techniques include spatial and statistical analyses us ing G I S , spreadsheets, databases, phys i ca l and statistical p ipe deterioration models and art i f ic ial intel l igence techniques. Here , patterns i n the data m a y be determined such as break patterns, and rates for differ ing p ipe materials, diameters, and ages and the spatial dis t r ibut ion o f the breaks over t ime. A s an example o f the use o f such observations, k n o w i n g the propor t ion o f pipe materials o f a dis t r ibut ion system and the failure rates w i t h i n each mater ial class can help determine the vulnerabi l i t ies and failures that m a y be expected o f the system. De te rmin ing the past, present and future failure rates for pipes o f different vintages, diameters, so i l condi t ions, and surface loadings is important for gu id ing a u t i l i ty ' s rehabi l i ta t ion program. 3.5 W A T E R M A I N B R E A K D A T A B A S E S F O R M A P L E RIDGE, B C The construct ion o f a data schematic for ana lyz ing water m a i n breaks is demonstrated here for the area o f L a i t y V i e w i n the Dis t r ic t o f M a p l e R i d g e . Th i s area comprises 13 percent o f the 335 k i lometer dis t r ibut ion system for the Dis t r i c t and represents an urban area. The L a i t y V i e w area experienced construct ion practices and has , so i l types typ ica l for M a p l e R i d g e . The Dis t r i c t has informat ion res id ing i n various formats (e.g., electronic, a rch iva l , and oral) that are distributed and managed across the organizat ion. F o r example , the Operations Department has paper copies w i t h l imi t ed informat ion on the break his tory o f water mains f rom 1983 to 2004, and no database, w h i l e the Eng inee r ing Department has a skeletonized hydraul ic m o d e l o f the system constructed i n 2001 i n a . D W G format and a spatial representation o f the pipe network i n G I S . 92 The purpose o f this analysis was to determine relationships among water m a i n breaks and factors such as pipe age, mater ial , so i l and depth o f cover so as to a id i n asset management ( N S G M I , 2003). The informat ion processing tools used were Mic roso f t E x c e l ® , M i c r o s o f t A c c e s s ® , A r c V i e w ® G I S and A u t o d e s k ® M a p . These software tools were selected because they are available in-house, and Dis t r ic t staff are trained to use them. The data set for the L a i t y V i e w area o f M a p l e R i d g e represents an intermediate water m a i n break data set w i t h a 20 year break his tory (1983 to 2004). The data inc luded pipe material , p ipe diameter, whether the pipe is under a boulevard or roadway, the year o f instal lat ion, depth o f cover, length o f pipe segment, surface mater ial , no rmal operating pressure, bedd ing mater ial , whether the pipe is wrapped or anode protected (wrapped/anodes), b a c k f i l l material , type o f road function, traffic c lassi f icat ion, type o f pipe l i n i n g and typ ica l f l ow i n the pipe. Constructing and linking data. The ava i lab i l i ty and loca t ion o f the data, l eve l o f confidence i n them, and informat ion regarding h o w they were created are ident i f ied and l is ted i n Table 3.1. Da ta associated w i t h a l o w leve l o f confidence are candidates for a data ver i f ica t ion program. B a s e d on the var ious sources o f the data and the goal o f a id ing asset management, the schematic o f h o w data can be related as shown i n F igure 3.5 was created. The schematic identifies potential l inks and inputs for analysis and major data o f interest. P r i m a r y sources o f data t yp i ca l l y aggregate data and are read i ly avai lable but do not contain a l l the data deemed o f interest for asset management. Secondary sources that contain addi t ional informat ion were identif ied. M a n y o f these use var ious data formats (e.g., databases and paper records) and are distributed across the organizat ion. Some data are avai lable f rom paral le l sources and one or a l l o f the sources m a y be used for analysis. F o r example , traffic vo lumes m a y be obtained f rom a transportation p lan or f rom a traffic 93 network p lan , traffic v o l u m e database and pavement management system. The transportation plan , traffic network p lan and pavement management system use A A D T for def ining the v o l u m e o f traffic w h i l e the traffic network p lan contains 24-hour vehic le vo lumes w h i c h m a y be transformed to equivalent A A D T . Where possible , data were l i nked us ing the p ipe I D as the c o m m o n l i n k across the databases i n order to facilitate updating o f a l l data sources us ing the results o f the knowledge d i scovery process and addi t ional f ie ld invest igat ion. L i k e m a n y uti l i t ies, the electronic water dis t r ibut ion network informat ion for M a p l e R i d g e includes year o f instal lat ion, diameter and material and these are avai lable from the G I S and d rawing files. The length o f the p ipe segment was obtained from the geometry o f the pipes i n these files. Au todesk M a p ® tools were used to define and create the shape f i le for the region. The study area was defined for extraction from the water network map, and exported to a shape file w i t h the object data for each pipe. The shape file was v i e w e d and plot ted i n A r c V i e w ® G I S 3 . 2 A and exported as a spreadsheet file as the m a i n data file for analyses. The Dis t r i c t ' s hydrau l ic m o d e l data are stored i n a . D W G format but the m o d e l uses l inks and nodes w h i c h do not comple te ly relate to specific pipes. In m a n y cases, l inks represent a number o f pipes i n series and required buffering. The break his tory for M a p l e R i d g e is l imi t ed i n detai l , but is re la t ively long . Breaks are recorded b y operat ion and maintenance staff and stored i n paper form. The recording o f break locat ions as w e l l as the amount o f environmental and break informat ion varies among the records w i t h i n a g iven year and dur ing the per iod o f record. F i e l d crews typ ica l ly record locat ions w i t h respect to the nearest cross street but do not record the exact locat ion o f the break. A s a result, i f a pipe experienced mul t ip le breaks but the exact locations o f these breaks are not identif ied, it cannot be determined i f the p ipe fai led at the same 94 locat ion or at mul t ip le sites a long the pipe. H o w e v e r , ident i f icat ion o f the exact loca t ion was not necessary because the purpose o f this analysis was to determine i f and w h e n a p ipe broke and not the exact loca t ion o f the break a long each pipe. T o create the electronic break database, the data f rom the field c rew reports were entered into an electronic spreadsheet. P ipe I D f rom the water ne twork map were added to the break record. The data worksheet was then converted to a database that was then exported as a . D B F fi le to G I S where it was plotted for v i sua l iza t ion . The Dis t r i c t does not have detailed so i l informat ion. T o construct these data, a number o f secondary sources inc lud ing federal, p r o v i n c i a l and loca l government reports (Golder , 2002; Lu t tmerd ing , 1981; Lut tmerd ing , 1980) were reviewed. W h i l e the p rov inc i a l reports use agricul tural so i l classifications, so i l groups based o n the parent mater ial (i.e., the upper stratigraphic unit) better represent the so i l types at instal lat ion depth. The three m a i n classes o f parent material are: marine c lay , marine sand or eol ian silt. The p rov inc i a l s o i l maps were converted into an electronic fo rm and intersected w i t h the water ne twork maps as described p rev ious ly i n the l i n k i n g data section. T o obtain informat ion regarding surface material , the ortho-photographs o f surface features were plotted as background to the water dis t r ibut ion network. The possible surface material types are asphalt, gravel ( typ ica l ly representing a road shoulder) and landscaping. Whether the water m a i n is under a boulevard or roadway was s i m i l a r l y determined and recorded. A GIS-based map o f the roads, over la id o n the water pipe network and knowledge based o n the Dis t r i c t o f M a p l e R i d g e Transportat ion P l a n was used to classify the traffic on the ground surface above the water ma in . Categories o f traffic loads that were used include those attributed to loca l , col lector , arterial, and commerc i a l roads, and lanes and those 95 exper iencing no traffic, such as boulevards. In the case where a p ipe is under two or more road classif icat ions, the c lass i f icat ion corresponding to the heavier traffic road function was selected. A s is the case for many uti l i t ies, the qual i ty and amount o f construct ion details p rov ided i n as-builts varies depending on the designer, contractor and t ime per iod dur ing w h i c h the m a i n was constructed. Thus , the confidence i n these details also varies. H o w e v e r , i n spite o f the var iab i l i ty o f records, ut i l i t ies m a y f ind that construct ion standards, i n place for years, m a y provide rel iable information. F o r example, the standard cover used for construct ion i n M a p l e R i d g e is general ly 900 mi l l imet res (three feet) and has been ver i f ied b y interviews w i t h staff (Thain , 2005). Da ta regarding bedding and b a c k f i l l material , and pipe l i n i n g and protect ion practices were determined through interviews w i t h staff. Rela t ionships between the bedding and pipe material were established and a data set o f bedding mater ial was created. S i m i l a r l y , whether p ipe protect ion exists for pipes i n the study area was determined us ing the s o i l type for each pipe. Where the so i l type indicates c l ay and the p ipe mater ial is ducti le i ron , the pipe was considered on the basis o f practice to be wrapped. A l l other pipes are considered to be unprotected. T h i s assumption is identif ied as one w h i c h m a y require further ver i f ica t ion. W h i l e some data were obtained us ing secondary sources, it was not possible to obtain or construct a l l data. A l s o , w h i l e m i n i m a l scrubbing o f the data was required, there were some gaps i n data. F o r example , when the Dis t r i c t replaces a pipe or segment o f a pipe, it does not retain any his tory o f the pipe. Consequent ly , there is no informat ion regarding the former his tory o f the age, material or diameter o f pipes that have been ' replaced unless the data are recoded on the break record fo rm ( typ ica l ly this w o u l d o n l y be diameter and mater ial data). 96 Preliminary analysis and knowledge discovery. K n o w l e d g e d i scovery results for this case are reported i n Figures 3.6 to 3.8 and Tables 3.2 and 3.3. In the study area, 69 percent o f the pipes are duct i le i ron , 26 percent are asbestos cement, f ive percent are cast i ron and less than one percent is steel pipe. The number o f breaks over time,, plotted i n F igure 3.6, m a y help managers develop strategies and budgets. W h i l e data indicate a stable number o f annual breaks over the past years, a predic t ion m o d e l w o u l d be useful to estimate i f and w h e n the number o f breaks w i l l increase. O f the 47 breaks that occurred, there were 32 first-time breaks. D u r i n g 1983-1999, ten breaks occurred i n nine pipes and these pipes were replaced. Because M a p l e R i d g e does not retain data on pipes that are replaced except what is o n the break records ( w h i c h m a y record the p ipe diameter and material) , o n l y 37 breaks had associated pipe diameter, material and age data. The usefulness o f knowledge d iscovery is i n determining patterns o f p ipe breakage and insights based o n these patterns. One example pattern is i l lustrated i n F igure 3.7 and Table 3.2 w h i c h show that the major i ty o f first breaks occur when pipes are between 15 to 19 years o l d , and that pipes o f the 1960-1974 vintage have a s igni f icant ly higher rate o f failure than others, and thus attention should be g iven to these pipes. In addi t ion, other relationships such as that between breaks and pipe size (as shown i n Table 3.3) and breaks and so i l condi t ions (as shown i n F igure 3.8) can prov ide insights, such as the amount o f failures i n duct i le i ron pipes that are instal led i n c lay soils . Current ly , the water m a i n replacement p rogram o f M a p l e R i d g e is targeted at rep lac ing asbestos cement pipes. A s a result o f this project, M a p l e R i d g e ini t iated a so i l cor ros iv i ty survey and plans to correlate those results w i t h the so i l data created i n this study. T h e y are also examin ing ways to improve pr ior i t iza t ion o f the rehabil i tat ion o f water mains us ing the n e w l y gained knowledge . Practices have also been revised inc lud ing : data 97 o n replaced pipes are n o w retained, f ie ld data are n o w be ing col lected w h e n new pipes are instal led, and new water m a i n break forms have been implemented . C o m m u n i c a t i o n on data co l l ec t ion is i m p r o v i n g as departments w o r k together to col lect and share data and have a better understanding o f each other 's role i n ach iev ing the c o m m o n goal o f effective asset management. 3.6 DISCUSSION The process o f creating a data schematic among mul t ip le databases for data compi la t ion , analysis and knowledge d iscovery m a y y i e l d valuable insights for i m p r o v i n g asset management practices. It expands the data avai lable for analysis for both present and future applicat ions and respects decentral ized data input and management. The use o f decentral ized data storage reduces problems related to data ownership among units w i t h i n organizations regarding data co l lec t ion , management and disseminat ion o f water, sewer, drainage or other infrastructure information. A s i n any business process, it is important to document the purpose for constructing, structuring, sourc ihg and l i n k i n g the data schematic. A c lear ly documented outl ine o f the relationships between the k e y data sets is important for future managers and those u t i l i z i n g the data. N S G M I (2003) suggests some k e y relat ing informat ion such as asset number, asset locat ion and w o r k order numbers. The w o r k undertaken herein suggests that those co l lec t ing data w i t h i n an organizat ion should share informat ion regarding the purpose for co l lec t ing and selecting the amount and type o f informat ion to avo id dupl ica t ion and focus efforts. D a t a managers must also be aware o f disclosure control i n w h i c h important or confident ial data m a y be inadvertently connected and unintent ional ly released to th i rd parties (Torra et al., 2004). F o r pub l i c ut i l i t ies, the issue o f private and proprietary 98 i informat ion is important and should be considered (e.g., cons ider ing the F reedom o f Information A c t i n B r i t i s h Co lumb i a . ) . Process ing o f data is a significant step i n data schematic construct ion and relat ing data. F o r example , i n the M a p l e R i d g e case study, use o f agricul tural so i l classif ications resulted i n too many s o i l zones for analysis but reducing the number o f classif icat ions and us ing the parent mater ial categories improved the understanding o f the relat ionship between s o i l type and the number o f water m a i n breaks. S u m m a r i z i n g and aggregating data requires expertise and knowledge o f the intended analyses. In seeking data sources, ut i l i t ies should consider data that other agencies are co l lec t ing even i f they ate do ing so for different purposes and determine whether the data are useful as a secondary source. A p p l i c a t i o n o f new technologies, such as infrared, electro-magnetic surveys and L i g h t Detec t ion and R a n g i n g ( L I D A R ) m a y be employed to capture relevant data. U t i l i t i e s face the challenge o f capturing undocumented inst i tut ional informat ion and knowledge over the next decades as their baby-boomer staff retire. A s demonstrated herein, in terviews are useful i n capturing these data, but the processes o f in te rv iewing staff can be awkward . The authors found that staff shared more informat ion w h e n interviewers began the session b y m a k i n g observations and ask ing about the v a l i d i t y o f these observations, and then ask ing specific questions. M a p s and other v i sua l cues usual ly triggered the in terviewee 's memory . It is important for interviewers to pose questions and present the exercise as so l i c i t ing informat ion to a id i n knowledge d iscovery rather than c r i t i c i sm o f past practices. It is equal ly important to, where appropriate, val idate the observations and experiences o f staff. It is noted that retired staff seem uncomfortable w i t h 99 general observations unless they cou ld also provide exceptions. T h o u g h there m a y be confidence i n o ra l ly recorded data, ver i f ica t ion should be undertaken where possible . A l imi ta t ion o f constructed databases is the poss ib i l i ty that created data are more correlated than data that are col lected independently. F o r example , i n the case study, a l l duct i le i ron pipes are defined as cement mortar l ined and the p ipe mater ial determined the b a c k f i l l and bedding data. Th i s m a y affect the amount o f explanatory variables i n an analysis. Other l imita t ions include the fact that data m a y not a lways be accurate or quantifiable. The l imita t ions m a y be overcome b y a program to ver i fy the data over t ime, w h i c h is a long-term exercise. F o r predic t ing future water m a i n breaks, it m a y be diff icul t to determine i f variables are significant i f there is a l imi t ed his tory o f breaks. It is important that the data are stored and that future break data be added to increase the his tory and data set for further analysis. 3.7 CONCLUSIONS G r i g g (2005) has ident i f ied the need for standardized m a i n break databases and cont inued research regarding database development as strategic for in formed infrastructure management though the topic o f databases has been the subject o f other authors such as D e b et al, (2002); H a b i b i a n (1992), and O ' D a y , 1982). H o w e v e r , surveys and literature indicate that data are t yp i ca l l y scarce. C o m p o u n d i n g this, water m a i n break data i n central ized databases are not c o m m o n and approaches and techniques to relate and manage data for analysis are needed. The approach presented herein expands the sources ( inc luding , i n particular, oral transmission) and the amount o f data for asset management. Researchers and managers m a y gain insight into a system b y systematical ly sourcing, relat ing, processing, b lend ing 100 and ana lyz ing data. The framework is f lexible , anticipates the evolu t ion o f data co l lec t ion , b u i l d i n g , ver i f ica t ion and storage and a l lows for a variety o f users. It does not abruptly disrupt data co l lec t ion and warehousing practices. A k e y benefit o f this approach o f relat ing data is that it a l lows managers to continue to expand data co l lec t ion because databases are decentralized. It also fosters a dialogue o f data development, knowledge d i scovery and informat ion processing across an organizat ion. It is f lex ib le and can be adapted to a l l ut i l i t ies, whether they are smal l , m e d i u m or large, and regardless o f the uniqueness o f the data col lected and organizat ional framework. The recording o f future breaks and ver i f ica t ion tasks are important for b u i l d i n g confidence i n the data and for augmenting it. A long-term strategy should be developed that verifies and improves the breadth o f data and confidence i n the database. The tasks can be opportunist ic , undertaken w h e n other repairs o f the system are occur r ing , or systematic. W h e n pipes are replaced or new service connections are instal led, opportunities arise for obtaining phys i ca l samples and ver i fy ing the nature and condi t ion o f p ipe protection, bedding, b a c k f i l l and the pipe exterior. A n example systematic program is a u t i l i ty -wide survey o f s o i l cor ros iv i ty i n var ious so i l classif ications and an exercise that improves the understanding o f the relat ionships among so i l classifications, cor ros iv i ty and breaks. T h i s approach can also be used for sewerage, drainage and other systems for i m p r o v i n g asset management, operation and maintenance analysis , performance and pub l i c accountabil i ty. F o r example, b y relat ing and ana lyz ing grease bui ld-up areas, complaints , slope, f l ow and m o d e l f lushing veloci t ies , a sewer system manager can analyze performance and resource efforts and develop plans to address p rev ious ly "un-connected" p rob lem areas. A s w e l l , for a road network, constructing relat ionships between complaints , ( 101 traffic vo lume , speed and crash data, l igh t ing leve l , signage, road condi t ion and geometry, managers m a y be able to improve road safety and predict h igh crash locations. A s observed i n the L a i t y V i e w area case study, the process and results improve communica t ion and the basis for dec is ion m a k i n g . N e w insights can assist managers i n focusing effort and resources and d i scover ing unanticipated issues and challenges. W h i l e the focus o f ut i l i t ies has been on co l lec t ing and storing data, the next step w i l l be i n the appl ica t ion o f data m i n i n g and knowledge discovery . A s more tools become avai lable to analyze data, managers need to consider the business intel l igence that it should emp loy to w i s e l y invest resources to meet future demands. 3.8 A C K N O W L E D G E M E N T S N The authors gratefully acknowledge the Dis t r ic t o f M a p l e R i d g e for p rov id ing data and support i n the fo rm o f employee resources, Mess rs . D . T h a i n (ret.), H . Y o u (ret.) and J . Scherban f rom the Dis t r i c t for p r o v i d i n g tacit informat ion, and Professors A . D . R u s s e l l , J . A twa te r and H . Schr ier at the U n i v e r s i t y o f B r i t i s h C o l u m b i a ( U B C ) for their insights and suggestions. M r . A . M a l y u k o f the Dis t r ic t o f M a p l e R i d g e assisted i n data processing and compi l a t i on and Mess r s B . K a m p a l a , M . A . S c . Candidate , U B C , and W . Johnstone, P r i n c i p a l , Spat ial V i s i o n Group assisted i n r ev i ewing the manuscript . 102 3 . 9 R E F E R E N C E S Cooper , N . R . , B l a k e y , G . , Sherwin , C , T a , T. , Whi te r , J. T . and W o o d w a r d , C . A . , 2000. The use o f G I S to develop a probabi l i ty-based trunk mains burst r i sk mode l . Urban Water, 2:2000: 97-103. D a v i s , D . N . , 2000. Agent-based dec i s ion support f ramework for water supply infrastructure rehabil i ta t ion and development. Computers, Environment and Urban Systems, 24:2000: 173-190. D e b , A . R . , Grab lu tz , F . M . , Hasi t , Y . J . , Synder, J .K. , Longanathan, G . V . and A g b e n o w s k i , N . , 2002. P r i o r i t i z i n g Water m a i n Replacement and Rehabi l i ta t ion . A W W A Research Foundat ion , 6666 Wes t Q u i n c y A v e n u e , Denver , C O . 80235. G o l d e r Associa tes L t d . , 2002. Geotechnica l Input to the seismic vu lnerab i l i ty assessment for the Dis t r i c t o f M a p l e R i d g e , B . C . 500-4260 S t i l l Creek D r i v e , Burnaby , B C , V 5 C 6 C 6 . G r i g g , N . S . , 2005. Assessment and R e n e w a l o f Water D i s t r ibu t ion Systems. Journal AWWA, 97:2: 58-67. G r i g g , N . S., 2004. Assessment and renewal o f water dis t r ibut ion systems. A W W A Research Foundat ion , 6666 Wes t Q u i n c y A v e n u e , Denver , C O . 80235. 103 Hab ib i an , A . , 1992. D e v e l o p i n g and u t i l i z i n g databases for water, m a i n rehabil i tat ion. Journal AWWA, 84:7: 75-79. K l e i n e r , Y . and Rajani , B . B . , 1999. U s i n g l imi t ed data to assess future needs. Journal AWWA, 91:7: 47-62. K l e i n e r , Y . and Rajan i , B . B . , 2001 . Comprehens ive rev iew o f structural deterioration o f water mains : statistical models. Urban Water, 3:3: 131-150. Lut tmerd ing , H . A . , 1981. Soils of the Langley-Vancouver map area: Report NoJ5, Volume 6. B . C . M i n i s t r y o f Env i ronment Assessment and P l a n n i n g D i v i s i o n , K e l o w n a , B C . Lut tmerd ing , H . A . , 1980. Soils of the Langley-Vancouver map area Report No.15 Volume 1. B . C . M i n i s t r y o f Env i ronment Assessment and P l a n n i n g D i v i s i o n . K e l o w n a , B C . N G S M I , (Nat iona l G u i d e to Sustainable M u n i c i p a l Infrastructure - Infraguide), 2003. Bes t Practices for U t i l i t y - B a s e d Data . Infraguide - Potable Water . Ot tawa, O N , Canada. N G S M I (Nat iona l G u i d e to Sustainable M u n i c i p a l Infrastructure - Infraguide), 2002. Deter iora t ion and Inspection o f Water Di s t r ibu t ion Systems. Infraguide - Potable Water . Ot tawa, O N , Canada. I 104 N a t i o n a l Research C o u n c i l o f the N a t i o n a l A c a d e m i e s - Commi t t ee o n P u b l i c Water S u p p l y Dis t r ibu t ion Systems: Assess ing and R e d u c i n g R i s k s , 2005 . Public Water Supply Distribution Systems: Assessing and Reducing Risks - First Report. O ' D a y , D . K . , 1982. O r g a n i z i n g and ana lyz ing leak and break data for m a k i n g m a i n replacement decisions. Journal A WW A, 74:11: 588-594. O ' D a y , D . K . , W e i s s , R . , C h i a v a r i , S., and B l a i r , D . , 1986. Wa te rma in Eva lua t i on for Rehabi l i t a t ion / Replacement . A W W A Research Founda t ion ( A W W A R F ) and U S Env i ronmen ta l Protect ion A g e n c y ( U S E P A ) , A W W A Research Foundat ion , 6666 Wes t Q u i n c y A v e n u e , Denver , C O . 80235." Pellet ier , G . , M a i l h o t , A . and V i l l e n e u v e , J . -P. , 2003 . M o d e l i n g water pipe breaks - three case studies. Journal of Water Resources Planning and Management, 129:2: 115-123. Rajan i , B . B . and M a k a r , J . , 2000. A methodology to estimate remain ing service life o f grey cast i ron water mains . Canadian Journal of Civil Engineering, 27:6: 1259-1272. Rossi ter , D . G . , 2005. A compendium of on-line soil survey information - Soil survey institutes and activities. A c c e s s e d M a y 31 , 2005, h t tp : / /www. i tc .n l / rossiter/research/ rsrch ss sources.html. 105 Sch ick , S., 2005. Toronto bridges data needs i n water network project. ITBusiness.ca July 21, 2005. Acces sed J u l y 22, 2005 http:/ /www.itbusiness.ca/index.asp7theaction =61&sd i= 59540. T h a i n , D . , 2005. Water mains i n the Dis t r i c t o f M a p l e R i d g e . A . W o o d , ed., M a p l e R i d g e , Interview notes. Tor ra , V . , Domingo-Fer re r , J . and Torres, A . , 2004. Da ta m i n i n g methods for l i n k i n g data c o m i n g f rom several sources. 3rd Joint Un/ECE-Eurostat Work Session on Statistical Data Confidentiality, Monographs in Official Statistics, L u x e m b o u r g , Eurostat. 143-150. V a n i e r , D . J . , 2001 . Asse t Management : " A " to " Z " , American Public Works Association Annual Congress and Exposition - Innovations in Urban Infrastructure Seminar, Phi lade lph ia , U . S . September, 2001 . 1-16. W o o d , A . and Lence , B . J . , Assessment o f Water M a i n Break D a t a for Asse t Management . Journal AWWA, 98:07. X u , C . and Goul ter , I . C , 1998. Probabi l i s t ic mode l for water dis t r ibut ion re l iabi l i ty . Journal of Water Resources Planning and Management, 124:4: 218-228. 106 V Table 3.1 Water main break data availability for Maple Ridge Data element Availability for "off the shelf analysis Secondary source Notes Confidence/reliability Pipe material Available in AutoCad in .DWG format High Pipe diameter Available in AutoCad in .DWG format and GIS High Type of water service Available in Ortho-photographs (0.5metre/1.6 feet * and0.15metre/0.5 feet intervals) Requires interpretation of data available Medium Under boulevard or roadway Available in 1 Ortho-photographs (0.5metre/1.6feet and0.15metre/0.5 feet intervals) Requires interpretation of data available High Year of installation /age Available in AutoCad in .DWG format and GIS Medium - high Depth of cover Orally recorded information Based on standards of the day Medium - but could be verified over time Length of pipe segment Available in AutoCad in .DWG format and GIS Medium Normal operating pressure Available in model and in .DWG format Need buffering to assign pipe with node data Medium - High Type of joint Not available Field investigation commenced for future pipe breaks Low Condition of pipe exterior Not available Field investigation commenced for future pipe breaks Bedding material Orally recorded information Data inferred from known pipe material, future field verification required Medium - but could be verified over time 707 Data element Availability for "off the shelf analysis Secondary source Notes Confidence/reliability Pipe protection (wrapped/anodes) Orally recorded information Use of soil maps to infer information, future field verification required Medium - but could be verified over time Backfill material Orally recorded information Data inferred from known pipe material, Future field verification required Medium - but could be verified over time Traffic classification or type of road usage Transportation plan designation and maps Need better understanding of traffic loading Type of pipe lining Orally recorded information Data inferred from known pipe material, future field verification required Medium - but could be verified over time Typical flow in area of break Available in hydraulic model and in .DWG format Some more modeling information (typical flow) Medium-high (from model confidence) 108 Table 3.2 Water main breaks for a given year of installation (1983-1999) Year of Installation Number of Pipes Length in metres (feet) Number of breaks as an age group Percentage of pipes in age group with breaks 1955-1959 14 1,687 (5,535) 4 29% 1960-1964 32 • 2,968 (9,738) 8 25% 1965-1969 12 1,511 (4,958) 7 58% 1970-1974 52 4,791 (15,719) 11 • 21% 1975-1979 56 4,030 (13,222) 3 5% 1980-1984 56 4,122 (13,524) 1 2% 1985-1989 56 4,584 (15,040) 3 5% 1990-1994 96 7,452 (24,450) 0 0% 1995-1999 51 3,003 (9,853) 0 0% Unknown 4 29 (95) 0 0% Total 429 34,177 (112,135) 37 9% 109 Table 3.3 Pipe breaks for pipes of a given diameter (1983-1999) Pipe diameter in millimeters Number of Pipes Number of breaks Percentage of pipes for each diameter group with breaks 100 2 0 0.0% 150 246 26 10.6% 200 117 7 6.0% 250 62 4 6.5% 300 2 0 0.0% 350 0 0 0.0% 429 37 9.0% 110 Figure 3.1 A schematic for constructing and using water main break data for knowledge discovery Verificalion"and:;upaating;of;aata';:;™s Soil maps transportation I plans , Ortho-photographsl reports AM/FM systerrf data Break data files Linking or relating data using identifiers common to two or more databases Processing Application Software: -GIS -CAD - spreadsheets Human analyst and application software 4 Data Analysis and Application Analysis tools -GIS -CAD - Spreadsheets - Databases Knowledge Discovery Strategies and Plans ill Figure 3.2 Process for digitizing and creating data from archival geographical data Scan hard copy image and create TIFF image Create closed polyline drawing Use GIS to create polygon coverage (closed polylines) and identify attributes to be linked Apply GIS processing tools (e.g., intersect function) to pipe network and the polygon to generate shape file Export attribute data of the shape file to analysis file (e.g., spreadsheet file) XZ1 = 5 Sde ndte%Mo%> 1 § for titisshfidkd I f = : :: 1 I i Note: Title of data columns Number Month Years Pipe of Pipe Material Year of Year Of Of of Years In length breaks ID Size Material Code installation Failure Failure Service Ground (metres) to 1999 Has pipe been Soil Number Under replaced since zone of soil boulevard Surface Traffic Pipe break? type zones or road material classification lining Bedding Backfill Q V C_number HGL Max demand day Pipe protection C factor Roughness (l/s) (m/s) (Hazen) (metres) pressure _(PSI) 112 Figure 3.3 Linking hydraulic model data with network data Determine hydraulic model input and output data and relationships of data. For example, are pressures calculated only for nodes or are they also assigned to model links? Do the pipe link data include all the data being sought for analysis? Combine hydraulic model output node pressures and link flow data for a given pipe ID. Determine pipe network information such as material, diameter, date of installation, length, etc. How does the pipe network relate to the model, i.e., are there one-to-one relationships or is the model skeletonized? Combine hydraulic model data with pipe network data. Export combined attributes to analysis file 113 Figure 3.4 Buffering data to create data relationships using GIS Link ID 1 is a link that defines connectivity in the hydraulic model. Each linkjs-~ identified as unique in the> model. Buffering the Link ID 1 data to Pipe ID 1 and Pipe ID 2 gives the attributes of Link ID 1 to the network pipes Pipe ID 1 and Pipe ID 2. Pipe ID 1 and Pipe ID 2 are network pipes in GIS. Each pipe identified as unique. ID 1 Pipe ID 1 with Link ID1 data Pipe ID 2 with Link ID1 data Steps to create buffered data 1. Create shape files of model data and network data. 2. Buffer data using capabilities of GIS. 3. Export the attributes of the buffered shape file as a spreadsheet file. 114 Figure 3.5 Maple Ridge water main break analysis data schematic Tacit data: bedding, construction standards, pipe protection, cover, etc. Project report: pipe materia], installation date, pipe length, etc. Hydraulic model: flow, pressure, pipe material, friction coefficient, etc. Geological Survey of Canada (GSC) data Ministry of Environment (MOE) soil data Pipe inspection record: pipe material, etc. Road as-built: surface material, road function, etc. Break report form: break data, date, costs and effort of repairs Primary sources Secondary sources Potential link (e.g. pipe ID) Potential input to analysis Accounting system: break activity costs, annual break expenditure, etc. Pavement management system: surface material, road function, etc. Traffic network plan: road function, traffic volume, etc. Traffic volume data base: traffic volume, road function, etc. 115 Figure 3.6 Cumulative breaks in Laity View area (1983-1999) 116 Figure 3.7 Number of years in service when break occurred in pipes (1983-1999) 10 Number of years in service Note: Of the 47 breaks in the area, no pipe age data were available for 10 of the 47 breaks. 117 Figure 3.8 Number of breaks for pipes in a given soil type installation (1983-1999) Asbestos cement pipes Cast iron pipes Ductile iron pipes • Marine Clay • Eolian Silt • Silty Clay 2 O Marine Clay a Marine Clay • Eolian Silt 118 C H A P T E R 4 USING W A T E R M A I N B R E A K D A T A TO I M P R O V E ASSET M A N A G E M E N T F O R S M A L L AND M E D I U M UTILITIES A version of this paper has been submitted for publication to ASCE Journal of Infrastructure Systems as Using Water Main Break Data to Improve Asset Management for Small and Medium Utilities by A. Wood and B. J. Lence. 119 PREFACE In the previous chapter, I created data and a number o f databases to demonstrate some techniques that ut i l i t ies can emp loy to enr ich their asset management data sets. In Chapter 4 ,1 demonstrate that once data are created and l i nked for analysis, uti l i t ies can use these data w i t h i n a f ramework that I developed for i m p r o v i n g their asset management practices. The intent o f this research is not to create a new m o d e l , but to develop a framework that uses break predic t ion models that smal l and m e d i u m size uti l i t ies can apply. The so i l and surface mater ial data that were created i n Chapter 3 were used i n the experimental appl ica t ion o f this f ramework and give 's ignif icant insights into the factors that influence pipe breaks. W h i l e the data created p rov ided a demonstration case, there was not sufficient informat ion to apply a l l the models that I i n i t i a l l y proposed to investigate. The use o f statistical determinist ic t ime-l inear and t ime-exponent ial models c o u l d be suff icient ly demonstrated w i t h the data created i n Chapter 3, but there were insufficient data to obtain meaningful results f rom an appl icat ion o f the surv iva l analysis and K A N E W (Deb at al, 1998) models . Thus , a l l four types o f models were appl ied i n an effort to obtain p r o o f o f concept, but o n l y two types o f models are reported i n the manuscript that comprises Chapter 4. It is important for ut i l i t ies to continue to create and mine data. T h i s research reinforces the no t ion that not a l l data m a y be useful for app ly ing sophisticated models but that unsophist icated pipe break models can provide insights into the performance o f a water m a i n system, be used i n ident i fy ing system specific factors that m a y cause breaks, guide the development o f a water m a i n break data co l l ec t ion strategy, be used to identify groups 120 o f pipes, their h is tor ica l and predicted break frequency to further investigate and pr ior i t ize for rep lac ing and thus be a benefit to communi t ies . 121 4.1 INTRODUCTION Water uti l i t ies have aging and deteriorating infrastructure and must pr ior i t ize the replacement o f their water mains to m i n i m i z e pipe breaks. Breaks result i n loss o f water to k e y businesses and cr i t i ca l facil i t ies, m a y lead to damage o f other infrastructure, and have been ident i f ied as a pa thway for m i c r o b i a l contaminat ion o f dis t r ibut ion systems ( A W W A and E E S , 2002). The need for rehabil i tat ing aging water mains is increasing, the costs o f repairs and replacement can be h igh , and the impact o n customers potent ia l ly significant ( U S E P A , 2001). Asse t management practices are general ly used to pr ior i t ize p ipe replacements and thereby identify investment strategies that, on one hand, avo id premature replacement o f pipes (i.e., unnecessary pre-investment o f funds), and o n the other hand, avo id water m a i n breaks, commensurate interruptions i n service and the costs o f damage. A n effective asset management dec is ion is dependent on the ab i l i ty to determine the future performance o f water mains b y predic t ing water m a i n breaks, and ident i fy ing h o w such breaks m a y occur. M u c h research has focused o n the development o f models for predic t ing water m a i n breaks and pipe deterioration, but the use o f such models is not c o m m o n among uti l i t ies. In addi t ion, the amount and qual i ty o f water m a i n break data avai lable for deve lop ing or implement ing these models varies among uti l i t ies ( W o o d and Lence , 2006) . M a n y uti l i t ies lack data and are not confident i n the data they have and this is general ly an impediment to their invest ing i n pipe predic t ion models . H o w e v e r , they can create and relate data that can be useful for asset management ( W o o d et al, 2007). T h i s paper develops a f ramework that guides uti l i t ies i n ident i fy ing k e y data to be used i n asset management i n general and spec i f ica l ly for p ipe break predic t ion mode l ing v and selecting the most appropriate mode l for predic t ing water m a i n breaks. T h i s 122 informat ion m a y then be used to enhance the development o f replacement priori t ies based on forecasted breaks, the maintenance o f the database, and the ident i f icat ion o f future data acquis i t ion programs. It provides the u t i l i ty w i t h a method for cons ider ing future p ipe breaks i n the analysis o f pipe pr ior i t iza t ion strategies, and it incorporates exis t ing tools for data management and analysis that are w i d e l y avai lable and easy to implement b y smal l and m e d i u m size uti l i t ies. The framework is appl icable to ut i l i t ies w i t h va ry ing amounts o f data, and it is demonstrated here w i t h a case study based on the L a i t y V i e w area o f M a p l e R i d g e , B . C and constructed data. The f o l l o w i n g sections rev iew the avai lable techniques for predic t ing pipe breaks, the factors that influence break predict ions, the framework developed for assisting i n asset management o f pipe networks and the results o f the M a p l e R i d g e example implementa t ion o f this framework. The framework can be appl ied wi thout creating and constructing data, but the usefulness wi thout such efforts is l imi ted . 4 . 2 W A T E R M A I N B R E A K S A number o f authors analyze and report o n the causes o f breaks, i nc lud ing O ' D a y (1982), M a r k s et al. (1987), M a l e et al. (1990), Sav ic and Wal ters (1999), Rajan i and M a k a r (2000), Rajan i and K l e i n e r (2001) and D i n g u s et al. (2002). A c c o r d i n g to Rajan i and Tesfamar iam (2005), a combina t ion o f circumstances leads to p ipe failure i n most cases and different factors cause failure i n different pipe networks. The causes o f breaks include deterioration as a result o f use (e.g., internal corrosion) , phys i ca l loads appl ied to the pipe (e.g., traffic, frost), l im i t ed structural resistance o f the pipe because o f construct ion practices dur ing instal la t ion and dec l in ing resistance over t ime (e.g., corros ion, aging factors). D i n g u s et al. (2002) surveyed the 46 largest A m e r i c a n Wate r W o r k s A s s o c i a t i o n Research Founda t ion ( A w w a R F ) member uti l i t ies i n 1997 and note mul t ip le c o m m o n 123 failure modes for cast i ron p ipe systems. Cor ros ion , improper insta l la t ion and ground movement are the three most c o m m o n causes o f pipe failure. A c c o r d i n g to L e v e l t o n (2005), cor ros ion is dependent o n a number o f factors i nc lud ing mater ial , s o i l type, chemica l characteristics o f so i l , so i l bacteria and stray electr ical currents. Prediction modeling of water main breaks. B reak predic t ion models have been developed to help the water industry understand h o w pipes deteriorate and w h e n pipes w i l l break i n the future. These models are t yp i ca l l y grouped into two classes - statistical and phys ica l -mechanica l models (K le ine r and Rajan i , 2001). Statist ical models use h is tor ica l pipe break data to identify break patterns and extrapolat ion o f these patterns to predict future p ipe breaks, or degrees o f deterioration. Phys ica l -mechan ica l mode ls predict failure b y s imula t ing the phys i ca l effects and loads on pipes and the capaci ty o f the pipe to'resist failure over t ime. Statist ical models are t yp i ca l ly characterized as either determinist ic or probabi l is t ic equations ( K l e i n e r and Rajan i , 2001). U n d e r the determinist ic models , the p ipe breakage is estimated based o n a fit o f pipe breakage data to var ious time-dependent equations, w h i c h m a y represent the cumula t ive p ipe breaks as a function o f t ime from date o f instal lat ion or f rom the earliest date o f avai lable break data, most c o m m o n l y are t ime-l inear (Ket t ler and Goul ter , 1985) or t ime-exponent ia l functions (Shamir and H o w a r d , 1979; W a l s k i , 1982 and K l e i n e r and Rajan i , 1999). P r io r to fi t t ing these functions, pipes are part i t ioned into groups that have s imi la r characteristics, and the functions are evaluated for these groups. The ' characteristics used to sort the pipes are based o n the factors that are assumed to influence breaks such as p ipe age, pipe material , diameter, or so i l type. Probabi l i s t ic models predict not o n l y the failure potential , but the dis t r ibut ion o f failure. These models are more complex than deterministic models and require more data. E x a m p l e s o f these include 124 cohort su rv iva l , such as K A N E W (Deb et al. 1998), Bay es i an diagnostic, break cluster ing, s e m i - M a r k o v C h a i n and data f i l ter ing methods. Phys ica l -mechan ica l models t yp i ca l l y fa l l into one o f two classes: determinist ic models w h i c h estimate p ipe failure based on s imula t ion o f the phys i ca l condit ions affecting the pipe (Doleac et al, 1980, and Rajani and M a k a r , 2000), or probabi l i s t ic models that use a dis t r ibut ion o f input condi t ions, such as rate o f corros ion, to predict the l i k e l i h o o d and dis t r ibut ion o f p ipe failure ( A h a m m e d and Melche r s , 1994). These models have been developed p r i m a r i l y for cast i ron and cement pipes. P h y s i c a l models have significant data needs. K l e i n e r and Ra jan i (2001) suggest that o n l y larger diameter mains w i t h cos t ly consequences o f failure m a y jus t i fy the required data co l lec t ion efforts for these models , and that statistical models based on fewer data m a y be used to gain insights for future performance. Rajan i and Tesfamar iam (2005), i n us ing a probabi l is t ic approach, suggests that breaks and causes o f breaks for any part icular water dis t r ibut ion network are system-specific and that a u t i l i ty must create its system-specific m o d e l based o n the deterioration factors that are relevant for that ut i l i ty . W h i l e smal l and m e d i u m uti l i t ies typ ica l ly have the capaci ty to use statistical determinist ic models , the implementa t ion o f phys i ca l models is not pract ical due to the data co l l ec t ion efforts and m o d e l maintenance required. F o r smal l and m e d i u m uti l i t ies, it is often most important to gain insights about the rate o f pipe breakage, that is , whether the quanti ty o f expected breaks is increasing l inear ly or exponential ly. K n o w i n g the rate o f change for u t i l i ty managers is important because budgets and performance are based i n part o n future needs such as the number and rate o f breaks i n the system. Factors for predicting water main breaks. A number o f studies identify factors for predic t ing water m a i n breaks, though what is considered relevant data appears to be 125 specific to the system investigated. O ' D a y (1982) reviews break studies i n Manhat tan and B inghamton , N e w Y o r k , and cites a number o f studies that use age as an indicator for predic t ing break rates for cast i ron pipes. H e notes, however , that age alone is a poor predictor o f m a i n break patterns and identifies the major determinants o f water m a i n break rates, as l oca l i zed factors such as cor ros ion condit ions, construct ion practices and external loads. H e also finds that so i l type affects external forces on water mains , such as shrink-swe l l , frost penetration and external corrosion. A c c o r d i n g to Jacobs and K a r n e y (1994), pipe age range is an effective basis for models because pipes o f a g iven age range are typ i ca l ly un i fo rm w i t h respect to manufacture, instal la t ion and to a large extent, operating condi t ions. M o r e o v e r , pipe instal led i n geographical ly contiguous sections often share s imi la r so i l condi t ions , instal lat ion condit ions and pressure regimes. In their study, Jacobs and K a r n e y group pipes based on material , diameter and fa i r ly broad age ranges and develop regression relationships for pipe breakage versus age and versus p ipe length. Sav ic and Wal ters (1999) suggest that the causes o f water m a i n failures m a y be spli t into pipe qual i ty and age, type o f environment, qual i ty o f construct ion workmansh ip and service condi t ion and f ind that age, length, and diameter are the most important variables i n inf luencing p ipe bursts. Ket t l e r and Goul te r (1985) f ind that break rate, age and material are related for asbestos cement and cast i ron pipes. In their study, no single type o f failure o f asbestos cement pipes exhibi ted a marked change i n the rate o f failure w i t h t ime, w h i l e there were distinct changes i n the failure rate w i t h t ime for some types o f failure i n cast i ron pipes. A c c o r d i n g to M a l e (1990), different manufacturing processes o f cast i r on pipes can account for differences i n durabi l i ty . Coope r et al (2000) apply a probabi l i s t ic approach to estimate trunk m a i n failure probabi l i ty , based on four k e y variables: number o f buses per hour, pipe diameter, s o i l cor ros iv i ty and density o f pipes i n a g iven area. T h e y f ind that 126 \ pipe age and mater ial are important factors contr ibut ing to the break probabi l i ty . Rajan i and Tesfamar iam (2005) show that long-term performance o f bur ied cast i ron is dictated b y pit g rowth rate, unsupported length, fracture toughness and temperature differential. Da ta t yp i ca l l y used i n models are surrogates for factors that can expla in breaks. F o r example , as shown i n Table 4 .1 , the age o f a pipe m a y represent the method o f p ipe manufacture or part icular construct ion standards, as w e l l as deterioration over t ime. B e d d i n g mater ial m a y be an indicator o f a part icular construct ion practice that induces phys ica l stress, o f the structural resistance o f the pipe, or o f the so i l type. F o r example, i n some uti l i t ies where native so i l is used as b a c k f i l l , the so i l m a y not screened for rocks and other objects or proper ly leveled. A s a result, this construct ion practice results i n circumstances where a stress is induced o n pipes and ul t imate ly causes failures. In some cases, fines migra t ion o f corrosive native s o i l through part icular bedd ing types can occur and create the potential for external corrosion. S o i l type can represent cor ros iv i ty and potential for external p ipe corros ion, this is also dependent o n the pipe mater ial . Availability of water main data within utilities for models. The amount o f water m a i n break data needed for extensive m o d e l development is not c o m m o n l y avai lable i n uti l i t ies ( W o o d and Lerice , 2006), i n spi te ,of best practices recommended b y the N a t i o n a l G u i d e to Sustainable M u n i c i p a l Infrastructure ( N G S M I , 2002) and A W W A R F (Deb et al, 2002). M o s t munic ipa l i t ies o n l y have l imi t ed recorded pipe breakage histories and do not have m u c h data for analysis (Pellet ier et al, 2003). H o w e v e r , i n m a n y instances uti l i t ies m a y have more avai lable data than they realize. T h e y can apply approaches such as constructing and relat ing avai lable data from archives, models and other such sources ( W o o d and Lence , 2006) to construct and l i n k databases for analysis. 127 A k e y to any data management strategy is ident i fy ing the purpose for w h i c h one is co l lec t ing and ana lyz ing the data, whether it is for asset management, c o m p i l i n g an inventory o f assets or d i scover ing the magnitude and nature o f p ipe breaks. There is g r o w i n g interest i n us ing K n o w l e d g e D i s c o v e r y techniques such as data m i n i n g for water m a i n break data (Savic and Wal ters , 1999). K n o w l e d g e D i s c o v e r y is the process o f ident i fy ing v a l i d , nove l , potent ia l ly useful and ul t imate ly understandable patterns i n data (Torra et al, 2004). Such patterns m a y help to identify factors that are related to breaks. 4 . 3 A F R A M E W O R K F O R USING D A T A AND PREDICTION M O D E L S T O I M P R O V E ASSET M A N A G E M E N T The framework developed herein m a y be used to guide a u t i l i ty i n ident i fy ing the magnitude o f its water m a i n break problems today and i n the future, and thereby enhance the development o f strategies for p r io r i t i z ing pipe replacements and data co l lec t ion . Its salient feature is that it integrates break predic t ion or deterioration models that provide an ind ica t ion o f future pipe condit ions w i t h exis t ing data, and thereby uses enhanced estimates o f vu lnerab i l i ty for each pipe. It is designed to accommodate systems w i t h l imi t ed data but is suff iciently f lex ib le to adapt for addi t ional informat ion that m a y be acquired over t ime. Other des ign considerations include ease and transparency o f use and faci l i ta t ion o f a dec i s ion-making process that is repeatable and defensible. Trad i t iona l ly , ut i l i t ies pr ior i t ize pipe replacements based on a combina t ion o f current management practices and his tor ical pipe breakage data. Management practices inc lude directives based on general guidelines, consequence assessments, legislat ive requirements, and other u t i l i ty priori t ies . Rud imenta ry analyses employed interpret h is tor ica l p ipe break data, i nc lud ing locat ion, t ime and date o f break, and pipe diameter and 128 material , and t yp i ca l l y has p rov ided informat ion regarding where and h o w many breaks are occurr ing , and what pipes are exper iencing breaks ( K l e i n e r and Rajani , 1999). Cons ide r ing this informat ion, the pr ior i ty o f the u t i l i ty m a y be to replace water mains o f a certain mater ial or size, those i n a certain area due to previous failures, those under roads that are to be re-paved, those that are current ly undersized, or those that have significant consequences i f failures were to occur, such as mains that serve hospitals. Some uti l i t ies m a y use a mul t ip le objective approach, we igh t ing each o f a number o f pr ior i t i za t ion cri teria, and assigning points to each pipe that describe the degree to w h i c h it meets a g iven cri teria (Deb et al, 2002; Sargeant, 2003). F o r each pipe, the sum o f the product o f the weight and assigned points for each pr ior i t iza t ion cri teria is obtained and used to pr ior i t ize candidate pipes. The framework developed i n this research is s h o w n i n F igure 4 .1 . In order to forecast p ipe breaks, the h is tor ica l data set m a y need to be expanded w i t h data available f rom other sources w i t h i n the u t i l i ty and from external agencies. In addi t ion to h is tor ica l p ipe breakage data, data for factors that m a y be important for predic t ing water m a i n breaks as p rev ious ly described m a y need to be obtained, i nc lud ing so i l type, surface, bedding, and b a c k f i l l material , type o f road usage, or typ ica l f l ow i n area o f break. T h i s informat ion m a y be consol idated b y creating a schematic o f data, w h i c h does not establish a new database per se, but draws from avai lable data for analysis when required, as described b y W o o d and Lence (2006) and W o o d et al, 2007. These data m a y be used direct ly i n the pr ior i t i za t ion process and as input to break predic t ion and deterioration models . The input to the models is developed b y grouping pipes i n w h i c h breaks have occurred based on factors that contribute to breaks. M a t e r i a l and diameter data are avai lable to most uti l i t ies and should be considered as the m i n i m u m 129 factors o n w h i c h to base pipe groups. The dec is ion o f whether to use a phys i ca l -mechanica l or statistical break predic t ion mode l m a y be made at this point , because the p ipe material determines whether a phys i ca l m o d e l exists for a g iven pipe and the diameter influences the pract ica l i ty o f app ly ing such a mode l . F o r sma l l and m e d i u m size uti l i t ies, the pract ical starting point is determinist ic statistical models , w h i c h m a y be developed w i t h read i ly avai lable commerc i a l software, i nc lud ing spreadsheets. M o r e capable uti l i t ies m a y consider more complex statistical or even phys ica l -mechanica l models , however , the l ong term use and maintenance o f these models is a serious considerat ion for those w h o choose these models . T o evaluate the accuracy o f a g iven statistical mode l , a por t ion o f the break data should be used to develop the equations and the most recent por t ion o f the break data should be retained as a holdout sample for compar ison . F o r example , i f a u t i l i ty has twenty years o f break history, it m a y choose to develop models based o n the first fifteen years o f data, and compare the m o d e l predict ions w i t h the remain ing five years o f actual breaks to assess the accuracy o f the predict ive mode l . W h i l e five years is a reasonable length o f holdout sample, this is a function o f the length o f record, and data required to generate the statistical models . In deve lop ing and us ing statistical models , one must determine the amount o f data that are required, the l eve l o f detail to be modeled , and the knowledge that w i l l be gained. In order to determine the length o f record required to develop a credible statistical mode l , the p ipe break record used to mode l the system m a y be var ied to evaluate the sensi t ivi ty o f the m o d e l accuracy to the length o f record used. In order to evaluate the important factors for predic t ing p ipe breaks, the pipe break data m a y be subdiv ided into different sub-groups and models for each o f these sub-groups 130 m a y be developed and compared i n terms o f their relative accuracy. T h i s process natural ly reduces the number o f breaks w i t h i n each sub-group used i n per forming statistical analyses, but m a y y i e l d more credible models . Cons ide r ing data that are t yp i ca l l y avai lable to uti l i t ies ( W o o d and Lence , 2006), potential sub-groups o f pipes for these models , inc lude those o f a specif ied i) p ipe material and diameter, w h i c h indicate pipe strength; i i ) p ipe material , diameter, and age w h i c h indicate pipe strength and age effects such as deterioration and construct ion practices; and i i i ) p ipe material , diameter, s o i l type, and age w h i c h indicate p ipe strength, interaction o f the p ipe mater ial and the so i l , and age effects. Shou ld the u t i l i ty have access to informat ion regarding surface condi t ions, this m a y also be considered i n fo rming the pipe sub-groups. W i t h the knowledge gained from the mode l results, managers can then target pipes that have the highest predicted breaks or rates o f breaks for pr ior i t iza t ion. T h i s informat ion is also useful for ident i fy ing future investigative programs such as s o i l and pipe condi t ion assessments and data acquis i t ion strategies such as changes i n f ie ld co l l ec t ion practices. The u t i l i ty m a y also choose to ver i fy the data or conduct invest igat ive assessments to understand the deterioration o f pipes that have significant breaks but cannot be accurately modeled . F r o m these activit ies, new data can be created to improve the understanding o f p ipe deterioration factors. P ipe network management practices m a y also be altered based o n the m o d e l results. E x a m p l e s o f such changes include ident if icat ion o f new design specifications such as the type o f jo ints required for certain pipes i n a part icular so i l , and in t roduct ion o f corrective measures such as cathodic protection programs. In order to main ta in relevance, it is recommended that models be rout inely rev iewed and updated as part o f the detailed capital p lan o f the u t i l i ty and to account for changes i n the rate at w h i c h breaks are occur r ing as a 131 result o f the changes i n pipe management practices. F i n a l l y , break data should be kept current. 4 . 4 BREAK PREDICTION MODELS FOR LAITY VIEW, MAPLE RIDGE, BC The appl ica t ion o f the framework is demonstrated us ing the L a i t y V i e w area o f M a p l e R i d g e , B C , Canada. T h i s area comprises 13 percent o f the 335 k i lometer dis t r ibut ion system for M a p l e R i d g e , is representative o f the urban area, experienced the same construct ion practices and has so i l types found i n the rest o f the munic ipa l i ty , and is home to a popula t ion o f approximate ly 6,000. The pipe materials found i n the area are asbestos cement, cast i ron , duct i le i r o n and steel, and i n diameters o f 150, 200 and 250 m m . P ipe insta l la t ion records began i n 1959 and few pipes i n M a p l e R i d g e were instal led before this date. The s o i l types found i n the L a i t y V i e w area are c lay , s i l ty-c lay , silt and sand. B reak data are avai lable f rom 1983 to 2004. A total o f 54 breaks occurred i n this per iod, and seven o f these occurred after the year 2000. P re l im ina ry analysis o f these data indicates that breaks are occur r ing i n asbestos cement, cast i r on and duct i le i ron pipes, i n pipes that are greater than 15 years o ld , and i n c l ay and s i l ty -c lay type soi ls ( W o o d et al, 2007). G i v e n the 20-year his tory o f record, the f inal f ive years f rom 2000 to 2004 was selected as the holdout sample. T o investigate the important factors for predic t ing p ipe breaks, pipes i n the area were grouped based o n the four types o f sub-groups p rev ious ly described. Information for surface mater ial w h i c h inc luded asphalt, concrete, and gravel or grass, is avai lable for this reg ion and thus another sub-grouping was examined that inc luded pipes o f a specif ied pipe material , diameter, age and surface material . The 132 combina t ion o f k n o w i n g w h i c h factors are important for predic t ing breaks and the c o m m o n failure types for a ne twork can provide insight on p ipe deterioration behavior. P ipe age sub-groups were created b y examin ing the data and ident i fy ing t ime periods i n w h i c h a meaningful number o f breaks occurred. F o r asbestos cement and cast i r on pipes, these sub-groups were compr ised o f pipes w i t h instal la t ion dates before 1959, between 1960 and 1974, and between 1975 and 1984. Asbestos cement and cast i ron pipes were not instal led i n M a p l e R i d g e after 1984. D u c t i l e i ron pipes were sub-grouped into pipes w i t h instal la t ion dates between 1970 and 1979, 1980 and 1989, 1990 and 1999, and subsequent to 1999. The o n l y steel pipes were instal led i n 1978 and are approximate ly 24 metres i n length. These have not broken. Statist ical determinist ic equations for each group o f L a i t y V i e w pipes were developed for t ime-l inear and t ime-exponent ia l functions. Statist ical determinist ic equations were selected as most appropriate for M a p l e R i d g e because they do not have a sufficient amount o f pipes (e.g. grey cast i ron) and data (such as remain ing p ipe w a l l thickness) to use phys ica l -mechanica l models or the resources to main ta in compl ica ted models ( M a p l e R i d g e has o n l y three engineers on staff and relies on technical support staff for m u c h o f the engineering department duties and responsibi l i t ies) . Statist ical determinist ic models can be easi ly taught to and appl ied b y technical staff and require fewer data. The results should provide insights for future performance and improve M a p l e Ridge ' s current practices o f p r io r i t i z ing water m a i n replacements w h i c h are based o n experience. The t ime-l inear equations for the cumulat ive number o f breaks at year t are based on Equa t ion 1. N(t) = A(t-to) + C (1) 133 Where N( t ) is the cumula t ive number o f breaks for the year t, t 0 is the reference year, i n the case o f L a i t y V i e w , 1983, A is a coefficient and C is a constant. T ime-exponent ia l equations for the cumulat ive number o f breaks at year t are based o n Equa t ion 2. N( t ) = A e k ( t " t 0 ) (2) Where A and k are coefficients and a l l other variables are as described above. A s noted earlier i n this chapter, these equations and their coefficients are specif ic to the L a i t y V i e w area pipes and their respective sub-groups. U t i l i t i e s should develop their o w n equations us ing their system-specific data, selected sub-groups and estimated coefficients (though they m a y choose to also use t ime-l inear and t ime-l inear regression). F o r each sub-group w h i c h had sufficient data, equations were der ived us ing S-Plus® and , spreadsheet software to solve for the coefficients. A m i n i m u m o f two breaks is required i n order to estimate these equations, and thus equations c o u l d not be der ived for a l l sub-groups analyzed. F o r each sub-grouping analysis, the percent o f a l l pipes for w h i c h an equation cou ld be der ived was estimated, as this is an ind ica t ion o f the extent o f the network that m a y be modeled . The accuracy o f the der ived equations, henceforth referred to as models , was calculated as the percent error o f mode l predict ions relative to the cumula t ive breaks i n 2004. F i n a l l y for t ime-l inear models , R - squared estimates are reported. Resu l t s o f b r e a k p r e d i c t i o n mode l s . The accuracy o f the predic t ion results for both t ime-l inear and t ime-exponent ia l models for the various sub-groups are shown i n Figures 4.2 through 4.6. The different amount o f breaks and the rate o f breaks among the 134 various groups suggest that there are differences i n behavior for deterioration and breakage. F o r the mater ial sub-groups, three sub-groups cou ld be modeled ; those for asbestos cement, cast i ron and ducti le i ron pipes and these represent approximate ly one hundred percent o f the pipe length i n the network. A s shown i n F igure 4.2, the t ime-l inear models are more accurate than the t ime-exponent ial models for asbestos cement and duct i le i r on pipes; the percent error for the t ime-l inear models was 29 and 34, and the percent error for the t ime-exponent ial models was 210 and 136, for the asbestos cement and ducti le i r on pipes, respectively. The range o f R-squared statistic for a l l o f the t ime-l inear models was 0.81 to 0.92 and the average R-squared value was 0.84. The results for the cast i r on pipes indicate that w h i l e few breaks have occurred i n these pipes they are occur r ing at an increasing rate. The accuracy o f predict ions for mater ial and diameter sub-groups is shown i n F igure 4.3. Here , seven sub-groups had sufficient number o f breaks to be mode led and these represent 99 percent o f the p ipe length i n the network. A g a i n , w i t h the except ion o f the cast-iron pipes, the t ime-l inear models are more accurate than the t ime-exponent ia l models . W h i l e the most accurate mode l is the t ime-l inear m o d e l for the duct i le i ron pipe w i t h a diameter o f 150 m m , i n general the performance o f t ime-l inear models for the asbestos cement and duct i le i ron pipes is s imi lar . The average R : s q u a r e d statistic for a l l o f the t ime-l inear models was 0.84 and the R-squared statistic was between 0.75 and 0.95. W h e n age was considered, seven sub-groups contained sufficient number o f breaks to be modeled , and these represent 56 percent o f the pipe length i n the network. A s shown i n F igure 4.4, the accuracy o f the t ime-l inear models for ducti le i ron pipes improved dramat ical ly , ind ica t ing that age effects are important i n predic t ing break rates for these pipes, and should be investigated. W i t h respect to the asbestos cement pipes, the age delineated sub-groups suggest that different age groups o f 150 m m asbestos cement pipes 135 are behaving differently w i t h respect to breaks, the abi l i ty to accurately predict breaks differ and that the number o f breaks for pipes instal led between 1975 and 1984 are increasing. The R-squared statistic for a l l o f the t ime-l inear models was between 0.75 and 0.94 and the average R-squared statistic was 0.84. W h e n p ipe - so i l interactions were considered, eight sub-groups cou ld be modeled , but this represented o n l y 3 8 % o f the pipe length i n the network. The accuracy o f predict ions for the mater ial , diameter, so i l and age sub-groups is shown i n F igure 4.5. These results suggest that the accuracy o f predict ions for pipes o f the same material differs i n different soi ls , even w h e n they are instal led at the same t ime. W h e n c l ay is considered as a factor i n the analysis , the accuracy o f the t ime-l inear models stayed the same or improved relative to analyses that considered o n l y material , diameter and age. The average R-squared statistic for a l l o f the t ime-l inear models for these sub-groupings was 0.78 and ranged between 0.63 and 0.94. ' The accuracy o f the models for material , diameter, age, and surface mater ial sub-groups is shown i n F igure 4.6. Here , eight sub-groups cou ld be mode led but these represent o n l y 40 percent o f the pipe length i n the network. W h i l e the average R-squared statistic for a l l t ime-l inear models for this case was 0.84 and ranged from 0.72 to 0.95, the accuracy o f these models is no better than the accuracy o f the t ime-l inear models for the material , diameter, and age sub-groups alone. Th i s indicates that, i n contrast to so i l type, surface mater ia l m a y not be an important factor to consider i n predic t ing pipe breaks for M a p l e R i d g e . O b s e r v a t i o n s . It is important to note that some o f the data that were created as part o f an earlier water m a i n break database constructed (see Chapter 3) contributed to increasing the accuracy o f the applications o f the break predic t ion models . In particular, the 136 • s o i l data p rov ided insights for engineering staff b y indica t ing that s o i l characteristics m a y be an influence on the rate o f cor ros ion i n certain pipes or bedding and b a c k f i l l used i n ins ta l l ing the pipes and thus conf i rmed the value o f creating, relat ing and processing data. A s a result, though the effort was significant, the data creat ion and m i n i n g p rov ided insights and is useful for management decisions and asset management. Wi thou t created data, the analysis and use o f predic t ion models w o u l d be l imi ted . F o r M a p l e R i d g e , the p ipe groups associated w i t h models that accurately predict h igh break rates are: 250 mi l l ime te r diameter asbestos cement pipes instal led i n c lay so i l between 1960 and 1969 and 150 mi l l ime te r diameter asbestos cement pipes instal led i n c lay s o i l between 1960 and 1969. A s a result o f these analyses, considerat ion o f the break rates o f var ious pipe groups and discussions w i t h operations and maintenance staff,, asbestos cement pipes w i l l be p r io r i t i zed for replacement (along w i t h cast i ron pipes w h e n opportunities arise) and further attention w i l l be g iven to co l l ec t ing data o n duct i le i ron pipes. M o r e important ly, because so i l type was identif ied as an important factor i n m o d e l i n g breaks, a so i l s ampl ing program was undertaken to improve the u t i l i ty ' s informat ion regarding s o i l resist ivi ty, p H , chlorides and s o i l type. A p re l imina ry p ipe sampl ing program was implemented at the same t ime to col lect informat ion on asbestos cement pipes and duct i le i ron pipes i n the area. A s a result o f the sampl ing programs, the importance o f bedding and back f i l l i ng practices and construct ion inspections was identif ied and changes i n construct ion specifications and inspect ion practices are be ing developed. Plans are underway to apply this f ramework to the rest o f the M a p l e R i d g e network. U l t ima te ly , schedul ing o f the p ipe replacements and budget estimates w i l l be undertaken i n conjunct ion w i t h other management considerations such as road rehabil i tat ion. 137 A n ongoing p rob lem for u t i l i ty managers is the a l locat ion o f scarce resources for both data co l lec t ion and analysis. One approach for determining the value o f the framework and a support ing data co l lec t ion program is to evaluate the value o f the addi t ional informat ion obtained. The value o f addi t ional informat ion m a y be estimated b y compar ing the dec is ion that w o u l d be undertaken wi thout the addi t ional informat ion w i t h the dec i s ion that w o u l d be undertaken w i t h the addi t ional informat ion (Schuyler , 2001) . F o r example , for L a i t y V i e w , the value o f deve lop ing statistical models that incorporate so i l data m a y be determined b y compar ing the cost o f rep lac ing the group o f pipes that has the highest break rates based o n data for material , diameter and age (i.e., 250 m m diameter asbestos cement pipes) w i t h that o f a replacement strategy that considers replac ing o n l y those 250 m m diameter asbestos cement pipes i n c l ay soils . I f a l l 250 m m diameter asbestos cement pipes, w i t h a total length o f 646 meters were to be replaced, the total cost o f replacement w o u l d be $193,800 (assuming a replacement cost o f $300 per meter). B y app ly ing the f ramework it was determined that a l l the breaks i n these pipes occurred i n c l ay so i l . I f it is assumed that a l l future breaks o f this pipe type w i l l occur i n c l ay soi ls , replacement o f these pipes, w i t h a total length o f o n l y 258 meters w o u l d cost $77,400. Thus the value o f the analysis and the so i l informat ion is approximate ly $193,800 - $77,400 = $116,400. W h i l e this addi t ional informat ion m a y not a lways lead to savings i n terms o f reducing the cost o f p ipe replacement, for example i n cases where the a l l pipes o f a certain material , diameter and age were instal led i n the same so i l type, the informat ion regarding so i l type m a y s t i l l be o f benefit. T h i s informat ion c o u l d be used to improve the instal lat ion practices or jus t i fy corrective measures. 138 4 . 5 CONCLUSIONS Predic t ive m o d e l i n g is useful for ident i fy ing replacement needs over t ime. H o w e v e r , ut i l i t ies do not c o m m o n l y use predict ive m o d e l i n g as part o f their asset, management practices. There are no c o m m o n databases for break analysis or c o m m o n condi t ion indices , and few uti l i t ies undertake cond i t ion assessment ( G r i g g , 2004), a l l o f w h i c h hinders indust ry-wide use o f predict ive mode l ing . The framework presented i n this paper improves upon the tradit ional pipe pr ior i t iza t ion approaches that o n l y l ook at the past his tory i n aggregate and do not necessari ly take into account trends and t i m i n g o f future breaks. A n advantage o f the framework is that it can be appl ied b y smal l to m e d i u m size uti l i t ies w i t h l imi ted informat ion and c o m m o n l y used analyt ical tools. F o r example , for M a p l e R i d g e , w h i l e useful informat ion was gained b y invest igat ing so i l type, reasonable insights m a y have been d rawn f rom analyses that considered o n l y material , diameter and age, informat ion that is t yp i ca l ly avai lable to most ut i l i t ies. Because factors that cause breaks va ry among ut i l i t ies , ut i l i t ies m a y f ind i n d i v i d u a l l y that creating more data (such as b y co l lec t ing traffic loading , b a c k f i l l and pressure data) and relat ing data for m i n i n g and analysis is wor thy o f the effort and expands the use o f this framework. W i t h this i n m i n d , the f ramework is f lex ib le and a l lows for considerat ion o f any avai lable data. In addi t ion to gu id ing water m a i n replacements, the f ramework m a y also be used to identify the k e y data for predic t ing water m a i n breaks. Because there is va r iab i l i ty i n the causes o f pipe breaks among different ut i l i t ies, i n order to understand the performance o f their system, 'uti l i t ies should col lect data as' ident i f ied i n recommended Best Practices; see N a t i o n a l G u i d e to Sustainable M u n i c i p a l Infrastructure ( N G S M I , 2002) and A W W A R P (Deb et al, 2002). A d d i t i o n a l informat ion m a y often be obtained eff iciently at the t ime o f the break repair b y rev i s ing forms to col lect 139 more informat ion, such as bedding or b a c k f i l l material ( W o o d and Lence , 2006) . T ra in ing w i l l often be required, and it is prudent to ver i fy data. C o n v i n c i n g staff to col lect data m a y be an obstacle, but i n v o l v i n g them i n dec is ion m a k i n g can be a w a y to gain support. B y us ing models to predict future breaks, r ev i ewing the accuracy o f the predict ions and updating the models , a u t i l i ty can improve its asset management practices. 4.6 A C K N O W L E D G E M E N T S The authors gratefully acknowledge the Dis t r i c t o f M a p l e R i d g e for p rov id ing data arid support i n the fo rm o f employee resources, and Professors A . D . R u s s e l l , J . W . Atwa te r at the U n i v e r s i t y o f B r i t i s h C o l u m b i a ( U B C ) for their insights and suggestions. M r . W . L i u assisted w i t h the preparation o f break data and M r . A . M a l y u k o f the Dis t r i c t o f M a p l e R i d g e assisted i n data processing and compi l a t i on . ' 140 4 . 7 R E F E R E N C E S A W W A and E E S , Inc., 2002. N e w or repaired water mains . A v a i l a b l e on- l ine at http:/ /www.epa.gov/safewater/tcr/pdf/maincontam.pdf. , A c c e s s e d February 12, 2006 Cooper , N . R . , B l a k e y , G . , She rwin , C , T a , T. , Whi te r , J . T . , and W o o d w a r d , C . A . , 2000. The use o f G I S to develop a probabi l i ty-based trunk mains burst r isk m o d e l . Urban Water, 2 :2000 :97 -103 . D e b , A . K . , Hansi t , Y . J . and Grabul tz , F . M . , 1998. Quant i fy ing Future Rehabi l i t a t ion and Replacement Needs o f Watermains . A W W A Research Foundat ion , 6666 Wes t Q u i n c y A v e n u e , Denver , C O . 80235. D e b , A . R . , Grablu tz , F . M . , Hasi t , Y . J . , Synder, J . K . , Longanathan, G . V . and A g b e n o w s k i , N . , 2002. P r i o r i t i z i n g Water m a i n Replacement and Rehabi l i ta t ion . 6666 Wes t Q u i n c y A v e n u e , Denver , C O . 80235, A W W A Research Founda t ion : 200. D i n g u s , M . , H a v e n , J . , and R u s s e l l , A . , 2002. Nondestructuve, N o n i n v a s i v e Assessment o f Underground Pipe l ines . AWWARFReport 90873, A W W A Research Foundat ion , 6666 Wes t Q u i n c y A v e n u e , Denver , C O 80235. Do leac , M . L . , L a c k e y , S. L . , and Brat ton, G . N . , 1980. P red ic t ion o f t ime-to-failure for bur ied cast i r on pipe. Proceedings of A WW A Annual Conference, Denver , C O . 141 G r i g g , N . S., 2004. Assessment and R e n e w a l o f Water Di s t r ibu t ion Systems. 6666 Wes t Q u i n c y A v e n u e , Denver , C O , A W W A Research Foundat ion . Jacobs, P . , and K a r n e y , B . , 1994. G I S development w i t h appl ica t ion to cast i ron water m a i n breakage rates. 2nd International Conference on Water Pipeline Systems, Ed inburgh , Scot land, 53-62. Ket t ler , A . J . and Goul ter , I. C , 1985. A n analysis o f pipe breakage i n urban water dis t r ibut ion networks. Canadian Journal of Civil Engineering, 12:2: 286-293. K l e i n e r , Y . , and Rajan i , B . B . , 2001 . Comprehens ive rev iew o f structural deterioration o f water mains : statistical models . Urban Water, 3:3: 131-150. K l e i n e r , Y . , and Rajani , B . B . , 1999. U s i n g l imi t ed data to assess future needs. Journal AWWA, 91:7: 47-62. L e v e l t o n Consultants L t d . , 2005. M a p l e R i d g e Water W o r k s C o r r o s i o n Investigation. Report 2705-0380, L e v e l t o n Consultants L t d . 102-19292 60th A v e n u e , Surrey, B C . M a l e , J . W . , W a l s k i , T . , and Slu tsky, A . F L , 1990. A n a l y z i n g Water M a i n Replacement Po l i c i e s . Journal of Water Resources Planning and Management, A S C E , 116:3: 362-374. 142 M a r k s , D . H . , A n d r e o u , S., Jeffrey, L . , Park , C , and Zas l avsky , A . , 1987. Statist ical M o d e l s for Water M a i n Fai lures . EPA/600/5-87/003, Wate r Eng inee r ing Research L a b , U S E P A . C inc inna t i , O H . N G S M I , 2002. Deter iora t ion and Inspection o f Water D i s t r ibu t ion Systems. Infraguide -Potable Water . Ot tawa, Canada, N a t i o n a l G u i d e to Sustainable M u n i c i p a l Infrastructure. O ' D a y , D . K . , 1982. O r g a n i z i n g and ana lyz ing leak and break data for m a k i n g m a i n replacement decisions. Journal A WWA, 74:11: 588-594. Pellet ier , G . , M a i l h o t , A . , and V i l l e n e u v e , J . -P. , 2003. M o d e l i n g water p ipe breaks - three case studies. Journal of'Water Resources Planning and Management, A S C E , 129:2: 115-123. Ra jan i , B . B . , and M a k a r J . , 2000. A methodology to estimate remain ing service life o f grey cast i ron water mains . Canadian Journal of Civil Engineering, 27: 1259-1272. Rajan i , B . B . , and K l i e n e r , Y . 2001 . Comprehens ive rev iew o f structural deterioration o f water mains : p h y s i c a l l y based models . Urban Water, 3:3: 151-164. Rajan i , B . B . , and Tesfamar iam, S., 2005. Es t imat ing t ime to failure o f ageing cast i ron water mains under uncertainties." Water Management for the 21st Century, U n i v e r s i t y o f Exeter , U K . , 1-7. 143 Sargeant, D . , 2003. Water M a i n Rehabi l i t a t ion Pr ior i t i za t ion . AWWA 2003 Seminar -Infrastructure: above and below ground, A n a h e i m , C A . Sav ic , D . A . , and Wal ters , G . A . , 1999. Hydro informat ics , D a t a M i n i n g and Main tenance o f U K Water Ne tworks . Anti-Corrosion Methods and Materials, 46:6: 415-425. Schuyler , J . , 2001 . Risk and Decision Analysis in Projects. Project Management Institute, F o u r Campus B l v d . N e w t o w n Square, Pennsy lvan ia . Shamir , U . and H o w a r d , C . D . D . , 1979. A n analytic approach to schedul ing pipe replacement. Journal AWWA, 71:5: 248-258 Torra , V . , Domingo-Fer re r , J . , and Torres, A . , 2004. D a t a m i n i n g methods for l i n k i n g data c o m i n g f rom several sources. 3rd Joint Un/ECE-Eurostat Work Session on Statistical Data Confidentiality, Monographs in Official Statistics, L u x e m b o u r g , Eurostat, 143-150 U S E P A , 2001 . D r i n k i n g Water Infrastructure Needs Survey. Second Repor t to Congress. EPA 816-R-01-004, U . S . Env i ronmenta l Protect ion A g e n c y Off ice o f Water , Washington , D C . W a l s k i , T . M . , 1982. E c o n o m i c A n a l y s i s o f Water M a i n Breaks . Journal of Water Resources Planning Management Division, A S C E , 108:3: 296-308. •J 144 W o o d , A . and Lence , B . J . , 2006. Assessment o f Water M a i n Break D a t a for Asse t Management . Journal AWWA, 98:07. W o o d , A . , Lence , B . J . and L i u , W . , 2007. Cons t ruc t ing Water M a i n Break Da ta for Asse t Management . Journal AWWA. 99:01. 145 Table 4.1 Typical data used in models and factors for which they are a surrogate Surrogate Factor Age Method of pipe manufacture, construction standards, deterioration over time Pipe material Construction practice, method of manufacture, failure mechanisms and causes, joint failures Pipe diameter Wall thickness and resistance to beam loading, pipe use, method of pipe manufacture, construction standards Type of pipe lining Method of pipe manufacture, resistance to corrosion Bedding and backfill material Physical stress on pipes caused by construction practices, structural resistance, soil type, fines migration Pipe protection (wrapped/anodes) Structural resistance, life expectancy, construction practice, method of pipe manufacture Pipe condition Remaining life Soil type Soil corrosivity, physical loading on the pipe such as swelling and frost, level of pipe protection, ground water effects such as draining ability or corrosion, construction practice, bedding and/or backfill material Under a boulevard or roadway Physical loading from surface loads such as traffic, road salt effects Depth of cover Physical loading on the pipe from the weight of soil Surface material/type Physical loading from surface use Normal operating pressure Internal pressure on pipe structure Typical flow in area of break Physical impact from factors such as accelerated internal corrosion from low flow mains Traffic classification Physical loading from surface loads such as traffic volumes and wheel loads Road/surface usage Physical loading from surface loads 146 Figure 4.1 Improving asset management using pipe break prediction models Management considerations Management strategies Master growth plans, construction of other infrastructure, risk assessments, legislative requirements, etc. "'Prioritization of pipe replaccmenl'for asset ^Ifl^wiagernent. Inputs'indude^he:,' ^consideration of managemehfrhistbiical and future predictions • [Historical data \ Stratify pipes into groups based on factors Data construction, linking and updating of data • Investigative programs '.- -• Verification program of constructed data • Pipe network practices assessments Predictions of , future breaks Apply models, compare results with holdout samples 'and evaluate . model performance Target pipes with critical or highest break rates as part of asset management replacement strategy 147 Figure 4.2 Degree of accuracy of time-linear and time-exponential predictions for material groups 250% 200% 150% 100% 50% 0% -50% -100% Asbestos cement pipes Cast iron pipes • Time-linear • Time-exponential Ductile iron pipes Note In 2004, there were a total of 32 breaks in asbestos cement pipes, 5 in cast iron pipes and 17 in ductile iron pipes. 148 Figure 4.3 Degree of accuracy of time-linear and time-exponential predictions for material and diameter groups 300% Notes AC denotes asbestos cement pipes, CI denotes cast iron pipes and DI denotes ductile iron pipes. Pipes are grouped by material and diameter (in millimeters). For example, AC 150pipes are asbestos cement pipes of 150 millimeters diameter. In 2004, there were 24 breaks in AC 150pipes, 5 in AC 200, 3 in AC 250, 4 in CI 150, 9 in DI 150 and 2 in DI 250 pipes. 149 Figure 4.4 Degree of accuracy of time-linear and time-exponential predictions for material, diameter and age groups 250% 200% 150% 100% 50% 0% -50% • Time-linear • Time-exponential AC 150 AC 150 AC 150- AC 200 AC 250 DI 150 1980- DI 200 1980-1960-1969 1970-1974 1975-1984 1970-1974 1960-1969 1989 1989 Notes AC denotes asbestos cement pipes, CI denotes cast iron pipes and DI denotes ductile iron pipes. Pipes are grouped by material, diameter (in millimeters) and age. For example, AC 150 1960-1969 pipes are asbestos cement pipes of 150 millimeters diameter installed between 1960 and 1969. In 2004, there were 12 breaks in AC 150 1960-1969pipes, 7 in AC 150 1970-1974, 5 in AC 150 1975-1984, 3 in AC 200 1970-1974, 3 in AC 250 1960-1969, 4 in DI 150 1980-1989 and 3 in DI 200 1980-1989 pipes. 150 Figure 4.5 Degree of accuracy of time-linear and time-exponential predictions for material, diameter, soil and age groups 400% 350% 300% 250% 200% 150% 100% 50% 0% • Time-linear • Time-exponential AC 150 AC 150 AC 150 A C 250 Dl 150 A C 150 AC 200 DI200 Clay Clay Clay Clay Clay Silt 1960- Silt 1970- Silt 1980-1960- 1970- 1975- 1960- 1980- 1969 1974 1989 1969 1974 1984 1969 1989 Notes AC denotes asbestos cement pipes, CI denotes cast iron pipes and DI denotes ductile iron pipes. Pipes are grouped by material, diameter (in millimeters), soil type and age. For example, AC 150 Clay 1960-1969 pipes are asbestos cement pipes of 150 millimeters diameter installed in clay soil between I960 and 1969. In 2004, there were 7 breaks in AC 150 Clay 1960-1969pipes, 7 in AC 150 Clay 1970-1974, 2 in AC 150 Clay 1975-1984, 2 in AC 250 Clay 1960-1969, 4 in DI 150 Clay 1980-1989, 3 in AC 150 Silt 1960-1969, 3 in AC 200 Silt 1970-1974 and 2 in DI200 Silt 1980-1989 pipes. 151 Figure 4.6 Degree of accuracy of time-linear and time-exponential predictions for material, diameter, age and surface material groups 200% 150% 100% 50% 0% -50% • Time-linear • Time-exponential *-' v." v.-^ ^ ^ ^ ^2 ^ %, 'S>± '<°> <9> ^ *3 \ \ V V V V \ \ \ \ \ * \ \ \ % \ % \ c?o °;o Notes AC denotes asbestos cement pipes, CI denotes cast iron pipes and DI denotes ductile iron pipes. Pipes are grouped by material, diameter (in millimeters), age and surface material. For example, AC 150 1970 - 1974 Asphalt pipes are asbestos cement pipes of 150 millimeters diameter installed between 1970 and 1974 under an asphalt surface. In 2004, there were 5 breaks in AC 150 1970-1974 Asphalt pipes, 7 in AC 150 1960-1969 Gravel/grass, 5 in AC 150 1970-1974 Gravel/grass, 3 in AC 150 1975-1984 Gravel/grass, 2 in AC 200 1 970-1974 Concrete, 2 in AC 250 1960-1969 Gravel/grass, 4 in DI 150 1980-1989 Gravel/grass and 2 in DI 200 1980-1989 Asphalt pipes. 152 C H A P T E R 5 CONCLUSIONS AND R E C O M M E N D A T I O N S 153 5.1 S U M M A R Y O F R E S E A R C H G O A L S Asset management o f water systems involves assessing w h e n to replace aging and deteriorating pipes. The goal o f this research is to assist sma l l to m e d i u m size uti l i t ies w i t h ident i fying, co l lec t ing and constructing relevant pipe break data to analyze their pipe network, and us ing break predict ions to in fo rm their water m a i n replacement strategy and guide their data acquis i t ion programs. Firs t , the data that are col lec ted and avai lable for analysis across ut i l i t ies i n N o r t h A m e r i c a are identif ied. N e x t , a methodology to create and l i n k data obtained f rom various data sources that can be used i n uti l i t ies o f a l l sizes to construct databases is developed. F i n a l l y , a f ramework to assist the pr ior i t iza t ion o f water m a i n replacements and data acquis i t ion based o n predic t ing future water m a i n breaks w i t h i n a g iven water dis t r ibut ion system is presented. The framework is appl icable for the range o f data avai lable i n typ ica l water ut i l i t ies , acknowledges exis t ing industry needs and practices and m a y help managers to acquire and use avai lable data. M u c h o f the focus o f water m a i n break research has been on the data r i c h and technica l ly sophisticated larger uti l i t ies. H o w e v e r , sma l l and m e d i u m size uti l i t ies need the techniques developed i n this research because they have scarce resources for asset management w i t h i n their organizations. Compared w i t h larger ut i l i t ies, they do not have the staffing expertise or the capaci ty for t ra ining, moni to r ing or deve lop ing back-up systems (Ontario P I R , 2005). W i t h i n these uti l i t ies, there is lit t le or no rel iable documentat ion regarding the locat ion, capacity, condi t ion and adequacy o f p ipe network elements for meet ing present or future needs ( M y e r s , 2001). These uti l i t ies m a y also lack the f inancial and organizat ional resources to implement a complex asset management p rogram or lack the h is tor ica l data or tools to fu l ly analyze their system. T h e y need re la t ive ly inexpensive techniques. T h i s research provides adaptable approaches for eff ic ient ly acquir ing data 154 regarding water m a i n breaks, c o m p i l i n g , ana lyz ing and us ing the data to predict future water m a i n breaks and i m p r o v i n g pr ior i t iza t ion o f pipe replacements. Se lec t ing the case s tudy . The research i n this thesis uses real data from the Dis t r i c t o f M a p l e R i d g e , B C . M a p l e R i d g e was selected because it is a m e d i u m size water u t i l i ty , is s imi la r to munic ipa l i t ies that have undergone urbanizat ion over the past decades and possesses data that were made available to me. M o r e o v e r , M a p l e R i d g e was interested i n us ing break predic t ion models to improve its asset management practices and w h i l e it l acked a comprehensive water m a i n break database, it was receptive to deve lop ing databases for analysis. It also needed a strategy to manage and main ta in the data after they were used to predict water m a i n breaks. A p p e n d i x C is a summary descr ipt ion o f the M a p l e R i d g e water system. 5.2 C O N C L U S I O N S Water m a i n break data co l lec t ion is evo lv ing and industry practices do not match best practices recommended b y N G S M I (2002) and D e b et al (2002) at this t ime. Ut i l i t i e s need a strategy for data qual i ty improvement that w i l l help them deal w i t h challenges such as d i f f icu l ty i n m o b i l i z i n g f inancia l and human resources, absence o f h is tor ica l data, l ack o f knowledge o f current organizat ional practices, l o w re l iab i l i ty o f p rev ious ly col lected data, d i f f icu l ty i n p r io r i t i z ing data co l lec t ion , and the need to develop effective data storage programs. In general, ut i l i t ies can be classif ied as those possessing expanded, intermediate, l imi t ed or m i n i m a l data. W h i l e both phys ica l and statistical models have been developed for predic t ing pipe deterioration and for deve lop ing water m a i n rehabil i ta t ion plans, it is evident that the choice and appl icat ion o f these models are l imi t ed b y the data that uti l i t ies have regarding water m a i n breaks (Rajani and K l e i n e r , 2001 ; K l e i n e r and Rajan i , 2001). 155 F o r practit ioners and researchers a l ike , characterizat ion o f these data classes m a y be used to in fo rm the development o f new asset management techniques that are tai lored to the data l imita t ions that ut i l i t ies face. U t i l i t i e s m a y also improve their data co l lec t ion b y m o d i f y i n g their current practices and more s ignif icant ly , they can seek out alternative data sources f rom w h i c h to analyze breaks and u l t imate ly predict future breaks. The alternate sources that are identif ied i n this research can y i e l d informat ion for researchers and managers al ike. The process o f creating the data schematic as developed i n this research is useful for l i n k i n g mul t ip le databases i n order to compi l e and analyze data. It expands the data avai lable for analysis for both present and future applicat ions and a l lows decentral ized data input and management. M o r e important ly, it is a f lexible approach that a l l ut i l i t ies can employ wi thout significant resource commitments . It reduces problems related to data ownership among units w i t h i n organizations regarding data co l lec t ion , management and disseminat ion o f infrastructure information. The framework developed i n this research for l i n k i n g data is f lex ib le , anticipates the evolu t ion o f data co l lec t ion , bu i ld ing , ver i f ica t ion and storage and a l lows for a var iety o f users. It does not abruptly disrupt data co l lec t ion and warehousing practices and it a l lows managers to continue to expand data co l lec t ion because databases are decentral ized. It is f lex ib le and can be easi ly adapted to a l l ut i l i t ies, whether they are smal l , m e d i u m or large, and regardless o f the uniqueness o f the data col lected and organizat ional framework. Th i s technique can also incorporate tacit data. The importance o f capturing tacit data w i l l increase over the next decades as baby boomer staff retire. T h i s thesis develops an approach for us ing break predic t ion models for ident i fy ing replacement needs over t ime and uses improvement i n m o d e l accuracy as means o f 156 ident i fy ing the k e y data for predic t ing future water m a i n breaks and in fo rming future data acquis i t ion strategies. Trad i t iona l approaches for p r io r i t i z ing p ipe replacements do not incorporate break predict ions. The framework developed i n this research a l lows for the construction, assessment and use o f any available data b y any size ut i l i ty . 5.3 O B S E R V A T I O N S G e n e r a l obse rva t ions . A number o f observations arise from this research. W h i l e this research p r i m a r i l y focuses on engineering science, a number o f the observations relate to management science and the relationships organizations and people have w i t h data u t i l iza t ion . W h i l e these topics arise from the research, they are not addressed i n this thesis and future research i n these areas w i l l be valuable. 1. A s noted i n the thesis, data are col lected throughout an organizat ion b y var ious departments and staff for various purposes. F o r data to be used corporately, executives must acknowledge and address data ownership among departments and managers. 2. Because asset management is a corporate responsibi l i ty , proprietary issues and organizat ional compartmental izat ion can pose major challenges to implement ing an asset management program. Corporate objectives o f knowledge management (e.g., database development and maintenance) should be established and most important ly, be accepted b y those responsible for co l lec t ing , managing and analysing the data. These objectives should be established and promoted b y u t i l i ty executives throughout the u t i l i ty because i n some organizations knowledge m a y be v i e w e d as power and data m a y be interpreted as a surrogate for knowledge . 157 3. A n important task for managers is to establish and encourage a culture o f knowledge sharing (Conne l ly , 2000). M o t i v a t i n g and coaching staff to share knowledge can be a major challenge. A s w e l l , managers themselves are not immune to the habit o f hoarding informat ion and knowledge , though this tendency m a y be reflective o f the corporate culture and the individual ' s relationship w i t h their subordinates, peers and supervisor. 4. A significant need exists i n uti l i t ies for capturing inst i tut ional m e m o r y and data that currently exist and w h i c h w i l l be lost as employees retire. C o m m o n l y , large amounts o f inst i tut ional m e m o r y are not recorded. F o r most ut i l i t ies, there is a need to capture the m e m o r y o f operating departments since they are more often characterized as "act ion oriented" and "hands on" rather than "paper l o v i n g " . Managers must f ind solutions to address this important issue. 5. Water ut i l i t ies also face recrui t ing, t ra ining and capaci ty b u i l d i n g challenges. The v i e w that staff w i l l j o i n an organizat ion early i n their career and spend thirty years i n that organizat ion is becoming extinct. F o r example , Dis t r ic t o f M a p l e R i d g e recruiters consider obta ining five to ten years o f service f rom a non-un ion manager (before he or she leaves the organizat ion) as a valuable experience. C o m p o u n d i n g this, currently, there is significant compet i t ion among B C employers to recruit and retain engineers. U t i l i t i e s also require t raining and capaci ty b u i l d i n g programs for new staff as w e l l as ex is t ing staff. One challenge for m a n y uti l i t ies is that t raining budgets are often the first to be cut i n t imes o f f inancial restraint (because budgets are p r i m a r i l y v i e w e d as support ing expenditures and t ra ining as a discret ionary expense). T h i s was the case i n M a p l e Ridge ' s history. The success o f t ra ining programs is dependent on the market ing and implementa t ion o f the t raining as w e l l as the qua l i ty o f the training. Th i s aspect o f organizat ional development is 158 also important because accord ing to Jacobson and Prusak (2006), organizations w i l l receive greater value f rom informat ion b y deve lop ing strategies and t ra ining staff to help them use what they have rather than b y searching for more data. 6. U t i l i t y managers also need to inspire and motivate posi t ive change. D u r i n g the course o f the research, the author observed that managers f ind that support for change (from their supervisor or employees) is not automatic, and factors that influence the support or change inc lude the career goals o f their supervisor, their l eve l o f influence w i t h i n the organization's pol i t ics , staff motivators and h o w the u t i l i ty is governed. F o r example , changes i n data co l l ec t ion practices because o f legis la t ion tend to be more rap id ly implemented than other reasons for changes ( N S G M I , 2003) . 7. A f inal observation is that organizat ional leadership, structure and behaviour have a major influence o n a uti l i ty 's focus and practices. Based on what I have observed o f var ious ut i l i t ies , the manner i n w h i c h engineering and maintenance departments function and i n w h i c h responsibi l i t ies are distributed w i t h i n a u t i l i ty can lead to dupl ica t ion o f w o r k (because o f ambigui ty or the desire to possess the informat ion or responsibi l i ty) or the incomple t ion o f w o r k (because each department m a y deny responsib i l i ty and assume that the other is addressing the issue). Furthermore, u t i l i ty executives need to provide strategic th ink ing and leadership o f the organizat ion, w h i l e ba lanc ing corporate and i nd iv idua l goals and strengths. Wi thou t this, staff efforts m a y be misp laced or frustrated or m a y flounder. P r o f e s s i o n a l a p p l i c a t i o n s . Th i s thesis has many pract ical applications for smal l and m e d i u m size uti l i t ies. It provides informat ion o n data co l lec t ion and presents an approach that a water u t i l i ty m a y adopt should they decide to use break predic t ion models . G i v e n the w o r k reported i n Chapter 2, ut i l i t ies can assess their practices against those o f their peers and those recommended as best practices. T h e y can ident ify and 159 improve their data co l l ec t ion practices and use the survey results to facilitate discussions w i t h i n their organizat ion regarding the ava i lab i l i ty and storage o f data. T h e y m a y f ind addi t ional data avai lable from other sources such as those ident i f ied i n this thesis. I f there are insufficient data for analysis, they m a y compi l e and l i n k data and construct addi t ional databases to extend the breadth o f data as demonstrated i n Chapter 3. F o l l o w i n g that example , they can construct a data schematic for their organizat ion to analyze their system for asset management i n general and to explore the under ly ing causes o f water m a i n breaks. Once they have constructed and analyzed the data w h i c h is useful despite the effort required, they can then use the framework developed and demonstrated i n Chapter 4 to . incorporate the use o f break predic t ion models to improve asset management and to in fo rm their future data acquis i t ion and storage programs. The approaches developed i n Chapters 3 and 4 address the problems faced b y uti l i t ies, and are designed to be adaptable to their needs and the examples used are based on real data. Researchers w i l l also benefit from the w o r k reported i n Chapters 2 and 3 w h i c h identifies the data that are available for deve lop ing future asset management tools and h o w uti l i t ies can access and construct data for research purposes. L e s s o n s l e a r n e d . W h i l e the research has a number o f applicat ions, a number o f lessons were learned. W h e n app ly ing the research as described i n Chapter 3, a u t i l i ty requires staff and external help i n two areas. F i r s t ly , they require technical assistance i n the f o l l o w i n g tasks: • D e c i d i n g o n the objective o f the exercise. A suggested objective is presented i n the thesis and other purposes are also identif ied. These should be developed b y managers and engineers. 160 • Crea t ing data b y r e v i e w i n g different sources o f data (internal and external to the ut i l i ty) . The thesis presents a number o f techniques such as buffering a co l l ec t ion o f data, in te rv iewing people to capture tacit informat ion, examin ing previous practice standards and conduct ing surveys. Some o f this w o r k can be undertaken b y consultants and b y training exis t ing staff. • D e c i d i n g upon the databases to be related and the nature o f the relationships. Some databases and relationships are suggested i n this thesis, but these decisions should be determined j o i n t l y b y u t i l i ty and data managers. Secondly , the u t i l i ty w i l l require more technical resources to: • R e v i e w the extent o f data ava i lab i l i ty throughout the organizat ion. The thesis suggests sources to explore. • Create data from paper records. . • Es tab l i sh l inks among various databases. • M a p the l inks and various databases. T h i s can be undertaken b y l ine staff and this thesis provides guidance for this task. • Per form some exploratory analyses. It should be noted, that the technical w o r k requires some understanding o f the data and some ab i l i ty to read design drawings. In addi t ion, the project manager app ly ing the research should have strong communica t ion and interpersonal sk i l l s to determine where data m a y be avai lable and to obtain consensus on data sharing among var ious departments. T h e y should be tactful, d ip lomat ic , persuasive, patient and persistent and should not be 161 easi ly discouraged because app ly ing the w o r k w i l l take t ime w i t h i n any ut i l i ty . Sponsorship and support f rom the u t i l i ty executive should be obtained w h i c h w i l l help w h e n w o r k i n g through departmental and corporate issues. F i n a l l y , it is not unrealist ic to expect that a project such as described i n Chapter 3 w o u l d take a 1.2 person years to two person years o f effort and a project such as described i n Chapter 4 m a y take as m u c h as one person year. Validation of the work. W h i l e the p r o o f o f this w o r k lies i n the arguments and demonstrat ion o f the approaches developed, the va l ida t ion o f the contr ibut ion w i l l be the acceptance o f the methods proposed i n practice and whether they are employed b y uti l i t ies to improve asset management and data product iv i ty . In us ing their o w n system-specific data and the thesis as guidance, this research m a y be appl ied and adapted to uti l i t ies o f various sizes possessing a range o f abil i t ies for i m p r o v i n g their asset management practices. U l t ima te va l ida t ion m a y be undertaken b y evaluat ing the success o f such applications. Further research. T o make the appl ica t ion o f this research more useful, further research is needed i n the f o l l o w i n g areas. 1. The survey was developed i n E n g l i s h and forwarded to those communi t ies l is ted i n A p p e n d i x E . O n l y one response was received f rom the A n g l o - Q u e b e c munic ipa l i t ies . Investigation o f French-Canadian water m a i n break data co l l ec t ion practices c o u l d in fo rm these communi t ies and the larger water u t i l i ty industry, al though the data avai lable to Pel le t ier et al. (2003) suggest that French-Canadian practices are no different than those identif ied i n this research. Regardless, translating and dis t r ibut ing the survey throughout Quebec is a potential future project. 2. Tes t ing the f ramework o f us ing water m a i n break predic t ion models i n a u t i l i ty that has more water m a i n breaks, a longer his tory o f breaks or different c l imate w o u l d add 162 further conf i rmat ion o f the appl icabi l i ty o f the research to other ut i l i t ies . The framework has been designed and demonstrated to be robust, though further conf i rmat ion w o u l d be useful. Furthermore, w i t h a larger number o f breaks to analyze, it is possible that other k e y data m a y be identif ied as important for determining the accuracy o f break predic t ion models . 3. A p p l i c a t i o n o f a combina t ion o f statistical and phys ica l -mechanica l models should be explored w i t h i n the framework p rov ided herein. The accuracy o f predict ions for the different types o f models c o u l d also be assessed to g ive further guidance for choos ing models . In addi t ion, c o m b i n i n g the models i n a case study c o u l d prov ide insights that can be used to potent ia l ly demonstrate or improve the robustness and f l ex ib i l i t y o f the f ramework developed herein. 4. F i n a l l y , the topics ident i f ied i n the general observations section should be further explored to assist ut i l i t ies i n app ly ing the research i n practice. These issues include h o w uti l i t ies can increase knowledge sharing (o f data and practices) w i t h i n their organizat ion and ident i fy ing k e y organizat ional structures, leadership attributes and motivators that are needed to improve water u t i l i ty management. W h i l e smal l and m e d i u m size uti l i t ies are able to make operating p o l i c y and practice changes q u i c k l y because dec i s ion m a k i n g typ ica l ly rests w i t h fewer staff than is the case i n larger organizat ions, they are l ike most organizations. T h e y are l im i t ed b y resources i nc lud ing leadership and mot iva t ion sk i l l s and training to execute large changes. Research i n determining and assessing the required sk i l l s , personali ty aptitudes, abi l i t ies , t raining and human resource needs for ins t i tu t ional iz ing the approaches presented i n Chapters 3 and 4 w o u l d be useful i n extending the impact o f this work . 163 Future research interests of the author. Three areas that I am consider ing for further research ar is ing f rom the w o r k i n this thesis inc lude app ly ing addi t ional approaches to ana lyz ing break data, app ly ing the data construct ion approach and framework developed herein to other infrastructure assets, and enhancing u t i l i ty knowledge management practices. 1. A p p l y i n g K n o w l e d g e D i s c o v e r y tools such as ar t i f ic ia l intel l igence to analyse large water m a i n break databases. T h i s has potential to assist those water ut i l i t ies fortunate enough to have a breadth o f data and a l ong his tory o f breaks and to reduce the necessity for h a v i n g m a n y experienced staff to manage infrastructure assets. 2. A p p l y i n g the concept o f l i n k i n g and relat ing data (as shown i n the water m a i n break schematic shown i n Chapter 3) and us ing statistical determinist ic and other predic t ion models to sewerage and drainage systems. Ex tend ing the approach presented i n this thesis to these infrastructure systems has several advantages. These systems are usua l ly o w n e d and managed w i t h i n the same manageria l unit and typ ica l ly have s imi la r replacement values as water systems. Nonetheless , there are differences among the systems. F o r example, sewer systems are easier to inspect us ing v ideo cameras and a c o m m o n condi t ion rat ing system for them exists. T h o u g h drainage systems c o u l d use the same condi t ion rat ing system, they are rarely evaluated and wear out at a faster rate. 3. E x a m i n i n g h o w to manage knowledge o f a system w i t h i n an organizat ion. The data schematic and concept o f relat ing relat ional databases as discussed i n this thesis has potential to p l ay a significant role i n connect ing data for var ious services among the members o f an organizat ion, but research is needed to assist ut i l i t ies i n capturing, managing, main ta in ing and us ing this knowledge . E x a m p l e research questions inc lude: what are the best techniques for in te rv iewing and recording tacit data from ret ir ing 164 employees, what is the op t ima l organizat ional structure for sharing knowledge among engineers and maintenance staff, and what are the most efficient and effective approaches that ut i l i t ies can emp loy to make data accessible across an organizat ion? 5 . 4 C L O S I N G R E M A R K S The approaches developed herein are easi ly appl ied. There are s ignif icant ly more sma l l and m e d i u m size uti l i t ies than larger uti l i t ies (Van ie r and R a h m a n , 2004) and these uti l i t ies can benefit from apply ing the work . The approaches have been demonstrated w i t h real data and m a y prov ide uti l i t ies w i t h insights and guidance for a l locat ing their scarce resources, consider ing their current l imita t ions and future needs. The appl ica t ion is pract ical and can be implemented incremental ly . The thesis chapters are at various stages o f pub l ica t ion or review. Chapter 2 was publ i shed i n the J u l y 2006 issue o f the Journal o f the A W W A . Chapter 3 is publ i shed i n the January 2007 issue o f the Journal o f the A W W A . Chapter 4 was submitted to the A S C E Journal o f Infrastructure Systems i n Ju ly , 2006. A n invi ted presentation on the results o f the first paper was made at the September 2006 A n n u a l P u b l i c W o r k s A s s o c i a t i o n o f B C (a chapter o f the A m e r i c a n P u b l i c W o r k s Assoc ia t ion) Conference i n Q u a l i c u m Beach , B C . In addi t ion, the w o r k w i l l be presented as part o f a water system asset management workshop to engineers i n the Greater V a n c o u v e r area. In c los ing , as a result o f the w o r k conducted i n this thesis, M a p l e R i d g e has implemented a number o f the findings to improve its water m a i n break data co l lec t ion practices. 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C l e a n Water and D r i n k i n g Water Infrastructure Gap A n a l y s i s , Env i ronmen ta l Protect ion A g e n c y , Off ice o f Water , D r i n k i n g Water D i v i s i o n , Wash ing ton , D C . U S E P A , 2001 . D r i n k i n g Water Infrastructure Needs Survey. Second Repor t to Congress. U n i t e d States. Env i ronmen ta l Protect ion A g e n c y , Off ice o f Water , D r i n k i n g Water D i v i s i o n , Wash ing ton , D C . U S E P A , 1999. D r i n k i n g Water Infrastructure Needs Survey. U n i t e d States Env i ronmen ta l Protect ion A g e n c y , Of f ice o f Water , D r i n k i n g Water D i v i s i o n , Wash ing ton , D C . U S F H W A , 1999. Asse t Management Pr imer , Federal H i g h w a y s Admin i s t r a t i on , U S Department o f Transportat ion, Off ice o f Asset Management , 400 7th Street, S . W . Wash ing ton D . C . 20590. V a n i e r , D . J . , 2001 . Asse t Management : " A " to " Z " , American Public Works Association Annual Congress and Exposition - Innovations in Urban Infrastructure Seminar, Phi lade lph ia , U . S . September, 2001 . 1-16. 176 V a n i e r , D J . and R a h m a n , S., 2004. M u n i c i p a l Infrastructure Investment P l a n n i n g (MID?) M U P Report : A P r i m e r o n M u n i c i p a l Infrastructure Asse t Management . Report B-5123.3, N a t i o n a l Research C o u n c i l Canada, Ottawa, O N . W a l s k i , T . M . , 1982. E c o n o m i c A n a l y s i s o f Water M a i n Breaks . Journal of Water Resources Planning Management Division, 108:3: 296-308. W i l d , C . J . and Seber, G . A . F . , 2000. Chance Encounters - A First Course in Data Analysis and Inference. John W i l e y and Sons Inc., N e w Y o r k , N . Y . W o o d , A . and Lence , B . J . , 2006. Assessment o f Water M a i n Break D a t a for Asse t Management . Journal AWWA, 98:07. W o o d , A . , Lence , B . J . and L i u , W . , 2007. Cons t ruc t ing Water M a i n Break D a t a for Asse t Management , Journal AWWA, 99:01. X u , C . and Goul ter , I .C . , 1998. Probabi l i s t ic mode l for water dis t r ibut ion re l iabi l i ty . Journal of Water Resources Planning and Management, 1 2 4 : 4 : 218-228. 177 P A G E L E F T B L A N K 178 APPENDICES APPENDIX A 179 A p p e n d i x A summarizes the uti l i t ies surveyed and the data queried b y Deb et al. (2002) and b y the author as part o f the survey reported o n i n Chapter 2. A compar i son o f the survey responses b y service popula t ion is shown i n Table A . l . A compar i son o f the questions asked b y the two surveys is shown i n Table A . 2 . Table A.l Comparison of North American utility responses by service populations Survey <100,000 >100,000 Survey b y D e b et al (2002) 5 32 Survey b y W o o d and L e n c e (2006) 37 22 Table A.2 Comparison of questions posed by Deb et al. (2002) and Wood and Lence (2006) Survey question by Deb et al (2002) Question addressed by Wood and Lence Notes Utility size yes Water production no Total length of pipe yes Main failures Formal program for control of failure n/a Main inventory n/a Computerized main inventory of total n/a Failure records yes Wood and Lence survey focused on failure records Computerized failure records of total n/a General Information yes Date, address yes Temperature yes Wood and Lence also queried air, water, change in water temperature and soil temperature Time of detection and arrival yes includes repair date Impact on surroundings Services affected yes Wood and Lence survey includes type of services and length of outage 180 Blocks affected no Wood and Lence survey includes quantityof parcels and number of customers affected and property damage Hydrants affected no Proximity to buried objects no Water main information Material yes Location in street yes Wood and Lence survey includes surface use Diameter yes Depth yes Cover depth Installation date yes Cathodic protection yes Wood and Lence survey queried pipe protection and /or anode installation Joint type yes Type of repair yes Pressure Range yes Operating pressure Pump station status no Wood and Lence survey queried flow in area Failures Type of failure yes Wood and Lence survey queried on suite of types (11), Debet al.just queried i f type of failure was recorded Probable cause yes Wood and Lence survey queried on suite of causes (13) Type of repair yes Wood and Lence survey queried on suite of repairs (7) and additional treatments Exterior/interior of pipe yes Wood and Lence survey queried on both exterior and interior, lining condition and other details Bell condition no Wood and Lence survey queried on Joint type Condition of valves Required for isolation yes Condition no 181 Reporting bedding conditions yes Wood and Lence survey queried on material and condition separately Reporting of seismic/geotechnical conditions Soil description yes Wood and Lence survey queried on native soil, soil pH, soil Moisture content while Deb at al. identified i f soil description was recorded Geologic unit description no Groundwater depth no Seismic hazard unit no Collecting field samples Pipe samples yes Soil samples yes Use of automated systems Wood and Lence survey explored other sources of data Field portable computers see'note GPS see note GIS see note D B M S see note Formal renewal program Main replacement n/a Main rehabilitation n/a Costs records Direct labour yes Wood and Lence survey queried on crew hours Indirect labour see note Wood and Lence survey queried on all labour costs Materials yes Equipment, yes Surface repairs see note Wood and Lence survey queried on Property damage costs Damage yes-Wood and Lence survey queried on Property damage costs 182 APPENDIX B 183 s Append ix B provides the statistical analysis for guiding the interpretation o f the survey results and their applicabili ty to the general population o f water utilities. G i v e n a specified percentage o f respondents that collect a particular type o f data, one may wish to determine the percentage o f a l l water utilities that are l ike ly to collect the given data. Such questions are addressed using the confidence range o f observations regarding the particular type o f data for utilities i n the general population, and these are based on the standard error o f the sample population. W i l d and Seber (2000) suggest that an accepted measure o f the confidence in the behaviour o f the general population (e.g., a l l water utilities) is equivalent to two standard errors o f the sample proportion (e.g., the respondents). The standard error o f the sample proportion is calculated using the equation: Se(p) = ( p * ( l - p ) / n ) 0 5 ( B l ) Where Se (p) = the standard error o f a sample proportion, p = the proportion o f the sample that collects a given data type or element, n = the sample size, in this case 59 utilities. For example, using Equation B l , i f 63 percent o f the respondents (i.e., 37 responses o f the 59 survey respondents), indicate that they record when water service was restored, we may expect that more than 50 percent (i.e., the lower confidence l imit) but less than 75 percent (i.e., the upper confidence l imit) o f a l l water utilities in the general population wou ld record the same. The lower confidence l imi t o f 50 percent is calculated by the response proportion minus two times the standard error o f the sample population, i.e., 0.50 = 0.63 - 0.13, where 0.13 = 2*Se(p) = 2 (0.63*0.37/59) ° ' 5 . 184 Because the standard error is calculated using the sample proportions, the standard error varies wi th the number o f responses. For example, the higher the number o f responses for ' recording a given type o f data, the more certain we are o f the general population recording that type o f data. The range o f standard error is between 5.5 percent and 6.5 percent for response proportions o f between 33 percent (20 responses) and 76 percent (45 responses) A summary o f values for the standard error for various levels o f responses and the general population confidence l imits corresponding to those responses is shown in Table B . l . Table B.l Confidence limits for the general population0 based on proportion of responses Upper limit of Lower limit of the confidence the confidence level for the level for the Number of Percentage of Standard error of general population (within 2 standard general population (within 2 standard responses respondents response - % errors) errors) 20 34% 6.2% 46% 22% 30 51% 1 6.5% 64% 38% 37 63% 6.3% 75% 50% 39 66% 6.2% 78% 54% 44 75% 5.7% 86% 63% 45 76% . 5.5% 87% 65% a) Based on 59 responses (i.e., the sample size). 185 P A G E L E F T B L A N K 186 APPENDIX C 187 A p p e n d i x C describes the mun ic ipa l i t y o f M a p l e R i d g e , its water u t i l i ty and the L a i t y V i e w area. MAPLE RIDGE, B.C. General description. The Dis t r i c t o f M a p l e R i d g e ( B C ) is a mun ic ipa l i t y located w i t h i n the Greater V a n c o u v e r region. O f the 75,000 people that resided i n the mun ic ipa l i t y i n 2005, approximate ly 65,000 residents were served b y the water u t i l i ty and 12,000 were served b y on-site private we l l s . The mun ic ipa l i t y is i n transit ion from be ing predominant ly rural to be ing a suburban communi ty . It has a t own centre and surrounding urban area. Outs ide o f the urban boundary are lands that are zoned rural and agricul tural . Distribution system. The dis t r ibut ion system o f M a p l e R i d g e has over 15,000 connections and is compr i sed o f 5 pump stations, 7 reservoirs and approximate ly 350,000 metres o f water mains . A summary o f the u t i l i ty ' s pipe inventory b y mater ial types for 2001 is shown i n Table C . l A summary o f the v o l u m e o f water purchased i n 2001 from the Greater V a n c o u v e r Wate r Dis t r ic t ( G V W D ) and distr ibuted da i l y is presented i n Table C . 2 . A compar i son o f the age o f M a p l e R i d g e water mains w i t h a number o f munic ipa l i t i es across Canada that are part o f the Ear th T e c h benchmark ing ini t ia t ive (Earth T e c h 2004) is shown i n Table C . 3 . The table shows the dis t r ibut ion o f pipes b y age cohorts o f M a p l e R i d g e compared w i t h the entire set o f communi t ies i n the study. The participants inc lude R i c h m o n d H i l l ( O N ) , C i t y o f D e l t a ( B C ) , C i t y o f Wate r loo ( O N ) , C i t y o f Ca lga ry ( A B ) , C i t y o f Ot tawa ( O N ) , Reg iona l M u n i c i p a l i t y o f H a l t o n ( O N ) , C i t y o f Saskatoon ( S K ) , C i t y o f L o n d o n ( O N ) , C i t y o f Toronto ( O N ) , C i t y o f H a m i l t o n ( O N ) , C i t y o f Thunder B a y ( O N ) , C i t y o f St. Catherines ( O N ) and C i t y o f V i c t o r i a ( B C ) . 188 F i n a n c i a l measures . F inanc i a l l y , the u t i l i ty operates as a se l f - l iquidat ing u t i l i ty -i.e., annual revenues and expenditures must balance. A five year business p l an is submitted to M a p l e R i d g e C o u n c i l each year and rates are established b y C o u n c i l by l aw . In 2003, residential water customers were charged $230 per household and metered customers were charged $0,395 per cubic metre. A f inancia l summary o f the 2001 major expenditure categories is shown i n Table C .4 . L a i t y V i e w . The L a i t y V i e w area o f M a p l e R i d g e represents approximate ly ten percent o f the water dis t r ibut ion system o f M a p l e R i d g e and serves a popula t ion o f approximate ly 6,000. The total length o f water mains i n this area is 36,300 metres. A regional water m a i n forms the boundary o n one side o f the study area w h i l e larger pipes m a y be used to form the internal boundaries for s ix selected p ipe zones. These zones are compr i sed o f m a i n l y 150 m m pipes. One zone has a few metres o f 100 m m pipe serving a ve ry short cul-de-sac. The zones are shown i n F igure C . l . Because M a p l e R i d g e has a m i n i m a l number o f pressure zones (most o f the urban part o f the Dis t r i c t is served b y one water pressure zone), the study area has o n l y one water pressure zone. L a i t y V i e w is k n o w n to have mul t ip le and routine breaks. T y p i c a l break repairs are approximate ly three metres i n length. The number o f connections and number o f people affected b y breaks are not recorded. A compar i son o f L a i t y V i e w break rates against those o f N o r t h A m e r i c a n and European water ut i l i t ies as ident i f ied i n an A W W A R F study (Deb et al, 2002) is shown i n Table C .5 be low. The break rates for L a i t y V i e w are comparable w i t h those o f other N o r t h A m e r i c a n ut i l i t ies , and are less than those o f European systems. 189 Table C.l - Maple Ridge water system inventory Asbestos cement (m) Cast iron (m) Copper (m) Ductile iron (m) Galvanized Iron (m) Poly Vinyl Chloride (m) Steel (m) Total length of mains (m) Total 67,422 13,183 59 252,501 180 2,968 11,856 348,169 Table C.2 Maple Ridge system water volumes Annual Average Daily Water Consumption (ML/d*) Peak Day (ML/d) Annual Total Volume Purchased (ML) 2001 2 9 M L / d (6.4 M G D ) 52 M L / d a y (11 .5MGD) 10,400 (22,900 M G ) * ML/d is Mega-litres per day, ML is Mega-litres and MGD is Million Imperial gallons per day and MG is Million Imperial gallons. Table C.3 Comparison of age cohorts of Maple Ridge pipes against Earth Tech National benchmarking utilities Maple Ridge Participating utilities 0-24 55 46 25-49 45 42 50-74 0 6 75-99 0 5 >100 0 1 Total 100 100 Table C.4 Summary of major annual expenditure categories for 2001 Total Utility Revenues Total Utility Expenditures Water Purchase Expenditures Debt Servicing 2001 S6 .5M S6 .5M S2 .4M S2 .6M 190 Table C.5 Comparison of Laity View pipe break rates against those of other North American and European systems Laity View average break rates North America break rates* European break rates * Break rate (breaks/m/year) 0.0001126 0.0001375 0.000313 * source: Deb et al. (2002) 191 Figure C.l Laity View area The f o l l o w i n g figure is o f the approximate extent o f M a p l e Ridge ' s water system and the boundaries o f the L a i t y V i e w system. There are some deve lop ing sections northeast o f the figure. S.SO KM 192 ( ( APPENDIX D 193 A p p e n d i x D is the survey that was distributed to N o r t h A m e r i c a n water ut i l i t ies i n 2004. The survey was compr i sed o f seven spreadsheets. Survey of Water System ( mains and fittings) failure Please complete this page and the 6 subsequent pages of questions about the information that your organization maintains on water main and fitting failures. If you are not the best source of this information please forward the survey to the appropriate person(s) in your organization. Organization Department Position title Contact (name of person who completed this survey) E-mail address: Telephone number: Area code Extension Address What is the total population of your jurisdiction What is the population served by your water system? What is the total length of your water mains? General water system breakage data are collected by: Our data are managed using: 194 D A T A CONFIDENCE I N C I D E N T G E N E R A L I N F O R M A T I O N R E C O R D E D L E V E L IN I N B R E A K D A T A RECORD C O L L E C T E D Date of reported break Time of reported break Reported by Address of reporter Ph. Number of reporter Date of repair start Time of repair start Date of repair finish Time when water service was resumed Total hours on site Quantity of parcels without service Was service to customers disrupted Estimated number of customers affected affected customers by residential type affected customers by commercial type affected customers by industrial type affected customers by institutional type Repaired by Indication of property damage y or n Property damage cost Employee researching pipe & completing form ID of water main feature being repaired ID assigned to break, leak etc Sketch of damaged facility Digital photo of damaged facility Length of unsupported pipe Job / work order number Dates of previous breaks at same location Equipment used Crew members Crew total hours Total labour cost Total materials cost Total equipment cost Please list any locational incident details that your organization records and also any comments that you would like to include: 195 INCIDENT L O C A T I O N INFORMATION D A T A R E C O R D E D I N B R E A K RECORD CONFIDENCE L E V E L IN D A T A C O L L E C T E D Nearest property address Distance from nearest property line Cross street name Distance from nearest cross street Northing and Easting coordinates Isolation Valve operated ( Gate valve ID ) Isolation Valve operated ( Gate valve ID ) Please list any locational incident details that your organization records and also any comments you would like to include: 196 D A T A INCIDENT P H Y S I C A L D A T A R E C O R D E D IN B R E A K R E C O R D Pipe diameter Pipe material Length ofpipe segment containing the repair Year of installation Pipe wall thickness/ classification Type of pipe lining Pipe protection ( wrapped / anodes) Type of joint Type of water service Normal operating pressure Under boulevard or roadway Surface material Depth of cover Bedding material Condition of bedding Backfill material Category of native soil Pipe sample collected Condition of pipe exterior Condition of unlinedpipe interior Condition of cement lined pipe interior Traffic classification or type of road useage Pipe modulus or rupture Pipe fracture toughness Typical flow in area of break C O N F I D E N C E L E V E L IN D A T A C O L L E C T E D IS D A T A A V A I L A B L E F R O M OTHER SOURCES? Y E S or N O OTHER SOURCE OF I N F O R M A -TION C O M M E N T S Please list any locational incident details that your organization records and also any comments that you would like to include: 197 INCIDENT FAILURE DESCRIPTION DATA RECORDED IN BREAK RECORD CONFIDENCE LEVEL IN DATA COLLECTED COMMENTS Types of failure are recorded in this precentage of our incidents IBB The following failure modes are fields that are recorded: YES or NO NONE - HIGH Longitudinal break Blow out Split bell Corrosion pit hole Leaking joint Leaking hydrant Leaking valve Tap failure Curbstop failure Leaking service connection Failed blow-off Please list below any additional types of failure that your organization records and any comments you would like to include: SUSPECTED CAUSE OF FAILURE DATA RECORDED IN BREAK RECORD CONFIDENCE LEVEL IN DATA COLLECTED ARE DATA EASILY AVAILABLE FROM OTHER SOURCES? IF DATA ARE AVAILABLE, SOURCE OF INFORMATION IS COMMENTS Is your water corrosive to your watermains (yes or no) Causes of failure are recorded in Ms percentage of our records The following causes are fields that are recorded: YES or NO NONE - HIGH YES or NO Corrosion Traffic load Poor construction practices Ground frost Settlement Joint failure rock contact Construction disturbance High pressure Water temperature change Frozen pipe Errosion / unsupported pipe Unknown Please list any locational incident details that your organization records and also any comments you would like, to include: 198 INCIDENT REPAIR DETAILS DATA RECORDED INBREAK RECORD CONFIDENCE LEVEL IN DATA COLLECTED Repair activities are recorded in this precentage of our incidents The following activities are fields that are recorded: YES or NO NONE - HIGH Repair clamp Replace pipe section Replace valve Replace service connection Replace hydrant part(s) Replace entire hydrant Anode installed External protection installed Repair joint Surface restoration Dechlorination performed Please list any locaiional incident details that your organization records and also any comments you would like to include: 199 INCIDENT ENVIRONMENT CONDITIONS Environment information is recorded in this percentage of our incidents DATA RECORDED IN BREAK RECORD CONFIDENCE LEVEL IN DATA COLLECTED ARE DATA EASILY AVAILABLE FROM OTHER SOURCES? 1 1 1 ! ! ! IF DATA ARE AVAILABLE, SOURCE OF • INFORMATION lilS COMMENTS The following information are fields that are recorded YES or NO NONE - HIGH YES or NO PICK BOX l i l l l l l l Water temperature Air temperature No. of consecutive days below 32 for 0 c Depth of frost Water temperature change Soil temperature at pipe depth Soil sample taken SoilPH Soil moisture content Please list any locational incident details that your organization records and also any comments you would like to include: Does your organization possess a water model? Is your model used? For what reasons does your organization use your model? What is the name of your water system model? Do you feel comfortable that the amount of data you collect and manage, adequately serves your utility? Development planning Capital Works planning Operation of water system Maintenance of water system Specify other: • . . • ' • How many minutes did you take to complete the survey? Comments on the survey : Would you like a copy of the survey results? Yes or No If so, by mail, fax or e-mail? ^ Please return the completed .xls file to Andrew W°°d by E-mail: , 200 aw00 Date of repair start 100 Date of repair start 100 332 Date of repair start 100 120 Date of repair start 100 260 Date of repair start 100 21 Date of repair start 100 432 Date of repair start 100 428 . Date of repair start 100 112 Date of repair start 0 392 Date of repair start 100 284 Date of repair start 100 283 Date of repair start 100 420 Date of repair start 100 42 Date of repair start 100 433 Date of repair start 100 407 Date of repair start 100 230 404 Date of repair start 100 379 76 Date of repair start Date of repair start 100 100 411 | Date of repair start 100 424 i Date of repair start 100 231 ; Date of repair start 100 301 | Date of repair start 100 416 | Date of repair start 100 55 : Date of repair start 100 342 1 Date of repair start 100 240 i Date of repair start 100 100 423 j Date of repair start 383 i Date of repair start 100 389 1 Date of repair start 100 418 i Date of repair start 100 418 ! Time of repair start 75 76 Time of repair start 100 402 Time of repair start 100 420 Time of repair start 100 427 i Time of repair start 100 409 i Time of repair start 100 10 Time of repair start 50 72 Time of repair start 0 249 Time of repair start 50 400 i Time of repair start 50 416 Time of repair start 100 422 Time of repair start 0 419 Time of repair start 50 231 Time of repair start 0 240 Time of repair start 100 227 i Time of repair start 100 423 Time of repair start 100 401 Time of repair start 100 383 Time of repair start 75. 417 Time of repair start 75 120 | Time of repair start 100 260 I Time of repair start 100 415 i Time of repair start 0 426 i Time of repair start 100 435 i Time of repair start 100 424 Time of repair start 100 379 Time of repair start 50 56 Time of repair start 0 301 Time of repair start 0 141 : Time of repair start 100 284 i Time of repair start 100 404 Time of repair start 100 43.1 Time of repair start 0 283 Time of repair start 100 231 48 Time of repair start 405 Time of repair start 55 ' Time of repair start 100 42 Time of repair start 50 407 Time of repair start 100 332 Time of repair start 100 432 Time of repair start 0 21 Time of repair start 100 408 Time of repair start 100 134 Time of repair start 100 392 Time of repair start 0 112 Time of repair start 0 430 Time of repair start 75 100 Time of repair start 0 413 Time of repair start 100 403 Time of repair start 100 414 Time of repair start 100 433 Time of repair start 100 295 Time of repair start ~ 100 342 Time of repair start 100 103 Time of repair start 100 428 Time of repair start 100 434 Time of repair start 100 389 Time of repair start 0 411 Time of repair start 100 400 Date of repair finish 50 240 Date of repair finish 100 392 Date of repair finish 0 411 Date of repair finish 100 426 Date of repair finish 100 417 Date of repair finish 75 433 Date of repair finish 100 100 Date of repair finish 100 424 Date of repair finish 100 416 Date of repair finish 100 430 Date of repair finish 100 55 Date of repair finish 100 383 Date of repair finish 75 422- Date of repair finish 0 260 Date of repair finish 100 403 Date of repair finish 100 295 Date of repair finish 100 231 Date of repair finish 100 283 Date of repair finish 100 112 Date of repair finish 0 227 Date of repair finish 100 423 Date of repair finish 100 405 Date of repair finish 419 Date of repair finish 50 232 48 Date of repair finish 434 Date of repair finish 100 408 Date of repair finish 100 42 Date of repair finish 100 249 Date of repair finish 100 72 Date of repair finish ' 100 10 Date of repair finish 100 402 Date of repair finish 100 141 Date of repair finish 100 432 i Date of repair finish 100 76 Date of repair finish 100 428 Date of repair finish 100 427 Date of repair finish 100 301 Date of repair finish 100 420 Date of repair finish 100 414 Date of repair finish 100 284 Date of repair finish 100 389 Date of repair finish 100 103 Date of repair finish 100 134 Date of repair finish . 100 413 Date of repair finish 100 56 Date of repair finish 100 100 409 Date of repair finish 332 Date of repair finish 100 342 Date of repair finish 100 120 Date of repair finish 100 401 Date of repair finish 100 404 Date of repair finish 75 407 Date of repair finish 100 21. Date of repair finish 100 431 Date of repair finish 100 418 Date of repair finish 75 415 Date of repair finish 100 379 Date of repair finish 100 43 S Date of repair finish 100 240 Time when water service was resumed 100 435 Time when water service was resumed 100 418 Time when water service was resumed 25 403 Time when water service was resumed 100 295 Time when water service was resumed 100 430 Time when water service was resumed 25 48 Time when water service was resumed 55 Time when water service was resumed 100 21 Time when water service was resumed 100 134 Time when water service was resumed 100 103 Time when water service was resumed 432 Time when water service was resumed 0 428 Time when water service was resumed 0 284 Time when water service was resumed 100 233 401 Time when water service was resumed 100 427 Time when water service was resumed 0 416 Time when water service was resumed 100 249 Time when water service was resumed 0 10 Time when water service was resumed 25 433 Time when water service was resumed 50 231 Time when water service was resumed 0 76 Time when water service was resumed 100 141 Time when water service was resumed 100 424 i Time when water service was resumed 100 426 Time when water service was resumed 0 227 Time when water service was resumed 0 419 Time when water service was resumed 50 283 Time when water service was resumed 100 420 Time when water service was resumed 100 423 Time when water service was resumed 100 407 Time when water service was resumed 50 260 Time when water service was resumed 100 415 Time when water service was resumed 0 75 417 Time when water service was resumed 404 Time when water service was resumed 75 332 Time when water service was resumed 75 100 Time when water service was resumed 0 434 Time when water service was resumed 100 409 Time when water service was resumed 100 392 Time when water service was resumed 0 301 Time when water service was resumed 0 42 Time when water service was resumed 25 414 Time when water service was resumed 100 120 Time when water service was resumed 100 400 i Time when water service was resumed 0 389 Time when water service was resumed 100 72 Time when water service was resumed 0 112 408 Time when water service was resumed 0 Time when water service was resumed 100 411 : Time when water service was resumed 25 56 Time when water service was resumed 0 383 Time when water service was resumed 75 431 Time when water service was resumed 0 379 i Time when water service was resumed 25 405 Time when water service was resumed 342 Time when water service was resumed 100 _4m 422 413 379 Time when water service was resumed 0 Time when water service was resumed 0 Time when water service was resumed 100 Total hours on site . 100 76 Total hours on site 75 415 Total hours on site 100 249 Total hours on site 100 234 424 Total hours on site 100 383 Total hours on site 100 423 Total hours on site 100 56 Total hours on site 100 141 404 Total hours on site 100 Total hours on site 100 55 I Total hours on site 100 134 1 Total hours on site 100 413 i Total hours on site 0 408 i Total hours on site 100 48 Total hours on site 103 Total hours on site 100 405 Total hours on site 433 Total hours on site 100 411 Total hours on site 100 432 Total hours on site 100 407 Total hours on site 100 402 Total hours on site 100 332 Total hours on site 100 21 Total hours on site 100 409 Total hours on site 100 427 Total hours on site 100 283 Total hours on site 100 301 Total hours on site 100 420 Total hours on site 100 342 Total hours on site 100 403 Total hours on site 100 414 Total hours on site 100 418 Total hours on site 100 417 Total hours on site 100 284 i Total hours on site 100 231 Total hours on site 25 10 Total hours on site 100 227 Total hours on site 100 428 Total hours on site 100 260 i Total hours on site 50 392 Total hours on site 0 120 Total hours on site 100 434 Total hours on site 100 '422 : Total hours on site 0 295 Total hours on site 100 . 100 Total hours on site 100 430 Total hours on site 25 419 Total hours on site 100 42 Total hours on site 100 400 Total hours on site 25 401 Total hours on site 100 426 Total hours on site 100 112 Total hours on site 100 235 240 Total hours on site 100 72 Total hours on site 100 389 Total hours on site 0 435. Total hours on site 100 416 Total hours on site 100 431 Total hours on site 100 407 Quantity of parcels without service 0 134 Quantity of parcels without service 100 435 Quantity of parcels without service , 50 72 j Quantity of parcels without service 0 434 Quantity of parcels without service 100 55 Quantity of parcels without service 100 405 Quantity of parcels without service 295 Quantity of parcels without service 25 431 Quantity of parcels without service 0 411 Quantity of parcels without service 0 10 Quantity of parcels without service 0 433 Quantity of parcels without service 0 100 Quantity of parcels without service 0 401 Quantity of parcels without service 0 48 Quantity of parcels without service 400 Quantity of parcels without service 0 231 Quantity of parcels without service 0 418 Quantity of parcels without service 0 423 Quantity of parcels without service 0 389 Quantity of parcels without service 0 413 Quantity of parcels without service 100 112 Quantity of parcels without service 0 240 416 Quantity of parcels without service 0 Quantity of parcels without service 0 383 j Quantity of parcels without service 0 424 Quantity of parcels without service 100 404 Quantity of parcels without service ; 75 0 260 Quantity of parcels without service 284 Quantity of parcels without service 100 120 1 Quantity of parcels without service 100 332 | Quantity of parcels without service 100 428 | Quantity of parcels without service 0 379 | Quantity of parcels without service 0 420 ! Quantity of parcels without service 100 342 Quantity of parcels without service 0 42 Quantity of parcels without service 0 432 Quantity of parcels without service 0 392 Quantity of parcels without service 0 283 Quantity of parcels without service 0 301 Quantity of parcels without service 0 430 Quantity of parcels without service 0 21 Quantity of parcels without service 0 76 Quantity of parcels without service 0 236 103 Quantity of parcels without service 227 Quantity of parcels without service 50 414 419 Quantity of parcels without service 100 Quantity of parcels without service 100 56 Quantity of parcels without service 0 422 141 Quantity of parcels without service 0 Quantity of parcels without service 100 417 Quantity of parcels without service 0 402 Quantity of parcels without service 0 415 Quantity of parcels without service 0 409 Quantity of parcels without service 75 403 Quantity of parcels without service 50 408 Quantity of parcels without service 100 0 427 Quantity of parcels without service 426 Quantity of parcels without service 0 249 Quantity of parcels without service 0 432 Was service to customers disrupted 0 389 Was service to customers disrupted 100 418 Was service to customers disrupted 0 301 Was service to customers disrupted 100 55 Was service to customers disrupted 100 379 Was service to customers disrupted 0 414 Was service to customers disrupted 100 427 Was service to customers disrupted 25 407 Was service to customers disrupted 100 42 Was service to customers disrupted 100 227 Was service to customers disrupted 100 56 Was service to customers disrupted 0 428 Was service to customers disrupted 0 383 Was service to customers disrupted 100 423 Was service to customers disrupted 0 112 Was service to customers disrupted 0 240 Was service to customers disrupted 50 409 Was service to customers disrupted 75 21 Was service to customers disrupted 75 231 ! Was service to customers disrupted 0 283 Was service to customers disrupted 100 260 Was service to customers disrupted 0 426 Was service to customers disrupted 0 392 Was service to customers disrupted 0 332 Was service to customers disrupted 75 417 Was service to customers disrupted 0 141 Was service to customers disrupted 0 120 Was service to customers disrupted 100 416 Was service to customers disrupted 0 10 Was service to customers disrupted 100 342 Was service to customers disrupted 0 404 Was service to customers disrupted . 75 401 Was service to customers disrupted 0 237 415 Was service to customers disrupted • 100 411 Was service to customers disrupted 100 402 Was service to customers disrupted 0 249 Was service to customers disrupted 100 413 | Was service to customers disrupted 0 431 Was service to customers disrupted 100 76 Was service to customers disrupted 50 72 Was service to customers disrupted 100 134 Was service to customers disrupted 100 408 Was service to customers disrupted 100 403 j Was service to'customers disrupted 100 435 1 Was service to customers disrupted 50 400 i Was service to customers disrupted 0 424 j Was service to customers disrupted 100 405 Was service to customers disrupted 48 Was service to customers disrupted 100 Was service to customers disrupted ' 0 284 Was service to customers disrupted 100 433 Was service to customers disrupted 100 430 | Was service to customers disrupted 50 422 i Was service to customers disrupted 0^ 100 434 Was service to customers disrupted 420 Was service to customers disrupted 100 103 Was service to customers disrupted 295 i Was service to customers disrupted 100 419 i Was service to customers disrupted 100 383 | Estimated number of customers affected 0 428 423 Estimated number of customers affected 0 Estimated number of customers affected 0 414 : Estimated number of customers affected 100 415 i Estimated number of customers affected 0 141 i Estimated number of customers affected 0 404 | Estimated number of customers affected 283 Estimated number of customers affected 0 56 Estimated number of customers affected 0 424 Estimated number of customers affected 100 76 Estimated number of customers affected 0 100 Estimated number of customers affected 403 ! Estimated number of customers affected 100 72 | Estimated number of customers affected 0 10 Estimated number of customers affected 0 400 Estimated number of customers affected 0 402 Estimated number of customers affected 0 435 I Estimated number of customers affected 50 401 i Estimated number of customers affected 0 431 i Estimated number of customers affected 0 2'H Estimated number of customers affected 0 434 Estimated number of customers affected 100 422 Estimated number of customers affected 0 238 120 Estimated number of customers affected 100 4I<> Estimated number of customers affected 100 41 S Estimated number of customers affected . 0 284 Estimated number of customers affected 100 392 Estimated number of customers affected 227 Estimated number of customers affected 50 42 Estimated number of customers affected 0 231 Estimated number of customers affected 0 417 Estimated number of customers affected 0 260 Estimated number of customers affected 0 416 Estimated number of customers affected 0 112 Estimated number of customers affected 0 240 Estimated number of customers affected 426 Estimated number of customers affected 0 389 Estimated number of customers affected 0 430 Estimated number of customers affected 0 301 Estimated number of customers affected 0 103 Estimated number of customers affected 48 Estimated number of customers affected 342 Estimated number of customers affected 0 413 Estimated number of customers affected 411 Estimated number of customers affected 0 433 Estimated number of customers affected 50 409 Estimated number of customers affected 55 Estimated number of customers affected 100 405 Estimated number of customers affected 432 Estimated number of customers affected 0 420 Estimated number of customers affected 100 -21 Estimated number of customers affected 0 249 Estimated number of customers affected 0 408 Estimated number of customers affected 427 Estimated number of customers affected 0 407 Estimated number of customers affected 0 134 Estimated number of customers affected 0 379 Estimated number of customers affected 0 332 Estimated number of customers affected 301 Estimated number of affected customers by residential type 295 Estimated number of affected customers by residential type 0 423 Estimated number of affected customers by residential type 434 Estimated number of affected customers by residential type 407 Estimated number of affected customers by residential type 103 Estimated number of affected customers by residential type 120 Estimated number of affected customers by residential type -1 260 Estimated number of affected customers by residential type 0 231 Estimated number of affected customers by residential type 112 Estimated number of affected customers by residential type 332 Estimated number of affected customers by residential type -1 422 Estimated number of affected customers by residential type 141 Estimated number of affected customers by residential type 239 419 Estimated number of affected customers by residential type -1 405 Estimated number of affected customers by residential type 100 Estimated number of affected customers by residential type 426 Estimated number of affected customers by residential type 0 284 | Estimated number of affected customers by residential type 100 240 Estimated number of affected customers by residential type 389 Estimated number of affected customers by residential type 416 Estimated number of affected customers by residential type 392 i Estimated number of affected customers by residential type 431 i Estimated number of affected customers by residential type 430 i Estimated number of affected customers by residential type 415 427 Estimated number of affected customers by residential type Estimated number of affected customers by residential type 0 134 Estimated number of affected customers by residential type 0 432 Estimated number of affected customers by residential type 424 Estimated number of affected customers by residential type 0 10 Estimated number of affected customers by residential type 100 418 Estimated number of affected customers by residential type 404 Estimated number of affected customers by residential type 342 Estimated number of affected customers by residential type 420 Estimated number of affected customers by residential type 100 72 Estimated number of affected customers by residential type 0 249 Estimated number of affected customers by residential type 76 Estimated number of affected customers by residential type 403 Estimated number of affected customers by residential type -1 408 Estimated number of affected customers by residential type 414 Estimated number of affected customers by residential type 0 435 Estimated number of affected customers by residential type 379 417 Estimated number of affected customers by residential type Estimated number of affected customers by residential type 0 48 | Estimated number of affected customers by residential type 21 Estimated number of affected customers by residential type 0 428 Estimated number of affected customers by residential type 0 227 Estimated number of affected customers by residential type 0 283 Estimated number of affected customers by residential type 433 : Estimated number of affected customers by residential type 55 Estimated number of affected customers by residential type 400 Estimated number of affected customers by residential type 42 Estimated number of affected customers by residential type 0 401 Estimated number of affected customers by residential type Estimated number of affected customers by residential type 413 Estimated number of affected customers by residential type 383 Estimated number of affected customers by residential type 411 Estimated number of affected customers by residential type 402 Estimated number of affected customers by residential type 0 409 Estimated number of affected customers by residential type 42 Estimated number of affected customers by commercial type 0 422 : Estimated number of affected customers by commercial type 231 Estimated number of affected customers by commercial type 0 240 428 Estimated number of affected customers by commercial type 0 407 Estimated number of affected customers by commercial type 0 55 Estimated number of affected customers by commercial type 434 Estimated number of affected customers by commercialtype 0 435 Estimated number of affected customers by commercial type 50 403 Estimated number of affected customers by commercial type 100 134 Estimated number of affected customers by commercial type 0 72 Estimated number of affected customers by commercial type 0 10 Estimated number of affected customers by commercial type 100 400 Estimated number of affected customers by commercial type 0 402 Estimated number of affected customers by commercial type 0 411 Estimated number of affected customers by commercial type 401 Estimated number of affected customers by commercial type 433 Estimated number of affected customers by commercial type 0 431 Estimated number of affected customers by commercial type 0 227 295 Estimated number of affected customers by commercial type 0 Estimated number of affected customers by commercial type 0 417 Estimated number of affected customers by commercial type 0 103 Estimated number of affected customers by commercial type 430 Estimated number of affected customers by commercial type 0 405 Estimated number of affected customers by commercial type 0 100 Estimated number of affected customers by commercial type 392 Estimated number of affected customers by commercial type 0 284 Estimated number of affected customers by commercial type 100 413 Estimated number of affected customers by commercial type 0 419 Estimated number of affected customers by commercial type -1 48 Estimated number of affected customers by commercial type 426 Estimated number of affected customers by commercial type 0 424 Estimated number of affected customers by commercial type 0 383 Estimated number of affected customers by commercial type 332 Estimated number of affected customers by commercial type 100 56 Estimated number of affected customers by commercial type 240 Estimated number of affected customers by commercial type 50 249 Estimated number of affected customers by commercial type 0 432 Estimated number of affected customers by commercial type 260 Estimated number of affected customers by commercial type II 301 Estimated number of affected customers by commercial type 112 389 Estimated number of affected customers by commercial type 0 Estimated number of affected customers by commercial type 0 423 Estimated number of affected customers by commercial type 141 Estimated number of affected customers by commercial type 0 427 Estimated number of affected customers by commercial type 0 408 Estimated number of affected customers by commercial type 418 Estimated number of affected customers by commercial type 0 120 Estimated number of affected customers by commercial type 100 283 Estimated number of affected customers by commercial type 0 415 Estimated number of affected customers by commercial type 100 379 Estimated number of affected customers by commercial type 0 416 Estimated number of affected customers by commercial type 0 241 414 Estimated number of affected customers by commercial type 0 420 Estimated number of affected customers by commercial type 100 409 Estimated number of affected customers by commercial type 0 404 76 342 21 Estimated number of affected customers by commercial type 25 Estimated number of affected customers by commercial type 0 Estimated number of affected customers by commercial type 0 Estimated number of affected customers by commercial type 0 431 Estimated number of affected customers by industrial type 0 76 Estimated number of affected customers by industrial type 0 434 | Estimated number of affected customers by industrial type 0 283 | Estimated number of affected customers by industrial type 0 295 Estimated number of affected customers by industrial type 0 379 Estimated number of affected customers by industrial type 0 10 Estimated number of affected customers by industrial type 100 48 : Estimated number of affected customers by industrial type 414 i Estimated number of affected customers by industrial type 0 408 Estimated number of affected customers by industrial type 435 Estimated number of affected customers by industrial type 75 427 Estimated number of affected customers by industrial type 0 420 : Estimated number of affected customers by industrial type 100 424 i Estimated number of affected customers by industrial type 0 56 Estimated number of affected customers by industrial type 411 Estimated number of affected customers by industrial type 403 Estimated number of affected customers by industrial type 100 404 Estimated number of affected customers by industrial type 25 383 Estimated number of affected customers by industrial type 432 Estimated number of affected customers by industrial type 423 Estimated number of affected customers by industrial type 342 Estimated number of affected customers by industrial type 0 400 : Estimated number of affected customers by industrial type 0 72 i Estimated number of affected customers by industrial type 0 249 Estimated number of affected customers by industrial type 0 401 Estimated number of affected customers by industrial type 134 Estimated number of affected customers by industrial type 0 402 Estimated number of affected customers by industrial type 0 417 | Estimated number of affected customers by industrial type 0 428 | Estimated number of affected customers by industrial type 0 392 Estimated number of affected customers by industrial type 0 416 Estimated number of affected customers by industrial type 0 332 Estimated number of affected customers by industrial type 100 21 i Estimated number of affected customers by industrial type 0 284 1 Estimated number of affected customers by industrial type 100 240 Estimated number of affected customers by industrial type 50 407 i Estimated number of affected customers by industrial type 0 55 | Estimated number of affected customers by industrial type 42 | Estimated number of affected customers by industrial type 0 419. | Estimated number of affected customers by industrial type -1 227 112 Estimated number of affected customers by industrial type 0 Estimated number of affected customers by industrial type 0 242 415 Estimated number of affected customers by industrial type 100 260 Estimated number of affected customers by industrial type 0 409 Estimated number of affected customers by industrial type 0 41? Estimated number of affected customers by industrial type 0 422 Estimated number of affected customers by industrial type 418 Estimated number of affected customers by industrial type 0 433 Estimated number of affected customers by industrial type 0 100 Estimated number of affected customers by industrial type 0 301 Estimated number of affected customers by industrial type 389 Estimated number of affected customers by industrial type ' 0 426 Estimated number of affected customers by industrial type 0 430 Estimated number of affected customers by industrial type 0 120 Estimated number of affected customers by industrial type 100 405 Estimated number of affected customers by industrial type 231 Estimated number of affected customers by industrial type 0 141 Estimated number of affected customers by industrial type 0 103 Estimated number of affected customers by industrial type 10 Estimated number of affected customers by institutional type 100 231 Estimated number of affected customers by institutional type 0 72 Estimated number of affected customers by institutional type 0 419 Estimated number of affected customers by institutional type -1 415 Estimated number of affected customers by institutional type 100 76 Estimated number of affected customers by institutional type 0 414 Estimated number of affected customers by institutional type 0 42 Estimated number of affected customers by institutional type 0 379 Estimated number of affected customers by institutional type 0 55 Estimated number of affected customers by institutional type 301 Estimated number of affected customers by institutional type 417 Estimated number of affected customers by institutional type _0_ 48 Estimated number of affected customers by institutional type 283 Estimated number of affected customers by institutional type 0 426 Estimated number of affected customers by institutional type 0 295 Estimated number of affected customers by institutional type 0 431 Estimated number of affected customers by institutional type 0 100 Estimated number of affected customers by institutional type 0 383 Estimated number of affected customers by institutional type 402 Estimated number of affected customers by institutional type 0 413 Estimated number of affected customers by institutional type 0 249 Estimated number of affected customers by institutional type 0 100 284 Estimated number of affected customers by institutional type 240 Estimated number of affected customers by institutional type 50 407 Estimated number of affected customers by institutional type 0 389 Estimated number of affected customers by institutional type 0 411 Estimated number of affected customers by institutional type 260 Estimated number of affected customers by institutional type 0 134 Estimated number of affected customers by institutional type 0 432 Estimated number of affected customers by institutional type 332 Estimated number of affected customers by institutional type 100 424 Estimated number of affected customers by institutional type 0 243 21 Estimated number of affected customers by institutional type 0 427 Estimated number of affected customers by institutional type 0 428 Estimated number of affected customers by institutional type 0 227 Estimated number of affected customers by institutional type 0 423 Estimated number of affected customers by institutional type , 420 Estimated number of affected customers by institutional type 100 409 Estimated number of affected customers by institutional type 0 433 Estimated number of affected customers by institutional type 0 434 Estimated number of affected customers by institutional type 0 141 Estimated number of affected customers by institutional type 0 400 Estimated number of affected customers by institutional type 0 401 Estimated number of affected customers by institutional type 408 Estimated number of affected customers by institutional type 404 Estimated number of affected customers by institutional type 0 342 Estimated number of affected customers by institutional type 0 435 ' Estimated number of affected customers by institutional type 75 405 Estimated number of affected customers by institutional type 422 Estimated number of affected customers by institutional type 120 Estimated number of affected customers by institutional type 100 416 Estimated number of affected customers by institutional type 0 112 Estimated number of affected customers by institutional type 0 418 Estimated number of affected customers by institutional type 0 403 Estimated number of affected customers by institutional type 100 430 Estimated number of affected customers by institutional type 0 392 Estimated number of affected customers by institutional type 0 103 Estimated number of affected customers by institutional type 56 Estimated number of affected customers by institutional type 55 Repaired by 100 301 Repaired by 100 433 Repaired by 100 332 Repaired by 100 342 Repaired by 100 430 Repaired by 75 21 Repaired by 100 432 Repaired by 100 - 407 N Repaired by 100 434 Repaired by 100 283 Repaired by 100 231 Repaired by 100 416 Repaired by 100 120 Repaired by 100 260 Repaired by 50 42 Repaired by 100 240 Repaired by 100 418 Repaired by 100 392 Repaired by 100 284 Repaired by 100 389 Repaired by 100 100 Repaired by 100 244 428 Repaired by 100 424 Repaired by 100 423 Repaired by 100 383 Repaired by 100 76 Repaired by 100 295 Repaired by 100 420 404 Repaired by 100 Repaired by 379 Repaired by 100 112 Repaired by 0 72 Repaired by 100 427 Repaired by 100 409 Repaired by 100 402 Repaired by 100 419 Repaired by 50 413 Repaired by 100 415 Repaired by 100 249 Repaired by 100 401 Repaired by 100 403 Repaired by 100 426 Repaired by 100 141 Repaired by 100 48 Repaired by 56 Repaired by 100 414 Repaired by 100 227 Repaired by 100 400 Repaired by 0 422 Repaired by 100 435 Repaired by 100 405 Repaired by 134 Repaired by 100 411 Repaired by 100 431 Repaired by 100 10 Repaired by 100 408 Repaired by 100 103 Repaired by 100 417 Repaired by 100 227 Indication of property damage y or n 0 417 Indication of property damage y or n 100 100 56 Indication of property damage y or n 389 Indication of property damage y or n 100 416 Indication of property damage y or n 100 403 Indication of property damage y or n 100 283 Indication of property damage y or n 100 418 Indication of property damage y or n • 50 240 Indication of property damage y or n 100 260 422 Indication of property damage y or n 0 Indication of property damage y or n 0 415 Indication of property damage y or n 100 245 402 Indication of property damage y or n 100 112 Indication of property damage y or n 0 I2ii Indication of property damage y or n 100 379 Indication of property damage y or n 50 407 Indication of property damage y or n 100 48 Indication of property damage y or n 405 Indication of property damage y or n 134 Indication of property damage y or n 100 433 Indication of property damage y or n 75 411 Indication of property damage y or n 100 103 Indication of property damage y or n 100 301 Indication of property damage y or n 0 408 Indication of property damage y or n 100 55 Indication of property damage y or n 100 249 Indication of property damage y or n 100 342 Indication of property damage y or n 100 141 Indication of property damage y or n 0 427 Indication of property damage y or n 100 424' Indication of property damage y or n 100 413 Indication of property damage y or n 100 432 Indication of property damage y or n 100 409 Indication of property damage y or n 100 426 Indication of property damage y or n 0 404 Indication of property damage y or n 50 420 Indication of property damage y or n 100 383 Indication of property damage y or n 75 332 Indication of property damage y or n -1 76 Indication of property damage y or n 0 414 Indication of property damage y or n 100 419 Indication of property damage y or n 100 423 Indication of property damage y or n 75 21 Indication of property damage y or n 100 400 Indication of property damage y or n 75 401 Indication of property damage y or n 100 10 Indication of property damage y or n 100 284 Indication of property damage y or n 1(10 434 Indication of property damage y or n 100 • 431 Indication of property damage y or n 100 72 Indication of property damage y or n 50 100 Indication of property damage y or n 100 430 Indication of property damage y or n 100 428 Indication of property damage y or n 100 42 Indication of property damage y or n 25 231 Indication of property damage y or n 0 435 Indication of property damage y or n "100 392 Indication of property damage y or n 0 295 Indication of property damage y or n 100 112 Property damage cost 0 427 Property damage cost 0 246 .55 Property damage cost 411 Property damage cost 0 432 Property damage cost 0 434 Property damage cost 0 408 Property damage cost 100 301 Property damage cost 0 48 Property damage cost 413 Property damage cost 420 Property damage cost 0 76 i Property damage cost 0 249 Property damage cost 100 134 Property damage cost 0 295 Property damage cost 100 407 Property damage cost 100 42 Property damage cost 0 332 Property damage cost 0 405 Property damage cost 433 Property damage cost 0 428 Property damage cost 100 431 Property damage cost x 0 342 Property damage cost 0 392 Property damage cost 0 418 Property damage cost 25 424 Property damage cost 0 283 Property damage cost 0 430 Property damage cost 0 389 Property damage cost 0 403 Property damage cost 100 423 Property damage cost 100 0 72 Property damage cost 409 i Property damage cost 100 400 Property damage cost 0 415 Property damage cost - 0 100 Property damage cost 50 56 Property damage cost 0 404 ; Property damage cost 25 227 i Property damage cost 0 416 Property damage cost 100 ; 0 0 231 120 Property damage cost Property damage cost 422 Property damage cost 0 284 Property damage cost 100 435 Property damage cost 100 417 Property damage cost ; 0 402 Property damage cost 0 260 Property damage cost 0 401 Property damage cost . 0 103 Property damage cost 426 Property damage cost 0 247 141 Property damage cost 0 21 Property damage cost Property damage cost 0 379 0 10 Property damage cost 100 414 Property damage cost 0 419 Property damage cost 50 383 Property damage cost 0 240 Property damage cost 0 48 Employee researching pipe & completing form 420 Employee researching pipe & completing form 100 55 Employee researching pipe & completing form 404 Employee researching pipe & completing form 100 342 432 Employee researching pipe & completing form 100 Employee researching pipe & completing form 0 21 Employee researching pipe & completing form 100 392 Employee researching pipe & completing form 0 379 Employee researching pipe & completing form 0 430 Employee researching pipe & completing form 100 332 Employee researching pipe & completing form 301 Employee researching pipe & completing form 100 426 Employee researching pipe & completing form 0 417 Employee researching pipe & completing form 75 .435 Employee researching pipe & completing form 100 403' Employee researching pipe & completing form 75 422 Employee researching pipe & completing form 100 402 Employee researching pipe & completing form 0 415 Employee researching pipe & completing form 0 400 Employee researching pipe & completing form 0 227 Employee researching pipe & completing form 0 10 Employee researching pipe & completing form 100 419 Employee researching pipe & completing form 50 56 Employee researching pipe & completing form 0 414 Employee researching pipe & completing form 100 434 Employee researching pipe & completing form . 75 • Employee researching pipe & completing form 0 431 Employee researching pipe & completing form 0 409 Employee researching pipe & completing form 100 413 Employee researching pipe & completing form 401 Employee researching pipe & completing form 100 427 Employee researching pipe & completing form 100 249 Employee researching pipe & completing form 100 408 Employee researching pipe & completing form 100 103 Employee researching pipe & completing form 100 411 Employee researching pipe & completing form 0 134 Employee researching pipe & completing form 100 295 Employee researching pipe & completing form 100> 405 Employee researching pipe & completing form 407 Employee researching pipe & completing form 100 433 Employee researching pipe & completing form 248 72 Employee researching pipe & completing form 0 120 Employee researching pipe & completing form 0 389 Employee researching pipe & completing form 0 428/ 283 424 423 Employee researching pipe & completing form 0 Employee researching pipe & completing form 100 Employee researching pipe & completing form 100 Employee researching pipe & completing form 100 418 Employee researching pipe & completing form 50 112 Employee researching pipe & completing form 0 260 i Employee researching pipe & completing form 0 76 I Employee researching pipe & completing form 100 240 Employee researching pipe & completing form 50 100 Employee researching pipe & completing form 75 383 i Employee researching pipe & completing form 50 231 : Employee researching pipe & completing form 100 416 Employee researching pipe & completing form 0 284 Employee researching pipe & completing form 0 42 Employee researching pipe & completing form 0 434 ID of watermain feature being repaired 100 120 i ID of watermain feature being repaired 0 432 i ID of watermain feature being repaired 0 301 ID of watermain feature being repaired 100 72 ID of watermain feature being repaired 0 260 ID of watermain feature being repaired 0 100 i ID of watermain feature being repaired 100 435 : ID of watermain feature being repaired 50 409 i ID of watermain feature being repaired 100 408 ! ID of watermain feature being repaired 100 21 ID of watermain feature being repaired 100 76 ID of watermain feature being repaired 100 430 i ID of watermain feature being repaired 100 414 i ID of watermain feature being repaired 0 295 i ID of watermain feature being repaired 100 418 | ID of watermain feature being repaired 50 249 ! ID of watermain feature being repaired 100 427 i ID of watermain feature being repaired 100 424 I ID of watermain feature being repaired 100 417 ID of watermain feature being repaired 100 431 ID of watermain feature being repaired 100 42d ID of watermain feature being repaired 0 423 ID of watermain feature being repaired 0 284 ID of watermain feature being repaired 100 42 ID of watermain feature being repaired 0 413 ID of watermain feature being repaired 332 : ID of watermain feature being repaired 75 433 : ID of watermain feature being repaired 100 48 ID of watermain feature being repaired 55 ID of watermain feature being repaired ' 401 ID of watermain feature being repaired 100 249 383 ID of watermain feature being repaired 100 392 ID of watermain feature being repaired 100 407 ID of watermain feature being repaired 100 134 ID of watermain feature being repaired 100 231 ID of watermain feature being repaired 75 415 ID of watermain feature being repaired 100 141 ID of watermain feature being repaired 100 405 ID of watermain feature being repaired 112. ID of watermain feature being repaired 100 402 ID of watermain feature being repaired 100 416 ID of watermain feature being repaired 0 420 ID of watermain feature being repaired 100 400 ID of watermain feature being repaired 0 389 ID of watermain feature being repaired 100 422 ID of watermain feature being repaired 75 379 ID of watermain feature being repaired 75 403 ID of watermain feature being repaired 100 56 ID of watermain feature being repaired 100 411 ID of watermain feature being repaired 0 419 ID of watermain feature being repaired 25 283 ID of watermain feature being repaired 100 404 ID of watermain feature being repaired 100 240 ID of watermain feature being repaired 100 428 ID of watermain feature being repaired 0 10 ID of watermain feature being repaired 0 342 ID of watermain feature being repaired 0 103 ID of watermain feature being repaired 100 227 ID of watermain feature being repaired 100 134 ID assigned to break, leak etc 100 428 ID assigned to break, leak etc 0 295 ID assigned to break, leak etc 100 408 ID assigned to break, leak etc 0 423 ID assigned to break, leak etc 0 411 ID assigned to break, leak etc 0 283 ID assigned to break, leak etc 0 417 ID assigned to break, leak etc 100 414 ID assigned to break, leak etc 0 416 ID assigned to break, leak etc 100 400 ID assigned to break, leak etc 100 402 ID assigned to break, leak etc 100 422 ID assigned to break, leak etc 75 415 ID assigned to break, leak etc 100 231 ID assigned to break, leak etc 100 112 ID assigned to break, leak etc 100 227 ID assigned to break, leak etc 100 10 ID assigned to break, leak etc 100 240 ID assigned to break, leak etc 100 403 ID assigned to break, leak etc 100 72 ID assigned to break, leak etc 0 250 56 ID assigned to break, leak etc l o o 434 ID assigned to break, leak etc 100 435 ID assigned to break, leak etc 100 141 ID assigned to break, leak etc 0 260 ID assigned to break, leak etc 0 42 ID assigned to break, leak etc 0 426 ID assigned to break, leak etc 0 120 ID assigned to break, leak etc 100 409 ID assigned to break, leak etc 100 413 ID assigned to break, leak etc 418 ID assigned to break, leak etc 50 401 ID assigned to break, leak etc 100 427 ID assigned to break, leak etc 100 249 ID assigned to break, leak etc 100 419 ID assigned to break, leak etc 25 301 ID assigned to break, leak etc 100 424 ID assigned to break, leak etc 100 342 ID assigned to break, leak etc 0 55 ID assigned to break, leak etc 100 430 ID assigned to break, leak etc 0 21 ID assigned to break, leak etc 100 392 ID assigned to break, leak etc 100 76 ID assigned to break, leak etc 0 48 ID assigned to break, leak etc 379 ID assigned to break, leak etc 100 407 ID assigned to break, leak etc 100 389 ID assigned to break, leak etc 100 433 ID assigned to break, leak etc 420 ID assigned to break, leak etc 100 431 ID assigned to break, leak etc 100 332 ID assigned to break, leak etc 100 103 ID assigned to break, leak etc 100 404 ID assigned to break, leak etc 100 432 ID assigned to break, leak etc 0 100 ID assigned to break, leak etc 100 405 ID assigned to break, leak etc 383 ID assigned to break, leak etc 100 284 ID assigned to break, leak etc 100 332 Sketch of damaged facility ' 25 55 Sketch of damaged facility 75 56 Sketch of damaged facility 25 414 Sketch of damaged facility 50 120 Sketch of damaged facility 100 301 Sketch of damaged facility 0 404 Sketch of damaged facility 25 408 Sketch of damaged facility 0 426 Sketch of damaged facility 0 76 Sketch of damaged facility 0 419 Sketch of damaged facility 25 251 72 Sketch of damaged facility 0 260 Sketch of damaged facility 100 21 Sketch of damaged facility 0 415 Sketch of damaged facility 0 417 Sketch of damaged facility 25 284 Sketch of damaged facility 100 42 Sketch of damaged facility 75 435 Sketch of damaged facility 50 403 Sketch of damaged facility 100 432 Sketch of damaged facility 100 400 Sketch of damaged facility 100 383 Sketch of damaged facility 50 416 Sketch of damaged facility 0 420 Sketch of damaged facility 100 10 Sketch of damaged facility 0 422 Sketch of damaged facility 0 430 Sketch of damaged facility 0 379 Sketch of damaged facility 0 112 Sketch of damaged facility 0 342 Sketch of damaged facility 0 227 Sketch of damaged facility 100 392 Sketch of damaged facility 0 424 Sketch of damaged facility 0 141 Sketch of damaged facility 0 231 Sketch of damaged facility 75 409 Sketch of damaged facility 100 240 Sketch of damaged facility 25 402 Sketch of damaged facility 0 283 Sketch of damaged facility 75 48 Sketch of damaged facility 401 Sketch of damaged facility 75 428 Sketch of damaged facility 0 100 Sketch of damaged facility 50 249 Sketch of damaged facility 100 434 Sketch of damaged facility 0 427 Sketch of damaged facility 0 389 Sketch of damaged facility 0 423 Sketch of damaged facility 0 411 Sketch of damaged facility _ _ 0 407 Sketch of damaged facility Sll 103 Sketch of damaged facility 295 Sketch of damaged facility 50 418 Sketch of damaged facility 25 405 Sketch of damaged facility 134 Sketch of damaged facility 0 433 Sketch of damaged facility 4 H Sketch of damaged facility 431 Sketch of damaged facility 0 408 Digital photo of damaged facility 0 252 295 Digital photo of damaged facility 100 ____ 379 Digital photo of damaged facility 0 240 Digital photo of damaged facility 50 435 Digital photo of damaged facility 100 389 Digital photo of damaged facility 0 112 Digital photo of damaged facility 0 227 Digital photo of damaged facility 0 415 Digital photo of damaged facility 50 433 Digital photo of damaged facility 25 141 Digital photo of damaged facility 0 332 Digital photo of damaged facility 50 '405 Digital photo of damaged facility 10 Digital photo of damaged facility 100 120 Digital photo of damaged facility 0 • 402 Digital photo of damaged facility 100 400 Digital photo of damaged facility 0 403 Digital photo of damaged facility 75 103 Digital photo of damaged facility 100 407 Digital photo of damaged facility 100 426 Digital photo of damaged facility 0 283 Digital photo of damaged facility 0 411 Digital photo of damaged facility 25 404 Digital photo of damaged facility 75 424 Digital photo of damaged facility 0 413 Digital photo of damaged facility 422 Digital photo of damaged facility 0 432 Digital photo of damaged facility 0 383 Digital photo of damaged facility 100 423 Digital photo of damaged facility 25 420 Digital photo of damaged facility 0 260 Digital photo of damaged facility 0 417 Digital photo of damaged facility 25 428 Digital photo of damaged facility 0 21 Digital photo of damaged facility _ _ 0 72 Digital photo of damaged facility 50 416 Digital photo of damaged facility 0 401 Digital photo of damaged facility 75 134 Digital photo of damaged facility 0 434 Digital photo of damaged facility 25 301 Digital photo of damaged facility 0 409 Digital photo of damaged facility 100 76 Digital photo of damaged facility 0 342 Digital photo of damaged facility 50 431 Digital photo of damaged facility 25 418 Digital photo of damaged facility 25 414 Digital photo of damaged facility 50 55 Digital photo of damaged facility 25 ' 231 Digital photo of damaged facility 50 419 Digital photo of damaged facility 25 253 100 Digital photo of damaged facility 0 284 Digital photo of damaged facility 0 427 Digital photo of damaged facility 0 430 Digital photo of damaged facility 25 42 ' Digital photo of damaged facility 100 392 Digital photo of damaged facility 0 249 Digital photo of damaged facility 50 48 Digital photo of damaged facility 56 Digital photo of damaged facility 25 400 Length of unsupported pipe 0 409 Length of unsupported pipe .0 413 Length of unsupported pipe 42 Length of unsupported pipe 0 431 Length of unsupported pipe 0 342 Length of unsupported pipe 0 383 Length of unsupported pipe 50 100 Length of unsupported pipe 0 120 Length of unsupported pipe 0 434 Length of unsupported pipe 0 72 Length of unsupported pipe 0 414 Length of unsupported pipe 50 56 Length of unsupported pipe 0 423 Length of unsupported pipe . 0 260 Length of unsupported pipe 0 332 Length of unsupported pipe 25-379 Length of unsupported pipe , 0 301 Length of unsupported pipe 0 405 Length of unsupported pipe 408 Length of unsupported pipe 0 389 Length of unsupported pipe 0 112 Length of unsupported pipe 0 404 Length of unsupported pipe 25 415 Length of unsupported pipe 0 422 Length of unsupported pipe 0 411 Length of unsupported pipe 0 417 Length of unsupported pipe ii 407 Length of unsupported pipe 0 392 Length of unsupported pipe 0 - 284 Length of unsupported pipe 0 103 Length of unsupported pipe 401 Length of unsupported pipe 0 295 Length of unsupported pipe 100 76 Length of unsupported pipe 0 231 Length of unsupported pipe 0 430 Length of unsupported pipe 0 249 Length of unsupported pipe ' 0 432 Length of unsupported pipe 0 418 Length of unsupported pipe 0 424 Length of unsupported pipe 0 254 283 Length of unsupported pipe 0 227 Length of unsupported pipe 0 419 Length of unsupported pipe 0 416 Length of unsupported pipe 0 240 Length of unsupported pipe 0 426 Length of unsupported pipe 0 141 Length of unsupported pipe c 0 428 Length of unsupported pipe 0 427 Length of unsupported pipe 0 435 i Length of unsupported pipe 25 420 Length of unsupported pipe 50 10 Length of unsupported pipe 100 21 Length of unsupported pipe 0 403 Length of unsupported pipe 100 55 Length of unsupported pipe 433 Length of unsupported pipe 48 Length of unsupported pipe 134 402 Length of unsupported pipe 0 Length of unsupported pipe 0 48 Job / work order number 407 Job / work order number 100 283 Job / work order number 0 405 Job / work order number 21 Job / work order number 0 428 Job / work order number 100 423 Job / work order number 100 301. Job / work order number 100 433 Job / work order number 100 260 Job / work order number 100 141 Job / work order number 100 409 Job / work order number 100 42 Job / work order number 100 112 Job / work order number 0 240 Job / work order number 100 426 Job / work order number 0 413 Job / work order number 416 Job / work order number 100 420 Job / work order number 100 432 Job / work order number 100 142 Job / work order number 100 103 Job / work order number 100 417 Job / work order number 100 403 Job / work order number 100 411 Job / work order number 100 383 Job / work order number 100 427 Job / work order number 100 424 Job / work order number .100 408 Job / work order number 0 379 Job / work order number 0 255 76 Job / work order number 0 404 Job / work order number 0 249 Job / work order number 100 332 Job / work order number 100 55 Job / work order number 389 Job / work order number 100 418 Job / work order number 100 134 Job / work order number 100 401 Job / work order number 0 56 Job / work order number 100 100 Job / work order number 100 431 Job / work order number 100 422 Job / work order number 0 419 Job / work order number 0 72 Job / work order number 100 430 Job / work order number 100 402 Job / work order number 100 227 Job / work order number 100 284 Job / work order number 100 295 Job / work order number 100 392 Job / work order number 100 415 Job / work order number 100 231 Job / work order number 100 434 Job / work order number 100 120 Job / work order number 100 10 Job / work order number 100 414 Job / work order number 100 400 Job / work order number 100 435 Job / work order number 100 433 Dates of previous breaks at same location 50 383 Dates of previous breaks at same location 100 400 Dates of previous breaks at same location 0 295 Dates of previous breaks at same location 100 411 Dates of previous breaks at same location 100 402 Dates of previous breaks at same location 100 424 Dates of previous breaks at same location 100 415 Dates of previous breaks at same location 0 405 Dates of previous breaks at same location 48 Dates of previous breaks at same location 401 Dates of previous breaks at same location 0 409 Dates of previous breaks at same location 100 76 Dates of previous breaks at same location 0 431 Dates of previous breaks at same location 100 417 Dates of previous breaks at same location 100 72 Dates of previous breaks at same location 0 332 Dates of previous breaks at same location 100 55 Dates of previous breaks at same location 379 Dates of previous breaks at same location 0 403 Dates of previous breaks at same location 25 256 10 Dates of previous breaks at same location 100 407 Dates of previous breaks at same location 100 103 Dates of previous breaks at same location . 100 134 Dates of previous breaks at same location 0 301 Dates of previous breaks at same location 75 435 Dates of previous breaks at same location 25 404 Dates of previous breaks at same location 0 432 Dates of previous breaks at same location , : 0 422 Dates of previous breaks at same location 0 408 Dates of previous breaks at same location 0 434 Dates of previous breaks at same location 0 21 Dates of previous breaks at same location 50 420 Dates of previous breaks at same location 0 419 Dates of previous breaks at same location 0 141 Dates of previous breaks at same location 100 430 Dates of previous breaks at same location 50 423 Dates of previous breaks at same location 100 426 Dates of previous breaks at same location 100 413 Dates of previous breaks at same location 42 Dates of previous breaks at same location 25 260 Dates of previous breaks at same location 0 283 Dates of previous breaks at same location 25 416 Dates of previous breaks at same location 100 120 Dates of previous breaks at same location 0 342 Dates of previous breaks at same location 100 56 Dates of previous breaks at same location 0 240 Dates of previous breaks at same location 0 100 Dates of previous breaks at same location 75 112 Dates of previous breaks at same location 0 231 . Dates of previous breaks at same location 75 227 Dates of previous breaks at same location 0 427 Dates of previous breaks at same location 100 284 Dates of previous breaks at same location 100 249 Dates of previous breaks at same location 0 414 Dates of previous breaks at same location 25 418 Dates of previous breaks at same location 100 428 Dates of previous breaks at same location _0_ 389 Dates of previous breaks at same location 0 392 Dates of previous breaks at same location 0 332 Equipment used 100 48 Equipment used 100 Equipment used 100 301 Equipment used 100 435 Equipment used 50 120 Equipment used 100 21 Equipment used 100 10 Equipment used 100 231 Equipment used 25 112 Equipment used 0 257 .400 Equipment used 50 428 Equipment used 100 42 Equipment used 100 240 Equipment used 100 283 1 Equipment used 25' 76 Equipment used ' 0 431 Equipment used 100 ^ 392 Equipment used 0 389 Equipment used 0 418 i Equipment used 100 424 Equipment used 100 284 Equipmentxused 100 383 Equipment used 100 432 Equipment used 100 430 Equipment used 25 342 Equipment used 100 55 Equipment used 100 423 Equipment used 100 260 Equipment used 100 434 Equipment used 100 416 Equipment used 100 404 Equipment used 75 72 Equipment used 100 401 Equipment used 100 420 Equipment used 100 379 Equipment used 25 295 Equipment used 100 414 Equipment used 100 422 Equipment used 75 407 Equipment used 100 415 | Equipment used 100 227 Equipment used 100 419 Equipment used 25 56 Equipment used 100 402 Equipment used 100 103 Equipment used 134 Equipment used 100 141 411 Equipment used 100 Equipment used 100 426 Equipment used 0 249 Equipment used 100 413 Equipment used 427 Equipment used 100 409 Equipment used 100 408 Equipment used 100 405 Equipment used 417 Equipment used 100 433 Equipment used 100 403 Equipment used 100 258 249 Crew members 100 408 Crew members 100 405 Crew members 404 Crew members 75 389 Crew members 100 403 Crew members 100 10 Crew members 100 134 Crew members 100 420 Crew members . 100 424 ! Crew members 100 426 Crew members 100 120 Crew members 100 416 Crew members 100 260 i Crew members 100 42 : Crew members 100 56 : Crew members 100 141 Crew members 0 383 Crew members 100 428 i Crew members 100 103 i Crew members 432 ! Crew members 100 419 414 Crew members 25 Crew members 100 231 i Crew members 75 100 Crew members 100 112: Crew members 100 379 i Crew members 100 433 i Crew members 100 413 ! Crew members 100 100 411 : Crew members 72 i Crew members 100 48 Crew members 418 Crew members 100 21 Crew members 100 434 Crew members 100 301 : Crew members 100 407 Crew members 100 422 Crew members 0 240 ! Crew members 100 295 i Crew members 100 409 Crew members 100 332 Crew members 100 435 Crew members 25 402 Crew members 100 y>2 423 Crew members 0 Crew members 100 430 i Crew members 100 284 Crew members 100 76 Crew members 100 259 415 Crew members 100 283 Crew members 0 342 Crew members 100 417 Crew members 427 i Crew members 431 | Crew members 100 100 100 55 i Crew members 100 400 Crew members 50 401 Crew members ' 100 227 Crew members 100 426 Crew total hours 100 416 Crew total hours 100 413 Crew total hours 100 260 Crew total hours 100 423 ! Crew total hours 100 _ 4 2 7 400 Crew total hours 100 Crew total hours 50 409 i Crew total hours 100 418 283 Crew total hours 100 Crew total hours 0 41 y (.'iew total hours 25 72 I Crew total hours 100 434 Crew total hours 100 295 : Crew total hours 100 415 ! Crew total hours 100 402 i Crew total hours 100 401 Crew total hours 100 431 Crew total hours 100 392 Crew total hours 0 227 Crew total hours 100 435 ! Crew total hours 25 284 Crew total hours 100 231 Crew total hours 75 430 Crew total hours 100 240 Crew total hours 100" 100 : Crew total hours 100 120 i Crew total hours 100 403 Crew total hours 100 414 Crew total hours 100 10 | Crew total hours 100 141 Crew total hours 100 428 Crew total hours 100 417 Crew total hours 100 42 Crew total hours 100 112 Crew total hours 100 56 Crew total hours 100 422 Crew total hours 0 407 Crew total hours 100 404 Crew total hours 100 260 301 Crew total hours 0 249 Crew total hours 100 379 Crew total hours 100 433 Crew total hours 100 342 Crew total hours 100 134 Crew total hours 100 424 Crew total hours 100 21 Crew total hours 100 383 Crew total hours 100 332 Crew total hours 100 408 Crew total hours 100 103 Crew total hours 55 Crew total hours 100 432 Crew total hours 100 411 Crew total hours 100 405 Crew total hours 48 Crew total hours 76 Crew total hours 0 389 Crew total hours 0 420 Crew total hours 100 407 Total labour cost 100 383 Total labour cost 100 42 Total labour cost 100 120 Total labour cost 100 332 Total labour cost 100 401 Total labour cost 0 240 Total labour cost 100 400 Total labour cost 0 295 Total labour cost 100 0 112 Total labour cost 389 Total labour cost 0 430 Total labour cost 100 415 Total labour cost 100 100 141 Total labour cost 231 Total labour cost 75 342 Total labour cost 100 392 Total labour cost 0 414 Total labour cost 50 103 Total labour cost 419 Total labour cost 25 418 Total labour cost 100 431 Total labour cost 100 426 Total labour cost 0 432 Total labour cost 55 Total labour cost 100 428 Total labour cost 100 409' Total labour cost 100 405 Total labour cost 402 Total labour cost 0 261 227 Total labour cost 100 ^ 21 403 Total labour cost 0 Total labour cost ^ 100 404 Total labour cost 25 42^ Total labour cost 100 408 Total labour cost 100 134 Total labour cost 100 283 Total labour cost 0 301 Total labour cost 0 435 Total labour cost 100 420 Total labour cost 75 422 Total labour cost 0 260 Total labour cost 100 427 Total labour cost 100 249 Total labour cost 100 100 Total labour cost 100 417 Total labour cost 100 72 Total labour cost 100 , 416 Total labour cost 100 76 Total labour cost 0 379 Total labour cost 0 434 Total labour cost 100 56 Total labour cost 100 10 Total labour cost 25 413 Total labour cost 100 284 Total labour cost 100 424 Total labour cost 100 48 Total labour cost 411 Total labour cost 100 433 Total labour cost 100 420 Total materials cost 0 134 Total materials cost 75 379 Total materials cost 0 422 Total materials cost 0 284 Total materials cost 100 55 Total materials cost 100 72 Total materials cost 100 400 Total materials cost 25 417 Total materials cost 100 25 10 Total materials cost 48 Total materials cost 403 Total materials cost 100 301 Total materials cost 0 435 Total materials cost 100 2 ' ^ Total materials cost 100 21 Total materials cost 0 392 Total materials cost 0 434 Total materials cost 100 433 Total materials cost 100 262 415 Total materials cost 100 407 Total materials cost 100 332 Total materials cost , 100 401 Total materials cost 402 ! Total materials cost 431 i Total materials cost 227 : Total materials cost 0 0 _ JM 100 112 Total materials cost 0 141 Total materials cost 100 103 1 Total materials cost 4 428 i Total materials cost 100 423 Total materials cost 100 383 Total materials cost 100 283 i Total materials cost 0 42 ! Total materials cost 100 419 : Total materials cost 25 260 Total materials cost 100 432 Total materials cost 249 Total materials cost 100 416 Total materials cost 100 405 Total materials cost 56 Total materials cost 100 424 Total materials cost 100 426 Total materials cost 0 41 1 Total materials cost 100 240 Total materials cost 100 427 Total materials cost 0 404 Total materials cost 25 342 Total materials cost 100 430 Total materials cost 100 76 i Total materials cost 0 Total materials cost 0 100 Total materials cost 100 231 Total materials cost 75 . ' 418 Total materials cost 100 413 < Total materials cost 100 408 : Total materials cost 100 414 Total materials cost 50 409 Total materials cost 100 120 Total materials cost 100 405 Total equipment cost 227 Total equipment cost 100 249 Total equipment cost 100 72 Total equipment cost 100 389 Total equipment cost 0 435 Total equipment cost 100 418 Total equipment cost 100 434 Total equipment cost 100 427 Total equipment cost 0 263 426 Total equipment cost 0 404 Total equipment cost 25 48 Total equipment cost 21 Total equipment cost 0 283 Total equipment cost 0 417 Total equipment cost 100 260 Total equipment cost 100 403 Total equipment cost ' 100 400 Total equipment cost 25 301 Total equipment cost 0 423 Total equipment cost 100 76 Total equipment cost 0 416 Total equipment cost 100 10 Total equipment cost 25 284 Total equipment cost 100 103 Total equipment cost 431 Total equipment cost 100 401 Total equipment cost 0 392 Total equipment cost 0 342 Total equipment cost 100 55 Total equipment cost 100 402 Total equipment cost 0 379 Total equipment cost 0 432 Total equipment cost 120 Total equipment cost 100 231 Total equipment cost 75 430' Total equipment cost 100 409 Total equipment cost 100 422 Total equipment cost 0 141 Total equipment cost 100 414 Total equipment cost 25 420 Total equipment cost 100 407 Total equipment cost 100 413 Total equipment cost 100 56 Total equipment cost 100 415 Total equipment cost 100 100 Total equipment cost 100 295 Total equipment cost 100 408 Total equipment cost 100 41') Total equipment cost 25 240 Total equipment cost 100 411 Total equipment cost 100 428 Total equipment cost 100 42 Total equipment cost 100 332 Total equipment cost 100 433 Total equipment cost 100 134 Total equipment cost 100 383 Total equipment cost 100 424 Total equipment cost 100 264 112 j Total equipment cost 265 Physical data recorded by survey respondents City ID . ttliillfBiBfiif^il^H Description Recorded!",,) Confidence \ \ai l jble from other - Sources Comments •>.; 21 Backfill material 1 0 0 ' HIGH N O Archival records •NIL 4 2 Backfill material 5 0 M E D I U M \ \ \ - \ NIL 5 5 Backfill material 1 0 0 HIGH Other NIL 5fi Backfill material 1 0 0 GOOD NO NA NIL 7 2 Backfill material 5 0 GOOD NA- N A NIL 4 2 8 Backfill material 0 . NA_ _ N A N A NIL 4 1 3 Backfill material 1 0 0 HIGH \<> \ \ NIL 1 0 0 Backfill material 1 0 0 HIGH \ ( ) N A NIL 1 0 3 Backfill material 1 0 0 HIGH N A N A NIL 1 1 2 Backfill material 0 N A N A N A NIL 1 2 0 Backfill material 0 N O N E \() \ \ NIL 1 3 4 Backfill material 1 0 0 HIGH N O N A NIL 4 1 8 Backfill material 0 N O N E NO N A NIL 2 2 7 Backfill' material 1 0 0 GOOD Y E S O & M records Hansen WO data 2 3 1 Backfill material 0 \ ( ) \ E NO N A NIL 2 4 0 Backfill material 5 0 GOOD NO N A NIL 2 4 9 Backfill material 1 0 0 M E D I U M N O N A as built drawings 2(.n Backfill material 0 N A N A NA NIL 4 0 1 Backfill material 0 N A YES Archival records NIL 2 8 3 Backfill material 0 GOOD NO N A NIL 2 8 4 Backfill material 2 5 L O W N A N A NIL 2 9 5 Backfill material i i HIGH N O N A NIL 3 0 1 Backfill material 1 0 0 GOOD N O N A NIL 4 2 4 Backfill material 0 HIGH N O N A NIL 4 3 3 Backfill material 7 5 GOOD N A N A NIL 3 3 2 Backfill material 5 0 M E D I U M \() N A NIL 4 3 5 Backfill material 1 0 0 GOOD N O N A NIL 4 0 0 Backfill material 0 N O N E N O N A NIL 3 8 3 Backfill material 1 0 0 HIGH \ \ N A NIL 3 9 2 Backfill material 0 N O N E YES Archival records NIL 4 0 3 Backfill material 1 0 0 HIGH YES External NIL 4 0 9 Backfill material 1 0 0 HIGH N A N A NIL 10 Backfill material 0 N A N A N A NIL 4 8 Backfill material 0 high no N A NIL 4 0 4 Backfill material 0 N O N E N A N A NIL 4 1 1 Backfill material N A N A N A NIL 7 6 Backfill material 0 N A Yes Archival records NIL 4 1 4 Backfill material 0 N A N O N A NIL 141 Backfill material 0 N A NO N A NIL 4 0 5 Backfill material 1 0 0 HIGH N A N A NIL 4 0 2 Backfill material 1 0 0 HIGH YES Archival records NIL 266 430 Backfill material 0 GOOD N O N A NIL 431 Backfill material 100 HIGH N O N A NIL 415 Backfill material 0 N O N E N O N A ' NIL 416 Backfill material 0 N O N E N O N A NIL 407 Backfill material 100 HIGH N O N A NIL 417 Backfill material 0 N O N E N O N A NIL 432 Backfill material 0 N A N O N A NIL 419 Backfill material 100 HIGH N O N A NIL __426 Backfill material 0 N O N E N A N A NIL 420 Backfill material 100 HIGH N O N A NIL 427 Backfill material 0 N O N E N O N A NIL 422 Backfill material 0 N O N O N A NIL 434 Backfill material 25 M E D I U M N O N A NIL 342 Backfill material 0 : N A N O N A NIL 408 Backfill material N A • N A N A \ l l 423 Backfill material 100 GOOD Y E S Archival records NIL 379 Backfill material 0 N O N E Y E S O & M records N I L 389 Backfill material 100 HIGH N A Other NIL 21 Bedding material 100 HIGH N O Archival records NIL 42 Bedding material 75 GOOD N A N A NIL _ ^ Bedding material . 0 N A N A N A NIL 56 Bedding material 0 N A N A N A NIL . . . 7 2 • Bedding material 50 GOOD N A N A NIL 428 Bedding material 0 N A N A N A NIL 413 Bedding material N A N A N A NIL 100 Bedding material 100 HIGH YES Archival records NIL 103 Bedding material 100 HIGH N A N A NIL 112 Bedding material 0 N O N E Y E S Archival records NIL 120 Bedding material 0 N O N E N O N A NIL 134 Bedding material 100 HIGH N O N A NIL 418 Bedding material 0 N O N E N O \ \ NIL 227 Bedding material 100 GOOD Y E S U W 1 records Hansen WO data 231 Bedding material 0 N O N E Y E S Archival records Soil beddign may be available from contract documents. 240 Bedding material 5i) M E D I U M N O N A NIL 249 Bedding material 100 L O W Y E S N A as built drawings 260 Bedding material 0 N A N A N A NIL 401 Bedding material 25 GOOD Y E S Archival records recorded if significant 283 Bedding material 0 GOOD N O N A NIL 284 Bedding material 25 L O W N A N A NIL 295 Bedding material 0 HIGH N O N A NIL 301 Bedding material 100 GOOD N O N A NIL 267 424 Bedding material 0 HIGH ' N O N A NIL 433 Bedding material 25 GOOD N A N A NIL 332 Bedding material 25 M E D I U M N O N A NIL 435 Bedding material 75 GOOD N O N A NIL 400 Bedding material 50 M E D I U M Y E S Archival records NIL 383 Bedding material 100 HIGH N A N A NIL 392 Bedding material 0 N O N E Y E S Archival records NIL 403 Bedding material 50 GOOD N O N A NIL 409 Bedding material 100 HIGH N A N A NIL 10 Bedding material 0 N A N A N A NIL 48 Bedding material 0 high no N A • NIL 404 Bedding material 0 N O N E N A N A NIL 411 Bedding material N A N A N A NIL 76 Bedding material 0 N A No External NIL 414 Bedding material 0 N A • N O N A NIL 141 Bedding material 0 \ \ N O N A , NIL 405 Bedding material 100 HIGH N A N A NIL 402 Bedding material 0 HIGH Y E S Archival records NIL 430 Bedding material 25 GOOD NO N A NIL 431 Bedding material 100 HIGH NO N A NIL 415 Bedding material •50 L O W N O N A NIL 416 Bedding material 0 N O N E N O N A NIL 407 Bedding material 100 HIGH NO N A NIL 417 Bedding material 0 N O N E N O N A NIL 432 Bedding material 100 GOOD N O N A M l 419 Bedding material 100 HIGH N O Archival records NIL 426 Bedding material 0 N O N E N A - N A NIL 420 Bedding material 0 N O N E Y E S O & M records NIL 427 Bedding material 0 N O N E Y E S O & M records Technical Specs 422 Bedding material 0 GOOD N O N A NIL 434 Bedding material 0 N A N O N A •.NIL 342 Bedding material 0 N A N O N A NIL 408 Bedding material 0 N O N E N O N A NIL 423 Bedding material 0 N A Y E S Archival records NIL 379 Bedding material 0 N O N E Y E S Archival records NIL 389 Bedding material 100 HIGH N A Other NIL 21 Category of native soil 0 N A N O N A NIL 42 Category of native soil 50 M E D I U M N A N A NIL 55 Category of native soil 0 N A N A N A NIL s56 Category of native soil 0 N A N A •NA NIL 268 72 Category of native soil 0 GOOD N A N A NIL 428 Category of native soil 0 N A N A N A NIL . 413 Category of native soil N A N A • N A NIL 100 Category of native soil 0 GOOD N O N A NIL 103 Category of native soil 0 N A N A N A NIL 112 Category of native soil 0 N A N A N A NIL 120 Category of native soil 0 N O N E N O N A NIL 134 Category of native soil 100 HIGH N O N A NIL 418 Category of native soil 0 N O N E NO N A NIL 227 Category of native soil 100 GOOD Y ES O & M records Hansen WO data 231 Category of native soil 100 GOOD YES Archival records Soil Condition may be available from geotechnical reports. 240 Category of native soil 75 M E D I U M NO N A NIL 249 Category of native soil 0 N O N E NO N A as built drawings 260 Category of native soil 0 N A N A N A NIL 401 Category of native soil 0 N A NO N A NIL 283 Category of native soil 100 GOOD NO ______ N A 1 NIL 284 Category of native soil 25 L O W N A N A NIL 295 Category of native soil 0 HIGH N O N A NIL .301 Category of native soil 0 N A N O N A NIL 424 Category of native soil 0 HIGH NO N A NIL 433 Category of native soil 25 L O W NA- N A NIL 332 Category of native soil 0 N O N E Y E S Other NIL 435 Category of native soil 50 GOOD N O N A NIL 400 Category of native soil 0 N O N E NO N A NIL 269 383 Category of native soil 0 N A N A N A NIL 392 Category of native soil 0 N O N E Y E S Archival records NIL 403 Category of native soil 0 N A N A N A NIL 409 Category of native soil 100 HIGH N A N A NIL 10 Category of native soil 0 N A N A N A NIL 48 Category of native soil 0 high no N A NIL ,404 Category of native soil 0 N O N E N A N A NIL 411 Category of native soil N A N A N A NIL 76 Category of native soil 0 N A Yes Archival records NIL 414 Category of native soil 0 N A N O N A NIL 141 Category of native soil 0 N A Y E S GIS system NIL 405 Category of native soil 0 N O N E N A N A NIL 402 Category of native soil 0 HIGH NO Archival records NIL 430 Category of native soil 0 GOOD NO N A NIL 431 Category of native soil 25 M E D I U M Y E S External NIL 415 Category of native soil 50 M E D I U M N O N A N I L 416 Category of native soil 0 N O N E NO N A NIL 407 Category of native soil 100 HIGH NO N A NIL 417 Category of native soil 0 N O N E N O N A NIL 432 Category of native soil 100 GOOD N O N A NIL 419 Category of native soil 0 LOW- N O N A NIL i Category of native 426 1 soil 0 N O N E N A N A NIL 420 Category of native soil 0 N O N E N O N A NIL 427 Category of native soil 0 N O N E Y E S O & M records Technical Specs 422 Category of native soil 0 GOOD NO N A NIL 434 Category of native soil 25 M E D I U M N O N A NIL 270 342 Category of native soil 0 N A Y ES GIS system NIL 408 . Category of native soil N A N A N A NIL 423 Category of native soil 0 N A N O N A NIL 379 Category of native . soil 0 N O N E Y ES Archival records NIL 389 Category of native soil 100 GOOD N A Other NIL 21 Condition of bedding 0 N A N O N A NIL 42 Condition of bedding 75 GOOD N A N A NIL 55 Condition of bedding 0 N A N A N A NIL 56 Condition of bedding 0 N A N A N A NIL 72 Condition of bedding 50 GOOD N A N A NIL 428 Condition of bedding 0 N A N A N A NIL 413 Condition of bedding N A N A N A NIL 100 Condition of bedding 50 GOOD N O N A NIL 103 Condition of bedding 0 N A N A N A NIL 112 Condition of bedding 0 N A N A N A NIL 120 Condition of bedding 0 N O N E N O N A NIL 134 Condition of bedding 0 N O N E NO N A NIL 418 Condition of bedding 0 N O N E NO N A NIL 227 Condition of bedding 100 GOOD Y E S O & M records Hansen WO data 231 Condition of bedding 0 N O N E N O N A NIL 240 Condition of bedding 25 L O W N O N A NIL 249 Condition of bedding 0 N O N E NO N A NIL 260 Condition of bedding 0 N A N A N A NIL 401 Condition of bedding 25 GOOD Y E S Archival records recorded if significant 283 Condition of bedding 0 GOOD N O N A NIL 284 Condition of bedding 25 L O W N A N A NIL 271 j . • 295 Condition of bedding 25 HIGH N O N A NIL 301 Condition of bedding 0 N A N A N A NIL 424 Condition of bedding 0 HIGH N O N A NIL 433 Condition of bedding 25 GOOD N A N A NIL 332 Condition of bedding 25 LOW- N O N A ' NIL 435 Condition of bedding 75 GOOD NO N A NIL 400 Condition of bedding 0 N O N E N O N A NIL 383 Condition of bedding 100 HIGH N A N A NIL 392 Condition of bedding 0 N O N E N O N A NIL 403 409 Condition of bedding 75 j GOOD NO N A NIL Condition of bedding ioo HIGH N A N A NIL 10 Condition of bedding 0 N A N A N A NIL 48 Condition of bedding 0 high no N A NIL 404 Condition of bedding 0 N O N E N A N A NIL 411 Condition of bedding N A N A N A NIL 76 Condition of bedding 0 N A No External NIL 414 Condition of bedding 0 N A NO N A NIL 141 Condition of bedding . 0 N A NO N A NIL 405 Condition of bedding 100 HIGH N A N A NIL 402 Condition of bedding 0 HIGH N O Archival records NIL 430 | Condition of bedding 25 GOOD NO N A NIL 431 i Condition of bedding 100 HIGH NO N A NIL 415 i Condition of bedding 100 GOOD N O N A NIL 416 | Condition of bedding 0 N O N E N O N A NIL 407 417 Condition of bedding 100 HIGH NO N A NIL Condition of bedding 0 N O N E N O N A NIL 272 432 Condition of bedding 100 GOOD N O N A NIL 419 Condition of bedding 100 HIGH N O Archival records NIL 426 Condition of bedding 0 N O N E N A N A NIL 420 Condition of bedding 0 N O N E NO N A NIL 427 Condition of bedding 0 N O N E NO N A NIL 422 Condition of bedding 0 GOOD NO N A .. NIL 434 Condition of bedding 50 M E D I U M NO N A NIL 342 Condition of bedding 0 N A , NO N A NIL 408 Condition of bedding N A N A N A NIL 423 Condition,of bedding 0 J N A _ Y ES Archival records NIL 379 Condition of bedding 0 N O N E NO O & M records NIL 389 Condition of bedding • 0 N A N A N A NIL 21 Condition of cement lined pipe interior 0 N A Y E S Other swabbing existing mains 42 Condition of cement lined pipe interior N A N A N A NIL 55 Condition of cement lined pipe interior' N A N A N A Not Applicable 56 Condition of cement lined pipe interior 25 GOOD NO N A NIL 72 Condition of cement lined pipe interior 0 GOOD N A • N A NIL 428 Condition of cement lined pipe interior 0 N A N A N A NIL 413 Condition of cement lined pipe interior N A N A N A NIL "100 Condition of cement lined pipe interior 0 _ GOOD N O N A NIL 103 Condition of cement lined pipe interior 0 N A N A N A NIL 273 112 Condition of cement lined pipe interior 25 HIGH N A N A NIL 120 Condition of cement lined pipe interior 0 N O N E N O N A NIL 134 Condition of cement lined pipe interior 0 N O N E Y E S Other Distribution System Model 418 Condition of cement lined pipe interior 0 N O N E N O N A NIL 227 Condition of cement lined pipe interior 0 N A N A N A NIL 231 Condition of cement lined pipe interior 0 N O N E NO N A NIL 240 Condition of cement lined pipe interior 25 M E D I U M N O N A NIL • 249 Condition of cement lined pipe interior 0 N O N E N O N A NIL 260 Condition of cement lined pipe interior 0 N A N A N A NIL 401 Condition of cement lined pipe interior 0 N A N O N A NIL 283 Condition of cement lined pipe interior 0 GOOD NO. N A NIL 284 Condition of cement lined pipe interior 25 L O W N A N A NIL 295 Condition of cement lined pipe interior 100 HIGH N O N A NIL 301 Condition of cement lined pipe interior 0 N A N A N A NIL 424 Condition of cement lined pipe interior 0 HIGH 1 NO N A NIL 433 Condition of cement lined pipe interior 0 M E D I U M •! N A N A NIL 332 Condition of cement lined pipe interior N A ! N A N A NIL 274 435 Condition of cement lined pipe interior 50 GOOD N O N A NIL 400 Condition of cement lined pipe interior 0 N O N E NO N A NIL 383 Condition of cement lined pipe interior 75 GOOD N A N A NIL 392 Condition of cement1 , lined pipe interior 0 N O N E N O N A NIL 403 Condition of cement lined pipe interior 100 HIGH N O N A NIL 409 Condition of cement lined pipe interior 25 M E D I U M N A N A NIL 10 Condition of cement lined pipe interior 0 N A N A N A NIL 48 Condition of cement lined pipe interior 0 high no N A NIL 404 Condition of cement lined pipe interior 50 GOOD Y E S Archival records NIL 411 Condition of cement lined pipe interior N A N A N A NIL 76 Condition of cement lined pipe interior 0 N A No Other NIL 414 Condition of cement lined pipe interior 50 . M E D I U M YES O & M records NIL 141 Condition of cement lined pipe interior 0 N A NO N A NIL 405 Condition of cement lined pipe interior 100 GOOD N A N A NIL 402 Condition of cement lined pipe interior 0 HIGH N O Other NIL 430 Condition of cement lined pipe interior 0 GOOD N O N A NIL 431 Condition of cement lined pipe interior 25 L O W Y E S External NIL 275 415 Condition of cement lined pipe interior 50 L O W N O N A • NIL 416 Condition of cement lined pipe interior 0 • N O N E N O N A NIL 407 Condition of cement lined pipe interior 100 HIGH N O N A NIL 417 Condition of cement lined pipe interior 0 N O N E N O N A NIL 432 Condition of cement lined pipe interior 0 N A NO N A NIL 419 Condition of cement lined pipe interior 50 M E D I U M Y E S N A NIL 426 Condition of cement lined pipe interior 0 N O N E N A N A NIL 420 Condition of cement lined pipe interior 0 N O N E N O N A NIL 427 Condition of cement lined pipe interior 0 N O N E N O N A . NIL 422 Condition of cement lined pipe interior 0 GOOD N O N A NIL 434 Condition of cement lined pipe interior 25 M E D I U M NO N A NIL 342 Condition of cement lined pipe interior 0 • N A N O N A NIL 408 Condition of cement lined pipe interior N A N A N A NIL 423 Condition of cement lined pipe interior 0 N A N A N A NIL 379 Condition of cement lined pipe interior 0 . N O N E N O N A NIL 389 Condition of cement lined pipe interior 0 N A N A N A NIL 21 Condition of pipe exterior 50 GOOD NO N A NIL 42 Condition of pipe exterior 100 GOOD N A N A NIL 276 55 Condition of pipe exterior N A N A N A When applicable 56 Condition of pipe exterior 25 M E D I U M N O N A NIL 72 • Condition of pipe exterior 0 GOOD N A N A NIL 428 Condition of pipe exterior 0 N A \ \ N A NIL 413 Condition of pipe exterior 100 H I G H NO N A NIL 100 Condition of pipe exterior 0 GOOD N O N A NIL 103 Condition of pipe exterior 100 H I G H N A N A NIL 112 Condition of pipe exterior 100 H I G H N A N A • NIL 120 Condition of pipe exterior 100 H I G H N O N A NIL 134 Condition of pipe exterior 25 L O W Y E S Other Distribution System Model 418 Condition of pipe exterior 0 N O N E r N O N A NIL 227 Condition of pipe exterior 0 N A N A N A NIL 231 Condition of pipe exterior 100 GOOD Y E S Other Occasional Picture taken 240 Condition of pipe exterior 25 L O W NO N A NIL 249 Condition of pipe exterior 0 N O N E N O N A If problem was evident it would be recorded 260 Condition of pipe exterior 0 N A N A . N A NIL '' 401 Condition of pipe exterior 25 GOOD NO N A recorded i f significant 283 Condition of pipe exterior 100 GOOD NO N A NIL 284 Condition of pipe exterior 25 L O W N A N A NIL 295 Condition of pipe exterior 100 H I G H NO N A NIL 301 Condition of pipe exterior 100 H I G H N O N A NIL 424 Condition of pipe exterior 25 H I G H NO N A NIL 433 Condition of pipe exterior 25 M E D I U M N A N A NIL 277 332 Condition of pipe exterior 25 M E D I U M NO N A If exterior is in very bad shape, this will be noted in foreman's report 435 Condition of pipe exterior 50 GOOD NO N A NIL 400 Condition of pipe exterior 0 N O N E N O N A NIL 383 Condition of pipe exterior 100 HIGH N A N A NIL 392 Condition of pipe exterior 0 N O N E Y E S Archival records NIL 403 Condition of pipe exterior 100 HIGH N O N A NIL 409 Condition of pipe exterior 100 HIGH N A N A NIL 10 Condition of pipe exterior 25 GOOD YES GIS system NIL 48 Condition of pipe exterior 0 high no N A NIL 404 Condition of pipe exterior 50 GOOD YES Archival records NIL 411 Condition of pipe exterior N A N A N A NIL 76 Condition of pipe exterior 0 N A No Other NIL 414 Condition of pipe exterior 50 M E D I U M N O O & M records NIL 141 Condition of pipe exterior 0 N A N O N A NIL 405 Condition of pipe exterior 100 HIGH N A N A NIL 402 Condition of pipe exterior 0 HIGH N O Other NIL 430 Condition of pipe exterior \ 0 GOOD N O N A NIL 431 Condition of pipe exterior 100 HIGH N O N A NIL 415 Condition of pipe exterior 100 GOOD NO N A NIL 416 Condition of pipe exterior 0 N O N E N O N A NIL 407 Condition of pipe exterior 50 HIGH N O N A NIL 417 Condition of pipe exterior 0 N O N E N O N A NIL 432 Condition of pipe exterior 100 GOOD N O N A NIL 419 Condition of pipe exterior 50 M E D I U M Y E S N A NIL 278 426 Condition of pipe exterior 0 N O N E N A N A NIL 420 Condition of pipe exterior 0 N O N E N O N A NIL 427 Condition of pipe exterior 75 M E D I U M NO N A NIL 422 Condition of pipe exterior 0 GOOD N O N A NIL 434 Condition of pipe exterior 25 M E D I U M \ ( ) N A NIL 342 Condition of pipe exterior 0 N A N O N A NIL 408 Condition of pipe exterior N A N A N A NIL 423 Condition of pipe exterior 100 N A N O N A NIL 379 Condition of pipe exterior 75 M E D I U M N O O & M records NIL 1 389 Condition of pipe exterior 0 N A N A N A NIL 21 Condition of unlined pipe interior 0 N A Y E S Other swabbing existing mains 42 Condition of unlined pipe interior 100 GOOD N A N A NIL 55 Condition of unlined pipe interior N A N A N A Not Applicable 56 Condition of unlined pipe interior 25 M E D I U M N O N A NIL 72 Condition of unlined pipe interior 0 GOOD N A N A NIL 428 Condition of unlined pipe interior 0 N A N A N A NIL 413 Condition of unlined pipe interior N A N A N A NIL 100 Condition of unlined pipe interior 0 GOOD N O N A NIL 103 Condition of unlined pipe interior 0 N A N A N A NIL 112 Condition of unlined pipe interior 25 HIGH ' N A N A NIL 120 Condition of unlined pipe interior 0 N O N E N O N A NIL 279 134 Condition of unlined pipe interior 25 L O W Y E S Other Distribution System Model 418 Condition of unlined pipe interior 0 N O N E N O N A NIL 227 Condition of unlined pipe interior 0 N A N A N A NIL 231 Condition of unlined pipe interior . 0 N O N E N O N A • NIL 240 Condition of unlined pipe interior 25 L O W N O N A NIL 249 Condition of unlined pipe interior 0 N O N E NO N A NIL 260 Condition of unlined pipe interior 0 N A N A N A NIL 401 Condition of unlined pipe interior 25. GOOD N O N A recorded i f significant 283 Condition of unlined pipe interior 0 GOOD N O N A NIL 284 Condition of unlined pipe interior 25 L O W N A N A •NIL 295 Condition of unlined pipe interior 100 HIGH N O N A NIL 301 Condition of unlined pipe interior 0 N A N A N A NIL 424 Condition of unlined pipe interior 0 HIGH N O N A NIL 433 Condition of unlined pipe interior 25 M E D I U M N A N A NIL 332 Condition of unlined pipe interior N A N A N A NIL 435 Condition of unlined pipe interior 50 GOOD N O N A NIL 400 Condition of unlined pipe interior 0 N O N E NO N A NIL 280 383 Condition of unlined pipe interior 75 GOOD N A N A NIL 392 Condition of unlined pipe interior 0 N O N E NO N A NIL 403 Condition of unlined pipe interior 100 HIGH N O N A NIL 409 Condition of unlined pipe interior 25 M E D I U M Y E S O & M records NIL 10 Condition of unlined pipe interior 25 GOOD Y E S GIS system NIL 48 Condition of unlined pipe interior 0 high no N A NIL 404 Condition of unlined pipe interior 50 GOOD YES Archival records NIL 411 Condition of unlined pipe interior N A N A N A NIL 76 Condition of unlined pipe interior 0 N A No Other NIL 414 Condition of unlined pipe interior 50 M E D I U M N O O & M records NIL 141 Condition of unlined pipe interior 0 N A N O N A NIL 405 Condition of unlined pipe interior 0 . N O N E N A N A NIL 402 Condition of unlined pipe interior 0 HIGH N O Other NIL 430 Condition of unlined pipe interior 0 GOOD N O N A NIL 431 Condition of unlined pipe interior 0 N O N E N O N A NIL 415 Condition of unlined pipe interior 50 L O W NO N A NIL 416 Condition of unlined pipe interior 0 N O N E N O N A NIL 281 407 Condition of unlined pipe interior 100 HIGH N O N A NIL 417 Condition of unlined pipe interior 0 NONE N O N A NIL 432 Condition of unlined pipe interior 25 M E D I U M N O N A NIL 419 Condition of unlined pipe interior 50 M E D I U M . Y ES N A NIL 426 Condition'of unlined pipe interior 0 NONE' N A N A NIL 420 Condition of unlined pipe interior 0 NONE NO N A NIL 427 Condition of unlined pipe interior ,0 NONE NO N A NIL 422 Condition of unlined pipe interior 0 GOOD N O N A NIL 434 Condition of unlined pipe interior 25 M E D I U M N O N A NIL 342 Condition of unlined pipe interior 0 N A N O N A NIL 408 Condition of unlined pipe interior N A N A N A NIL 423 Condition of unlined pipe interior 100 N A N O . N A NIL 379 Condition of unlined pipe interior 0 NONE N O N A NIL 389 Condition of unlined pipe interior 0 N A N A N A NIL 21 Depth of cover 100 HIGH Y E S Archival records NIL 42 Depth of cover 75 HIGH N A N A NIL 55 Depth of cover 100 HIGH Y E S Other NIL 56 Depth of cover 75 GOOD N O N A NIL 72 Depth of cover 50 GOOD N A . N A NIL 428 Depth of cover 0 N A N A N A NIL 413 Depth of cover 100 HIGH N O N A NIL 100 Depth of cover 100 HIGH Y E S Archival records NIL 103 Depth of cover 100 HIGH N A N A NIL 282 112 Depth of cover 100 HIGH Y E S Archival records NIL 120 Depth of cover 100 (j(K)D \ o N A NIL 134 Depth of cover 100 M E D I U M Y E S Archival records NIL ' 418 Depth of cover 0 N O N E Y E S Archival records NIL 227 Depth of cover 100 GOOD -YES O & M records Hansen WO data 231 Depth of cover 100 HIGH NO Other Depth of Main recorded on break sheet. . 240 Depth of cover 100 GOOD NO N A NIL 249 Depth of cover 100 GOOD Y E S N A as built drawings 260 Depth of cover 0 N A Y E S Archival records NIL 401 Depth of cover 0 N A Y E S Archival records NIL 283 Depth of cover 100 GOOD YES Archival records NIL 284 Depth of cover 50 M E D I U M N A N A NIL 295 Depth of cover 0 HIGH N O N A NIL 301 Depth of cover 0 N A Y E S N A NIL 424 Depth of cover 100 HIGH Y E S Archival records NIL 433 Depth of cover 25 GOOD N A GIS system NIL 332 Depth of cover 75 GOOD YES _ Archival records NIL 435 Depth of cover 100 GOOD NO N A NIL '400 Depth of cover 75 GOOD N O N A NIL 383 Depth of cover 25 N A N A N A NIL 392 Depth of cover 100 M E D I U M Y E S Archival records NIL 403 Depth of cover 100 HIGH N O N A NIL 409 Depth of cover 100 HIGH N A N A NIL 10 Depth of cover 0 N A N A N A NIL 48 Depth of cover 100 high no N A . NIL 404 Depth of cover 50 GOOD YES Archival records NIL 41 1 Depth of cover N A N A N A M I . 76 Depth of cover 0 N A Yes Archival records NIL 414 Depth of cover 75 GOOD N O O & M records J_JJ_L__ 141 Depth of cover - 0 N A NO N A NIL 405 Depth of cover 100 GOOD N A N A NIL 402 Depth of cover 0 HIGH Y E S Archival records NIL 283 430 Depth of cover .25 GOOD Y E S O & M records NIL 431 Depth of cover 100 HIGH Y E S GIS system NIL 415 Depth of cover 100 GOOD Y E S Archival records NIL 416 Depth of cover 0 N O N E \() N A NIL 407 Depth of cover 100 HIGH V ) NA NIL 417 Depth of cover 25 L O W \() N A NIL 432 Depth of cover 100 HIGH V ) NA NIL 419 Depth of cover 100 HIGH N O Archival records NIL 426 Depth of cover 0 N O N E \ \ N A NIL 420 Depth of cover 0 N O N E Y ES O & M records NIL 427 Depth of cover 0 V ) \ ' E \<> N A NIL 422 Depth of cover 0 GOOD N O N A NIL 434 Depth of cover 100 HIGH NO N A NIL 342 Depth of cover 0 N A Y ES Archival records NIL 408 Depth of cover 75 GOOD Y E S Oihei As-built dwg 423 Depth of cover 0 N A Y ES Archival records NIL 379 Depth of cover 0 L O W NO Archival records NIL 389 Depth of cover 100 GOOD N A Other NIL 21 Length of pipe segment containing the repair 0 N A Y E S GIS system NIL 42 Length of pipe segment containing the repair 100 HIGH N A N A N I L 55 Length of pipe segment containing the repair N A N A N A Available, not included in break report 56 Length of pipe segment containing the repair 100 M E D I U M N O NIL 72 Length of pipe segment containing the repair 0 GOOD . N A N A NIL 428 Length of pipe segment containing the repair 0 N A N A N A NIL 413 Length of pipe segment containing the repair N A N A N A NIL 100 Length of pipe segment containing the repair 100 HIGH NO N A NIL 103 Length of pipe segment containing the repair . 100 HIGH N A N A NIL 112 Length of pipe segment containing the repair 100 HIGH Y E S Archival records NIL 284 120 Length of pipe segment containing the repair 0 N O N E N O N A NIL 134 Length of pipe segment containing the repair 0 NONE Y E S GIS system NIL 418 Length of pipe segment containing the repair 75 GOOD Y E S O & M records NIL 227 Length of pipe segment containing the repair 0 N A Y E S O & M records Hansen IMS data 231 Length of pipe segment containing the repair 25 M E D I U M N O Other Sheet not set-up for tracking, but occasionally is recorded. 240 Length of pipe segment containing the repair 50 GOOD N O N A • NIL 249 Length of pipe segment containing the repair ' 0 N O N E Y E S GIS system NIL 260 Length of pipe segment containing the repair 50 GOOD N O NIL 401 Length of pipe segment containing the repair 100 GOOD Y E S GIS system entered automatically from database 283 Length of pipe segment containing the repair 25 GOOD N O N A NIL 284 Length of pipe segment containing the repair 100 GOOD N A N A NIL 295 Length of pipe segment containing the repair 25 HIGH N O N A NIL 301 Length of pipe segment containing the repair 0 N A Y E S N A NIL 424 Length of pipe segment containing the repair 100 HIGH N O N A NIL 433 Length of pipe segment containing the repair 25 GOOD N A GIS system NIL 332 Length of pipe segment containing the repair 0 N O N E Y E S GIS system NIL 435 Length of pipe segment containing the repair 75 GOOD NO N A NIL 400 Length of pipe segment containing the repair 100 HIGH N O N A • NIL 383 Length of pipe segment containing the repair 100 HIGH N A N A NIL 285 392 Length of pipe segment containing the repair 0 N O N E N O N A NIL 403 Length of pipe segment containing the repair 100 HIGH N O N A NIL 409 Length of pipe segment containing the repair 100 50 HIGH GOOD N A _ Y E S N A . NIL 10 Length of pipe segment containing the repair GIS system . NIL 48 Length of pipe segment containing the repair 100 high no N A NIL 404 Length of pipe segment containing the repair 100 GOOD N A N A NIL 411 Length of pipe segment containing the repair N A N A N A NIL 76 Length of pipe segment containing the repair 0 N A Yes Archival records NIL 414 Length of pipe segment containing the repair 100 HIGH Y E S O & M records NIL 141 Length of pipe segment containing the repair 0 N A Y E S GIS system NIL 405 Length of pipe segment containing the repair 100 HIGH N A N A NIL 402 Length of pipe segment containing the repair 0 HIGH Y E S O & M records NIL 430 Length of pipe segment containing the repair 100 HIGH Y E S O & M records NIL 431 Length of pipe segment containing the repair 0 N O N E Y E S GIS system NIL 415 Length of pipe segment containing the repair 0 100 N O N E _ HIGH N O N A NIL 416 Length of pipe segment containing the repair NO N A NIL 407 Length of pipe segment containing the repair 100 • HIGH NO N A NIL 417 Length of pipe segment containing the repair 50 L O W NO N A NIL 432 Length of pipe segment containing the repair 0 N A N O NIL 419 Length of pipe segment containing the repair 100 HIGH Y E S GIS system NIL 286 426 Length of pipe segment containing the repair 0 N O N E N O N A NIL 420 Length of pipe segment containing the repair 100 HIGH N O N A NIL 427 422 Length of pipe segment containing the repair 0 N O N E YES GIS system NIL Length of pipe segment containing the repair 50 M E D I U M NO N A NIL 434 Length of pipe segment containing • the repair 0 N A . YES GIS system NIL 342 Length of pipe segment containing the repair 0 N A Y E S GIS system NIL 408 Length of pipe segment containing the repair 25 HIGH N O Archival records NIL 423 Length of pipe segment containing the repair 0 N A N O N A NIL 379 Length of pipe segment containing the repair 0 N O N E Y E S Archival records NIL 389 Length of pipe segment containing the repair 0 N A N A N A NIL 21 Normal operating pressure 0 N A YES Other J.D.Edwards 42 Normal operating pressure N A N A N A NIL 55 Normal operating pressure N A N A N A Not Applicable 56 Normal operating pressure 0 N A Y E S O & M records NIL 72 Normal operating pressure 0 GOOD N A N A NIL 428 Normal operating pressure 0 N A N A N A NIL 413 Normal operating pressure 100 HIGH Y E S Archival records NIL 100 Normal operating pressure 0 HIGH N O N A NIL 103 Normal operating pressure 0 N A N A N A NIL 112 Normal operating pressure 0 N A Y E S Archival records NIL 120 Normal operating pressure Normal operating pressure 0 N O N E YES Other NIL 134 25 M E D I U M Y E S O & M records NIL 257 418 Normal operating pressure 0 NONE YES Other NIL 227 Normal operating pressure ;0 N A N \ N A NIL 231 Normal operating pressure 100 GOOD YES Other Hydrant records 240 Normal operating pressure 25 L O W Y E S Other hydraulic model .249 Normal operating pressure 0 N O N E Y E S O & M records NIL 260 Normal operating pressure 0 N A Y E S Other i Fire Dept. flow tests 401 Normal operating pressure 0 N A Y E S GIS system NIL 283 Normal operating pressure 0 GOOD Y E S O & M records NIL 284 Normal operating pressure 50 M E D I U M N A N A NIL ' 295 Normal operating pressure 0 HIGH Y E S Archival records NIL 301 Normal operating pressure 0 N A Y E S N A NIL 424 Normal operating pressure 0 HIGH N O N A NIL 433 Normal operating pressure 0 GOOD N A External NIL 332 Normal operating pressure 0 N O N E Y E S Other Entire distribution system has been electronically modelled 435 Normal operating pressure 75 GOOD YES • N A NIL 400 Normal operating pressure 0 N O N E NO- N A NIL 383 Normal operating pressure 0 NA N A N A NIL 392 Normal operating pressure 0 N O N E Y E S Other NIL 403 Normal operating pressure 25 M E D I U M Y E S GIS system NIL 409 Normal operating pressure - 0 HIGH Y E S O & M records NIL 10 Normal operating pressure 25 GOOD Y E S GIS system NIL 48 Normal operating pressure o _ ; high no N A NIL 404 Normal operating pressure 0 N O N E N A N A NIL 411 Normal operating pressure N A N A N A NIL 76 Normal operating pressure 0 N A • Yes Archival records NIL 255 414 Normal operating pressure 0 N A Y E S O & M records NIL 141 Normal operating pressure 100 HIGH Y E S O & M records NIL ' 405 Normal operating pressure 100 GOOD N A ' N A NIL 402 Normal operating pressure 0 HIGH Y E S O & M records NIL 430 Normal operating pressure 0 GOOD Y E S Other Hydraulic model 431 Normal operating pressure 100 HIGH Y E S GIS system NIL 415 Normal operating pressure 50 M E D I U M Y E S O & M records NIL 416 Normal operating pressure 0 N O N E Y E S Other Model 407 Normal operating pressure 0 HIGH N O N A NIL 417 Normal operating pressure 50 M E D I U M N O N A NIL 432 Normal operating pressure 0 N A Y E S Archival records NIL 419 Normal operating pressure 100 HIGH Y E S External NIL 426 Normal operating pressure 0 N O N E Y E S O & M records NIL 420 Normal operating pressure 0 N O N E Y E S O & M records NIL 427 Normal operating pressure 0 N O N E N O N A NIL 422 Normal operating pressure 0 GOOD Y E S Other NIL 434 Normal operating pressure 0 N A Y E S GIS system NIL 342 Normal operating pressure 0 N A YES GIS system NIL 408 Normal operating pressure 100 HIGH Y E S ' GIS system NIL 423 Normal operating pressure 0 N A Y E S O & M records NIL 379 Normal operating pressure 0 NONE Y E S Archival records NIL 389 Normal operating pressure 0 N A N A N A NIL 21 Pipe diameter 100 HIGH Y E S GIS system NIL 42 Pipe diameter 100 HIGH N A N A NIL 55 Pipe diameter 100 HIGH Y E S GIS system NIL 56 Pipe diameter 100 HIGH Y E S Other Cadastrals 72 Pipe diameter 50 GOOD N A N A NIL 428 Pipe diameter 100 HIGH N A N A NIL 289 413 Pipe diameter 100 HIGH Y E S Archival records NIL 100 Pipe diameter 100 HIGH Y E S Archival records NIL 103 Pipe diameter 100 HIGH N A \ \ NIL 112 Pipe diameter 100 HIGH Y E S Archival records NIL 120 Pipe diameter 100 HIGH Y E S GIS system NIL 134 Pipe diameter 100 HIGH Y E S GIS system NIL 418 Pipe diameter 100 HIGH Y E S GIS system NIL 227 Pipe diameter 75 HIGH Y E S O & M records Hansen IMS data, distribution sheets 231 Pipe diameter 100 HIGH Y E S GIS system Also available on record dwgs. 240 Pipe diameter 100 GOOD Y E S GIS system NIL 249 Pipe diameter 100 GOOD Y E S GIS system NIL 260 Pipe diameter 0 N A Y E S Archival records NIL 401 Pipe diameter 100 GOOD Y E S GIS system entered manually as a check against database 283 Pipe diameter 100 GOOD Y E S Archival records NIL 284 Pipe diameter 100 GOOD N A N A NIL 295 Pipe diameter 100 HIGH Y ES Archival records NIL 301 Pipe diameter 100 HIGH Y E S O & M records NIL 424 Pipe diameter 100 HIGH Y E S Archival records NIL 433 Pipe diameter 100 HIGH Y ES GIS system NIL 332 Pipe diameter 100 HIGH Y E S GIS system NIL 435 Pipe diameter 100 GOOD Y E S Archival records NIL 400 Pipe diameter 100 GOOD Y E S GIS system NIL 383 Pipe diameter 100 HIGH N A N A NIL 392 Pipe diameter 100 HIGH Y E S GIS system NIL 403 Pipe diameter 100 HIGH Y E S GIS system NIL 290 409 Pipe diameter 100 HIGH N A \ \ NIL 10 Pipe diameter 75 GOOD Y ES GIS system NIL 48 Pipe diameter 100 high no N A NIL 404 Pipe diameter . 100 GOOD Y E S GIS system NIL 411 Pipe diameter 100 N A . N A N A NIL 76 Pipe diameter 100 High . Y E S Archival records NIL 414 Pipe diameter 100 HIGH Y E S O & M records NIL 141 Pipe diameter 100 HIGH Y E S GIS system NIL 405 Pipe diameter 100 HIGH N A N A NIL 402 Pipe diameter 100 HIGH Y E S Archival records NIL 430 Pipe diameter 100 • HIGH Y E S O & M records NIL 431 Pipe diameter 100 HIGH Y E S GIS system NIL 415 Pipe diameter 100 GOOD Y E S Archival records NIL 416 Pipe diameter 100 . HIGH Y E S O & M records NIL 407 Pipe diameter 100 HIGH N O N A NIL 417 Pipe diameter 75 GOOD N O N A NIL . 432 Pipe diameter 100 HIGH Y E S Archival records NIL 419 Pipe diameter 100 HIGH Y E S GIS system NIL 426 Pipe diameter 100 HIGH Y E S GIS system NIL 420 Pipe diameter 100 HIGH Y E S O & M -records NIL 427 Pipe diameter 100 GOOD Y E S GIS system NIL 422 Pipe diameter 100 GOOD Y E S Archival records N I L 434 Pipe diameter 100 HIGH Y E S GIS system NIL 342 Pipe diameter 100 HIGH Y E S GIS system NIL Pipe diameter 100 HIGH Y ES GIS system NIL 423 Pipe diameter 100 HIGH Y E S GIS system NIL 379 Pipe diameter 100 HIGH Y E S Archival records NIL 389 Pipe diameter 100 HIGH N A Archival records NIL 21 Pipe fracture toughness 0 N A N O N A NIL 291 42 Pipe fracture toughness N A N A N A NIL 55 Pipe fracture toughness 0 N A N A N A NIL 56 Pipe fracture ' toughness 0 N A N A N A NIL 72 Pipe fracture toughness 0 GOOD N A • N A NIL 428 Pipe fracture toughness 0 N A N A N A NIL 413 Pipe fracture toughness N A N A N A NIL 100 Pipe fracture toughness 0 GOOD N O N A NIL 103 Pipe fracture toughness 0 N A N A • N A NIL 112 Pipe fracture toughness 0 N A N A N A NIL 120 Pipe fracture toughness 0 N O N E N O N A NIL 134 Pipe fracture toughness 0 N O N E 1 NO N A NIL I Pipe fracture 418 i toughness 0 N O N E | Y E S External f NIL 227 Pipe fracture toughness 0 N A \ N A N A NIL 231 Pipe fracture toughness 0 N O N E N O N A NIL 240 Pipe fracture toughness 0 N O N E NO N A NIL 249 Pipe fracture toughness 0 N O N E ' N O N A N I L 260 401 Pipe fracture toughness 0 N A N A N A NIL Pipe fracture toughness 0 N A N O N A N A NIL _____ NIL 283 Pipe fracture toughness 0 GOOD NO 284 Pipe fracture toughness 0 N O N E N A N A NIL 295 Pipe fracture toughness Pipe fracture toughness 0 HIGH ! NO N A NIL 301 0 N A 1 N A N A NIL 424 Pipe fracture toughness i 0 " HIGH N O N A NIL 433 332 Pipe fracture toughness 0 M E D I U M N A N A NIL Pipe fracture toughness N A N A N A NIL 435 Pipe fracture toughness 50 GOOD N O N A NIL 292 400 Pipe fracture toughness 0 N O N E N O ' N A NIL 383 Pipe fracture toughness 0 N A N A N A NIL 392 Pipe fracture toughness 0 N O N E NO N A NIL 403 Pipe fracture toughness 0 N A N A N A NIL 409 Pipe fracture toughness 0 N A N A N A NIL 10 Pipe fracture toughness 50 GOOD Y E S GIS system NIL 48 Pipe fracture toughness 0 Jljgh no N A NIL 404 Pipe fracture toughness 0 N O N E N A N A NIL 411 Pipe fracture toughness N A N A J N A NIL 76 Pipe fracture toughness 0 N A No . Other NIL 414 Pipe fracture toughness 0 N A Y E S Archival records NIL 141 Pipe fracture toughness 0 N A NO N A NIL 405 Pipe fracture toughness 100 HIGH N A N A NIL 402 Pipe fracture toughness 0 HIGH Y E S Other NIL 430 Pipe fracture toughness 0 GOOD N O N A NIL 431 Pipe fracture toughness 0 L O W N O N A NIL ' 415 Pipe fracture toughness 0 N O N E N O N A ^ NIL 416 Pipe fracture toughness 0 N O N E Y E S External NIL 407 Pipe fracture toughness 0 HIGH N O N A NIL 417 Pipe fracture toughness 0 N O N E NO N A NIL • 432 Pipe fracture toughness 0 N A NO N A NIL 419 Pipe fracture toughness 50 M E D I U M N O N A NIL 426 Pipe fracture toughness 0 N O N E N A N A NIL 420 Pipe fracture toughness 0 N O N E N O N A NIL 427 Pipe fracture toughness 0 N O N E NO N A NIL 422 Pipe fracture toughness 0 GOOD N O N A NIL 293 434 Pipe fracture toughness 0 N A NO N A NIL 342 Pipe fracture toughness 0 N A N O N A NIL 40'8 Pipe fracture toughness N A N A N A NIL 423 Pipe fracture toughness 0 N A N A N A NIL 379 Pipe fracture toughness 0 . N O N E N O N A NIL 389 Pipe fracture toughness 0 N A N A N A NIL 21 _ Pipe material 100 HIGH Y E S GIS system NIL 42 Pipe material 100 GOOD N A N A NIL 55 Pipe material 100 HIGH Y E S GIS system NIL 56 Pipe material 100 HIGH Y E S Other NIL 72 Pipe material 50 GOOD N A N A NIL _ 4 2 8 Pipe material 100 HIGH N A N A NIL 413 Pipe material 100 HIGH Y E S Archival records NIL 100 Pipe material 100 HIGH Y ES Archival records NIL 103 Pipe material 100 HIGH N A N A NIL 112 Pipe material 100 HIGH Y E S Archival records NIL 120 Pipe material 100 HIGH Y E S GIS system NIL 134 Pipe material 100 HIGH Y E S O & M records NIL 418 Pipe material 100 HIGH Y E S GIS system NIL 227 Pipe material 100 HIGH Y ES O & M records Hansen IMS data, distribution sheets 231 Pipe material • 100 HIGH Y E S GIS system Record book of main materials 240 Pipe material 100 GOOD Y ES GIS system NIL 249 Pipe material 100 GOOD Y E S GIS system NIL 260 Pipe material 50 GOOD Y E S Archival records NIL 401 Pipe material 100 GOOD Y E S GIS system entered manually as a check against database 283 Pipe material 100 GOOD Y E S Archival records NIL 294 284 1 Pipe material 100 GOOD N A N A NIL 295 Pipe material 100 HIGH Y ES Archival records NIL 301 Pipe material 100 HIGH Y E S Archival records NIL 424 Pipe material 100 ! HIGH Y E S Archival records NIL 433 Pipe material 100 ! HIGH N A GIS system NIL 332 Pipe material 100 GOOD Y E S GIS system NIL 435 Pipe material 100 GOOD Y E S Archival records NIL 400 Pipe material 100 HIGH Y E S GIS system NIL 383 Pipe material 100 HIGH N A N A NIL 392 Pipe material 100 HIGH Y E S GIS system NIL 403 Pipe material 100 1 HIGH Y E S GIS system NIL 409 Pipe material 100 1 HIGH N A N A NIL 10 Pipe material 100 ! GOOD Y E S GIS system NIL 48 Pipe material 50 high no N A NIL 404 Pipe material 100 1 GOOD Y E S GIS system NIL 411 Pipe material 100 1 N A N A N A NIL 76 Pipe material -100 ! High Yes Archival records NIL 414 Pipe material 100 I HIGH • Y E S O & M ' records NIL 141 Pipe material 100 ! HIGH N O N A NIL 405 Pipe material 100 ! HIGH N A N A NIL 402 Pipe material 100 1 HIGH Y E S Archival records NIL 430 Pipe material 100 HIGH Y E S O & M records NIL 431 Pipe material 100 HIGH Y E S GIS system NIL 415 Pipe material 100 GOOD Y E S Archival records NIL 416 Pipe material 100 HIGH Y ES O & M records NIL 407 Pipe material 100 ! HIGH N O N A NIL 417 Pipe material 75 1 GOOD N O N A NIL 432 Pipe material 100 HIGH Y E S O & M records NIL 419 Pipe material 100 HIGH Y E S GIS system NIL 426 Pipe material 100 HIGH Y E S GIS system NIL 295 420 Pipe material 100 HIGH Y E S O & M records NIL 427 Pipe material 100 GOOD Y E S GIS system NIL 422 Pipe material 100 GOOD Y E S Archival records NIL 434 Pipe material 100 HIGH Y E S GIS system NIL 342 Pipe material 100 HIGH Y ES Archival records NIL 408 Pipe material 100 HIGH Y ES Archival records NIL 423 Pipe material 100 HIGH Y E S GIS system NIL 379 Pipe material 0 N O N E Y E S Archival records NIL 389 Pipe material 100 HIGH N A Other NIL 21 Pipe modulus or rupture 0 N A N O N A . NIL 42 Pipe modulus or rupture N A N A N A NIL 55 Pipe modulus or rupture 100 HIGH Yes Other NIL 56 Pipe modulus or rupture 100 HIGH N A N A NIL 72 Pipe modulus or rupture 0 GOOD N A N A NIL 428 Pipe modulus or rupture 0 N A N A N A NIL 413 Pipe modulus or rupture N A N A N A NIL 100 Pipe modulus or rupture 0 GOOD N O N A NIL 103 Pipe modulus or rupture 100 HIGH N A N A NIL 112 Pipe modulus or ; rupture 100 HIGH N A N A NIL 120 Pipe modulus or rupture 0 N O N E NO N A NIL 134 Pipe modulus or rupture 0 N O N E N O N A NIL 418 Pipe modulus or rupture 0 N O N E Y E S External NIL 227 Pipe modulus or , rupture 0 N A •NA N A NIL 231 Pipe modulus or rupture 0 N O N E N O N A NIL 240 Pipe modulus or rupture 0 N O N E N O N A NIL 249 Pipe modulus or rupture 0 N O N E N O N A NIL 260 Pipe modulus or rupture 0 N A N A N A NIL 296 401 Pipe modulus or rupture 0 N A N O N A NIL 283 Pipe modulus or rupture 0 GOOD N O N A NIL 284 Pipe modulus or rupture 0 N O N E N A N A NIL 295 Pipe modulus or rupture 0 HIGH N O N A NIL 301 Pipe modulus or rupture 100 GOOD N O N A NIL 424 Pipe modulus or rupture 0 HIGH NO N A NIL 433 Pipe modulus or rupture 0 M E D I U M N A N A NIL 332 Pipe modulus or rupture 0 N O N E N A N A Has been recorded in past, but is no longer tracked 435-Pipe modulus or rupture 50 M E D I U M N O N A . NIL 400 Pipe modulus or rupture 0 N O N E N O N A NIL 383 Pipe modulus or rupture 100 HIGH - N A N A NIL 392 Pipe modulus or rupture 0 N O N E N O N A NIL 403 Pipe modulus or rupture 0 N A N A N A ' NIL 409 Pipe modulus or rupture 0 N A N A N A NIL 10 Pipe modulus or rupture 50 GOOD Y E S GIS system NIL 48 Pipe modulus or rupture 0 ...high no N A NIL V 404 Pipe modulus or rupture 0 N O N E N A N A NIL 411 Pipe modulus or rupture N A N A N A NIL "f> Pipe modulus or rupture 0 N A No Other NIL 414 Pipe modulus or rupture 0 N A N O O & M records NIL 141 Pipe modulus or rupture 0 N A Y E S GIS system NIL 405 Pipe modulus or rupture 100 HIGH N A N A NIL 402 Pipe modulus or rupture 0 HIGH N O Other NIL 430 Pipe modulus or rupture 0 GOOD N O N A NIL 431 Pipe modulus or rupture 100 HIGH N O N A NIL 297 415 Pipe modulus or rupture 100 GOOD NO N A NIL 416 Pipe modulus or rupture 0 N O N E Y E S External NIL 407 Pipe modulus or rupture 100 HIGH N O N A NIL 417 Pipe modulus or rupture 0 N O N E N O N A NIL 432 Pipe modulus or rupture 0 N A N O N A NIL 419 Pipe modulus or rupture 50 M E D I U M N O . N A NIL 426 Pipe modulus or rupture 0 N O N E N A N A NIL 420 Pipe modulus or rupture 0 N O N E N O N A NIL. 427 Pipe modulus or rupture 0 N O N E N O N A NIL 422 Pipe modulus or rupture 0 GOOD N O N A • NIL . 434 Pipe modulus or rupture 0 N A N O N A NIL 342 Pipe modulus or rupture 0 N A N O N A NIL 408 Pipe modulus or rupture N A N A N A NIL 423 Pipe modulus or rupture 0 N A N A N A NIL 379 Pipe modulus or rupture 100 HIGH N O N A NIL 389 Pipe modulus or rupture 0 N A N A N A NIL 21 Pipe protection ( wrapped / anodes) 100 HIGH Y ES Archival records NIL 42 Pipe protection ( wrapped / anodes) N A N A N A NIL 55 Pipe protection ( wrapped / anodes) 100 HIGH Y E S Other Another Database 56 Pipe protection ( wrapped / anodes) 25 GOOD Y E S Archival records NIL 72 Pipe protection ( wrapped / anodes) 0 GOOD N A N A NIL 428 Pipe protection ( wrapped / anodes) 0 N A N A N A NIL 413 Pipe protection ( wrapped / anodes) -N A N A N A NIL 298 100 Pipe protection ( wrapped / anodes) 100 HIGH Y E S Archival records NIL 103 Pipe protection ( wrapped / anodes) 0 N A N A N A NIL 112 Pipe protection ( wrapped / anodes) 0 N A N A N A NIL 120 Pipe protection ( wrapped / anodes) 0 N O N E Y E S GIS system NIL 134 Pipe protection ( wrapped / anodes) 100 HIGH N O N A NIL 418 Pipe protection ( wrapped / anodes) ) N O N E N O N A NIL 227 Pipe protection ( wrapped / anodes) 100 HIGH Y E S O & M records Hansen IMS data 231 Pipe protection ( wrapped / anodes) 0 N O N E N A Other sometimes recorded. 240 Pipe protection ( wrapped / anodes) 25 L O W N O N A NIL , 249 Pipe protection ( wrapped / anodes) 0 N O N E Y E S N A as built drawings 260 Pipe protection ( wrapped / anodes) 0 N A Y E S Archival records NIL 401 Pipe protection ( wrapped / anodes) 0 N A Y E S Archival records NIL 283 Pipe protection ( wrapped / anodes) 0 GOOD Y E S Archival records Sometimes 284 Pipe protection ( wrapped / anodes) 50 M E D I U M N A N A NIL 295 Pipe protection ( wrapped / anodes) 25 HIGH N O N A NIL 301 Pipe protection ( wrapped / anodes) 100 HIGH l.s N A NIL 424 Pipe protection ( wrapped / anodes) 100 HIGH Y ES Archival records NIL 299 433 Pipe protection ( wrapped / anodes) 0 GOOD N A GIS system NIL 332 Pipe protection ( wrapped / anodes) 75 M E D I U M N O N A • • NIL 435 Pipe protection ( wrapped / anodes) 75 GOOD Y E S N A NIL 400 Pipe protection ( wrapped / anodes) 0 N O N E Y E S O & M records NIL 383 Pipe protection ( wrapped / anodes) 0 N A N A N A NIL 392 Pipe protection ( wrapped / anodes) 0 N O N E Y E S GIS system NIL 403 Pipe protection ( wrapped / anodes) 0 N O N E Y E S GIS system NIL 409 Pipe protection ( wrapped / anodes) 100 HIGH N A N A NIL 10 Pipe protection ( wrapped / anodes) 0 N A N A N A NIL 48 Pipe protection ( wrapped / anodes) 0 high no N A NIL 404 Pipe protection ( wrapped / anodes) 0 N O N E N A N A NIL 411 Pipe protection ( wrapped / anodes) N A N A N A NIL 76 Pipe protection ( wrapped / anodes) 0 N A Yes Archival records NIL 414 Pipe protection ( wrapped / anodes) 100 HIGH Y E S O & M records NIL 141 Pipe protection ( wrapped / anodes) 0 N A N O N A NIL 405 Pipe protection ( wrapped / anodes) 0 N O N E N A N A NIL 402 Pipe protection ( wrapped / anodes) 100 HIGH Y E S Archival records NIL 300 430 Pipe protection ( •wrapped / anodes) 50 GOOD NO N A NIL 431 Pipe protection ( wrapped / anodes) 100 HIGH Y E S GIS system NIL 415 Pipe protection ( wrapped / anodes) 100 M E D I U M N O N A NIL 416 Pipe protection ( wrapped / anodes) 0 N O N E N O N A NIL 407 Pipe protection ( wrapped / anodes) . 0 HIGH N O N A NIL 417 Pipe protection ( wrapped / anodes) 0 N O N E N O N A NIL 432 Pipe protection ( wrapped / anodes) 0 N A N O N A NIL 419 Pipe protection ( wrapped / anodes) 100 HIGH Y E S GIS system NIL 426 Pipe protection ( wrapped / anodes) 0 N O N E N A N A NIL 420 Pipe protection ( wrapped / anodes) 100 HIGH Y E S O & M records NIL 427 Pipe protection ( wrapped / anodes) 0 N O N E Y E S O & M records Technical Specs 422 Pipe protection ( wrapped / anodes) 0 GOOD N O N A NIL 434 Pipe protection ( wrapped / anodes) 50 HIGH Y E S GIS system NIL 342 Pipe protection ( wrapped / anodes) 0 N A Y E S Archival records NIL 408 Pipe protection ( wrapped / anodes) 0 N O N E NO N A NIL 423 Pipe protection ( wrapped / anodes) 0 N A Y E S Archival records NIL 379 Pipe protection ( wrapped / anodes) 0 L O W Y E S Archival records NIL 301 389 Pipe protection ( wrapped / anodes) N A N A N A NIL 21 Pipe sample collected 0 N A Y E S Other coupons from main tappings 42 Pipe sample collected 50 HIGH N A N A NIL 55 Pipe sample collected 0 N A N A N A NIL 56 Pipe sample collected 25 LOW- N O N A NIL 72 Pipe sample collected 0 GOOD N A N A NIL 428 Pipe sample collected 100 HIGH N A N A NIL 413 Pipe sample collected N A N A N A • NIL 100 Pipe sample collected 25 GOOD N O N A NIL 103 Pipe sample collected 100 HIGH N A N A NIL 1 12 Pipe sample collected 25 HIGH N A • N A NIL ! Pipe sample" 120 collected 0 N O N E N O N A NIL 134 Pipe sample collected 25 0 M E D I U M N O N A NIL 418 Pipe sample collected N O N E N O N A NIL ' 227 Pipe sample collected 0 N A N A N A NIL 231 Pipe sample collected 0 N O N E N O N A NIL 240 Pipe sample collected 25 LOW- NO N A NIL 249 Pipe sample collected 0 N O N E NO Archival records NIL 260 Pipe sample collected 0 N A N A N A NIL 401 Pipe sample collected 0 N A N O N A NIL 283 Pipe sample collected 25 GOOD N O N A NIL 284 Pipe sample collected 25 LOW N A N A NIL 295 Pipe sample collected 25 HIGH N O N A NIL 301 Pipe sample collected 25 M E D I U M N O N A NIL 424 Pipe sample collected 0 HIGH N O N A NIL 302 433 Pipe sample collected 0 GOOD N A N A NIL 332 Pipe sample collected 0 NONE N A N A NIL 435 Pipe sample collected 25 GOOD NO NA NIL 400 Pipe sample collected 0 N O N E N O N A NIL 383 Pipe sample collected 75 GOOD N A N A . NIL 392 Pipe sample collected 0 N O N E NO N A NIL 403 Pipe sample collected 100 ' HIGH N A N A NIL 409 Pipe sample collected 25 M E D I U M N A N A NIL 10 Pipe sample collected 0 N A N A N A NIL 48 Pipe sample collected 0 high no N A NIL 404 Pipe sample collected 50 GOOD Y E S Archival records NIL 411 Pipe sample collected N A N A N A NIL 76 Pipe sample collected 0 N A No Other NIL 414 Pipe sample collected 0 N A N O " o & M records NIL , 141 Pipe sample collected 0 N A N O N A NIL 405 Pipe sample collected 100 HIGH N A N A NIL 402 Pipe sample collected 0 HIGH N O Other NIL 430 Pipe sample collected 0 GOOD N O N A NIL 431 Pipe sample collected 25 GOOD Y E S O & M records NIL 415 Pipe sample collected 0 NONE Y ES Archival records NIL 416 Pipe sample collected , 0 NONE NO N A NIL 407 Pipe sample collected 100 HIGH NO N A NIL 417 Pipe sample collected - 0 N O N E N O N A NIL 432 Pipe sample collected 0 N A N O N A NIL 419 Pipe sample collected 0 L O W N O N A NIL 426 Pipe sample collected 0 N O N E N A N A NIL 303 420 Pipe sample collected 0 N O N E NO N A NIL 427 Pipe sample collected 0 N O N E N O N A NIL 422 Pipe sample collected 0 GOOD NO N A NIL 434 Pipe sample collected 0 N A N A N A NIL 342 Pipe sample collected 25 GOOD N O N A NIL 408 Pipe sample collected N A N A N A NIL 423 Pipe sample collected 25 N A N O N A NIL 379 Pipe sample collected 0 L O W N O Other NIL 389 Pipe sample collected 0 N A N A N A NIL 21 Pipe wall thickness / classification 0 N A N O N A . NIL 42 Pipe wall thickness / classification N A N A N A NIL 55 Pipe wall thickness / classification 0 N A N A N A NIL 56 Pipe wall thickness / classification 0 N A Y E S Archival records NIL 72 Pipe wall thickness / classification. 0 GOOD N A N A NIL 428 Pipe wall thickness / classification 0 N A N A N A NIL 413 Pipe wall thickness / classification HIGH N O N A . NIL 100 Pipe wall thickness / classification 100 HIGH N O • N A . NIL 103 Pipe wall thickness / classification 0 N A N A N A NIL 112 Pipe wall thickness / classification 0 N A N A N A NIL 120 Pipe wall thickness / classification 0 N O N E Y E S Archival records NIL 304 134 Pipe wall thickness / classification 0 N O N E N O N A NIL 418 Pipe wall thickness / classification 0 N O N E Y E S External NIL 227 Pipe wall thickness / classification 0 N A N A N A NIL 231 Pipe wall thickness / classification 0 N O N E N O N A We do nt record pipe wall thickness during repair. 240 Pipe wall thickness / classification 0 L O W Y E S External NIL 249 Pipe wall thickness / classification 0 N O N E N O N A NIL 260 Pipe wall thickness / classification 0 N A Y E S Archival records NIL 401 Pipe wall thickness / classification 0 N A Y E S Archival records NIL 283 Pipe wall thickness / classification 0 GOOD N O N A NIL 284 Pipe wall thickness / classification 0 N O N E N A N A NIL 295 Pipe wall thickness / classification 0 HIGH N O N A NIL 301 Pipe wall thickness / classification 0 N A N O N A NIL 424 Pipe wall thickness / classification HIGH Y E S Archival records NIL 433 Pipe wall thickness / classification 0 GOOD N A N A NIL 332 Pipe wall thickness / classification 0 N O N E Y E S Archival records NIL 435 Pipe wall thickness / classification 50 GOOD N O N A NIL 400 Pipe wall thickness / classification N O N E N O N A NIL 305 383 Pipe wall thickness / classification N A N A N A NIL 392 Pipe wall thickness / classification 0 N O N E N O N A NIL 403 Pipe wall thickness / classification 25 HIGH Y E S External NIL 409 Pipe wall thickness / classification M E D I U M Y E S O & M records NIL 10 Pipe wall thickness / classification 0 N A N A N A NIL 48 Pipe wall thickness / classification high no N A NIL 404 Pipe wall thickness / classification 25 M E D I U M YES Archival records NIL 411 Pipe wall thickness / classification N A N A N A NIL 76 Pipe wall thickness / classification 0 N A Yes Archival records NIL 414 Pipe wall thickness / classification 50 M E D I U M Y E S Archival records NIL 141 Pipe wall thickness / classification 0 N A N O N A NIL 405 Pipe wall thickness / classification 25 M E D I U M N A N A NIL 402 Pipe wall thickness / classification 0 HIGH N O Archival records NIL 430 Pipe wall thickness / classification 0 GOOD NO N A NIL 431 Pipe wall thickness / classification 100 HIGH Y E S GIS system NIL 415 Pipe wall thickness / classification 0 N O N E N O N A NIL 416 Pipe wall thickness / classification 0 N O N E Y E S O & M records NIL 306 407 Pipe wall thickness / classification 100 HIGH NO NA NIL 417 Pipe wall thickness / classification NONE NO NA NIL 432 Pipe wall thickness / classification 0 NA NO NA NIL 419 Pipe wall thickness / classification 100 HIGH YES GIS system NIL 426 Pipe wall thickness / classification 0 NONE NO NA NIL 420 Pipe wall thickness / classification NONE YES O&M records NIL 427 Pipe wall thickness / classification 0 NONE YES r O&M records Technical Specs 422 V Pipe wall thickness / classification 0 GOOD YES Archival records NIL 434 Pipe wall thickness / classification 0 NA YES GIS system NIL 342 Pipe wall thickness / classification 0 NA YES Archival records NIL 408 Pipe wall thickness / classification 0 . NONE NO NA NA 423 Pipe wall thickness / classification 0 NA NO NA NIL 379 Pipe wall thickness / classification 0 NONE YES Archival records NIL 389 Pipe wall thickness / classification 0 NA •NA NA NIL 21 Surface material 100 HIGH YES NA NIL 42 Surface material NA NA NA ' NIL 55 Surface material 100 HIGH YES Other NIL 56 Surface material 100 HIGH NO NA NIL 72 Surface material 50 GOOD NA NA NIL 428 Surface material 0 NA NA NA NIL 413 Surface material NA NA NA NIL 100 Surface material 100 HIGH NA N A NIL 103 Surface material 100 HIGH NA NA NIL 112 Surface material 100 HIGH YES Archival records NIL 307 120 Surface material 0 N O N E Y ES Other NIL 134 Surface material 100 ' HIGH Y E S Archival records NIL 418 Surface material 0 N O N E Y ES GIS system NIL 227 Surface material 100 GOOD Y E S O & M records Hansen WO data 231 Surface material 100 GOOD NO' Other surface recorded on break sheet. 240 Surface material 100 GOOD Y E S Other pavement management system 249 Surface material 100 GOOD Y ES N A as built drawings 260 Surface material 50 GOOD N A N A NIL 401 Surface material 0 N A NO N A NIL 283 Surface material 0 GOOD Y ES GIS system NIL 284 Surface material 50 M l 1)11 \1 N A N A NIL 295 Surface material 0 HIGH NO N A NIL 301 _ Surface material 100 HIGH Y ES N A NIL 424 Surface material 100 HIGH Y E S Archival records NIL 433 Surface material 100 GOOD N A GIS system NIL 332__ Surface material 75 GOOD Y E S GIS system NIL 435 Surface material 75 GOOD ^ LS N A NIL 400 Surface material 75 GOOD YES GIS system NIL 383 Surface material 0 N A Y \ N A NIL 392 Surface material 0 N O N E Y E S GIS system NIL 403 Surface material 100 HIGH N O N A • NIL 409 Surface material 100 HIGH N A N A NIL 10 Surface material 100 GOOD Y ES GIS system NIL 48 Surface material 0 high no N A NIL 404 Surface material 50 GOOD Y E S GIS system NIL 411 Surface material N A S A N A NIL 76 Surface material 50 Low Yes Archival records NIL 414 Surface material 0 N A Y E S N A NIL 141 Surface material 100 HIGH NO N A NIL 4HS Surface material 100 HIGH N A N A NIL 402 Surface material 0 HIGH Y ES Archival records NIL 430 Surface material 0 M E D I U M S O N A NIL 431 Surface material 100 ' HIGH Y E S GIS system NIL 308 415 Surface material 0 N O N E Y E S Archival records NIL 416 Surface material 0 N O N E N O N A NIL 407 Surface material 100 HIGH N O N A NIL 417 Surface material 0 N O N E N O N A NIL 432 Surface material 100 HIGH N O N A NIL 419 Surface material 100 HIGH N O GIS system NIL 426 Surface material 0 N O N E N A N A NIL 420 Surface material 75 GOOD Y E S O & M records NIL 427 Surface material 0 N O N E Y E S Other NIL 422 Surface material 0 GOOD N O N A NIL 434 Surface material 0 N A Y E S GIS system NIL 342 Surfacematerial 0 N A Y E S GIS system NIL 408 423 Surface material 0 ! N O N E Y E S Other As-built dwg Surface material 100 ! GOOD Y E S GIS system NIL 379 Surface material 50 M E D I U M N O Other NIL 389 Surface material 100 HIGH N A Other NIL 21 Traffic classification or type of road useage 0 N A Y E S N A NIL 42 Traffic classification or type ofroad useage r N A N A N A NIL 55 Traffic classification or type of road useage N A N A N A Not Applicable 56 Traffic classification or type of road useage 0 N A N A N A NIL 72 Traffic classification or type of road useage 0 GOOD N A N A NIL 428 Traffic classification or type of road useage 0 N A N A N A NIL 413 Traffic classification or type of road useage N A N A N A NIL 100 Traffic classification or type of road useage 0 GOOD N O N A NIL 103 Traffic classification or type of road useage 0 N A N A N A NIL 112 Traffic classification or type ofroad useage 0 N O N E Y E S Archival records NIL 120 Traffic classification or type of road useage 0 N O N E Y E S External NIL 309 134 Traffic classification or type of road useage 0 N O N E Y ES GIS system NIL 418 Traffic classification or type of road useage 0 N O N E Y E S Other NIL 227 Traffic classification or type of road useage 0 N A 1 N A N A NIL 231 Traffic classification or type of road useage 0 N O N E 1 N O N A NIL 240 Traffic classification or type of road useage 0 L O W ! NO N A NIL 249 Traffic classification or type of road useage 0 N O N E nO N A NIL 260 Traffic classification or type ofroad useage 0 N A Y E S Archival records NIL 401 Traffic classification or type of road useage 0 N A Y E S GIS system NIL 283 Traffic classification or type of road useage 0 GOOD Y E S GIS system NIL 284 Traffic classification or type of road useage 0 N O N E N A N A NIL 295 Traffic classification or type of road useage 0 HIGH N O N A NIL 301 Traffic classification or type of road useage 100 GOOD Y E S N A NIL 424 Traffic classification or type of road useage 0 HIGH Y E S Archival records NIL 433 Traffic classification or type of road useage 25 M E D I U M N A GIS system NIL 332 Traffic classification or type of road useage 0 N O N E Y E S GIS system NIL 435 Traffic classification or type of road useage 25 GOOD Y E S N A NIL 400 383 Traffic classification or type of road useage 0 N O N E N O N A NIL Traffic classification or type of road useage 0 N A N A N A NIL 392 Traffic classification or type of road useage 0 N O N E Y E S GIS system NIL 310 403 Traffic classification or type of road useage 50 GOOD N O N A NIL 409 Traffic classification or type of road useage 100 HIGH N A N A NIL 10 Traffic classification or type of road useage 0 N A N A N A NIL 48 Traffic classification or type of road useage 0_ high no N A NIL 404 Traffic classification or type of road useage 25 M E D I U M Y E S O & M records NIL 411 Traffic classification or type of road useage N A N A N A NIL 76 Traffic classification or type of road useage 0 N A Yes Archival records NIL 414 Traffic classification or type of road useage 0 N A Y E S N A NIL 141 Traffic classification or type of road useage 0 N A Y E S External NIL 405 Traffic classification or type of road useage 0 N O N E N A N A NIL 402 Traffic classification or type of road useage 0 HIGH Y E S Other NIL 430 Traffic classification or type of road useage 0 GOOD NO N A NIL 431 Traffic classification or type of road useage 0 LOW- Y E S GIS system NIL 415 Traffic classification or type of road useage 0 N O N E Y E S Archival records NIL 416 Traffic classification or type of road useage 0 N O N E Y E S GIS system NIL 407 Traffic classification or type of road useage _ 0 HIGH N O N A NIL 417 Traffic classification or type of road useage 0 N O N E NO N A - NIL 311 432 Traffic classification or type of road useage 0 N A Y E S GIS system NIL 419 Traffic classification or type of road useage 50 M E D I U M N O N A NIL 426 Traffic classification or type of road useage 0 N O N E N A N A NIL 420 Traffic classification or type of road useage 0 N O N E Y E S O & M records NIL 427 Traffic classification or type of road useage 0 N O N E Y E S GIS system NIL - 422 Traffic classification or type of road useage 0 GOOD N O N A NIL 434 Traffic classification or type of road useage 0 N A Y E S GIS system NIL 342 Traffic classification or type of road useage 0 N A Y E S GIS system NIL 408 Traffic classification or type of road useage 75 GOOD Y E S Other Traffic 423 Traffic classification or type of road useage 0 N A N A N A ' NIL 379 Traffic classification or type of road useage 0 NONE N O Other NIL 389 Traffic classification or type of road useage 0 N A N A N A NIL 21 Type of joint 50 GOOD NO N A NIL 42 Type of joint \ \ N A N A NIL " Type of joint 0 \ \ NIL 56 Type of joint 75 HIGH NO N A NIL 72 Type of joint 50 GOOD N A N A NIL 428 Type of joint 0 N A N A N A NIL 413 Type of joint 100 HIGH N O N A NIL 100 Type of joint 100 HIGH Y E S Archival records NIL H i3 Type of joint 100 HIGH N A N A NIL 112 Type of joint 0 N A N A N A NIL 120 Type of joint 0 NONE Y E S Archival records NIL 134 Type of joint 100 HIGH N O N A NIL 418 Type of joint 0 N O N E Y E S Archival records NIL 312 227 Type of joint 50 GOOD Y E S O & M records NIL 231 Type of joint 50 M E D I U M N A N A NIL 240 Type of joint 25 M E D I U M N O N A NIL 249 Type of joint 100 GOOD Y E S O & M records as built drawings 260 Type of joint 0 N A N A N A NIL 401 Type of joint 0 N A Y E S Archival records NIL 283 Type of joint 0 GOOD N O N A NIL 284 Type of joint 50 M E D I U M N A N A NIL 295 Type of joint 25 HIGH NO N A NIL 301 Type of joint ' 100 HIGH NO N A NIL 424 Type of joint 50 HIGH YES Archival records NIL 433 Type of joint 75 GOOD N A GIS system NIL 332 Type of joint 50 M E D I U M YES GIS system NIL 435 Type of joint 50 GOOD NO N A NIL 400 Type of joint 50 GOOD Y E S Archival records NIL 383 Type of joint 100 HIGH • N A N A 300 392 Type of joint 50 M E D I U M N O N \ NIL 403 Type of joint 100 HIGH Y E S GIS system NIL 409 Type of joint 100 HIGH N A N A NIL 10 Type of joint 0 N A N A N A NIL 48 Type of joint 0 high no N A NIL 404 Type of joint 0 N O N E N A N A NIL 411 Type of joint N A N A N A NIL 76 Type of joint 50 Good Yes Archival records NIL 414 Type of joint 100 HIGH YES O & M records NIL 141 Type of joint 0 • N A ' N O N A NIL 405 Type of joint 0 N O N E N A N A NIL 402 Type of joint 100 HIGH Y E S Archival records NIL 430 Type of joint 0 M E D I U M N O N A NIL 431 Type of joint 100 HIGH Y E S GIS system NIL 415 Type of joint 100 GOOD Y E S -Archival records NIL 416 Type of joint 0 N O N E Y E S O & M records NIL 407 Type of joint 100 HIGH N O N A NIL 417 Type of joint 0 N O N E N O N A NIL 432 Type of joint 0 N A NO N A NIL 419 Type of joint 100 HIGH Y E S GIS system NIL 426 Type of joint 0 N O N E N A N A NIL 313 420 Type of joint 50 M E D I U M Y E S O & M records 427 Type of joint 0 N O N E YES GIS system NIL 422 Type of joint 0 GOOD NO N A NIL 434 Type of joint 25 HIGH Y E S GIS system NIL 342 Type of joint 0 N A Y E S Archival records NIL 408 Type of joint 75 GOOD N O Archival records NIL 423 Type of joint 0 N A Y E S Archival records NIL 379 Type of joint 0 L O W Y E S 314 NIL 389 Type of joint 100 HIGH N A Other NIL 21 Type of pipe lining 0 N A N O N A NIL 42 Type of pipe lining _NA_ N A N A NIL 55 Type of pipe lining N A N A N A Not Applicable 56 Type of pipe lining 25 GOOD Y E S Archival records NIL 72 Type of pipelining 0 GOOD N A N A NIL 428 Type of pipe lining 0 N A N A N A NIL 413 Type of pipe lining N A N A N A NIL 100 Type of pipe lining 0 HIGH N O N A NIL 103 Type of pipe lining 0 N A N A N A NIL 112 Type of pipe lining 0 N A N A N A NIL 120 Type of pipe lining 0 N O N E Y E S Archival records NIL . 134 Type of pipe lining 0 N O N E N O N A NIL 418 Type of pipe lining 0 N O N E Y E S External NIL 227 Type of pipe lining 0 N A N A N A NIL 231 Type of pipe lining .25 M E D I U M N A Other Sometimes recorded, sometimes not. 240 Type of pipe lining 25 M E D I U M Y E S External1 NIL 249 Type of pipe lining 0 N O N E Y E S N A as built drawings 260 Type of pipe lining 0 N A Y E S Archival records NIL 401 Type of pipe lining 0 N A Y E S Archival records NIL 283 Type of pipe lining 0 GOOD N O N A NIL 284 Type of pipe lining 100 GOOD N A N A NIL 295_ Type of pipe lining II HIGH N O N A NIL 301 Type of pipe lining 0 N A Y E S N A NIL 4_24_ Type of pipe lining 0 HIGH Y E S Archival records NIL 433 Type of pipe lining 0 GOOD N A N A NIL 314 332 Type of pipe lining 435 400 Type cT^pjpeJinnig 383 Type of pipe lining 392 Type of pipe lining 403 Type of pipe lining 409 10 48 404 411 76 Type of pipe lining Type of pipe lining 414 Type of pipe lining 141 Type of pipe lining 405 Type ofjypejujing 402 1 Type _of_pjr___Ji_mng_ 430 Type of pipe lining 431 415 416 407 417 432 Type of pipe lining Type of pipe lining Type of pipe lining Type of pipe lining Type of pipe lining Type of pipe lining 419 Type of pipe lining 426 Type of pipe lining 420 Type of pipe lining 427 Type of pipe lining 422 Type of pipe lining 434 Type of pipe lining 342 Type of pipe lining 408 Type of pipe lining 423 379 Type of pipe lining 389 Type of pipe lining Type of pipe lining 25 25 100 50 Type of pipe lining, j 0 Type of pipe lining Type of pipe lining T y p e of pipe lining 100 25 100 75 100 N A GOOD HIGH N A N O N E HIGH M E D I U M N A high N O N E N A N A HIGH N A N O N E HIGH M E D I U M HIGH N O N E N O N E HIGH GOOD N A HIGH N O N E N O N E N O N E GOOD N A N A N O N E N A N O N E N A N A Y E S Y E S N A N O Y E S Y E S N A no N A N A Yes Y E S N O •NA N O NO Y E S NO Y E S NO NO N O Y E S N A YES YES. NO YES Y E S N O Y E S Y E S N A N A N A O & M records N A N A GIS system O & M records N A N A N A N A Archival records O & M records N A N A Archival records N A GIS system N A O & M records N A N A -N A GIS system N A O & M records GIS system N A GIS system Archival records N A GIS system_ Archival records N A To date, we have not lined any water mains NIL NIL NIL NIL NIL NIL NIL NIL NIL-NIL NIL NIL NIL NIL NIL NIL NIL NIL NIL NIL NIL NIL NIL NIL NIL NIL NIL NIL NIL NIL NIL NIL 315 21 Type of water service 100 ' HIGH Y E S Archival records NIL 42 Type of water service 100 HIGH N A N A NIL 55 Type of water service 100 HIGH Y E S Other NIL 56 Type of water service 100 HIGH Y E S Other Cadastrals 72 Type of water service ^0 GOOD N A N A NIL 428 Type of water service 100 ' H I G H N A N A NIL 413 Type of water service 100 HIGH Y E S Archival records NIL 100 Type of water service 100 HIGH Y E S Archival records NIL 103 Type of water service 100 HIGH N A N A NIL 112 Type of water service 0 N A N A N A NIL 120 Type of water service 0 N O N E N O N A NIL 134 Type of water service 100 HIGH Y E S O & M records- NIL 418 Type of water service 25 L O W Y E S GIS system NIL 227 Type of water service 0 N A N A N A NIL 231 Type of water service 100 HIGH Y E S GIS system 90% of service material in GIS 240 Type of water service 100 GOOD Y E S Archival records NIL 249 Type of water service 100 GOOD Y E S O & M records as built drawings 260 Type of water service 0 N A . N A N A NIL 401 Type of water service 0 N A Y E S GIS system NIL 283 Type of water service 0 GOOD Y E S GIS system Sometimes 284 Type of water service 50 M E D I U M N A N A NIL 295 Type of water service 0 HIGH N O N A NIL 301 Type of water service 100 GOOD Y E S N A NIL 424 Type of water service 100 HIGH Y E S Archival records NIL-433 Type of water service 100 GOOD N A GIS system NIL 332 Type of water service 100 GOOD Y E S GIS system NIL 316 435 Type of water service 75 GOOD Y E S N A NIL 400 Type of water service 75 HIGH N O Archival records NIL 383 Type of water service 100 HIGH N A N A NIL 392 Type of water service 0 N O N E Y E S Other NIL 403 Type of water service 100 HIGH N O N A NIL 409 Type of water service 100 HIGH N A N A NIL 10 Type of water service 100 GOOD Y E S GIS system NIL 48 Type of water service 100 high no N A NIL 404 Type of water service 100 GOOD Y E S GIS system NIL 411 Type of water service 100 N A N A N A NIL 76 Type of water service 0 N A Yes Archival records NIL 414 Type of water service 100 HIGH Y E S O & M records NIL 141 Type of water service 0 N A NO N A NIL 405 Type of water service 100 HIGH N A N A NIL 402 Type of water service 100 HIGH Y E S Archival records NIL 430 Type of water service 100 HIGH Y E S O & M records NIL 431 Type of water service 100 HIGH Y E S GIS system NIL 415 Type of water service 100 GOOD Y E S Archival records NIL 416 Type of water service 100 HIGH N O N A NIL ' 407 Type of water service 100 HIGH N O N A NIL 417 Type of water service 0 N O N E N O N A NIL 432 Type of water service 100 HIGH Y E S O & M records NIL 419 Type of water service 100 HIGH Y E S Archival records NIL 426 Type of water service 100 GOOD N O N A NIL 420 Type of water service 100 HIGH Y E S O & M records NIL 427 Type of water service 0 N O N E • Y E S Other NIL 317 422 Type of water service 0 GOOD Y E S Archival records NIL 434 Type of water service 100 HIGH Y E S GIS system _NIL ^ 342 Type of water service 100 HIGH Y E S Archival records NIL 408 Type of water service 100 HIGH Y E S GIS system NIL 423 Type of water service 0 N A Y E S GIS system NIL 379 Type of water service 50 M E D I U M Y E S Archival records NIL 389 Type of water service 100 HIGH N A Other NIL 21 Typical flow in area of break • 0 N A Y ES Archival records NIL 42 Typical flow in area of break N A N A N A NIL 55 Typical flow in area of break 0 N A N A N A NIL 56 Typical flow in area ofbreak 0 N A Y E S O & M records NIL 72 Typical flow in area of break 0 GOOD N A N A NIL 428 Typical flow in area of break 0 N A N A N A NIL 413 Typical flow in area of break N A N A N A NIL 100 Typical flow in area of break 0 GOOD N O N A NIL 103 Typical flow in area of break 0 N A N A N A NIL 112 Typical flow in area of break 0 N A ' N A N A NIL 120 Typical flow in area ofbreak N O N E Y E S Other NIL 134 Typical flow in area of break 0 N O N E Y E S Other Distribution System Model 418 Typical flow in area of break 0 N O N E Y E S Other NIL 227 Typical flow in area ofbreak 0 N A N A N A NIL 231 Typical flow in area of break 0 N O N E Y E S Other Modelling or manual calculation 240 Typical flow in area of break 0 N O N E Y E S Other hydraulic model 249 Typical flow in area of break 0 N O N E Y E S O & M .records treatment plant data 260 Typical flow in area of break .0 N A Y E S Other NIL 401 Typical flow in area of break 0 N A Y E S Other N I L 318 283 Typical flow in area of break 0 GOOD Y E S Other NIL 284 Typical flow in area of break 0 N O N E N A N A NIL 295 Typical flow in area ofbreak 0 HIGH NO N A NIL 301 Typical flow in area of break 0 N A N A N A NIL 424 Typical flow in area of break 0 HIGH N O N A NIL 433 Typical flow in area of break 0 M E D I U M N A External NIL 332 Typical flow in area of break 0 N O N E Y E S GIS system NIL 435 Typical flow in area of break .75 M E D I U M Y E S N A NIL 400 Typical flow in area of break 0 N O N E N O N A NIL 383 Typical flow in area of break 0 N A N A N A NIL 392 Typical flow in area of break 0 N O N E Y E S Other NIL 403 Typical flow in area of break 0 N A N A N A NIL 409 Typical flow in area of break 0 N A Y E S O & M 'records NIL 10 Typical flow in area of break 0 N A N A N A NIL 48 Typical flow in area of break 0 ' high no N A NIL 404 Typical flow in area of break 0 N O N E N A N A NIL 411 Typical flow in area of break N A N A N A NIL 76 Typical flow in area of break 0 N A Yes Archival records NIL 414 Typical flow in area of break 0 N A Y E S O & M records NIL ; Typical flow in area 141 i of break 100 HIGH 1 Y E S O & M records NIL Typical flow in area 405 | of break 0 N O N E ! N A N A NIL Typical flow in area 402 | of break 50 HIGH N O Other NIL i Typical flow in area 430 ' of break 0 GOOD Y E S Other Hydrualic model 431 Typical flow in area ofbreak 0 GOOD Y E S External NIL 415 Typical flow in area of break 0 N O N E N O N A NIL 416 Typical flow in area of break 0 N O N E Y E S Other Model 319 407 Typical flow in area of break 100 HIGH NO NA NIL 417 Typical flow in area of break 0 NONE NO NA NIL 432 Typical flow in area of break 0 NA NO NA NIL 419 Typical flow in area ofbreak 75 MEDIUM NO NA NIL 426 Typical flow in area ofbreak 0 NONE NA NA NIL 427 Typical flow in area of break 0 NONE NO NA NIL 422 Typical flow in area of break 0 GOOD NO NA NIL . 434 Typical flow in area of break 0 NA YES GIS system NIL 342 Typical flow in area of break 0 NA YES Other Water Model 408 Typical flow in area of break NA NA NA NIL 423 Typical flow in area of break 0 NA NA NA NIL 379 Typical flow in area of break 0 NONE YES Other NIL 389 Typical flow in area of break 0 NA NA NA NIL 21 Under boulevard or roadway 100 HIGH YES NA NIL 42 Under boulevard or roadway 100 GOOD NA NA NIL 55 Under boulevard or roadway 100 HIGH YES Other Water Break Report 56 Under boulevard or roadway 0 NA NA NA NIL 72 Under boulevard or roadway 0 GOOD NA NA NIL 428 Under boulevard or roadway 100 HIGH NA NA NIL 413 Under boulevard or roadway 100 HIGH YES Archival records NIL 100 Under boulevard or roadway 100 HIGH YES Archival records NIL 103 Under boulevard or roadway 0 NA NA NA NIL 112 Under boulevard or roadway 100 HIGH YES Archival records NIL 120 Under boulevard or roadway 0 NONE YES GIS system NIL 134 Under boulevard or roadway 100 HIGH YES Archival records NIL 418 Under boulevard or roadway 25 MEDIUM YES GIS system NIL 320 227 Under boulevard or roadway 100 GOOD YES O & M records Hansen WO data 231 Under boulevard or roadway 100 GOOD YES GIS system break location identifies this. 240 Under boulevard or roadway 100 GOOD NO N A NIL 249 Under boulevard or roadway 100 GOOD YES N A as built drawings 260 Under boulevard or roadway , 50 GOOD ' N A N A NIL 401 Under boulevard or roadway 0 N A Y E S Archival records .NIL _. 283 Under boulevard or roadway 0 GOOD Y E S GIS system NIL 284 Under boulevard or roadway 50 M E D I U M N A N A NIL 295 Under boulevard or roadway 0 HIGH N O N A NIL 301 Under boulevard or roadway 100 HIGH Y E S N A N I L 424 Under boulevard or roadway 0 HIGH Y E S Archival records NIL . 433 Under boulevard or roadway 100 GOOD N A GIS system NIL 332 Under boulevard or roadway 75 GOOD Y E S GIS system NIL 435 Under boulevard or roadway 100 GOOD YES N A NIL 400 Under boulevard or roadway 25 GOOD YES GIS system NIL 383 Under boulevard or roadway 25 M E D I U M N A N A NIL 392 Under boulevard or roadway 0 N O N E Y E S GIS system NIL 403 Under boulevard or roadway 100 GOOD N O N A NIL 409 Under boulevard or roadway 100 HIGH N A N A NIL 10 Under boulevard or roadway 25 GOOD YES GIS system NIL 48 Under boulevard or roadway 100 high no N A NIL 404 Under boulevard or roadway 100 GOOD Y E S GIS system NIL v411 Under boulevard or roadway N A N A . N A NIL 76 Under boulevard or roadway 50 Good Yes Archival records NIL 414 Under boulevard or roadway 0 N A Y E S Archival records NIL 141 Under boulevard or roadway 0 ' N A Y E S External . NIL 321' 405 Under boulevard or roadway 100 HIGH N A N A NIL 402 Under boulevard or roadway 0 HIGH Y E S Archival records NIL 430 Under boulevard or roadway 25 M E D I U M N O N A NIL 431 Under boulevard or roadway 100 HIGH Y E S GIS system NIL 415 Under boulevard or roadway 0 N O N E N O N A NIL 416 Under boulevard or roadway 100 HIGH Y E S GIS system NIL 407 Under boulevard or roadway 100 HIGH N O N A NIL 417 Under boulevard or roadway 0 N O N E NO N A NIL 432 Under boulevard or roadway 100 HIGH Y E S O & M records NIL 419 Under boulevard or roadway 100 HIGH Y E S G I S ' system NIL 426 Under boulevard or roadway 0 N O N E N A N A NIL 420 Under boulevard or roadway 100 HIGH Y E S O & M records NIL 427 Under boulevard or roadway 0 N O N E Y E S GIS system NIL 422 Under boulevard or roadway 0 GOOD Y E S Archival records NIL 434 Under boulevard or roadway 0 N A , Y E S GIS system NIL 342 Under boulevard or roadway 100 HIGH Y E S Archival records NIL 408 Under boulevard or roadway 100 GOOD Y E S GIS system NIL 423 Under boulevard or roadway 0 N A Y E S GIS system NIL 379 Under boulevard or roadway 100 GOOD N O Other NIL 389 Under boulevard or roadway 100 HIGH N A Other NIL 21 Year of installation 75 GOOD Y E S Archival records NIL 42 Year of installation 100 HIGH N A N A NIL 55 Year of installation N A N A N A Available, not recorded 56 Year of installation • 0 N A Y E S Archival records NIL 72 Year of installation ' 0 GOOD N A N A NIL 428 Year of installation 0 N A N A N A NIL 413 Year of installation 0 N A N A NIL 100 Year of installation 75 HIGH Y E S Archival records NIL 103 Year of installation 0 N A N A N A NIL 322 112 Year of installation 100 GOOD Y E S Archival records NIL 120 Year of installation 0 N O N E Y E S GIS system NIL 134 Year of installation 0 N O N E Y E S Archival records NIL 418 Year of installation 0 N O N E Y E S GIS system NIL 227 Year of installation 0 M E D I U M Y E S O & M records Hansen IMS data 231 Year of installation 100 GOOD Y E S GIS system Record book of Mains installed 240 Year of installation • 75 M E D I U M Y E S GIS system NIL 249 Year of installation 0 ) N O N E Y E S GIS system as built drawings 260 Year of installation 0 N A Y E S Archival records NIL 401 Year of installation 100 GOOD Y E S GIS system entered automatically from database 283 Year of installation 0 ____ • GOOD Y E S Archival records Sometimes 284 Year of installation 100 GOOD N A N A NIL 295 Year of installation 25 HIGH YES Archival records NIL 301 Year of installation 75 GOOD YES NA NIL 424 Year of installation 100 HIGH YES Archival records NIL 433 Year of installation , 0 GOOD N A GIS system NIL 332 Year of installation 25 L O W Y E S GIS system N I L 435 Year of installation 25 GOOD Y E S N A NIL 400 Year of installation 0 N O N E Y E S GIS system NIL 383 Year of installation 100 HIGH N A N A NIL 392 Year of installation 0 N O N E Y E S GIS system NIL 403 Year of installation 100 HIGH Y E S GIS system NIL 409 Year of installation 100 HIGH N A . N A NIL 10 Year of installation 0 N A N A N - \ NIL 48 Year of installation 0 high N A N A NIL 404 Year of installation 25 M E D I U M Y E S Archival records NIL 411 Year of installation N A N A N A NIL 76 Year of installation. 0 N A Yes Archival records NIL 414 Year of installation 100 HIGH Y E S O & M records NIL 141 Year of installation 0 N A N O N A NIL 405 Year of installation 100 HIGH ' N A N A NIL 323 402 Year of installation 0 HIGH Y E S Archival records NIL 430 Year of installation 100 HIGH Y E S O & M records NIL 431 Year of installation 100 HIGH Y E S GIS system NIL 415 Year of installation 100 L O W Y E S Archival records NIL 416 Year of installation 0 N O N E Y ES . O & M records NIL 407 Year of installation 0 HIGH NO 1 N A NIL 417 Year of installation 75 GOOD i N O NA NIL 432 Year of installation 0 N A : Archival Y E S ; records NIL 419 Year of installation 100 HIGH 1 GIS Y E S i system NIL 426 420 Year of installation 0 1 N O N E Y E S Other NIL Year of installation 0 1 N O N E Y E S O & M records NIL 427 Year of installation 75 ! M E D I U M Y E S GIS system NIL 422 Year of installation 0 GOOD Y E S Archival records NIL 434 Year of installation 0 | N A Y E S GIS system NIL 342 Year of installation 0 | N A Y ES Archival records NIL 408 Year of installation 0 ! NONE Y E S Other As-built dwg 423 Year of installation 0 N A ! Archival Y E S j records NIL 379 Year of installation 0 N O N E Y E S Archival records NIL 389 Year of installation 0. N A N A N A NIL 324 Failure Cause data recorded by survey respondents City I D •' • Description>V": i •• Data Kcciiulk'ii C onuik'iits 417 Is your water corrosive to your watermains (yes or no) N A 379 Is your water corrosive to your watermains (yes or no) N O 112 295 Is your water corrosive to your watermains (yes or no) Y E S Is your water corrosive to your watermains (yes or no) N O 100 Is your water corrosive to your watermains (yes or no) N O 424 Is your water corrosive to your watermains (yes or no) NO 120 Is your water corrosive to your watermains (yes or no) NO 10 Is your water corrosive to your watermains (yes or no) NO N A 408 Is your water corrosive to your watermains (yes or no) N A 418 Is your water corrosive to your watermains (yes or no) Y E S 420 Is your water corrosive to your watermains (yes or no) NO 426 Is your water corrosive to your watermains (yes or no) NO 415 Is your water corrosive to your watermains (yes or no) N A NIL 284 Is your water corrosive to your watermains (yes or no) Y E S 48 Is your water corrosive to your watermains (yes or no) NO 392 Is your water corrosive to your watermains (yes or no) NO 409 Is your water corrosive to your watermains (yes or no) NO 383 Is your water corrosive to your watermains (yes or no) Y E S 42 Is your water corrosive to your watermains (yes or no) Y E S 404 Is your water corrosive to your watermains (yes or no) NO 428 Is your water corrosive to your watermains (yes or no) NO 430 Is your water corrosive to your watermains (yes or no) N O 260 Is your water corrosive to your watermains (yes or no) NO 342 Is your water corrosive to your watermains (yes or no) N O 423 Is your water corrosive to your watermains (yes or no) N O 405 Is your water corrosive to your watermains (yes or no) NO 435 Is your water corrosive to your watermains (yes or no) N A 21 Is your water corrosive to your watermains (yes or no) N O N A 416 Is your water corrosive to your watermains (yes or no) N A 249 Is your water corrosive to your watermains (yes or no) N A 419 Is your water corrosive to your watermains (yes or no) N A NIL 402 Is your water corrosive to your watermains (yes or no) N A 389 Is your water corrosive to your watermains (yes or no) NO 332 Is your water corrosive to your watermains (yes or no) N O 134 Is your water corrosive to your watermains (yes or no) NO 401 Is your water corrosive to your watermains (yes or no) Y E S NA™ 141 Is your water corrosive to your watermains (yes or no) 301 Is your water corrosive to your watermains (yes or no) N A 240 Is your water corrosive to your watermains (yes or no) Y E S 422 Is your water corrosive to your watermains (yes or no) NO 231 Is your water corrosive to your watermains (yes or no) NO 427 Is your water corrosive to your watermains (yes or no) NO 407 Is your water corrosive to your watermains (yes or no) NO 56 Is your water corrosive to your watermains (yes or no) NO 325 72 Is your water corrosive to your watermains (yes or no) N A '283 Is your water corrosive to your watermains (yes or no) NO 432 Is your water corrosive to your watermains (yes or no) N O 76 Is your water corrosive to your watermains (yes or no) No 411 Is your water corrosive to your watermains (yes or no) N A NIL 227 Is your water corrosive to your watermains (yes or no) NO 403 Is your water corrosive to your watermains (yes or no) NO 400 Is your water corrosive to your watermains (yes or no) N A 413 Is your water corrosive to your watermains (yes or no) NO -433 Is your water corrosive to your watermains (yes or no) N A 103 Is your water corrosive to your watermains (yes or no) NO 434 Is your water corrosive to your watermains (yes or no) N A 55 Is your water corrosive to your watermains (yes or no) NO 414 Is your water corrosive to your watermains (yes or no) Y E S 431 Is your water corrosive to your watermains (yes or no) Y E S 332 Corrosion NO NIL 21 Corrosion Y E S NIL 342 Corrosion Y E S NIL 411 Corrosion N A NIL 227 Corrosion NO NIL 416 Corrosion NO NIL 427 Corrosion Y E S NIL 419 Corrosion Y E S NIL 389 Corrosion N A NIL 414 Corrosion Y E S Work Order System 260 Corrosion NO NIL 403 Corrosion N O NIL 1 379 Corrosion Y E S NIL 415 Corrosion Y E S NIL 426 Corrosion NO NIL 420 Corrosion Y E S NIL 383 Corrosion Y E S NIL 301 Corrosion Y E S NIL 408 Corrosion NO NIL 424 Corrosion Y E S NIL 405 Corrosion Y E S NIL 422 Corrosion N A NIL 141 Corrosion N A NIL 428 Corrosion NO NIL 409 Corrosion N A NIL 418 Corrosion Y E S NIL 402 Corrosion NO NIL 407 Corrosion Y E S 433 Corrosion Y E S NIL 417 Corrosion Y E S NIL 56 Corrosion Y E S NIL 413 Corrosion N A NIL 103 Corrosion YES NIL 326 392 Corrosion Y E S NIL 134 Corrosion NO NIL 435 Corrosion N A NIL 10 Corrosion Y E S Other is our work order 112 Corrosion Y E S NIL 100 Corrosion Y E S NIL 120 Corrosion N A NIL 295 Corrosion Y E S NIL 284 Corrosion Y E S NIL 42 Corrosion Y E S NIL 231 Corrosion Y E S NIL 48 Corrosion yes 434 Corrosion YES NIL 240 Corrosion NO NIL 431 Corrosion Y E S NIL 283 Corrosion Y E S Y E S NIL 72 Corrosion NIL 432 Corrosion . Y E S NIL 76 Corrosion No NIL 400 Corrosion Y E S NIL 55 Corrosion Y E S Access Database 430 Corrosion NO NIL 404 Corrosion Y E S Recorded taps 249 Corrosion N A NIL 401 Corrosion Y E S . NIL 423 Corrosion NO NIL 431 Traffic load NO NIL-414 Traffic load NO NIL 103 Traffic load N A . NIL 55 Traffic load NO Titan and Tops Traffic Data 434 Traffic load Y E S NIL 401 Traffic load N A NIL 284 Traffic load NO NIL 56 Traffic load NO NIL 231 Traffic load NO NIL 426 Traffic load NO NIL 392 Traffic load NO NIL 435 Traffic load N A NIL NIL 21 Traffic load NO 415 Traffic load NO NIL 409 Traffic load N A NIL 433 Traffic load NO NIL 260 Traffic load NO NIL 430 Traffic load NO NIL 400 Traffic load NO NIL 403 Traffic load Y E S NIL 411 Traffic load N A NIL 327 227 Traffic load NO NIL 76 Traffic load No NIL 428 Traffic load NO NIL 301 Traffic load NO NIL 283 Traffic load NO NIL 240 Traffic load NO pavement management 141 Traffic load N A NIL 422 Traffic load N A NIL 427 Traffic load NO NIL 72 Traffic load Y E S NIL 413 Traffic load N A NIL 432 Traffic load NO NIL 379 Traffic load NO NIL 407 Traffic load Y E S 418 Traffic load Y E S NIL 419 Traffic load Y E S NIL 383 Traffic load NO NIL 295 Traffic load NO NIL 405 Traffic load NO NIL 249 Traffic load N A NIL 112 Traffic load Y E S NIL 100 Traffic load NO NIL 402 Traffic load NO NIL 424 Traffic load NO NIL 134. Traffic load NO NIL 10 Traffic load NO system 42 Traffic load NO NIL 389 Traffic load N A NIL 416 Traffic load NO NIL 332 Traffic load NO NIL 342 Traffic load N O NIL 120 Traffic load N A NIL 408 Traffic load NO NIL 420 Traffic load Y E S NIL 423 Traffic load NO NIL 404 Traffic load Y E S NIL 417 Trallk load NO NIL 48 Traffic load no 76 Poor construction practices No NIL 10 Poor construction practices Y E S NIL 430 Poor construction practices NO NIL 417 Poor construction practices NO NIL 411 Poor construction practices N A NIL 283 Poor construction practices NO NIL 141 Poor construction practices N A NIL 284 Poor construction practices NO NIL 426 Poor construction practices NO NIL 415 Poor construction practices Y E S NIL 328 227 Poor construction practices N O NIL 249 Poor construction practices N A NIL 435 Poor construction practices N A NIL 419 Poor construction practices Y E S NIL 416 Poor construction practices NO NIL 48 Poor construction practices no 401 Poor construction practices Y E S NIL 295 Poor construction practices Y E S NIL . 428 Poor construction practices N O NIL 103 i Poor construction practices Y E S NIL 414 Poor construction practices Y E S Work Order System 231 Poor construction practices NO NIL 402 Poor construction practices NO NIL 55 Poor construction practices NO NIL 240 Poor construction practices Y E S NIL 433 Poor construction practices N O If crew believes they may comment, only theoretical. 432 Poor construction practices Y E S NIL 21 Poor construction practices NO NIL 424 Poor construction practices NO NIL 427 Poor construction practices N O NIL 134 Poor construction practices Y E S NIL 418 Poor construction practices Y E S NIL 420 Poor construction practices Y E S NIL 405 Poor construction practices Y E S NIL 120 Poor construction practices N A NIL 423 Poor construction practices Y E S NIL 422 Poor construction practices N A NIL 301 Poor construction practices Y E S NIL 332 Poor construction practices NO NIL 400 Poor construction practices NO NIL 392 Poor construction practices NO NIL 72 Poor construction practices Y E S NIL 407 Poor construction practices Y E S 404 Poor construction practices N O NIL 383 Poor construction practices N A NIL 56 Poor construction practices NO NIL 434 Poor construction practices N A NIL 260 Poor construction practices NO NIL 342 Poor construction practices Y E S NIL 409 Poor construction practices N A NIL 379 Poor construction practices Y E S NIL 408 Poor construction practices NO NIL 413 Poor construction practices N A NIL 431 Poor construction practices Y E S NIL 100 Poor construction practices N O NIL 112 Poor construction practices Y E S NIL 329 42 Poor construction practices Y E S NIL 389 Poor construction practices N A NIL 403 Poor construction practices Y E S NIL 112 Ground frost Y E S NIL 433 Ground frost Y E S Only i f crew comments on frost depth. 392 Ground frost NO NIL 227 Ground frost NO NIL 72 Ground frost Y E S NIL 402 Ground frost NO NIL 426 Ground frost NO NIL 432 Ground frost Y E S NIL 55 Ground frost Y E S Access Database 430 Ground frost NO NIL 416 Ground frost N O N O NIL NIL 260 Ground frost 405 Ground frost NO NIL 231 Ground frost Y E S Env. Canada Temp. Data 240 Ground frost Y E S NIL 419 Ground frost N O NIL 417 Ground frost N O NIL 48 Ground frost no 342 Ground frost Y E S NIL 403 Ground frost Y E S NIL 408 Ground frost NO NIL 21 Ground frost Y E S NIL 411 Ground frost N A NIL 409 Ground frost N A NIL 415 Ground frost Y E S NIL 420 Ground frost Y E S NIL 428 Ground frost NO NIL 400 Ground frost Y E S NIL 295 Ground frost Y E S NIL 120 Ground frost N A NIL 422 Ground frost N A NIL 389 Ground frost N A NIL 427 Ground frost NO NIL 423 Ground frost NO NIL 413 Ground frost N A NIL 134 Ground frost Y E S NIL 424 Ground frost NO NIL 284 Ground frost Y E S NIL 435 Ground frost N A NIL 332 Ground frost N O NIL 383 Ground frost NO NIL 100 Ground frost NO NIL 76: Ground frost No NIL 418 Ground frost NO NIL 330 401 Ground frost N A NIL 379 Ground frost Y E S NIL 434 Ground frost N A NIL 407 Ground frost NO 103 Ground frost Y E S NIL 249 Ground frost N A NIL ' 404 Ground frost NO NIL 141 Ground frost N A NIL 431 Ground frost NO NIL 42 Ground frost Y E S NIL 56 Ground frost NO NIL 414 Ground frost Y E S Work Order System 301 Ground frost NO NIL 10 Ground frost NO NIL 283 Ground frost NO NIL 418 Settlement Y E S NIL 416 Settlement NO NIL 332 Settlement NO NIL 342 Settlement Y E S NIL 231 Settlement Y E S NIL ' 389 Settlement N A NIL 404| Settlement Y E S NIL 100 Settlement Y E S NIL 48 Settlement no 112 Settlement Y E S NIL 400 Settlement N O NIL 10 Settlement N O NIL 42 Settlement Y E S NIL 134 Settlement Y E S NIL 120 Settlement N A NIL 435 Settlement N A NIL 249 Settlement N A NIL 401 Settlement Y E S NIL 419 Settlement Y E S NIL 430 Settlement NO NIL , 431 Selllemenl Y E S NIL 426 Settlement NO NIL 392 Settlement NO NIL 260 Settlement NO NIL 428 Settlement N O NIL 55 Settlement No NIL 284 Settlement Y E S NIL 403 Settlement Y E S NIL 423 Settlement NO NIL 422 Settlement N A NIL 141 Settlement N A NIL 407 Settlement Y E S 433 Settlement NO NIL 331 420 Settlement Y E S NIL 240 Settlement N O NIL 415 Settlement Y E S NIL 72 Settlement Y E S NIL 434 21 Settlement Y E S Y E S " NIL Settlement NIL 408 Settlement NO NIL 432 Settlement Y E S NIL 413 Settlement N A NIL 427 Settlement NO NIL 301 Settlement NO NIL 283 Settlement NO NIL 414 Settlement Y E S Work Order System 56 Settlement Y E S NIL NIL ' 103 Settlement Y E S 409 Settlement N A NIL 227 Settlement NO NIL 402 Settlement NO NIL 76 Settlement No NIL 379 Settlement Y E S NIL 295 Settlement Y E S NIL 383 Settlement Y E S NIL 405 Settlement Y E S NIL 417 Settlement NO NIL 424 Settlement NO NIL 411 Settlement N A NIL 423 Joint failure N O NIL 401 Joint failure Y E S NIL 411 Joint failure Y E S NIL 100 Joint failure Y E S NIL 295 Joint failure Y E S NIL 404 Joint failure Y E S NIL 414 Joint failure Y E S Y E S " Work Order System 103 Joint failure NIL 76 Joint failure No NIL 283 Joint failure Y E S NIL 413 Joint failure N A NIL 10 Joint failure Y E S NIL 141 Joint failure N A NIL 112 Joint failure Y E S NIL 407 Joint failure Y E S 134 Joint failure Y E S NIL 427 Joint failure Y E S NIL 284 Joint failure Y E S NIL 403 Joint failure Y E S NIL 120 Joint failure N A ' NIL 42 Joint failure Y E S NIL 332 435 Joint failure N A NIL 400 Joint failure Y E S . NIL 422 Joint failure N A NIL 72 Joint failure Y E S NIL 227 Joint failure N O NIL 420 Joint failure Y E S NIL 55 Joint failure Y E S Access Database 392 Joint failure Y E S NIL 301 Joint failure Y E S NIL 417 Joint failure Y E S NIL 56 Joint failure Y E S NIL 408 Joint failure N O NIL 434 Joint failure Y E S NIL 389 Joint failure N A NIL 416 Joint failure NO NIL 419 Joint failure Y E S NIL 383 Joint failure Y E S NIL 405 Joint failure Y E S NIL 424 Joint failure Y E S NIL 332 Joint failure Y E S NIL 428 Joint failure NO NIL 418 Joint failure Y E S NIL 231 Joint failure Y E S NIL 342 Joint failure Y E S NIL 426 Joint failure N O NIL 249 Joint failure N A NIL 402 Joint failure N O NIL 48 Joint failure yes 431 Joint failure Y E S NIL 433 Joint failure Y E S NIL 260 Joint failure N O NIL 240 Joint failure Y E S NIL 379 Joint failure Y E S NIL 409 Joint failure N A • NIL 21 Joint failure NO NIL 432 Joint failure Y E S NIL 415 Joint failure Y E S NIL 430 Joint failure NO NIL 100 rock contact NO NIL 392 rock contact NO NIL 283 rock contact Y E S NIL 400 rock contact NO NIL 434 rock contact Y E S NIL 72 rock contact Y E S NIL 240 rock contact Y E S NIL 295 rock contact Y E S NIL 284 rock contact NO NIL 431 rock contact Y E S NIL 432 rock contact Y E S NIL 333 231 rock contact Y E S NIL 55 rock contact Y E S Access Database 76 rock contact No NIL 120 rock contact N A NIL 414 rock contact Y E S Work Order System 332 rock contact NO NIL 405 rock contact Y E S NIL 424 rock contact Y E S NIL 420 rock contact Y E S NIL 417 rock contact Y E S NIL 408 rock contact NO NIL 21 rock contact Y E S NIL 409 rock contact N A NIL 379 rock contact NO NIL 415 rock contact Y E S NIL 402 rock contact NO NIL 56 rock contact NO NIL 383 rock contact Y E S NIL 103 rock contact Y E S NIL 301 rock contact NO NIL 10 rock contact Y E S NIL 427 rock contact Y E S NIL 422 rock contact N A NIL 413 rock contact N A NIL 407 rock contact NO 141 rock contact N A NIL 403 rock contact Y E S NIL 227 rock contact NO NIL 411 rock contact N A NIL 433 rock contact NO Unless crew comment. 423 rock contact N O NIL 42 rock contact Y E S NIL 426 rock contact N O NIL 430 rock contact N O NIL 418 rock contact Y E S NIL 435 rock contact N A NIL 404 rock contact Y E S NIL 112 rock contact Y E S NIL 260 rock contact NO NIL 342 rock contact Y E S NIL 389 rock contact N A NIL 428 rock contact NO NIL 401 rock contact N A NIL 419 rock contact Y E S NIL 48 rock contact yes 249 rock contact N A JNIL. 416 rock contact NO NIL 334 134 rock contact Y E S NIL " ~ 76 Construction disturbance No NIL 260 Construction disturbance N O NIL 413 Construction disturbance N A NIL 407 Construction disturbance Y E S 134 Construction disturbance Y E S NIL 48 Construction disturbance yes 411 Construction disturbance N A NIL 42 Construction disturbance N A NIL 249 Construction disturbance N A NIL 301 Construction disturbance N O NIL 432 Construction disturbance Y E S NIL 431 Construction disturbance Y E S NIL 415 Construction disturbance Y E S NIL 389 Construction disturbance N A NIL 417 Construction disturbance NO NIL 379 Construction disturbance Y E S NIL 426 Construction disturbance NO NIL 419 Construction disturbance YES NIL 100 Construction disturbance NO NIL 55 Construction disturbance Y E S Access Database 402 Construction disturbance N O NIL 383 Construction disturbance Y E S NIL 414 Construction disturbance Y E S Work Order System 72 Construction disturbance Y E S NIL 103 Construction disturbance N A NIL 433 Construction disturbance NO NIL 231 Construction disturbance Y E S NIL 418 Construction disturbance Y E S NIL 21 Construction disturbance Y E S NIL 284 Construction disturbance Y E S NIL 295 Construction disturbance Y E S NIL 423 Construction disturbance Y E S NIL 434 Construction disturbance Y E S NIL 408 Construction disturbance NO NIL 427 Construction disturbance NO NIL 424 Construction disturbance NO NIL 404 Construction disturbance Y E S NIL 10 Construction disturbance Y E S NIL 392 Construction disturbance NO NIL 120 Construction disturbance N A NIL 416 Construction disturbance NO NIL 112 Construction disturbance Y E S NIL 435 Construction disturbance N A NIL 401 Construction disturbance Y E S NIL 428 Construction disturbance NO NIL 409 Construction disturbance N A NIL 430 Construction disturbance NO NIL 335 420 Construction disturbance Y E S NIL 400 Construction disturbance NO NIL 283 Construction disturbance NO NIL 332 Construction disturbance NO NIL 405 Construction disturbance Y E S NIL 56 Construction disturbance Y E S NIL 227 Construction disturbance N O NIL 422 Construction disturbance N A NIL 342 Construction disturbance Y E S NIL 240 Construction disturbance Y E S NIL 141 Construction disturbance N A NIL 403 416 Construction disturbance Y E S NIL High pressure NO NIL 301 High pressure NO NIL 402 High pressure NO NIL 332 High pressure NO communicated from Water Treatment Plant when output pressures change 418 High pressure NO NIL 403 High pressure Y E S NIL 42 High pressure NO NIL 112 High pressure Y E S NIL 419 High pressure Y E S NIL 383 High pressure Y E S NIL 422 High pressure N A - NIL 428 High pressure NO NIL 56 High pressure NO NIL 430 High pressure ' NO NIL 426 High pressure NO NIL 407 High pressure Y E S 100 High pressure N O NIL 427 High pressure Y E S NIL 103 High pressure Y E S NIL 405 High pressure Y E S \ I I 389 High pressure N A NIL 141 High pressure N A NIL 413 High pressure N A NIL 414 High pressure N O . NIL 408 High pressure NO NIL 409 High pressure N A NIL 424 High pressure N O NIL 342 High pressure Y E S NIL 404 High pressure Y E S NIL 260 High pressure NO NIL 415 High pressure Y E S NIL 417 High pressure NO NIL 21 High pressure NO NIL 227 High pressure NO NIL 336 423 High pressure NO NIL 420 High pressure YES NIL 10 High pressure NO NIL 411 High pressure NA NIL 433 High pressure NO Crew would not be able to determine in field. 231 High pressure YES Review with Field Ops. NIL 400 High pressure NO 76 High pressure No NIL 431 High pressure YES NIL 392 High pressure NO NIL 48 High pressure yes 434 High pressure NA NIL 432 High pressure NO NIL 134 High pressure YES NIL 435 High pressure NA NIL 401 High pressure YES NIL 284 High pressure NO NIL 295 High pressure YES' NIL 72 High pressure NO NIL 379 High pressure YES NIL 120 High pressure NA NIL 240 High pressure NO hydraulic model 283 High pressure NO NIL 55 High pressure YES Access Database 249 High pressure NA NIL 431 Water temperature change NO NIL 283 Water temperature change NO NIL 417 Water temperature change NO NIL 260 Water temperature change NO NIL 404 Water temperature change NO NIL 433 Water temperature change NO NIL 420 Water temperature change YES NIL 10 Water temperature change NO NIL 48 Water temperature change no 21 Water temperature change NO NIL 295 Water temperature change YES . NIL 141 Water temperature change NA NIL 389 Water temperature change NA. NIL 432 Water temperature change NO NIL 231 Water temperature change NO NIL 76 Water temperature change No NIL 413 Water temperature change NA NIL 342 Water temperature change NO NIL 227 Water temperature change NO NIL NIL 103 Water temperature change NA 411 Water temperature change NA NIL 434 Water temperature change NA NIL 337 414 Water temperature change NO NIL 240 Water temperature change NO NIL 284 Water temperature change NO NIL 408 Water temperature change NO NIL 400 Water temperature change NO NIL 55 Water temperature change No From Pump Station 422 Water temperature change N A NIL 379 Water temperature change N O NIL 428 Water temperature change NO NIL - 401 Water temperature change N A NIL 301 Water temperature change NO NIL 419 Water temperature change N O NIL 435 Water temperature change N A NIL 383 Water temperature change N O NIL 403 Water temperature change NO ' NIL 426 Water temperature change NO NIL 416 Water temperature change NO NIL 430 Water temperature change NO NIL 249 Water temperature change N A NIL 407 Water temperature change NO 134 Water temperature change NO NIL 72 415 Water temperature change NO NIL Water temperature change NO NIL 392 Water temperature change NO NIL 424 Water temperature change NO NIL 332 Water temperature change NO communicated from Water Treatment Plant when output temp changes 405 Water temperature change Y E S NIL 56 Water temperature change NO NIL 423 Water temperature change NO NIL 100 Water temperature change NO NIL 409 Water temperature change N A NIL 427 Water temperature change NO NIL 402 Water temperature change NO NIL 112 Water temperature change Y E S NIL 42 Water temperature change NO NIL 120 Water temperature change N A NIL 418 Water temperature change NO NIL 413 Frozen pipe N A NIL 432 Frozen pipe Y E S NIL 76 Frozen pipe No NIL 405 Frozen pipe Y E S NIL 56 Frozen pipe NO NIL 332 Frozen pipe Y E S NIL 400 Frozen pipe Y E S NIL . 403 Frozen pipe Y E S NIL 338 72 Frozen pipe Y E S NIL 227 Frozen pipe NO NIL 301 Frozen pipe Y E S NIL 407 Frozen pipe Y E S 411 Frozen pipe N A NIL 422 Frozen pipe N A NIL 283 Frozen pipe NO NIL 240 Frozen pipe Y E S NIL 409 Frozen pipe N A NIL 415 Frozen pipe Y E S NIL 10 Frozen pipe NO NIL 424 Frozen pipe NO NIL 379 Frozen pipe N O NIL 402 Frozen pipe NO NIL 423 Frozen pipe NO NIL 418 Frozen pipe N O NIL 416 Frozen pipe N O NIL 392 Frozen pipe N O NIL 435 Frozen pipe N A NIL 420 Frozen pipe Y E S NIL 134 Frozen pipe Y E S NIL 100 Frozen pipe Y E S NIL 112 Frozen pipe Y E S NIL 428 Frozen pipe NO NIL 401 Frozen pipe N A NIL 120 Frozen pipe N A NIL 426 Frozen pipe NO NIL 408 Frozen pipe NO NIL 249 Frozen pipe N A NIL _ 42 Frozen pipe Y E S NIL 48 Frozen pipe yes 231 Frozen pipe Y E S Review with Field Ops. 389 Frozen pipe N A NIL 427 Frozen pipe Y E S NIL 434 Frozen pipe N A NIL 103 Frozen pipe N A NIL ' "55 Frozen pipe Y E S Access Database 342 Frozen pipe Y E S NIL 414 Frozen pipe Y E S Work Order System 284 Frozen pipe Y E S NIL 141 Frozen pipe N A NIL 419 Frozen pipe Y E S NIL 433 Frozen pipe Y E S NIL 430 Frozen pipe Y E S NIL 383 Frozen pipe Y E S NIL 404 Frozen pipe NO NIL 21 Frozen pipe NO NIL 339 417 Frozen pipe N O NIL 295 Frozen pipe N O NIL 260 Frozen pipe N O NIL 431 Frozen pipe Y E S NIL 408 Errosion / unsupported pipe N O NIL 112 Errosion / unsupported pipe Y E S NIL 72 Errosion / unsupported pipe Y E S NIL 400 Errosion / unsupported pipe NO NIL 434 Errosion / unsupported pipe Y E S NIL 431 Errosion / unsupported pipe Y E S NIL 392 Errosion / unsupported pipe NO NIL 100 Errosion / unsupported pipe NO NIL 423 Errosion / unsupported pipe NO NIL 42 Errosion / unsupported pipe NO NIL 405 Errosion / unsupported pipe Y E S NIL 404 Errosion / unsupported pipe Y E S NIL 342 Errosion / unsupported pipe Y E S NIL 260 Errosion / unsupported pipe NO NIL 389 Errosion / unsupported pipe N A NIL 332 Errosion / unsupported pipe Y E S NIL 383 Errosion / unsupported pipe Y E S NIL 120 Errosion / unsupported pipe N A NIL 401 Errosion / unsupported pipe Y E S NIL 415 Errosion / unsupported pipe Y E S NIL 433 Errosion / unsupported pipe Y E S Would comment i f thought. 21 Errosion / unsupported pipe NO NIL 417 Errosion / unsupported pipe NO NIL 420 Errosion / unsupported pipe Y E S NIL 424 Errosion / unsupported pipe NO NIL 379 Errosion / unsupported pipe NO NIL 402 Errosion / unsupported pipe NO NIL 416 Errosion / unsupported pipe NO NIL 428 Errosion / unsupported pipe NO NIL 419 Errosion / unsupported pipe Y E S NIL 426 Errosion / unsupported pipe NO NIL 414 Errosion / unsupported pipe Y E S Work Order System 249 Errosion / unsupported pipe N A NIL 418 Errosion / unsupported pipe Y E S NIL 435 Errosion / unsupported pipe N A NIL 10 Errosion / unsupported pipe Y E S NIL 134 Errosion / unsupported pipe Y E S NIL 48 Errosion / unsupported pipe no 295 Errosion / unsupported pipe Y E S NIL 284 Errosion / unsupported pipe N O NIL 231 Errosion / unsupported pipe Y E S NIL 55 Errosion / unsupported pipe Y E S Access Database 240 Errosion / unsupported pipe NO NIL 340 432 Errosion/ unsupported pipe NO NIL 283 Errosion / unsupported pipe Y E S NIL 76 Errosion / unsupported pipe No NIL 430 Errosion / unsupported pipe N O NIL 409 Errosion / unsupported pipe N A NIL 227 Errosion / unsupported pipe NO NIL 103 Errosion / unsupported pipe Y E S NIL 407 Errosion / unsupported pipe Y E S 411 Errosion / unsupported pipe N A NIL 403 Errosion / unsupported pipe Y E S NIL 427 Errosion / unsupported pipe Y E S NIL 422 Errosion / unsupported pipe N A NIL 141 Errosion / unsupported pipe N A NIL 301 Errosion / unsupported pipe NO NIL 56 Errosion / unsupported pipe NO NIL 413 Errosion / unsupported pipe N A NIL 431 Unknown Y E S NIL 434 Unknown Y E S NIL 10 Unknown Y E S NIL 405 Unknown Y E S NIL 422 Unknown N A NIL 435 Unknown N A NIL 407 Unknown Y E S 100 Unknown NO NIL 392 Unknown NO NIL 134 Unknown Y E S NIL 48 Unknown no 295 Unknown Y E S NIL 284 Unknown Y E S NIL 55 Unknown No • NIL 301 Unknown N O NIL 400 Unknown Y E S NIL 432 Unknown N A NIL 231 Unknown Y E S NIL 240 Unknown Y E S NIL . 408 Unknown N A NIL 72 Unknown NO NIL 283 Unknown N A NIL 409 Unknown N A NIL 76 Unknown No NIL 379 Unknown N A NIL 56 Unknown N O NIL 433 Unknown Y E S They would mark if leak type was unknown. 424 Unknown N O NIL 227 Unknown NO NIL 417 Unknown NO NIL 420 Unknown Y E S NIL 341 21 Unknown Y E S NIL 383 Unknown Y E S NIL 141 Unknown N A NIL 413 Unknown N A NIL 427 Unknown Y E S NIL 404 Unknown Y E S NIL 415 Unknown N A NIL . 414 Unknown Y E S Work Order System 260 Unknown N O NIL 103 Unknown N A NIL 423 411 Unknown NO NIL Unknown i N A NIL 249 Unknown N A NIL 402 Unknown NO NIL 403 Unknown Y E S NIL 342 Unknown Y E S NIL 430 Unknown NO NIL 120 Unknown N A NIL 418 Unknown NO NIL 419 Unknown Y E S NIL 332 Unknown N A NIL 428 Unknown NO NIL 112 Unknown Y E S NIL 389 Unknown N A NIL 42 Unknown N A NIL 416 Unknown NO NIL 401 Unknown Y E S NIL 426 Unknown NO NIL 342 Repair data recorded by survey respondents ->• . , • i- '. v,-, Data d u l l ) Description Recorded 426 Repair clamp Y E S 428 Repair clamp Y E S 427 Repair clamp Y E S 389 Repair clamp YES 112 Repair clamp Y E S 405 Repair clamp YES 418 Repair clamp Y E S 76 Repair clamp Y E S 411 Repair clamp Y E S 424 Repair clamp Y E S 260 Repair clamp Y E S 141 Repair clamp N A 404 Repair clamp YES 240 Repair clamp Y E S 408 Repair clamp Y E S 413 Repair clamp Y E S 283 Repair clamp Y E S 432 Repair clamp Y E S 21 Repair clamp Y E S 55 Repair clamp Y E S 342 Repair clamp Y E S 48 Repair clamp yes 379 Repair clamp Y E S 433 Repair clamp Y E S 249 Repair clamp Y E S 420 Repair clamp Y E S 416 Repair clamp Y E S 134 Repair clamp Y E S 332' Repair clamp Y E S ZZJ83 Repair clamp Y E S 423 Repair clamp Y E S 407 Repair clamp Y E S 103 Repair clamp YES 301 Repair clamp Y E S 430 Repair clamp Y E S 72 Repair clamp Y E S 295 Repair clamp Y E S 401 Repair clamp Y E S 403 Repair clamp Y E S 120 Repair clamp Y E S 400 Repair clamp Y E S 56 Repair clamp Y E S 415 Repair clamp YES 343 414 Repair clamp Y E S 434 Repair clamp Y E S 100 Repair clamp Y E S 431 Repair clamp Y E S 21284 Repair clamp Y E S 402_ Repair clamp Y E S 227 Repair clamp Y E S 42 Repair clamp Y E S 392 Repair clamp Y E S 422 Repair clamp N A 409 Repair clamp Y E S 419 Repair clamp Y E S 417 Repair clamp Y E S 10 Repair clamp Y E S 435 Repair clamp N A 231 Repair clamp Y E S 134 Replace pipe section Y E S 415 Replace pipe section Y E S 301__ Replace pipe section Y E S 422 Replace pipe section N A 342 Replace pipe section Y E S 332 Replace pipe section Y E S 417 Replace pipe section Y E S 433 Replace pipe section Y E S 411 Replace pipe section Y E S 419 Replace pipe section Y E S "2 408 Replace pipe section Y E S 141 Replace pipe section N A 48 Replace pipe section yes 227 Replace pipe section Y E S 409 Replace pipe section Y E S 103 Replace pipe section 427 Replace pipe section Y E S ... ?6 Replace pipe section Y E S 405 Replace pipe section Y E S 414 Replace pipe section Y E S 402 Replace pipe section Y E S 413 Replace pipe section Y E S 249 Replace pipe section Y E S 407 Replace pipe section Y E S 426 Replace pipe section Y E S 100 Replace pipe section Y E S 112 Replace pipe section Y E S 4 1 8 Replace pipe section Y E S 283 Replace pipe section Y E S 416 Replace pipe section Y E S 120 Replace pipe section Yl.s 428 Replace pipe section YI s 344 42 Replace pipe section Y E S 392 Replace pipe section Y E S _ 3 8 9 430 Replace pipe section Y E S Replace pipe section Y E S 260 i Replace pipe section Y E S 434 ; Replace pipe section Y E S 2 8 i _ _ 4 0 1 295 Replace pipe section Y E S Replace pipe section Y E S Replace pipe section Y E S 431 : Replace pipe section Y E S 400 ' L 4 3 5 10 Replace pipe section Y E S Replace pipe section N A Replace pipe section Y E S 72 i Replace pipe section Y E S 231 i Replace pipe section Y E S 432 i Replace pipe section Y E S 423 i Replace pipe section Y E S 403 ! Replace pipe section Y E S 420 i Replace pipe section Y E S 383 i Replace pipe section YES 379 i Replace pipe section NO 404 i Replace pipe section Y E S 55 Replace pipe section Y E S 76 Replace pipe section Y E S 21 Replace pipe section Y E S 240 Replace pipe section Y E S 424 Replace pipe section Y E S 420 Replace valve Y E S 402 Replace valve Y E S ' 284 Replace valve Y E S 401 i Replace valve Y E S 433 i Replace valve Y E S 417 i Replace valve Y E S 231 i Replace valve Y E S 422 i Replace valve N A 295 Replace valve Y E S 435 Replace valve N A . 10 Replace valve YES _ 21 403 Replace valve NO Replace valve Y E S 55 Replace valve Y E S 76 Replace valve Y E S 249 Replace valve Y E S 103 Replace valve Y E S 283 Replace valve NO 416 Replace valve YES 427 Replace valve Y E S 426 Replace valve Y E S 227 Replace valve YES 424 Replace valve YES 134 Replace valve YES 240 Replace valve YES 428 Replace valve Y E S 141 Replace valve N A 419 Replace valve YES 432 Replace valve Y E S 418 Replace valve Y E S 430 Replace valve Y E S 48 Replace valve yes 414 Replace valve Y E S 413 Replace valve Y E S 434 Replace valve Y E S 120 Replace valve Y E S 260 Replace valve Y E S 392 Replace valve Y E S 100 Replace valve Y E S __ 3 4 2 Replace valve Y E S 404 Replace valve Y E S 409 Replace valve Y E S 301 Replace valve Y E S 431 Replace valve Y E S 408 Replace valve Y E S 400 Replace valve Y E S 379 Replace valve YES 423 Replace valve YES . 72 Replace valve Y E S _ 407 Replace valve Y E S 389 Replace valve YI-.S 415 Replace valve Y l S 56 Replace valve NO 332 Replace valve Y E S 411 Replace valve Y E S 112 Replace valve Y E S 42 Replace valve Y E S 383 Replace valve Y E S 4 0 5 Replace valve Y E S 332 Replace service connection Y E S 433 Replace service connection Y E S 428 Replace service connection Y E S 134 Replace service connection YES 42_ Replace service connection Y E S 342 Replace service connection YES 48 Replace service connection yes 407 Replace service connection Y E S 301 Replace service connection Y E S 403 Replace service connection Y E S 3 8 9 Replace service connection YES ______ 418 Replace service connection YES _____ 423 Replace service connection YES 424 Replace service connection YES 112 Replace service connection YES 432 Replace service connection YES 383 Replace service connection NA _ 2 6 0 Replace service connection YES 404 Replace service connection YES 240 Replace service connection YES 422 Replace service connection NA 416 Replace service connection YES 55 Replace service connection YES 231 Replace service connection YES 379 Replace service connection YES 21 Replace service connection NO 120 Replace service connection YES 283 Replace service connection NO 295 Replace service connection YES 284 Replace service connection YES 419 Replace service connection YES 103 Replace service connection YES 401 Replace service connection NO 409 Replace service connection NA 227 Replace service connection YES 431 Replace service connection YhS 141 Replace service connection \ \ 414 Replace service connection YES 413 Replace service connection NA 56 Replace service connection YES 435 Replace service connection \ \ 400 Replace service connection NA 417 Replace service connection YES 415 Replace service connection YES 72 Replace service connection YES 10 Replace service connection YhS 402 Replace service connection YTS 249 Replace service connection YES 76 Replace service connection YES 434 Replace service connection YES 405 Replace service connection ^ 1 S 392 Replace service connection YES 426 Replace service connection YES 100 Replace service connection YES 420 Replace service connection NA 411 Replace service connection \ LS 408 Replace service connection vrs 427 Replace service connection YES 347 430 Replace service connection YES 112 Replace hydrant partes) YES 430 Replace hydrant part(s) YES • 231 Replace hydrant part(s) YES 435 Replace hydrant part(s) NA 72 Replace hydrant part(s) YES 418 Replace hydrant part(s) YES 400 Replace hydrant part(s) YES 295 Replace hydrant part(s) YES 260 Replace hydrant part(s) YES 434 Replace hydrant part(s) YES 42 Replace hydrant part(s) YES 416 Replace hydrant part(s) YES 100 Replace hydrant part(s) YES 428 Replace hydrant part(s) YES 431 Replace hydrant part(s) YES-392 Replace hydrant part(s) YES 240 Replace hydrant part(s) YES 401 Replace hydrant part(s) NO 284 Replace hydrant part(s) YES 120 Replace hydrant part(s) Y L S 283 Replace hydrant part(s) \ ( ) 103 Replace hydrant part(s) NA 426 Replace hydrant part(s) YES 48 Replace hydrant part(s) yes 249 Replace hydrant part(s) ^ 1 S 419 Replace hydrant part(s) YI S _____ 433 Replace hydrant part(s) ^ 1 S 414 Replace hydrant part(s) YES 134 Replace hydrant part(s) YES 10 Replace hydrant part(s) YI-.S 407 Replace hydrant part(s) YES 21 Replace hydrant part(s) NO ' _ 402 Replace hydrant part(s) YES 76 Replace hydrant part(s) YES 411 Replace hydrant part(s) ^ IS 227 Replace hydrant part(s) ^ IS 405 Replace hydrant part(s) YES 427 Replace hydrant part(s) YES 409 Replace hydrant part(s) ^ 1 S 332 Replace hydrant part(s) ^ CS 141 Replace hydrant part(s) NA 422 Replace hydrant part(s) NA 389 Replace hydrant part(s) YES 413 Replace hydrant part(s) NA 423 Replace hydrant part(s) YES 424 Replace hydrant part(s) YES 415 Replace hydrant part(s) YES 348 432 Replace hydrant part(s) NO 56 Replace hydrant part(s) NO _ _____ Replace hydrant part(s) Y E S 301 Replace hydrant part(s) Y E S 404 Replace hydrant part(s) Y E S 408 Replace hydrant part(s) Y E S 420 Replace hydrant part(s) Y E S 55 Replace hydrant part(s) Y E S 379 Replace hydrant part(s) NO 403 Replace hydrant part(s) Y E S 342 Replace hydrant part(s) Y E S 417 Replace hydrant part(s) Y E S 413 Replace entire hydrant N A 431 Replace entire hydrant YES 402 Replace entire hydrant Y E S . 295 Replace entire hydrant Y E S 417 Replace entire hydrant Y E S 72 Replace entire hydrant Y E S 415 Replace entire hydrant Y E S 414 Replace entire hydrant Y E S 301 Replace entire hydrant YES 76 Replace entire hydrant Y E S 389 Replace entire hydrant Y E S 432,. Replace entire hydrant Y E S 260 Replace entire hydrant Y E S 383 Replace entire hydrant Y E S 283 Replace entire hydrant NO 379 Replace entire hydrant Y E S 48 Replace entire hydrant yes 231 Replace entire hydrant Y l S 240 Replace entire hydrant Y E S 284 Replace entire hydrant Y E S 134 Replace entire hydrant Y E S 249 Replace entire hydrant YES 407 Replace entire hydrant Y E S 55 Replace entire hydrant Y E S 100 Replace entire hydrant Y E S 426 Replace entire hydrant Y E S 411 Replace entire hydrant Y E S 419 Replace entire hydrant Y E S 42 Replace entire hydrant Y E S 420 Replace entire hydrant YES 416 Replace entire hydrant Y E S 430 Replace entire hydrant Y E S 141 Replace entire hydrant N A 433 Replace entire hydrant Y E S 408 Replace entire hydrant Y E S 342 Replace entire hydrant Y E S 409 Replace entire hydrant Y E S 392 Replace entire hydrant Y E S 401 Replace entire hydrant NO 21 Replace entire hydrant NO 4 IS Replace entire hydrant Y E S 103 Replace entire hydrant Y E S 405 Replace entire hydrant Y E S 332 Replace entire hydrant Y E S 120 Replace entire hydrant ^ 1'S 428 Replace entire hydrant YES 427_ Replace entire hydrant YES 56 Replace entire hydrant NO 400 Replace entire hydrant Y E S 10 Replace entire hydrant Y E S 423 Replace entire hydrant Y1.S 403 Replace entire hydrant YES 435 Replace entire hydrant NA 424 Replace entire hydrant YES 422 Replace entire hydrant N A 112 Replace entire hydrant Y E S • 227 Replace entire hydrant Y E S 404 Replace entire hydrant Y E S 434 Replace entire hydrant Y E S 423 Anode installed NO 301 Anode installed Y E S 389 Anode installed NO 21 Anode installed Y E S 134 Anode installed Y E S 432 Anode installed N O 55 Anode installed Y E S 379 Anode installed NO 383 Anode installed NO 424 Anode installed Y E S 342 Anode installed NO 420 Anode installed Y E S 404 Anode installed NO 48 Anode installed no 141 Anode installed NA 415 Anode installed NO 422 Anode installed N \ 403 Anode installed NO 417 Anode installed Y E S 10 Anode installed YES 414 Anode installed YES 56 Anode installed NO 227 Anode installed Yl:S 402 Anode installed NO 103 Anode installed Y E S 350 409 Anode installed Y E S 433 Anode installed Y E S 419 Anode installed Y E S 411 Anode installed NO 427 426 408 Anode installed Anode installed Anode installed NO NO _ _ j NO 407 Anode installed Y E S 249 i Anode installed Y E S 405 i Anode installed Y E S 332 j Anode installed Y E S 413 Anode installed Y E S . 428 Anode installed Y E S 401 Anode installed Y E S 284 Anode installed Y E S 430 Anode installed NO 392 Anode installed Y E S 431 Anode installed Y E S 100 Anode installed Y E S 283 Anode installed Y E S 434 Anode installed NO 42 Anode installed Y E S 416 Anode installed Y E S 112 Anode installed Y E S 260 Anode installed Y E S 400 Anode installed Y E S 435 Anode installed N A 295 Anode installed Y E S 231 Anode installed NO 418 Anode installed NO 120 i Anode installed Y E S 72 Anode installed NO 240 Anode installed Y E S 76 i Anode installed NO 411 External protection installed . NO 427 i External protection installed N O 392 | External protection installed NO 100 External protection installed Y E S 55 External protection installed Y E S 408 ! External protection installed NO 426 ! External protection installed NO 231 i External protection installed NO 407 External protection installed Y E S 103 External protection installed N A 227 External protection installed Y E S 10 External protection installed Y E S 400 External protection installed NO 422 External protection installed N A f 351 403 External protection installed NO 72 External protection installed NO 414 External protection installed t^ 1 S 295 External protection installed ^ 1 S 141 External protection installed \ .\ 56 External protection installed NO 409 External protection installed Y E S 434 External protection installed NO 402 External protection installed Y E S 413 External protection installed N A 431 External protection installed Y E S 284 External protection installed Y E S 249 External protection installed Y E S 401 External protection installed NO 419 External protection installed YI-.S 4 . " External protection installed N A 416 External protection installed Y E S 48 External protection installed yes 379 External protection installed NO 112 External protection installed YES 420 External protection installed Y E S 430 External protection installed Y E S 283 External protection installed NO 415 External protection installed \() 42 External protection installed ^ 1 s 383 External protection installed YI S 342 External protection installed Y E S 404 External protection installed NO 424 External protection installed NO 260 External protection installed Y E S 432 External protection installed NO 389 External protection installed Yl.S 423 External protection installed NO 76 External protection installed ^ 1 S 418 External protection installed NO 417 External protection installed NO 332 External protection installed NO 405 External protection installed NO 120 External protection installed \() 433 External protection installed ,> 1 S 240 External protection installed vr.s 134 External protection installed Y E S 301 External protection installed NO 428 External protection installed Y E S 21 External protection installed Y E S 431 Repair joint Yl-.S 400 Repair joint Y l s 120 Repair joint Y E S 352 411 Repair joint Y E S 405 Repair joint Y E S 422 Repair joint N A " 414 Repair joint Y E S 42 Repair joint Y E S 389 Repair joint Y E S 404 Repair joint Y E S 72 Repair joint Y E S 408 Repair joint Y E S 260 Repair joint Y E S 379 Repair joint NO 407 Repair joint Y E S 342 Repair joint Y E S 112 Repair joint YES 409 Repair joint Y E S 434 Repair joint Y E S 383 Repair joint Y E S 301 Repair joint Y E S 392 Repair joint Y E S 56 Repair joint Y E S 413 Repair joint Y E S 100 Repair joint Y E S 332 Repair joint Y E S 423 Repair joint Y E S N A 21 Repair joint 231 Repair joint Y E S 76 Repair joint Y E S 433 Repair joint Y E S 141 Repair joint N A 419 i Repair joint Y E S 432 i Repair joint Y E S 240 i Repair joint YES 424 i Repair joint Y E S 55 : Repair joint Y E S 134 : Repair joint Y E S 427 i Repair joint YES 426 i Repair joint NO 283 i Repair joint Y E S 416 i Repair joint Y E S 418 ! Repair joint Y E S 249 1 Repair joint Y E S 103 Repair joint YES 4.28_ 417 48 10 Repair joint Y E S Repair joint Y E S Repair joint yes Repair joint Y E S 295 Repair joint Y E S 420 Repair joint Y E S / 353 435 Repair joint N A 430 Repair joint Y E S 403 Repair joint Y E S 415 Repair joint Y E S 284 Repair joint Y E S 227 Repair joint \ \ [ 402 Repair joint Y E S 401 Repair joint Y E S 389 Surface restoration Y E S 404 Surface restoration Y E S 424 Surface restoration Y E S 383 Surface restoration Y E S 342 Surface restoration Y E S 418 Surface restoration Y E S 420 Surface restoration Y E S 48 Surface restoration yes 417 Surface restoration NO 428 Surface restoration Y E S 432 Surface restoration Y E S 231 Surface restoration Y E S 400 Surface restoration Y E S 10 Surface restoration Y E S 295 Surface restoration Y E S 72 Surface restoration YES 434 Surface restoration Y E S 435 Surface restoration N A 284 Surface restoration Y E S 431 Surface restoration Y E S 112 Surface restoration Y E S 401 Surface restoration NO 76 Surface restoration Y E S 430 Surface restoration Y E S 100 Surface restoration Y E S 120 Surface restoration NO 240 Surface restoration Y E S 42 Surface restoration N A 283 Surface restoration • NO 416 Surface restoration Y E S _ 260 Surface restoration Y E S 423 Surface restoration Y E S 392 Surface restoration NO 402 Surface restoration Y E S 405 Surface restoration YES 249 Surface restoration Y E S 409 Surface restoration Y E S 56 ' Surface restoration NO 407 Surface restoration Y E S 413 Surface restoration . N A 354 414 Surface restoration Y E S 426 Surface restoration Y E S 227 Surface restoration Y E S 427 Surface restoration YES 379 Surface restoration YES 55 Surface restoration YES 141 Surface restoration N A 411 Surface restoration Y E S 419 Surface restoration YES 408 Surface restoration YES 301 Surface restoration YES 103 Surface restoration Y E S 21 Surface restoration Y E S 134 Surface restoration YES 403 Surface restoration Yl-S 332 Surface restoration ^ LS 422 Surface restoration N A 415 Surface restoration Y E S 433 Surface restoration Y E S 403 Dechlorination performed NO 415 Dechlorination performed SO 400 Dechlorination performed YES 100 Dechlorination performed NO 402 Dechlorination performed Y E S 120 Dechlorination performed NO 10 . Dechlorination performed Y E S 295 Dechlorination performed YES 231 Dechlorination performed S O 141 Dechlorination performed N A 413 Dechlorination performed N A 414 Dechlorination performed Y E S 392 Dechlorination performed NO 431 Dechlorination performed NO 56 Dechlorination performed YES 422 Dechlorination performed N A 72 Dechlorination performed NO 42 Dechlorination performed N A 227 Dechlorination performed Y E S 284 Dechlorination performed Y E S 435 Dechlorination performed N A 434 Dechlorination performed VPS 417 Dechlorination performed NO 401 Dechlorination performed NO 21_ Dechlorination performed NO 433 Dechlorination performed YES 389 Dechlorination performed YES 404 Dechlorination performed NO 405 Dechlorination performed Y E S 355 301 Dechlorination performed YES 424 Dechlorination performed NO 428 Dechlorination performed YES 134. Dechlorination performed NO 249 Dechlorination performed Y E S 383 Dechlorination performed Y E S 342 Dechlorination performed NO 332 Dechlorination performed NO 420 Dechlorination performed YES 48 Dechlorination performed no 379 Dechlorination performed NO 55 Dechlorination performed Y E S 408 Dechlorination performed NO 240 Dechlorination performed NO 409 Dechlorination performed Yl-S 411 Dechlorination performed NO 419 Dechlorination performed Y E S 427 Dechlorination performed NO 112 Dechlorination performed Y E S 4^2 Dechlorination performed NO 426 Dechlorination performed NO 418 Dechlorination performed NO 416 Dechlorination performed Y E S 76 Dechlorination performed NO 407 Dechlorination performed YES 260 Dechlorination performed YES 423 Dechlorination performed NO 103 Dechlorination performed N A 430 Dechlorination performed Y E S 283 Dechlorination performed Y E S 356 Environmental data recorded by survey respondents " : £ity {'ID Description Data Recorded Available from other • • ,.' Sources 379 Water temperature NO NO N A 411 Water temperature NO N A N A 405 Water temperature NO \ A N A 420 407 Water temperature NO NO N A Water temperature NO N A N A 332 Water temperature NO Y E S Other 432 Water temperature NO NO N A 419 Water temperature NO YES External 301 Water temperature NO N A N A 112 Water temperature NO N A N A 76 408 Water temperature NO Y E S Other Water temperature NO N A N A 404 Water temperature NO Y E S External 418 Water temperature NO NO N A 283 Water temperature NO NO N A 383 Water temperature NO N A N A 423 Water temperature _ N O NO Y E S Y E S O & M records 416 Water temperature O & M records 24() Water temperature NO Y E S External 389 Water temperature NO N A N A 424 Water temperature NO NO N A 415 Water temperature NO NO Other 22~ Water temperature NO NO N A 141 Water temperature N A Y E S External 402 Water temperature NO . NO N A 403 Water temperature NO NO N A 72 Water temperature NO N A N A 426 Water temperature NO NO N A 417 Water temperature NO NO N A 422 Water temperature N A N A N A 55 Water temperature No Y E S Other 249 Water temperature NO NO N A 21 Water temperature NO NO N A 56 Water temperature NO N A N A 103 Water temperature NO N A N A 134 Water temperature NO N O N A 414 Water temperature NO N A NIL 409 Water temperature NO Y E S O & M records 433 Water temperature N A N A N A 48 Water temperature no no N A 413 Water temperature NO N A N A 342 Water temperature NO N A N A 427 Water temperature NO N O N A 2l>5 Water temperature Y E S N O Archival 357 records 100 Water temperature NO N O N A 434 Water temperature NO N O N A 435 Water temperature NO Y E S Archival records 430 Water temperature NO NO N A 401 Water temperature NO Y E S Other 120 Water temperature N A N A N A 260 Water temperature NO N A N A 10 Water temperature NO N A N A 231 Water temperature N O NO N A 428 Water temperature NO N A N A 431 Water temperature NO Y E S i External 2S4 Water temperature N O Y E S O & M records 400 Water temperature NO NO N A 392 Water temperature NO ' NO N A 42 Water temperature no N A N A . 100 Air temperature NO Y E S External 112 Air temperature \ ( ) NA N \ 2S4 Air temperature Y E S Y E S External 426 Air temperature NO Y E S External 409 Air temperature NO Y E S External 408 Air temperature Y E S Y E S Archival records 405 Air temperature Y E S N A N A 411 Air temperature \ ( ) N A NA 55 Air temperature \ o Y E S Other 401 Air temperature NO Y E S External 301 Air temperature NO N A N A 134 Air temperature Y E S Y E S Other 249 Air temperature NO NO N A 422 Air temperature \ A N A N A 415 Air temperature NO NO Other 400 Air temperature Y E S NO N A . 56 Air temperature NO N A N A 433 Air temperature N A N A N A 295 Air temperature Y E S N O Archival records 413 Air temperature Y E S N A NA 417 Air temperature NO N O NA 414 Air temperature YI S Y E S Other 434 Air temperature NO NO N A 407 Air temperature NO N A N A 427 48 Air temperature NO NO _NA _____ N \ Air temperature' no no H)3 Air temperature . NO Air temperature NO N A N \ 419 Y E S External 420 Air temperature NO j NO N A 231 Air'temperature Y E S Y E S External 358 120 Air temperature N A N A N A 404 Air temperature ' NO Y E S External 283 Air temperature NO NO N A ' 383 Air temperature NO N A N A 418 Air temperature NO Y E S External 423 Air temperature NO Y E S O & M records 141 Air temperature N A N O N A 416 Air temperature NO Y E S O & M records 428 Air temperature NO N A N A 240 Air'temperature Y E S Y E S External 389 Air temperature Vl .S N A External 227 Ai r temperature NO NO N A 72 Air temperature NO N A N A Archival 260 Air temperature NO Y E S records 424 Air temperature NO Y E S External 76 Air temperature NO Y E S Other 431 Air temperature NO YES External 402 Air temperature NO NO N A 342 Air temperature Y E S N A External 403 Air temperature NO Y E S N A 392 Air temperature NO NO N A 430 Air temperature NO N O N A 21 Air temperature YES Y E S External Archival 435 Air temperature NO Y E S records 332 Air temperature NO Y I : S External 379 Air temperature NO NO N A 10 Air temperature NO N A N A 432 Air temperature NO Y E S External 42 Air temperature no N A N A 427 No. of consecutive days below 32 for 0 c NO N O N A 419 No. of consecutive days below 32 f or 0 c N O YES External 141 No. of consecutive days below 32 f or 0 c N A Y E S External 10 No. of consecutive days below 32 f or 0 c NO N A N A 426 No. of consecutive days below 32 for 0 c NO Y E S External 420 No. of consecutive days below 32 for 0 c N A N O N A 240 No. of consecutive days below 32 for 0 c NO Y E S External 428 No. of consecutive days below 32 f or 0 c NO N A N A 416 No. of consecutive days below 32 f or 0 c NO Y E S O & M records 283 No. of consecutive days below 32 f or 0 c NO NO N A 76 No. of consecutive days below 32 f or 0 c NO Y I S Other 418 No. of consecutive days below 32 f or 0 c NO YhS External 231 No. of consecutive days below 32 for 0 c NO Y E S External 430 No. of consecutive days below 32 for 0 c NO N O N A 21 No. of consecutive days below 32 f or 0 c NO Y I S External Archival 432 No. of consecutive days below 32 f or 0 c NO Y E S records 249 No. of consecutive days below 32 f or 0 c NO Y E S External 359 55 No. of consecutive days below 32 for 0 c No Y E S Other 284 No. of consecutive days below 32 f or 0 c NO Y E S External 401 No. of consecutive days below 32 f or 0 c NO Y E S External 48 No. of consecutive days below 32 f or 0 c no no N A 433 No. of consecutive days below 32 f or 0 c \ \ \ A \ \ 134 No. of consecutive days below 32 f or 0 c NO Y E S External 295 No. of consecutive days below 32 f or 0 c NO N A N A 435 No. of consecutive days below 32 for 0 c NO Y E S Archival records 103 No. of consecutive days below 32 for 0 c NO N A N A 424 No. of consecutive days below 32 f or 0 c N A N O N A 423 No. of consecutive days below 32 for 0 c NO Y E S External 409 No. of consecutive days below 32 f or 0 c N A Y E S External 413 No. of consecutive days below 32 f or 0 c N A N A N A 408 No. of consecutive days below 32 f or 0 c NO N A N A ' 411 No. of consecutive days below 32 f or 0 c NO N A N A 405 407 No. of consecutive days below 32 f or 0 c NO N A N A No. of consecutive days below 32 for 0 c NO N A N A 332 No. of consecutive days below 32 f or 0 c NO Y I S External 227 No. of consecutive days below 32 f or 0 c NO NO N A 342 No. of consecutive days below 32 f or 0 c NO Y E S External 379 No. of consecutive days below 32 for 0 c NO NO N A 414 No. of consecutive days below 32 f or 0 c \ ( ) N A NIL 383 No. of consecutive days below 32 f or 0 c N A \-\ \.\ 301 No. of consecutive days below 32 f or 0 c NO N A N A 389 No. of consecutive days below 32 for 0 c NO N A N A 112 No. of consecutive days below 32 f or 0 c NO N A N A 260 No. of consecutive days below 32 f or 0 c NO Y E S Archival records 120 No. of consecutive days below 32 f or 0 c N A ~1 N A N A 42 No. of consecutive days below 32 for 0 c no N A N A 392 No. of consecutive days below 32 f or 0 c \ ( ) N O N A 100 No. of consecutive days below 32 f or 0 c NO Y E S External 434 No. of consecutive days below 32 f or 0 c NO Y E S External 431 No. of consecutive days below 32 for 0 c NO Y E S External 400 No. of consecutive days below 32 f or 0 c N A N O N O N A _ N A _ ; N A ' 72 No. of consecutive days below 32 f or 0 c 404 No. of consecutive days below 32 f or 0 c NO Y E S External 415 No. of consecutive days below 32 f or 0 c YES NO Other 403 No. of consecutive days below 32 f or 0 c NO NO N A 402 No. of consecutive days below 32 f or 0 c Y E S Y E S O & M records 422 No. of consecutive days below 32 f or 0 c N A N A N \ 56 No. of consecutive days below 32 f or 0 c i NO N A N A 417 No. of consecutive days below 32 f or 0 c N A NO N A 10 Depth of frost NO N A N A 260 Depth of frost NO N A N A 112 Depth of frost NO N A N A 428 Depth of frost N O N A N A 240 Depth of frost Y E S N O N A 360 426 Depth of frost NO NO N A 423 Depth of frost NO Y E S External 42 Depth of frost Y E S N A . N A 416 Depth of frost NO 1 NO N A 301 Depth of frost NO NA N A 427 Depth of frost NO NO N A 76 404 Depth of frost NO Y E S Other Depth of frost NO Y E S External 417 Depth of frost NO NO N A 389 Depth of frost YI.S NA Other 141 227 Depth of frost N A YES External Depth of frost NO N O N A 72 Depth of frost NO N A N A 400 Depth of frost YI S N O N A 419 Depth of frost NO NO N A 435 Depth of frost NO N O N A 295 Depth of frost NO N A N A 231 Depth of frost Y E S NO N A 434 Depth of frost NO NO N A -120 Depth of frost N A NA N A 100 Depth of frost NO NO N A / 401 Depth of frost NO NO N A 284 Depth of frost , Y E S NO N A , 392 Depth of frost NO NO N A 402 Depth of frost NO NO N A : 383 Depth of frost NO i N A N A 430 Depth of frost NO 1 NO N A 431 Depth of frost NO Y E S External 48 Depth of frost no no N A 407 Depth of frost NO I N A N A 420 Depth of frost NO NO N A 379 Depth of frost NO NO N A 405 283 Depth of frost YES N A N A Depth of frost YES ! NO N A 249 Depth of frost NO NO NO NA YES NO N A N A Other' 411 Depth of frost 415 Depth of frost 21 Depth of frost NO NO N A 55 Depth of frost No M S Other 103 Depth of frost NO NA N A 413 Depth of frost Y E S N A N A 409 Depth of frost Y E S N A N A 433 Depth of frost N A N A N A 134 Depth of frost Y E S NO N A 56 Depth of frost NO i N A N A 414 Depth of frost YES YES Other 408 Depth of frost NO N A N A 403 Depth of frost Y E S Y E S Archival records 361 422 Depth of frost N A N A N A ' 432 Depth of frost Y E S • NO N A 424 Depth of frost Y E S N O N A 332 Depth of frost NO Y E S External 342 Depth of frost NO N A N A 418 Depth of frost NO Y E S External 134 419 Water temperature change NO NO N A Water temperature change NO NO N A 72 Water temperature change NO N A N A 379 Water temperature change N O NO N A ' 231 Water temperature change NO N O N A 76 Water temperature change NO Y E S Other 413 Water temperature change NO N A N A 431 Water temperature change NO Y E S External 383 Water temperature change NO N A N A 414 Water temperature change NO N A NIL 402 Water temperature change N O NO N A 295 Water temperature change Y E S NO Archival records 42 Water temperature change no N A N A 415 Water temperature change NO N O Other 417 Water temperature change \() N O N A 260 Water temperature change NO N A N A 407 Water temperature change N O N A N A 55 Water temperature change NO Y E S Other 301 Water temperature change N O N A N A 48 Water temperature change no no N A 426 Water temperature change NO N O N A 284 Water temperature change NO N O N A 249 Water temperature change NO Y E S O & M records 432 Water temperature change NO N O N A 411 Water temperature change - NO N A N A 283 Water temperature change N O NO N A 100 Water temperature change NO NO N A 240 Water temperature change NO NO N A 389 Water temperature change N A N A N A 403 Water temperature change NO N O N A • 416 Water temperature change NO Y E S O & M records 332 Water temperature change N O Y E S ! Other 56 Water temperature change NO N A N A 430 Water temperature change NO NO N A 408 Water temperature change NO N A N A 420 Water temperature change NO NO N A 120 Water temperature change N A N A N A 404 Water temperature change NO Y E S External 103 Water temperature change NO N A N A 21 Water temperature change NO N O N A 433 Water temperature change N A N A N A 401 Water temperature change NO Y E S Other 362 112 Water temperature change N O N A N A 392 Water temperature change NO NO N A Archival 435 Water temperature change NO Y E S records 423 Water temperature change NO Y E S External 418 Water temperature change N A Y E S O & M records 400 Water temperature change NO N O N A 141 Water temperature change N A Y E S External 424 Water temperature change \ ( ) NO N A 227 Water temperature change NO NO N A 405 Water temperature change NO N A N A 10 Water temperature change NO N A N A 422 Water temperature change N A N A .NA 342 Water temperature change NO N A N A 434 Water temperature change N O NO N A 428 Water temperature change N O N A N A 427 Water temperature change NO NO N A 409 Water temperature change NO N A N A 41 1 Soil temperature at pipe depth \ ( ) N A N A 48 Soil temperature at pipe depth no no N A - . 408 Soil temperature at pipe depth NO N A N A 420 Soil temperature at pipe depth NO NO N A 407 Soil temperature at pipe depth N O N A N A . 405 Soil temperature at pipe depth \ ( ) N \ N A 301 Soil temperature at pipe depth NO N A N A 424 Soil temperature at pipe depth NO N O N A 432 Soil temperature at pipe depth NO N O N A 55 Soil temperature at pipe depth NO N A N A 103 Soil temperature at pipe depth NO N A N A 402 Soil temperature at pipe depth N O N O N A 141 Soil temperature at pipe depth N A • NO N A 419 Soil temperature at pipe depth NO NO N A 227 Soil temperature at pipe depth NO N O N A 10 Soil temperature at pipe depth NO N A N A 427 Soil temperature at pipe depth N O N O N A 426 Soil temperature at pipe depth NO NO N A 433 Soil temperature at pipe depth N A N A N A 415 Soil temperature at pipe depth NO NO Other 21 Soil temperature at pipe depth N O NO N A 249 Soil temperature at pipe depth N O NO N A 422 Soil temperature at pipe depth N A N A N A 414 Soil temperature at pipe depth NO N A NIL 56 Soil temperature at pipe depth NO N A N A 332 Soil temperature at pipe depth N O N O N A 134 Soil temperature at pipe depth NO NO N A 413 Soil temperature at pipe depth NO N A N A 409 Soil temperature at pipe depth NO N A N A 403 Soil temperature at pipe depth NO N O N A 401 Soil temperature at pipe depth NO N O N A 363 428 Soil temperature at pipe depth NO N A N A 240 Soil temperature at pipe depth NO N O N A 417 Soil temperature at pipe depth NO N O N A 112 Soil temperature at pipe depth NO N A N A 430 Soil temperature at pipe depth NO NO N A 231 Soil temperature at pipe depth NO NO N A 42 Soil temperature at pipe depth no N A N A 423 Soil temperature at pipe depth NO NO N A 100 Soil temperature at pipe depth NO NO N A 260 Soil temperature at pipe depth NO N A N A 284 Soil temperature at pipe depth NO NO NA-392 Soil temperature at pipe depth NO N O N A 431 Soil temperature at pipe depth NO NO N A 435 Soil temperature at pipe depth NO NO N A 295 Soil temperature at pipe depth NO N A N A . 434 Soil temperature at pipe depth NO NO N A 72 Soil temperature at pipe depth NO N A N A ' • 400 Soil temperature at pipe depth NO NO N A 120 Soil temperature at pipe depth N A N A N A 76 Soil temperature at pipe depth NO Y E S Other 342 Soil temperature at pipe depth NO N A N A 418 Soil temperature at pipe depth NO NO N A 389 Soil temperature at pipe depth NO N A ' N A 383 Soil temperature at pipe depth \ o N A N A 404 Soil temperature at pipe depth \() YI S External 379 Soil temperature at pipe depth NO N O N A 283 Soil temperature at pipe depth NO N O N A 416 Soil temperature at pipe depth NO NO N A 403 Soil sample taken NO NO N A 405 Soil sample taken NO N A N A 3«>2 Soil sample taken NO NO N A 431 Soil sample taken Y E S NO N A 415 Soil sample taken NO NO Other 417 Soil sample taken NO N O N A 120 Soil sample taken N A N A N A 227 Soil sample taken NO NO N A 379 Soil sample taken NO NO N A 434 Soil sample taken Y E S NO N A 72 Soil sample taken NO N A N A 402 Soil sample taken NO NO N A 400 Soil sample taken NO NO N A • 301 Soil sample taken NO N A N A 408 Soil sample taken NO N A N A ' 411 Soil sample taken NO N A N A 423 Soil sample taken NO N O N A 409 Soil sample taken Y E S NA N A . 389 Soil sample taken NO N A N A 404 Soil sample taken NO Y E S External ( 364 260 Soil sample taken NO N A N A 383 Soil sample taken NO N A N A 56 Soil sample taken NO N A N A 342 Soil sample taken N A N A | N A 332 Soil sample taken NO Y E S : External 42 Soil sample taken no N A N A 407 Soil sample taken NO N A N A 414 Soil sample taken NO N A NIL 422 Soil sample taken N A N A NA 100 Soil sample taken NO NO N \ 112 Soil sample taken NO N A N A 413 Soil sample taken NO N A | N A 432 231 Soil sample taken ' NO NO N \ Soil sample taken NO NO NA 103 Soil sample taken NO NA X \ 249 Soil sample taken NO NO N ' \ 418 Soil sample taken NO NO I N A 284 Soil sample taken NO N O 1 N A 295 Soil sample taken NO N A ! N A 435 Soil sample taken NO NO N A 430 Soil sample taken NO NO N A 134 Soil sample taken NO N O N A 76 Soil sample taken NO Y E S Other - 424 Soil sample taken N O NO N A 21 Soil sample taken Y E S NO I N A 48 Soil sample taken no no N A 55 Soil sample taken N O N A N A 420 240 Soil sample taken NO NO N A Soil sample taken Y E S NO N A 401 Soil sample taken NO NO N A 433 Soil sample taken N A N A \ A 427 Soil sample taken NO NO i N A 428 Soil sample taken NO N A NA 10 419 Soil sample taken NO N A i N A Soil sample taken NO NO ! N A 426 Soil sample taken NO NO N - \ 141 Soil sample taken N A NO N A 283 416 Soil sample taken NO NO N A Soil sample taken NO NO N A 423 Soil P H NO NO ! N A 407 Soil P H NO N A N \ 417 Soil P H NO NO N A 428 Soil P H NO N A N A 401 Soil P H NO NO N A 100 Soil P H NO NO N A 405 Soil PH NO N A N A 240 Soil P H Y E S NO N A 260 Soil P H NO N A N A 365 301 Soil P H NO N A N A 424 Soil P H NO NO N A 55 Soil P H NO N A N A 389 Soil P H NO N A N A 383 Soil P H N O N A N A 416 Soil P H N O NO N A 404 Soil P H NO Y E S , External 342 Soil PH N A N A N A 284 Soil P H NO N O N A 432 Soil P H NO N O N A 112 Soil P H NO N A N A 430 Soil I ' l l NO NO N A 231 Soil P H NO NO N A 283 Soil P H N O NO N A 379 Soil P H NO NO N A 42 Soil P H no N A N A 120 Soil P H N A N A N A 76 Soil P H NO Y E S Other 418 Soil P H NO N O N A 426 Soil P H NO NO N A 433 Soil P H N A N A N A 414 Soil P H N O N A NIL 295 Soil P H N O N A N A 408 Soil P H NO N A N A 422 Soil P H N A N A N A 103 Soil P H NO N A N A 415 Soil P H NO N O Other 56 Soil P H NO N A N A 403 Soil P H NO NO N A 434 Soil P H YES NO N A 427 Soil P H NO NO \ \ 10 Soil P H NO N A N A 227 Soil P H NO NO N A 419 Soil P l l NO NO N \ 141 Soil P l l N A NO \ A 402 Soil P H NO NO \ A 400 Soil P H - NO NO N A 72 Soil P H NO N A N A 411 Soil P H NO N A ^ N A _ 420 Soil P H NO N O N A 332 So i lPH N O NO N A 413 Soil P H NO N A N A 134 Soil P H NO NO N A 48 So i lPH no no N A 431 Soil PH NO NO N A 249 Soil P H NO NO \ \ 409 Soil P H NO N A \ ' \ 392 Soil P H NO NO N A 366 21 Soil P H NO N O N A 435 Soil P H NO N O N A 10 Soil moisture content NO N A N A 392 Soil moisture content NO NO N A 400 Soil moisture content NO NO N A 120 Soil moisture content N A N A N A 240 Soil moisture content N O NO N A 430 Soil moisture content N O NO N A 112 Soil moisture content NO N A N A 295 Soil moisture content NO N A N A 42 Soil moisture content no N A N A 72 Soil moisture content NO N A N A 431 Soil moisture content NO N O N A 434 Soil moisture content NO NO N A 284 Soil moisture content NO NO N A 435 Soil moisture content N A N A N A 401 Soil moisture content NO NO N A 231 Soil moisture content NO NO N A 100 Soil moisture content NO NO N A 103 Soil moisture content NO N A N A 379 Soil moisture content NO NO N A 409 Soil moisture content NO N A N A 21 Soil moisture content NO NO N A 134 Soil moisture content NO NO N A 413 Soil moisture content NO N A N A 56 Soil moisture content NO N A N A 433 Soil moisture content N A N A N A . 249 Soil moisture content NO N O N A 48 Soil moisture content no no N A 422 Soil moisture content N A . N \ N A 420 Soil moisture content NO NO N A 415 Soil moisture content NO NO Other 403 Soil moisture content NO NO N A 426 Soil moisture content NO NO N A 42" Soil moisture content NO NO N A 41" Soil moisture content N O NO N A 227 Soil moisture content NO NO N A 419 Soil moisture content N A N A N A 402 Soil moisture content NO NO N A 414 Soil moisture content NO N A ' NIL 332 Soil moisture content NO VI.S External 423 Soil moisture content NO NO N A 428 Soil moisture content NO N A N A 283 Soil moisture content NO NO N A 389 Soil moisture content NO N A N A . 404 Soil moisture content NO ^ IS External 416 Soil moisture content NO NO N A 76 Soil moisture content NO Y E S Other 367 . 383 Soil moisture content N A N A N A 411 Soil moisture content NO N A N A 418 Soil moisture content NO N O N A 260 Soil moisture content N O N A N A 141 Soil moisture content \ . NO N A 432 Soil moisture content NO \ ( ) N A 301 Soil moisture content NO N A N A 405 Soil moisture content Y E S N A N A 424 Soil moisture content NO NO N A 55 Soil moisture content NO N A N A 407 Soil moisture content NO N A N A 408 Soil moisture content NO N A N A 342 Soil moisture content NO N - \ N A 368 Types of failure recorded by survey respondents • City ID • Description DataRecorded -v'-V/,-v Comments* ." 21 Blow out Y E S NIL 42 Blow out YES NIL 55 Blow out Y E S NIL 56 Blow out NO NIL ~ 72 Blow out Y E S NIL 100 Blow out NO NIL 103 Blow out Y E S NIL 112 Blow out Y E S NIL 120 Blow out Y E S NIL 134 Blow out Y E S NIL 227 Blow out ^ 1 s NIL 231 Blow out Y E S NIL 240 Blow out Y E S NIL 249 Blow out YES NIL 260 Blow out Y E S NIL 283 Blow out Y E S NIL 284 Blow out Y E S NIL 295 Blow out Y E S NIL 301 Blow out YES NIL 332 Blow out YES NIL 383 Blow out YES NIL 392 Blow out Y E S NIL 400 Blow out YES NIL 401 Blow out Y E S NIL 413 Blow out NA NIL 418 Blow out Y E S NIL 424 Blow out Y E S NIL 42S Blow out \() NIL 433 Blow out YI : S NIL 435 Blow out YI:S NIL 10 Blow out YES NIL 48 Blow out N A NIL 76 Blow out Y E S NIL 141 Blow out YES NIL 342 Blow out Yl'.S NIL 379 Blow out Y E S NIL 389 Blow out Y E S NIL 402 Blow out NO NIL 403 Blow out Y E S NIL 404 Blow out YI-S NIL 405 Blow out Y E S NIL 407 Blow out Y E S NIL 408 Blow out NO NIL 409 Blow out Y E S NIL 411 Blow out NA NIL 369 414 Blow out YES | Work Order System 415 Blowout Blow out YES M I 41d YES Field Experience 417 Blow out Y E S NIL 419 Blowout YES NIL 420 Blow out Y E S NIL 422 Blowout N A NIL 42? Blow out YES M L 420 Blow out NO M I . 427 Blow out Y E S NIL 430 Blow out Y E S NIL 431 Blow out Y E S NIL 432 Blow out Y E S NIL 434 Blowout YES NIL 21 Corrosion pit hole YES M l . 42 Corrosion pit hole Y l S NIL 55 Corrosion pit hole Y E S NIL 56 Corrosion pit hole Y E S NIL 72 Corrosion pit hole Y E S NIL 100 Corrosion pit hole NO NIL 103 Corrosion pit hole YES NIL 112 Corrosion pit hole YES NIL 120 Corrosion pit hole YES NIL 134 Corrosion pit hole YES NIL 227 Corrosion pit hole YES NIL 231 Corrosion pit hole Y E S NIL 240 Corrosion pit hole YES NIL 249 Corrosion pit hole Corrosion pit hole YES NIL 260 YES M I 283 Corrosion pit hole Y E S M l 2S4 Corrosion pit hole s YES NIL 295 Corrosion pit hole Y E S NIL 301 Corrosion pit hole i YES NIL 332 Corrosion pit hole YES NIL 383 Corrosion pit hole N A NIL Corrosion pit hole YES NIL 400 Corrosion pit hole N A NIL 401 Corrosion pit hole YES NIL 413 Corrosion pit hole N A NIL 418 Corrosion pit hole Y E S NIL 424 Corrosion pit hole vrs NIL 428 Corrosion pit hole NO NIL 433 Corrosion pit hole Y E S NIL •435 Corrosion pit hole Y E S NIL 10 Corrosion pit hole Y E S NIL 4S Corrosion pit hole N A NIL " f t Corrosion pit hole i Y E S NIL 141 Corrosion pit hole YES NIL 342 Corrosion pit hole YES NIL 370 379 Corrosion pit hole Y E S NIL 389 Corrosion pit hole Y E S NIL 402 Corrosion pit hole NO NIL 403 ! Corrosion pit hole Y E S NIL 404 i Corrosion pit hole Y E S NIL 405 Corrosion pit hole YES NIL 407 Corrosion pit hole Y E S NIL Corrosion pit hole NO NIL 409 Corrosion pit hole N A M l 411 i Corrosion pit hole N A M l 414 Corrosion pit hole Y E S Work Order System 415 416 Corrosion pit hole Y E S NIL Corrosion pit hole Y E S Field Experience 417 i Corrosion pit hole Y E S NIL 419 Corrosion pit hole • YES NIL 420 Corrosion pit hole Y E S NIL 422 Corrosion pit hole N A NIL 423 Corrosion pit hole Y E S NIL 426 Corrosion pit hole NO NIL 427 Corrosion pit hole Y E S NIL 430 Corrosion pit hole Y E S NIL 431 Corrosion pit hole Y E S NIL • 432 Corrosion pit hole Y E S NIL 434 Corrosion pit hole Y E S NIL 21 | Curbstop failure NO NIL 42 Curbstop failure Y E S NIL 55 Curbstop failure Y E S NIL 56 Curbstop failure Y E S NIL 72 Curbstop failure Y E S NIL 100 Curbstop failure Y E S NIL 103 : Curbstop failure . N A NIL 112 Curbstop failure Y E S MI 120 Curbstop failure YES NIL 134 Curbstop failure Curbstop failure Curbstop failure YES • YES NIL 227 NIL 231 YES NIL 240 Curbstop failure i YES NIL 249 Curbstop failure Y E S NIL 260 Curbstop failure Y E S NIL 283 Curbstop failure NO NIL 284 i Curbstop failure Y E S NIL 295 i Curbstop failure Y E S NIL 301 Curbstop failure Y E S NIL 332 Curbstop failure Y E S NIL 383 Curbstop failure Y E S NIL 392 Curbstop failure Y E S NIL 400 Curbstop failure NO NIL 401 Curbstop failure NO recorded in other databases 413 Curbstop failure Y E S NIL 371 418 Curbstop failure Y E S NIL 424 Curbstop failure Y E S NIL 428 Curbstop failure NO NIL 433 Curbstop failure Y E S NIL 435 ! Curbstop failure Y E S NIL 10 i Curbstop failure Y E S NIL 48 ! Curbstop failure N A NIL 76 j Curbstop failure Y E S NIL 141 i Curbstop failure Y E S NIL 342 i Curbstop failure Y E S NIL 379 j Curbstop failure > Y E S NIL 389 ! Curbstop failure Y E S \1I 402 403 Curbstop failure YES NIL Curbstop failure Y E S NIL 404 Curbstop failure YES NIL 405 Curbstop failure Y E S NIL 407 i Curbstop failure Y E S NIL 408 i Curbstop failure NO NIL 409 Curbstop failure Y E S NIL 411 Curbstop failure Y E S NIL 414 Curbstop failure Y E S Work Order System 415 Curbstop failure Y E S NIL 416 Curbstop failure Y E S Field Experience 417 419 Curbstop failure Y E S N i l Curbstop failure Y E S NIL 420 Curbstop failure Y E S NIL 422 Curbstop failure N A NIL 423 Curbstop failure Y E S NIL 426 Curbstop failure NO NIL 427 : Curbstop failure Y E S NIL 430 i Curbstop failure Y E S NIL 431 Curbstop failure Y E S NIL 432 Curbstop failure v NO NIL 434 Curbstop failure NO (service failure) 21 Failed blow-off NO NIL 42 Failed blow-off Y E S NIL 55 I Failed blow-off Y E S NIL 56 Failed blow-off NO NIL 72 Failed blow-off Y E S NIL 100 Failed blow-off NO NIL 10? 1 ailed blow-off N A • NIL 112. Failed blow-off Y E S NIL 120 Failed blow-off Y E S NIL 134 Failed blow-off Y E S NIL 227 Failed blow-off Y E S NIL 231 1 ailed blow-off Y E S NIL 240 Failed blow-off Y E S NIL 249 Failed blow-off Y E S NIL 260 Failed blow-off Y E S NIL 372 283 Failed blow-off NO NIL 284 Failed blow-off Y E S NIL 295 Failed blow-off Y E S NIL 301 332 383 392 Failed blow-off Y E S NIL Failed blow-off YES' NIL Failed blow-off Y E S NIL Failed blow-off NO NIL 400 ! Failed blow-off Y E S NIL 401 Failed blow-off Y E S NIL 413 i Failed blow-off N A NIL 418 Failed blow-off YI'S NIL 424 Failed blow-off NO NIL 428 Failed blow-off NO NIL 433 Failed blow-off Y E S ,NIL 435 Failed blow-off Y E S NIL 10 Failed blow-off Y E S NIL 48 ! Failed blow-off N A NIL 76 i Failed blow-off Y E S NIL 141 Failed blow-off Y E S NIL 342 Failed blow-off Y E S NIL 379 Failed blow-off NO NIL -389 Failed blow-off Y E S NIL 402 Failed blow-off NO NIL •403 Failed blow-off Y E S NIL 404 Failed blow-off Y E S NIL 405 • Failed blow-off Y E S NIL 407 Failed blow-off Y E S NIL 408 ' Failed blow-off NO _ Y E S NIL 409 Failed blow-off NIL 411 : Failed blow-off N A Ni l 414 : Failed blow-off Y E S Work Order System 415 Failed blow-off Y E S NIL , 416 Failed blow-off Y E S Field Experience 417 Failed blow-off NO NIL 419 Failed blow-off Y E S NIL 420 Failed blow-off Y E S NIL 422 Failed blow-off N A NIL 423 Failed blow-off Y E S NIL 426 Failed blow-off NO NIL 427 Failed blow-off Y E S NIL 430 1 ailed blow-off Y E S NIL 431 Failed blow-off Y E S NIL 432 Failed blow-off NO NIL 434 Failed blow-off Y E S NIL 21 i Leaking hydrant NO NIL 42 i Leaking hydrant Y E S NIL 55 i Leaking hydrant Y E S NIL 56 Leaking hydrant NO NIL 72 Leaking hydrant Y E S NIL 373 100 Leaking hydrant Y E S NIL 103 Leaking hydrant Y E S NIL 112 Leaking hydrant Y E S NIL 120 Leaking hydrant YES NIL 134 Leaking hydrant Y E S NIL 227 Leaking hydrant Y E S NIL 231 Leaking hydrant Y E S NIL 240 Leaking hydrant Y E S NIL 249 Leaking hydrant YES NIL 260 Leaking hydrant Y E S NIL 283 Leaking hydrant NO NIL 284 Leaking hydrant Y E S NIL .295 Leaking hydrant Y E S NIL 301 Leaking hydrant Y E S NIL 332 Leaking hydrant YES NIL 383 Leaking hydrant YES NIL 392 Leaking hydrant Y E S NIL 400 Leaking hydrant NO NIL 401 Leaking hydrant NO recorded in other databases 413 Leaking hydrant \ \ NIL 418 Leaking hydrant Y E S NIL 424 Leaking hydrant Y E S NIL 428 Leaking hydrant NO . NIL 433 Leaking hydrant Y E S NIL 435 Leaking hydrant Y E S NIL 10 Leaking hydrant Y E S NIL 48 Leaking hydrant N A NIL 76 Leaking hydrant Y E S NIL 141 Leaking hydrant Y E S NIL 342 Leaking hydrant YES NIL 379 Leaking hydrant V I S NIL 389 Leaking hydrant Y E S NIL 402 Leaking hydrant Y E S NIL 403 Leaking hydrant YES NIL 404 Leaking hydrant YES NIL . 405 Leaking hydrant V I S NIL 407 Leaking hydrant Y E S NIL 408 Leaking hydrant Y E S NIL 409 Leaking hydrant Yl-S NIL 411 Leaking hydrant Y L S Ni l 414 Leaking hydrant Y E S Work Order System 415 Leaking hydrant Y E S NIL 416 Leaking hydrant Y E S Field Experience 417 Leaking hydrant Y E S NIL 419 Leaking hydrant Y E S NIL 420 Leaking hydrant Y E S NIL 422 Leaking hydrant N A NIL 423 Leaking hydrant Y E S NIL 426 Leaking hydrant Y E S NIL 374 427 Leaking hydrant Y E S NIL 430 Leaking hydrant Y E S NIL 431 Leaking hydrant Y E S NIL 432 i Leaking hydrant Y E S NIL 434 i Leaking hydrant Y E S NIL 21 Leaking joint YES NIL 42 " Leaking joint YES NIL 55 Leaking joint YES NIL 56 Leaking joint N O NIL 72 | Leaking joint Y E S NIL 100 : Leaking joint NO NIL 103 Leaking joint .YES NIL 112 Leaking joint Y E S NIL 120 i Leaking joint Y E S NIL 134 Leaking joint Y E S NIL 227 Leaking joint Y E S NIL 231 Leaking joint Y E S NIL 240 Leaking joint Y E S NIL 249 Leaking joint Y E S NIL 2(>0 Leaking joint Y E S M l . 283 Leaking joint Y E S NIL 284 Leaking joint YES NIL 295 Leaking joint Y E S NIL 301 Leaking joint Y E S NIL 332 Leaking joint Y E S NIL 383 Leaking joint Y E S NIL 392 Leaking joint Y E S NIL 400 Leaking joint NO NIL 401 Leaking joint Y E S NIL 413 Leaking joint Y E S NIL 418 i Leaking joint Y1:S NIL 424 | Leaking joint ^ 1 S M I 428 Leaking joint NO NIL 433 Leaking joint Y E S NIL 435 Leaking joint Y E S NIL 10 i Leaking joint Y E S NIL 48 i Leaking joint N A NIL 76 Leaking joint Y E S NIL 141 Leaking joint Y1".S NIL 342 Leaking joint YES NIL 3~9 Leaking joint YES NIL 389 Leaking joint Y E S NIL 402 i Leaking joint NO NIL 403 Leaking joint Y E S NIL 404 Leaking joint Y E S NIL 405 Leaking joint Y E S NIL 407 Leaking joint YES NIL 408 Leaking joint NO NIL r 409 Leaking joint YES NIL 375 411 Leaking joint Y E S NIL 414 Leaking joint Y E S Work Order System 415 Leaking joint YES NIL 416 Leaking joint YES Field Experience 417 Leaking joint YES NIL 419 Leaking joint Y E S NIL 420 Leaking joint Y E S NIL 422 Leaking joint N A NIL 423 Leaking joint Y E S NIL 426 Leaking joint NO NIL 427 Leaking joint Y E S NIL 430 Leaking joint Y E S NIL 431 Leaking joint Y E S • NIL 432 Leaking joint Y E S NIL 434 Leaking joint V I S Ni l 21 Leaking service connection NO NIL 42 Leaking service connection V I S NIL 55 Leaking service connection YES NIL 56 Leaking service connection Y E S NIL 72 Leaking service connection Y E S NIL 100 Leaking service connection NO NIL 103 Leaking service connection N A NIL 112 Leaking service connection ,> 1 s NIL 120 Leaking service connection Y r s Ni l 134 Leaking service connection Y E S NIL 227 Leaking service connection YES NIL 231 Leaking service connection Y E S NIL 240 Leaking service connection Y E S NIL 249 Leaking service connection Y E S NIL 260 Leaking service connection Y E S NIL 283 Leaking service connection NO NIL 284 Leaking service connection Y E S NIL 295 Leaking service connection Y E S NIL 301 Leaking service connection Y E S NIL 332 Leaking service connection Y E S NIL 383 Leaking service connection YES Ni l 392 Leaking service connection Y E S NIL 400 Leaking service connection .YES NIL 401 Leaking service connection NO recorded in other databases 413 Leaking service connection Y E S NIL 418 Leaking service connection Y E S NIL 424 Leaking service connection Y E S NIL 428 Leaking service connection NO NIL 43- ? Leaking service connection ^ 1 S NIL 4 " Leaking service, connection V I S NIL 10 Leaking service connection Y E S NIL 48 Leaking service connection N A NIL 76 Leaking service connection Y E S NIL 141 Leaking service connection Y E S NIL 376 342 Leaking service connection YES NIL 379 Leaking service connection YES NIL 389 Leaking service connection YES NIL 402 Leaking service connection YES NIL 403 Leaking service connection YES NIL 404 Leaking service connection YES NIL 405 Leaking service connection YES NIL 407 Leaking service connection YES NIL 408 Leaking service connection NO NIL 409 Leaking service connection YES NIL 411 Leaking service connection YES NIL 414 Leaking service connection YES Work Order System 415 Leaking service connection YES NIL 416 Leaking service connection YES Field Experience 417 Leaking service connection YES NIL 419 Leaking service connection YES NIL 420 Leaking service connection YES NIL 422 Leaking service connection NA NIL 423 Leaking service connection YES NIL 426 Leaking service connection YES NIL 427 Leaking service connection ^ L S NIL 430 Leaking service connection YES NIL 431 Leaking service connection YES NIL 432 Leaking service connection YES NIL 434 Leaking service connection YES NIL 21 Leaking valve NO NIL 42 Leaking valve YES NIL 55 Leaking valve YES NIL 56 Leaking valve NO NIL 72 Leaking valve YES NIL 100 Leaking valve NO NIL 103 Leaking valve YES NIL 112 Leaking valve YES NIL 120 Leaking valve YES NIL 134 Leaking valve Y l S NIL 227 Leaking valve Y L S NIL 231 Leaking valve Y l . S M l 240 Leaking valve \ 1 S NIL 249 Leaking valve YES NIL 260 Leaking valve YES NIL 283 Leaking valve \() NIL 284 Leaking valve YES NIL 295 Leaking valve YES NIL 301 Leaking valve YES NIL 332 Leaking valve YES NIL 383 Leaking valve \ 1 S NIL 392 Leaking valve Y L S NIL 400 Leaking valve YES NIL 401 Leaking valve NO recorded in other databases 377 413 Leaking valve Y E S NIL 418 Leaking valve Y E S NIL 424 Leaking valve Y E S NIL 428 Leaking valve NO NIL 433 Leaking valve Y E S NIL 435 Leaking valve Y E S NIL 10 Leaking valve Y E S NIL 48 Leaking valve N A NIL 76 Leaking valve YES NIL 141 Leaking valve Y E S NIL 342 Leaking valve Y E S NIL 379 Leaking valve Y E S NIL 389 Leaking'valve Y E S NIL 402 Leaking valve Y E S NIL 403 Leaking valve Y E S NIL 404 Leaking valve Y E S NIL 405 Leaking valve Y E S NIL 407 Leaking valve Y E S NIL 408 Leaking valve Y E S NIL 409 Leaking valve Y E S N i l 411 Leaking valve Y E S NIL 414 Leaking valve Y E S Work Order System 415 JLeaking valve Y E S NIL 416 Leaking valve YI S ^ LS Field Experience 417 Leaking valve . NIL 419 Leaking valve Y E S NIL 420 Leaking valve Y E S NIL - 422 Leaking valve N A NIL 423 Leaking valve Y E S NIL 426 Leaking valve NO NIL 427 Leaking valve Y E S NIL 430 Leaking valve YES NIL 431 Leaking valve Y E S NIL 432 Leaking valve Y E S NIL 434 Leaking valve Yl .S NIL 21 Longitudinal break V I S NIL 42 Longitudinal break Y E S NIL 55 Longitudinal break Y E S NIL 56 Longitudinal break Y E S NIL 72 Longitudinal break i NO NIL 100 Longitudinal break NO NIL 103 Longitudinal break Y E S NIL 112 Longitudinal break YES NIL 120 Longitudinal break Y E S NIL 134 Longitudinal break Y E S NIL 227 Longitudinal break Y E S NIL 231 Longitudinal break Y E S NIL 240 Longitudinal break YES NIL 249 Longitudinal break Y E S NIL 378 2 6 0 Longitudinal break Y E S NIL 2 8 3 Longitudinal break YES NIL 2 S 4 Longitudinal break YES NIL 2 9 5 Longitudinal break YES NIL 3 0 1 Longitudinal break YES NIL 3 3 2 Longitudinal break YES NIL 3 8 3 Longitudinal break Y E S NIL 3 9 2 Longitudinal break Y E S NIL 4 0 0 Longitudinal break YES NIL 4 0 1 Longitudinal break YES NIL 4 1 3 Longitudinal break YES M l 4 1 8 Longitudinal break YES NIL 4 2 4 Longitudinal break YES NIL 4 2 8 Longitudinal break NO NIL 4 3 3 Longitudinal break YES NIL 4 3 5 Longitudinal break YES NIL 1 0 Longitudinal break NO NIL 4 8 Longitudinal break N A NIL 7 6 Longitudinal break Y E S NIL 141 Longitudinal break Y E S NIL 3 4 2 Longitudinal break , Y E S NIL 3 7 9 Longitudinal break Y E S NIL 3 8 9 Longitudinal break Y E S NIL 4 0 2 Longitudinal break NO M I 4 0 3 Longitudinal break YES NIL 4 0 4 Longitudinal break Y E S NIL 4 0 5 Longitudinal break YES NIL 4 0 7 4 0 8 Longitudinal break Y E S NIL Longitudinal break NO NIL 4 0 9 Longitudinal break Y E S NIL 4 1 1 i Longitudinal break N A NIL 4 1 4 Longitudinal break ,> 1 s Work Order System 4 1 5 Longitudinal break Y E S NIL 4 1 6 Longitudinal break Y E S Field Experience 4 1 7 Longitudinal break Y E S NIL 4 1 9 ! Longitudinal break Y l S NIL v 4 2 0 Longitudinal break YI :S NIL 4 2 2 Longitudinal break N A NIL 4 2 3 Longitudinal break Y E S NIL 4 2 6 Longitudinal break NO NIL 4 2 " Longitudinal break YES NIL 4 3 0 Longitudinal break ^ 1 S NIL 4 3 1 Longitudinal break Y E S NIL 4 3 2 Longitudinal break Y E S NIL 4 3 4 Longitudinal break ^ L S NIL 21 Split bell N O NIL 4 2 Split bell YES NIL 5 5 Split bell YES NIL 5 6 Split bell YES NIL 379 72 Split bell Y E S NIL 100 Split bell N O NIL 103 Split bell Y E S NIL 112 120 134 227 Split bell Y E S NIL . Split bell Y E S NIL Split bell Y E S NIL Split bell NO NIL 231 Split bell Y E S NIL 240 Split bell Y E S NIL 249 ! Split bell Y E S NIL 260 Split bell Y E S NIL 283 Split bell Y E S NIL 284 Split bell Y E S NIL 295 Split bell Y E S \ I I M)\ Split bell YES M l . 332 Split bell Y E S NIL 383 Split bell Y E S NIL 392 Split bell Y E S NIL 400 Split bell Y E S NIL 401 Split bell Y E S NIL 413 Split bell Y E S NIL 418 Split bell Y E S NIL 424 Split bell Y E S NIL 428 Split bell NO NIL 433 Split bell Y E S NIL 435 Split bell Y E S NIL 10 Split bell Y E S NIL 48 Split bell N A NIL 76 Split bell YES NIL 141 Split bell YES NIL 342 Split bell YES NIL 379 Split bell Y E S NIL 389 Split bell Y E S NIL 402 Split bell N O NIL 403. Split bell Y E S NIL 404 ! Split.bell YES NIL 405 Split bell Y E S NIL 407 Split bell Y E S NIL • 408 Split bell NO NIL 409 Split bell Y E S NIL 411 Split bell N A NIL 414 Split bell Y E S Work Order System 415 Split bell YES NIL 416 Split bell Y E S Field Experience 417 Split bell YES NIL 419 Spin bell YES NIL 420 Split bell Y E S NIL 422 Split bell N A NIL 423 Split bell Y E S NIL 380 426 Split bell NO NIL 427 430 Split bell Split bell Y E S NIL Y E S NIL 431 Split bell Y E S NIL 432 Split bell NO NIL 4*4 Spin bell NO NIL 21 Tap failure NO NIL 42 i Tap failure Y E S Y E S NIL NIL 55 i Tap failure 56 i Tap failure Y E S NIL 72 j Tap failure Y E S NIL 100 i Tap failure NO NIL 103 i Tap failure N A N i l 1 1 2 i Tap failure Y E S NIL 120 Tap failure Y E S NIL 134 Tap failure Y E S NIL 227 Tap failure Y E S NIL 231 Tap failure Y E S NIL 240 ! Tap failure ^ 1 S NIL 249 ! Tap failure Y E S M I 260 Tap failure Y E S NIL 283 Tap failure . NO NIL 284 Tap failure Y E S NIL 295 Tap failure Y E S NIL 301 Tap failure Y E S NIL 332 Tap failure Y I S NIL 383 Tap failure N A NIL 392 Tap failure Y E S NIL 400 Tap failure N O NIL 401 Tap failure YES NIL 413 : Tap failure Y E S NIL 418 Tap failure Y I S NIL 424 Tap failure Y E S NIL 428 433 435 10 Tap failure N O NIL Tap failure Y E S NIL Tap failure YES NIL Tap failure Y E S NIL 48 Tap failure N A NIL 76 Tap failure Y E S NIL 141 Tap failure Y E S NIL 342 Tap failure Y E S NIL 379 Tap failure Y E S NIL 389 Tap failure Y E S NIL 402 ! Tap failure Y E S NIL 403 Tap failure Y E S NIL 404 Tap failure Y E S NIL 405 Tap failure YES NIL 407 Tap failure Y E S NIL 408 Tap failure NO NIL 381 409 Tap failure Y E S NIL 411 Tap failure Y E S Y E S NIL 414 Tap failure Work Order System 415 Tap failure . Y E S NIL 416 Tap failure Y L S Field Experience 417 Tap failure Y E S NIL 419 Tap failure YES NIL 420 Tap failure Y E S NIL 422 Tap failure N A NIL 423 i Tap failure Y E S NIL 426 Tap failure NO NIL 427 Tap failure Y E S NIL 430 i Tap failure Y E S NIL 431 i Tap failure Y l S NIL 432 Tap failure \() NIL 434 Tap failure Y E S NIL 382 Location data recorded by survey respondents II) Description " II Recorded 404 Nearest property address 100 424 Nearest property address 100 103 Nearest property address 100 134 Nearest property address 100 301 Nearest property address 100 342 Nearest property address 100 433 Nearest property address 75 407 Nearest property address 100 379 Nearest property address 100 249- Nearest property address 100 415 Nearest property address 100 21 Nearest property address 100 403 Nearest property address 100 420 Nearest property address 75 383 Nearest property address 100 423 Nearest property address 100 432 Nearest property address 75J 48 Nearest property address 100 408 Nearest property address 100 56 Nearest property address 100 422 Nearest property address 50 417 . Nearest property address 50 414 Nearest property address loo 409 Nearest property address 100 72 Nearest property address 75 332 Nearest property address 100 4 M Nearest property address 100 55 Nearest property address 100 • 227 Nearest property address 100 419 Nearest property address 100 141 Nearest property address 100 411 Nearest property address 100 405 Nearest property address 50 426 Nearest property address . 100 427 Nearest property address 100 402 Nearest property address 0 240 Nearest property address 100 434 Nearest property address 0 100 Nearest property address 100 430 Nearest property address 100 76 Nearest property address 100 428 Nearest property address 100 401 Nearest property address 100 295 Nearest property address 100 383 392 Nearest property address 100 42 Nearest property address 100 2N4 Nearest property address 100 400 Nearest property address 100 231 Nearest property address 100 416 Nearest property address 100 418 Nearest property address 100 389 Nearest property address _ 100 112 Nearest property address 0 431 Nearest property address 100 10 Nearest property address 100 435 Nearest property address 75 283 Nearest property address 100 260 Nearest property address 50 120 Nearest property address 0 22" Distance from nearest property line 0 402 Distance from nearest property line 0 417 Distance from nearest property line 0 295 Distance from nearest property line 25 435 Distance from nearest property line 25 401 Distance from nearest property line 0 284 Distance from nearest property line 0 419 Distance from nearest property line 0 141 Distance from nearest property line 0 415 Distance from nearest property line 0 10 Distance from nearest property line 0 403 Distance from nearest property line 100 422 Distance from nearest property line 0 433 Distance from nearest property line 75 424 Distance from nearest property line 0 432 Distance from nearest property line 0 "() Distance from nearest property line 0 418 Distance from nearest property line 0 420 Distance from nearest property line 0 283 Distance from nearest property line 50 416 Distance from nearest property line 0 430 Distance from nearest property line 0 48 Distance from nearest property line 0 426 Distance from nearest property line 0 240 Distance from nearest property line 0 428 Distance from nearest property line 100 134 Distance from nearest property line 0 103 Distance from nearest property line 0 249 Distance from nearest property line 50 231 Distance from nearest property line 55 Distance from nearest property line 100 427 Distance from nearest property line 0 21 Distance from nearest property line 0 407 Distance from nearest property line 0 384 112 Distance from nearest property line 0 342 Distance from nearest property line 0. 411 Distance from nearest property line . 0 405 Distance from nearest property line 75 100 Distance from nearest property line 75 400 Distance from nearest property line 25 408 Distance from nearest property line 0 431 Distance from nearest property line 25 389 Distance from nearest property line 0 332 Distance from nearest property line 75 423 Distance from nearest property line 0 383 Distance from nearest property line 0 301 Distance from nearest property line 0 5(. Distance from nearest property line 0 404 Distance from nearest property line 25 379 Distance from nearest property line 0 434 Distance from nearest property line 0 392 Distance from nearest property line 75 "2 Distance from nearest property line 75 413 Distance from nearest property line 100 42 Distance from nearest property line 0 260 Distance from nearest property line 50 414 Distance from nearest property line 0 120 Distance from nearest property line 100 409 Distance from nearest property line 100 428 Cross street name 100 42 Cross street name 100 240 Cross street name 75 383 Cross street name 100 423 Cross street name 0 403 Cross street name 100 434 Cross street name 100 404 Cross street name 50 21 Cross street name 100 420 Cross street name 100 389 Cross street name 0 432 Cross street name 75 120 Cross street name 100 424 Cross street name 25 416 Cross street name 100 283 Cross street name 50 284 Cross street name 100 260 Cross street name 100 430 Cross street name 100 76 Cross street name 25 100 Cross street name 100 418 Cross street name 50 112 Cross street name 100 231 Cross street name 100 385 409 Cross street name 100 295 Cross street name 25 433 Cross street name 75 408 Cross street name 0 ' 227 Cross street name 25 435 Cross street name 75 402 Cross street name 0 48 Cross street name 100 400 Cross street name 100 141 Cross street name 0 10 Cross street name 100 417 Cross street name 0 414 Cross street name 100 "2 Cross street name 0 56 Cross street name 0 422 Cross street name 0 415 Cross street name 25 413 Cross street name 0 103 Cross street name 401 Cross street name 0 55 Cross street name 342 Cross street name 100 134 Cross street name 100 419 Cross street name 100 392 Cross street name 75 332 Cross street name 75 301 i Gross street name 75 431 249 Cross street name 50 Cross street name 50 407 Cross street name 100 379 Cross street name 25 427 Cross street name 100 426 Cross street name 100 405 Cross street name 100 411 Cross street name 25 284 Distance from nearest cross street 100 100 Distance from nearest cross street 0 72 Distance from nearest cross street 0 431 Distance from nearest cross street 0 295 Distance from nearest cross street 25 231 Distance from nearest cross street 134 Distance from nearest cross street 50 415 Distance from nearest cross street 0 414 Distance from nearest cross street 0 417 Distance from nearest cross street 0 413 Distance from nearest cross street 100 402 Distance from nearest cross street 0 411 Distance from nearest cross street 0 419 Distance from nearest cross street 0 386 426 Distance from nearest cross street 0 407 Distance from nearest cross street 0 55 Distance from nearest cross street 301 Distance from nearest cross street 0 240 Distance from nearest cross street 379 Distance from nearest cross street 25 48 Distance from nearest cross street 25 383 Distance from nearest cross street O 432 Distance from nearest cross street 0 389 Distance from nearest cross street 0 76 Distance from nearest cross street 0 260 Distance from nearest cross street 100 283 Distance from nearest cross street 50 42 Distance from nearest cross street 25 249 Distance from nearest cross street 25 418 Distance from nearest cross street 0 141 Distance from nearest cross street 0 408 Distance from nearest cross street 0 420 Distance from nearest cross street 25 120 Distance from nearest cross street 50 427 Distance from nearest cross street 100 416 Distance from nearest cross street 0 405 Distance from nearest cross street 50 430 Distance from nearest cross street 0 103 Distance from nearest cross street 0 428 Distance from nearest cross street 0 332 Distance from nearest cross street 25 423 Distance from nearest cross street 0 433 Distance from nearest cross street 50 - 424 Distance from nearest cross street 0 342 Distance from nearest cross street 0 404 Distance from nearest cross street 25 21 Distance from nearest cross street 0_ 112 Distance from nearest cross street 100 401 Distance from nearest cross street 0 227 Distance from nearest cross street 0 435 Distance from nearest cross street 75 422 Distance from nearest cross street 0 392 Distance from nearest cross street 75 400 Distance from nearest cross street 50 434 Distance from nearest cross street 100 409 Distance from nearest cross street 100 403 Distance from nearest cross street 100 10 Distance from nearest cross street 100 so Distance from nearest cross street 0 301 Northing and Easting coordinates 0 332 Northing and Easting coordinates O 433 Northing and Easting coordinates 0 414 Northing and Easting coordinates 0 387 56 Northing and Easting coordinates 0 134 Northing and Easting coordinates 0 379 Northing and Easting coordinates 0 21 Northing and Easting coordinates 0 422 Northing and Easting coordinates 0 48 Northing and Easting coordinates 0 415 Northing and Easting coordinates 100 413 Northing and Easting coordinates 402 Northing and Easting coordinates 0 409 Northing and Easting coordinates 411 Northing and Easting coordinates 0 141 Northing and Easting coordinates 0 227 Northing and Easting coordinates 0 419 Northing and Easting coordinates 0 103 Northing and Easting coordinates 0 427 Northing and Easting coordinates 0 249 Northing and Easting coordinates 0 426 Northing and Easting coordinates 100 407 Northing and Easting coordinates 0 10 Northing and Easting coordinates 0 405 Northing and Easting coordinates 100 408 Northing and Easting coordinates 0 403 Northing and Easting coordinates 25 342 Northing and Easting coordinates • 0 383 Northing and Easting coordinates 260 Northing and Easting coordinates 0 430 Northing and Easting coordinates 0 112 Northing and Easting coordinates 0 416 Northing and Easting coordinates 0 283 Northing and Easting coordinates 0 434 Northing and Easting coordinates 0 42 Northing and Easting coordinates 0 401 Northing and Easting coordinates 0 76 Northing and Easting coordinates 0 428 Northing and Easting coordinates 0 240 Northing and Easting coordinates 0 120 Northing and Easting coordinates 0 392 Northing and Easting coordinates 0 100 Northing and Easting coordinates 0 231 Northing and Easting coordinates 100 2.S4 Northing and Easting coordinates 0 435 Northing and Easting coordinates 50 400 Northing and Easting coordinates 420 Northing and Easting coordinates 41" Northing and Easting coordinates 55 Northing and Easting coordinates 0 404 Northing and Easting coordinates 0 72 Northing and Easting coordinates 0 295 Northing and Easting coordinates 0 388 431 Northing and Easting coordinates 0 424 Northing and Easting coordinates 432 Northing and Easting coordinates 0 389 Northing and Easting coordinates 0 423 Northing and Easting coordinates .0 418 Northing and Easting coordinates 0 413 Isolation Valve operated ( Gate valve ID ) 100 431 Isolation Valve operated ( Gate valve ID ) 100 434 Isolation Valve operated ('Gate valve ID ) 50 392 Isolation Valve operated ( Gate valve ID ) 0 56 Isolation Valve operated ( Gate valve ID ) 0 400 Isolation Valve operated ( Gate valve ID ) 100 72 Isolation Valve operated ( Gate valve ID ) 100 405 Isolation Valve operated ( Gate valve ID ) 100 383 Isolation Valve operated ( Gate valve ID ) 0 342 Isolation Valve operated ( Gate valve ID ) 0 404 Isolation Valve operated ( Gate valve ID ) 100 389 Isolation Valve operated ( Gate valve ID ) 0 379 Isolation Valve operated ( Gate valve ID ) 0 332 Isolation Valve operated ( Gate valve ID ) 100 423 Isolation Valve operated ( Gate valve ID ) 0 408 Isolation Valve operated ( Gate valve ID ) 0 260 Isolation Valve operated ( Gate valve ID ) 0 409 Isolation Valve operated ( Gate valve ID ) 100 112 Isolation Valve operated ( Gate valve ID ) 100 42 Isolation Valve operated ( Gate valve ID ) 0 414 Isolation Valve operated ( Gate valve ID ) 0 407 Isolation Valve operated ( Gate valve ID ) 0 120 Isolation Valve operated ( Gate valve ID ) 100 100 Isolation Valve operated ( Gate valve ID ) 0 411 Isolation Valve operated ( Gate valve ID ) 0 301 Isolation Valve operated ( Gate valve ID ) 0 416 Isolation Valve operated ( Gate valve ID ) 0 103 Isolation Valve operated ( Gate valve ID ) 0 249 Isolation Valve operated ( Gate valve ID ) 0 433 Isolation Valve operated ( Gate valve ID ) 25 134 Isolation Valve operated ( Gate valve ID ) 25 21 Isolation Valve operated ( Gate valve ID ) 0 48 Isolation Valve operated ( Gate valve ID ) 0 55 Isolation Valve operated ( Gate valve ID ) 100 424 Isolation Valve operated ( Gate valve ID ) 0 432 Isolation Valve operated ( Gate valve ID ) 0 426 Isolation Valve operated ( Gate valve ID ) 0 76 Isolation Valve operated ( Gate valve ID ) 50 420 Isolation Valve operated ( Gate valve ID ) 0 2 S3 Isolation Valve operated ( Gate valve ID ) 0 428 Isolation Valve operated ( Gate valve ID ) 0 240 Isolation Valve operated ( Gate valve ID ) 50 430 Isolation Valve operated ( Gate valve ID ) 0 -389 231 Isolation Valve operated ( Gate valve ID ) 0 401 Isolation Valve operated ( Gate valve ID ) 284 Isolation Valve operated ( Gate valve ID ) 0 435 Isolation Valve operated ( Gate valve ID ) 100 295 Isolation Valve operated ( Gate valve ID ) 0 10 Isolation Valve operated ( Gate valve ID ) 100 418 Isolation Valve operated ( Gate valve ID ) 0 41" Isolation Valve operated ( Gate valve ID ) 75 42" Isolation Valve operated ( Gate valve ID ) 0 22" Isolation Valve operated ( Gate valve ID ) 100 422 Isolation Valve operated ( Gate valve ID ) 0 402 Isolation Valve operated ( Gate valve ID ) 0 415 Isolation Valve operated ( Gate valve ID ) 0 419 Isolation Valve operated ( Gate valve ID ) 0 141 Isolation Valve operated ( Gate valve ID ) 0 403 Isolation Valve operated ( Gate valve ID ) 100 56 Isolation Valve operated - ( Gate valve ID ) 0 430 Isolation Valve operated - ( Gate valve ID ) 0 100 Isolation Valve operated - ( Gate valve ID ) 120 Isolation Valve operated - ( Gate valve ID ) 100 240 Isolation Valve operated - ( Gate valve ID ) 50 428 Isolation Valve operated - ( Gate valve ID ) 0 283 Isolation Valve operated - ( Gate valve ID ) 0 42 Isolation Valve operated - ( Gate valve ID ) 0 112 Isolation Valve operated - ( Gate valve ID ) 100 227 Isolation Valve operated - ( Gate valve ID ) 100 413 Isolation Valve operated - ( Gate valve ID ) 100 416 Isolation Valve operated - ( Gate valve ID) 0 401 Isolation Valve operated - ( Gate valve ID ) 0 392 Isolation Valve operated - ( Gate valve ID ) 0 403 Isolation Valve operated - ( Gate valve ID ) 100 415 Isolation Valve operated - ( Gate valve ID ) 0 284 Isolation Valve operated - ( Gate valve ID ) 0 434 Isolation Valve operated - ( Gate valve ID ) 50 431 Isolation Valve operated - ( Gate valve ID ) 100 435 Isolation Valve operated - ( Gate valve ID ) 100 72 Isolation Valve operated - ( Gate valve ID ) 100 295 Isolation Valve operated - ( Gate valve ID ) 0 10 Isolation Valve operated - ( Gate valve ID ) 0 414 Isolation Valve operated - ( Gate valve ID ) 0 400 Isolation Valve operated - ( Gate valve ID ) 100 231 Isolation Valve operated - ( Gate valve ID ) 240 Isolation Valve operated - ( Gate valve ID ) 0 21 Isolation Valve operated - ( Gate valve ID ) 0 134 Isolation Valve operated - ( Gate valve ID ) 3 "l> Isolation Valve operated - ( Gate valve ID ) 0 332 Isolation Valve operated - ( Gate valve ID ) 1 100 419 Isolation Valve operated - ( Gate valve ID ) 0 76 Isolation Valve operated - ( Gate valve ID ) 50 390 433 Isolation Valve operated - ( Gate valve ID ) 25 383 Isolation Valve operated - ( Gate valve ID ) 0 408 Isolation Valve operated - ( Gate valve ID ) 301 Isolation Valve operated - ( Gate valve ID ) 0 405 Isolation Valve operated - ( Gate valve ID ) 100 407 Isolation Valve operated - ( Gate valve ID ) 0 103 Isolation Valve operated - ( Gate valve ID ) 0 426 Isolation Valve operated - ( Gate valve ID ) 0 427 Isolation Valve operated - ( Gate valve ID ) 0 404 Isolation Valve operated - ( Gate valve ID ) 100 2W) Isolation Valve operated - ( Gate valve ID ) 0 423 Isolation Valve operated - ( Gate valve ID ) 0 402 . Isolation Valve operated - ( Gate valve ID ) 0 418 Isolation Valve operated - ( Gate valve ID ) 432 Isolation Valve operated - ( Gate valve ID ) 0 40') Isolation Valve operated - ( Gate valve ID ) 75 48 Isolation Valve operated - ( Gate valve ID ) 0 389 Isolation Valve operated - ( Gate valve ID ) 342 Isolation Valve operated - ( Gate valve ID ) 0 424 Isolation Valve operated - ( Gate valve ID ) 0 417 Isolation Valve operated - ( Gate valve ID ) 75 141 Isolation Valve operated - ( Gate valve ID ) 0 422 Isolation Valve operated - ( Gate valve ID ) 0 420 Isolation Valve operated - ( Gate valve ID ) 0 55 Isolation Valve operated - ( Gate valve ID ) 411 Isolation Valve operated - ( Gate valve ID ) 0 \ 391 P A G E L E F T B L A N K 392 APPENDIX G 393 A p p e n d i x G contains the break data c o m p i l e d and created as part o f the research and used i n Chapters 3 and 4. Laity View pipe break records with pipe identification numbers (1983-2004) PIPE ID CEP Check (break to current pipe or pipe replaced) MATERIAL SIZE YEAR INSTALLED REPLACED (FROM GIS) DATE OF BREAK COMMENTS 10012 current AC 150 1975 N 14/04/19 83 Water hammer caused by something plugging hydrant during line flushing of mains. Valved down pressure to control leakage, repaired damage section of pipe 13347 replaced DI 75 1985 Y 08/03/19 83 Failure of needle valve on pressure reducing valve caused 15# increase in line pressure. Cut out bad section and installed new 6' piece 13827 current AC 250 1964 N 20/09/19 83 12535 replaced DI 100 1986 Y 09/07/19 84 100mm C/l w/m broken straight across - probable cause due to settlement of material under pipe. 13889 replaced DI 150 1994 Y 08/05/19 84 Repaired broken 150mm A/C w/m caused by overtightening of service corp. stop. 13895 replaced DI 150 1994 Y 09/07/19 84 Break occurred where sewer connection had been installed some time ago. Repaired 150mm A/C w/m by installing 150mm x 300mm repair clamp 13974 current AC 150 1964 N 13/12/19 84 Watermain broken due to settlement of old sanitary sewer trench. No property damage from break. Cut out damaged section of A/C w/m and repaired with D/l pipe. 12320 current CI 150 1968 N 22/08/19 85 13980 replaced DI 150 1994 Y 27/12/19 85 150mm 2/m broke due to settlement of storm sewer trench. 12307 current AC 150 1972 N 24/09/19 86 150mm A/C w/m had been marked by back-hoe tooth when sewer connection was installed by Contractor a few years ago. Installed s/s repair clamp over horizontal crack. 12461 replaced DI 200 1992 Y 26/12/19 86 Old light C/l w/m split approx. 5' along side of pipe possibly from shoulder settlement. Repaired broken 20mm C/l w/m. 394 Repaired broken 150mm A/C w/m with s/s/ repair 11386 current AC 150 1971 N 14/04/19 • 87 clamp which was damaged by shoulder settlement. (Note: pipe is deep to go under culvert). 100mm C/l w/m broke straight across due to settlement of road shoulder where new sewerline was installed 12461 replaced Dl 100 1992 Y 21/01/19 87 (Note: 3rd break). Repaired broken 100mm C/l w/m. 150mm A/C w/m broke due to settlement of shoulder. Installed s/s 09/09/19 repair clamp where A/C pipe had cracked by 13974 current AC 150 <• 1964 N 87 connection tap. Shoulder of road settling where sewer had crossed line caused break of 100mm C/l w/m. (Exist 14584 replaced Dl 100 1991 Y 20/02/19 88 100 CI pipe segments abandoned). Resident pounded rebar through collar in 150mm A/C w/m while fixing up end of his driveway culvert. Crew put on a 19/04/19 rebard repair clamp & resident will clean up 12286 . current AC 150 1972 N 89 shoulder & seed area. 150mm A/C w/m broke where contractor had 16/02/19 installed storm under a 13974 current AC 150 1964 N 89 few years ago. Repaired 6" A/C w/m with 14/06/19 stainless steel repair 11405 current AC 150 1975 N 90 - clamp. (Leaking at collar). Roads Foreman called out due to hole in road, undermined due to leak in waterline. Hole temporarily filled with 3/4".crushed 13872 current Dl 100 1986 N 14/03/19 90 rock and flasher put up. Repaired by Water Dept. on Apr. 20th. ' Turned water off on the street and dug it out. Put on a stainless steel saddle with a 3/4 hole as the 03/11/19 service saddle rusted 12308 current AC 18 1972 N 91 away. Backfill. 31/01/19 Pipe broke due to settlement of road 12448 replaced Dl 100 1991 Y 91 shoulder. 08/06/19 11014 replaced Dl 150 1999 Y 92 Repair watermain break. 21/12/19 11494 current AC 200 1973 N 92 Repair watermain break. 20/02/19 12017 current Dl 200 1982 N 92 Repair watermain break. 21/07/19 12259 current AC 150 1969 N 92 Repair watermain break. 08/06/19 12437 current AC 150' 1964 N 92 Repair watermain break. 06/03/19 14302 current AC 150 1959 N 92 Repair watermain break. 395 10118 current CI 150 1959 N 24/09/19 93 Repair watermain break. 11151 current AC 250 1964 N 23/02/19 93 Repair watermain break. 12308 current AC 150 1972 N 02/04/19 93 Repair watermain break. 12541 current DI 200 1986 N 02/05/19 93 Repair watermain break. 14548 current DI 250 1974 N 08/10/19 93 Repair watermain break. 10363 current AC 250 1964 N 19/05/19 94 Repaired AC waterline on 224 St where crossing for building was. 12284 current AC 150 1969 N 12/02/19 94 "COMPLETION TO REPAIRS & A LATER DATE 13896 current AC 150 1973 N . 20/06/19 94 Possibly caused by construction near this location. (Note: large trucks hauling) 10019 current AC 200 1964 10/02/19 95 11391 current AC 150 1975 N 12/11/19 95 12254 current AC 150 1969 N 13/12/19 95 W/M broke where gas service had been installed (possibly hit by mole). Approx. 2' section blown out of pipe bottom - some houses in area flooded. 12254 current AC 150 1969 14/12/19 95 12255 current AC 150 1969 12/12/19 95 12284 current AC ' 150 1969 05/12/19 95 12471 current DI 150 1986 19/11/19 95 12471 current DI 150 1986 N 18/11/19 95 150mm DIW/M broke possibly due to electrolysis corrosion of W/M. 13986 current AC 150 1969 N 12/01/19 95 10027 current AC 200 1973 N 14/02/19 93 Repair watermain break. 10269 current AC 200 1959 N 02/12/19 93 Repair watermain break. 12313 current AC 150 1972 N 14/02/19 93 Repair watermain break. 14523 current AC 200 1973 N 17/12/19 95 12471 current DI 150 1986 N 23/04/20 02 . Clay soil causing.DI pipe to corrode which is causing holes in the pipe (put dechlorination bags in 2 spots; valved down W/M & crews arrived to repair W/M. 10118 current CI 150 1959 N 15/02/20 03 Broken copper waterline 3" from cork @ main (split copper). Large sinkhole at site. Old line, wear & tear, vibration caused? Found leak, placed dechl. pucks at c/b. Shut down main for approx. 1.5 hrs to repair service. Rep'd w 150 robar 396 11364 current AC 150 1975 N 11/03/20 01 old 150mm A/C main in poor shape (very soft in the area of this break). Cut out 4' section of A/C main & replaced with D/l pipe. Put cork in main for 12475-214 St. at the same time. 11408 current AC 150 1977 N 21/04/20 02 Leak appears to be on our side @ edge of s/w. Need hoe & crew to repair 100mm PVC pipe. Installed meter setter & box @ 21285 Douglas Ave. 12293 current AC 150 1969 N 05/08/20 02 Broken AC W/M @ intersection of 126 Ave. & Grace St. Crew & hoe arrived and repairs made. • ,12317 current CI . 200 1959 N 25/07/20 02 Broken 200mm CI W/M. Repaired sidewalk as well. 11361 current CI 150 1977 N 03/07/20 03 Repaired with 150 AC robar repair clamp. AC broken at intersection of 124 Ave. & Laity St. going east on 124 Ave. 397 PIPE ID Size Pipe mat. Year Year Of Failure -all first breaks Soil zone Month Of Failure Number of breaks (to 1999) #of first breaks # of 2nd breaks Age cohort 12448 200 DI 1991 1991 30 1 1 0 1990-1994 13872 150 DI 1986 1990 30 3 1 1 1985-1989 12541 200 DI 1986 1993 40 5 1 1 1985-1989 10012 150 A C 1975 1983 30 4 1 1 1975-1979 12471 150 DI 1986 1995 30 11 1 1985-1989 12017 200 DI 1982 1992 40 2 1 1 1980-1984 12307 150 A C 1972 1986 30 9 1 1 1970-1974 11405 150 A C 1975 1990 60 6 1 1 1975-1979 11386 150 . A C 1971 1987 30 4 1 1 1970-1974 12286 150 A C 1972 1989 30 4 1 1 1970-1974' 12320 150 CI 1968 1985 30 8 1 1 1965-1969 12308 150 A C 1972 1991 30 11 1 1 1970-1974-13827 250 A C 1964 1983 30 9 1 1 1960-1964 11494 200 A C 1973 1992 40 12 1 1 1970-1974 14548 250 DI 1974 1993 40 10 1 1 1970-1974 11391 150 A C 1975 1995 30 11 1 1 1975-1979 10027 200 A C 1973 1993 40 2 1 1 1970-1974 13974 150 A C 1964 1984 40 12 1 2 1960-1964 12313 150 A C 1972 1993 30 2 1 1 1970-1974 13896 150 A C 1973 1994 30 6 1 1 1970-1974 14523 200 A C 1973 1995 40 12 1 1 1970-1974 12284 150 A C 1969 1994 30 2 1 1 1965-1969 12254 150 A C 1969 1995 30 12 1 1 1965-1969 12255 150 A C 1969 1995 30 12 1 1 1965-1969 13986 150 A C 1969 1995 30 1 1 1 1965-1969 12437 150 A C 1964 1992 60 6 1 1 1960-1964 11151 250 A C 1964 1993 60 2 1 1 1960-1964 10363 250 A C 1964 1994 30 5 1 1 1960-1964 10019 200 A C 1964 1995 40 2 1 1 1960-1964 14302 150 A C 1959 1992 40 3 1 1 1955-1959 10269 200 A C 1959 1993 30 12 1 I 1955-1959 10118 150 CI 1959 1993 •30 9 1 1 1955,-1959 12259 150 A C 1969 1992 30 1 1 1965-1969 12535 200 DI 1986 1984 30 7 1 0 1985-1989 13895 200 DI 1994 1984 30 7 1 0 1990-1994 13980 200 DI 1994 .. 1985 30 12 1 0 1990-1994 12461 150 DI 1992 1986 30 12 0 1990-1994 14584 150 DI 1991 1988 40 2 1 0 1990-1994 13347 150 DI 1985 1983 60 3 1 0 1985-1989 13889 200 DI 1994 1984 60 5 1 0 1990-1994 11014 250 DI 1999 1992 60 6 1 0 1995-1999 47 32 5 Note : 4 7 brea cs, 9 pipes u n k n o w n , 10 creaks u n k n o w n 398 1 Soil data codes T y p e o f s o i l C o d e M a r i n e C l a y ( C l a y e y M a r i n e ) 30 E o l i a n S i l t (S i l ty Eo l i an ) 40 C l a y e y / S i l t y 60 S i l ty /Sandy 70 S a n d y / C l a y e y 80 M a r i n e Sand (Sandy M a r i n e ) 50 No te : The type o f s o i l is defined b y Lut tmerd ing , 1980 and Lut tmerd ing , 1981. 399 The f o l l o w i n g section is the break data fi le used for the experiments i n Chapter 4. It also contains the data created as part o f Chapter 3. 400 A H I J K - L M N 1 WATERID Size Material Material Code Year Year Of Failure Month Of Failure Years of Service 2 10010 150 AC 1 1975 3 10011 250 DI 3 1994 4 10012 150 AC 1 1975 1983 4 8 5 10013 150 DI 3 1983 6 10014 150 DI 3 1983 7 10015 250 AC 1 1974 -8 10017 200 AC 1 1964 9 10018 200 AC 1 1964 10 10019 200 AC 1 1964 1995 2 31 11 10020 200 AC 1 1982 12 10027 200 AC 1 1973 1993 2 20 13 10068 250 DI 3 1997 14 10118 150 CI 2 1959 1993 9 34 15 10119 250 AC 1 1959 .16 10120 250 AC 1 1959 17 10121 150 DI 3 1985 18 10122 200 DI ' 3 1984 ' 19 ; 10194 250 AC 1 1959 20 10195 250 AC 1 1959 21 10266 . 150 DI 3 1982 22 10267 250 DI 3 1978 23 10268 250 DI 3 1982 24 10269 200 AC 1 1959 1993 12 34 25 10274 200 AC 1 1973 26 10275 200 AC 1 1973 27 10276 150 DI 3 1986 28 10277 200 AC 1 1973 29 10344 150 AC 1 1975 30 10363 250 AC 1 . 1964 1994 5 30 31 10377 250 DI 3 1999 32 . 10397 200 DI 3 1995 33 10411 150 DI 3 1981 34 10497 250 DI 3 1999 35 10552 200 DI 3 1995 36 10640 150 DI 3 1983 37 10673 250 AC 1 1974 38 10736 150 DI 3 1981 39 10809 150 DI 3 1995 40 10810 200 DI 3 1975 41 10811 200 DI 3 1995 42 10812 200 j DI 3 1995 43 10954 150 DI 3 1984 44 10970 250 DI 3 1999 45 10989 150 DI 3 1999 46 11014 250 DI 3 1999 1992 6 47 11015 250 DI 3 1999 401 A H I J K L M N 48 11016 250 DI 3 1999 49 11017 250 DI 3 1999 50 11078 200 DI 3 1984 51 11114 200 DI 3 1976 52 11150 250 AC 1 1964 53 11151 250 AC 1 1964 1993 2 29 54 11152 150 DI 3 1991 55 11153 150 AC 1 1972 56 11351 150 AC 1 1959 57 11352 150 DI 3 1992 58 11353 150 DI 3 1991 59 11354 150 DI 3 1991 60 11357 150 DI 3 1980 61 11358 150 DI 3 1994 62 11360 150 DI 3 1982 63 11361 150 CI 2 1977 64 11362 150 CI 2 1977 65 11363 150 CI 2 1977 66 11364 150 AC 1 1975 67 11365 150 DI 3 1990 68. 11366 150 DI 3 1991 69 11367 150 DI 3 1991 70 11368 150 DI 3 1990 71 11369 150 DI 3 1991 72 11370 150 DI 3 1991 73 11373 200 DI 3 1982 74 11375 200 DI 3 1982 75- 11376 200 DI 3 1982 76 11377 150 AC 1 1964 77 11379 200 DI 3 1997 78 11380 . 200 DI 3 1982 79 11381 200 DI 3 1982 80 11382 200 DI 3 1980 81 11383 200 DI 3 1980 82 11385 200 DI 3 1991 83 11386 150 AC 1 1971 1987 4 16 84 11387 150 DI 3 1987 85 11388 150 DI 3 1982 86 11389 150 DI 3 1982 87 11390 150 AC 1 1975 88 11391 150 AC 1 1975 1995 11 20 89 11392 150 AC 1 1975 90 11393 150 AC 1 1975 91 11394 150 AC 1 1975 92 11397 150 DI 3 1986 93 11398 150 DI 3 1986 94 11399 150 AC 1 1975 95 11400 150 DI 3 1986 96 11401 150 . AC 1 1975 97 11402 150 AC 1 1975 98 11403 150 AC 1 1975 402 A H I J K L M N 99 11404 150 Dl 3 1983 100 11405 150 AC 1 1975 1990 6 15 101 11406 150 AC 1 1975 102 11407 150 AC 1 1975 103 11408 150 AC - 1 1977 104 11409 150 AC 1 1977 105 11410 150 AC 1 1977 106 11411 150 AC 1 1975 107 11412 150 Dl 3 1983 108 11413 150 Dl > 3 1983 109 11414 150 Dl 3 1983 110 11416 150 AC 1 1975 111 11430 200 Dl 3 1976 112 11431 200 Dl 3 1976 113 11432 200 Dl 3 1976 11.4 11433 200 Dl 3 1976 115 11445 200 AC 1 1973 116 11491 200 AC 1 1971 117 11492 200 AC 1 1973 118 11494 200 AC 1 1973 1992 12 19 119 11500 200 AC 1 1973 120 11961 200 Dl 3 1991 121 11966 200 AC 1 1959 122 11991 200 Dl 3 1995 123 11992 200 Dl 3 1995 124 12015 150 Dl 3 1997 125 12016 200 Dl 3 1997 126 12017 200 Dl 3 1982 1992 2 10 127 12035 200 Dl 3 1995 128 12037 150 Dl 3 1998 129 12038 150 CI 2 1964 130 12043 150 Dl 3 1997 131 12046 250 Dl 3 1998 132 12047 250 Dl 3 1998 133 12253 200 Dl 3 1994 134 12254 150 AC 1 1969 1995 12 26 135 12255 150 AC 1 1969 1995 12 26 136 12258 150 Dl 3 1982 137 12259 150 AC 1 1969 1992 23. 138 12274 200 Dl 3 1991 139 12282 150 Dl 3 1995 140 12283 150 Dl 3 1995 141 12284 150 AC 1 1969 1994 2 25 142 12286 150 AC 1 1972 1989 4 17 143 12287 150 AC 1 1972 144 12288 150 AC 1 1972 145 12289 150 AC 1 1969 146 12291 150 AC 1 1969 147 12292 150 AC 1 1972 148 12293 150 AC 1 1969 149 12294 150 Dl 3 1986 403 A H I J K -L M N 150 12297 150 AC 1 1972 151 12298 150 DI 3 1994 152 12299 200 DI 3 1994 153 12301 150 DI 3 1994 154 12302 150 DI 3 1994 155 12303 100 CI 2 1965 156 12305 200 DI 3 1994 157 12307 150 AC 1 1972 1986 9 14 158 12308 150 AC 1 1972 1991 11 19 159 12309 150 AC 1 1972 160 12310 150 AC 1 1972 161 12311 150 AC 1 0 162 12312 150 AC 1 1975 163 12313 150 AC 1 1972 1993 2 21 164 12314 150 AC 1 1972 165 12315 150 CI 2 0 166 12316 200 CI 2 1956 167 12317 200 CI 2 1959 168 12319 150 AC 1 1964 169 12320 150 CI 2 1968 1985 8 17 170 12321 150 DI 3 0 171 12324 150 DI 3 1990 172 12326 150 DI , 3 1990 173 12327 150 DI 3 1990 174 12328 100 CI 2 0 175 12329 150 DI 3 1990 176 12330 150 DI 3 1990 177 12331 150 DI 3 1997 178 12332 150 AC 1 1975 179 12333 150 AC 1 1972 180 12334 150 AC 1 1972 181 12335 150 AC 1 1980 182 12337 150 DI 3 1978 183 12338 150 DI 3 1994 184 12339 150 AC 1 1964 185 12340 200 AC 1 1973 186 12341 200 AC 1 1973 187 12342 200 AC 1 1973 188 12343 150 DI 3 1986 189 12344 150 DI 3 0 190 12346 200 AC 1 1973 191 12347 200 AC 1 1973 192 12349 200 AC 1 1973 193 12350 200 AC 1 1973 194 12429 200 AC 1 1959 195 12430 200 AC 1 1973 196 12431 200 AC 1 1973 197 12432 200 AC 1 1959 198 12433' 200 CI 2 1956 199 12435 . 150 DI 3 1990 200 12436 150 DI 3 1990 404 A H I J K L M N 201 12437 150 AC 1 1964 1992 6 28 202 12439 250 DI 3 1982 . 203 12441 150 CI 2 1975 204 12442 250 DI 3 1978 205 12443 250 DI 3 1978 206 12445 250 DI 3 1978 207 12446 150 AC .1 1969 208 12447 200 DI 3 1991 209 12448 200 DI 3 1991 1991 1 0 210 12450 200 DI 3 1991 211 12451 200 DI 3 1991 212 12452 150 AC 1 1964 213 12453 250 DI 3 1978 214 12456 150 DI 3 1982 215 12457 150 DI 3 1982 216 12458 150 DI 3 1992 217 12459 150 DI 3 1992 218 12460 150 DI 3 1992 .21.9 12461 150. DI 3 1992 1986 12 220 12462 200 DI 3 1994 221 12464 150 DI 3 1984 222 12465 150 DI. 3 1986 223 12466 150 DI 3 1985 224 12467 150 DI 3 1985 225 12468 150 DI .3 1989 226 12469 150 DI 3 1989 227 12470 150 DI 3 1989 228 12471 150 DI 3 1986 1995 11 9 229 12472 150 DI 3 1985 230 12475 150 DI 3 1990 231 12476 150 DI 3 1990 232 12477 200 DI 3 1994 233 12478 .150 DI 3 1986 234 12479 150 DI 3 1990 235 12480 150 DI 3 1986 236 12481 150 DI 3 1986 237 12483 200 DI 3 1993 238 12484 200 CI 2 1979 239 12521 200 DI 3 1986 240 12533 200 DI 3 1986 241 12535 200 DI 3 1986 1984 7 242 12537 200 DI 3 1986 243 12539 200 DI 3 1986 244 12540 • 200 DI 3 1986 245 12541 200 DI 3 1986 1993 5 7 246 12542 200 DI 3 1986 247 12543 150 AC 1 1964 248 13053 300 STL 4 1978 249 13054 300 STL 4 1978 250 13061 ; 250 DI 3 1982 251 13091 200 DI 3 1993 405 A H I J K L M N 252 13092 200 Dl 3 1993 253 13095 250 Dl 3 1978 254 13296 250 Dl 3 1993 255 13298 250 Dl 3 1993 256 13322 200 Dl 3 1997 257 13323 150 AC 1 1964 258 13324 150 AC 1 1975 259 13326 150 AC 1 1972 260 13329 150 Dl 3 1986 261 13330 150 Dl 3 1986 262 13337 250 Dl 3 1993 263 13338 250 Dl 3 1993 264 13339 250 Dl 3 1993 265 13340 250 Dl 3 1993 266 13342 250 AC 1 1964 267 13343 250 Dl 3 1993 268 13344 200 Dl 3 1993 269 13345 200 Dl 3 1993 270 13346 150 Dl 3 1985 271 13347 150 Dl 3 1985 1983 3 272 13348 250 Dl 3 1993 273 13349 200 Dl 3 1993 274 1.3350 150 AC 1 1964 275 13354 150 Dl 3 1996 276 13355 150 . Dl 3 1996 277 13375 200 Dl 3 1978 278 13388 150 Dl 3 1995 279 13390 200 Dl 3 1995 280 13391 150 Dl 3 1982 281 13827 250 AC 1 1964 1983 9 19 282 13828 250 AC 1 1964 283 13829 250 AC 1 1964 284 13830 • 200 Dl 3 1993 285 13833 200 Dl 3 1986 286 13868 200 Dl 3 1993 287 13869 150 Dl 3 1990 288 13870 150 Dl 3 1990 289 13871 150 Dl 3 1994 290 13872 150 Dl 3 1986 1990 3 4 291 13873 200 Dl 3 1984 292 13874 200 Dl 3 1984 293 13875 150 Dl 3 1986 294 13876 150 Dl 3 1986 295 13877 150 Dl 3 1984 296 13878 150 Dl 3 1984 297 13879 200 Dl 3 1984 298 13880 200 Dl 3 1984 299 13881 200 Dl 3 1988 300 13882 200 Dl 3 1986 301 13883 150 Dl 3 1989 302 13884 150 Dl 3 1989 406 A H I J K L M N 303 13885 150 Dl 3 1988 304 13886 150 Dl 3 1985 305 13887 150 Dl 3 1985 306 13888 150 Dl 3 1985 307 13889 200 Dl 3 1994 1984 5 308 13890 200 Dl 3 1994 309 13891 200 Dl 3 1994 310 13892 150 Dl 3 1994 311 13893 200 Dl 3 1994 312 13894 200 Dl 3 1994 313 13895 200 Dl 3 1994 1984 7 314 13896 150 AC 1 1973 1994 6 21 315 13897 150 AC 1 1973 316 13898 150 Dl 3 1983 317 13899 150 Dl 3 1983 318 13900 150 Dl 3 1982 319 13903 150 Dl 3 1988 320 13905 150 Dl 3 1978 321 13906 150 Dl 3 1982 322 13907 150 Dl 3 1983 323 13908 150 Dl 3 1990 324 13909 150 CI 2 1999 325 13952 150 AC 1 1971 326 13953 150 Dl 3 1987 327 13954 150 AC 1 1964 328 13955 150 AC 1 1964 329 13956 150 AC 1 1964 330 13957 150 AC 1 1964 331 13958 150 AC 1 1964 332 13959 150 AC 1 1964 333 13962 150 AC 1 1964 334 13963 150 Dl 3 1990 335 13964 150 Dl 3 1990 336 13965 150 Dl 3 1990 337 13967 150 Dl 3 1990 338 13968 150 Dl 3 1990 339 13969 150 Dl . 3 1990 340 13970 150 AC 1 1964 341 13971 150 AC 1 1964 342 13974 150 AC 1 1964 1984 12 20 343 13975 150 Dl 3 1979 344 13976 150 Dl 3 1979 345 13977 150 AC 1 1964 346 13978 150 AC 1 1964 347 13979 150 Dl 3 1994 348 13980 200 Dl 3 1994 1985 12 349 13981 200 Dl 3 1994 350 13982 150 Dl 3 1991 351 13983 150 Dl 3 1991 352 13984 150 Dl 3 1991 353 13985 150 AC 1 1972 407 A H I J K L M N 354 13986 150 AC 1 1969 1995 1 26 355 13987 150 AC 1 1969 356 13990 200 DI 3 1986 357 13991 200 DI 3 1986 358 13996 150 AC 1 1972 359 13997 150 AC 1 1972 360 13998 150 ' DI 3 1995 361 14260 250 DI 3 1974 362 14264 250 DI 3 . 1994 363 14265 250 DI 3 1997 364 14266 250 DI 3 1997 365 14267 250 DI 3 1997 366 14268 250 DI 3 1997 367 14270 250 DI 3 1997 368 14271 250 DI 3 1997 369 14272 250 DI 3 1997 370 14281 200 DI 3 1996 371 14282 200 DI 3 1996 372 14283 200 DI 3 1996 373 14284 150 DI 3 1982 374 14285 150 DI 3 1996 375 14301 250 DI 3 1997 376 14302 150 AC 1 1959 1992 3 33 377 14303 250 DI 3 1997 378 14304 200 DI 3 1997 379 14305 150 DI 3 1997 380 14346 250 DI 3 1974 381 14347 150 DI 3 1995 382 14374 200 DI 3 1991 383 14375 .150 DI 3 1981 384 14523 200 AC 1 1973 1995 12 22 385 14524 200 AC 1 1973 386 14548 250 ' DI 3 1974 1993 10 19 387 14554 250 AC 1 1974 388 14555 250 DI 3 , 1998 389 14557 150 DI 3 1986 390 14558 150 DI 3 1986 391 14559 150 DI 3 1983 392 14560 150 AC 1 1975 393 14561 150 AC 1 1975 394 14562 150 AC 1 . 1975 395 14563 150 AC 1 1975 396 14564 150 AC 1 . 1975 397 14565 150 AC 1 1975 398 14566 150 DI 3 1986 399 14567 150 DI 3 1986 400 14569 150 DI 3 1986 401 14570 150 DI 3 1986 402 14571 150 DI 3 1986 403 14572 150 DI 3 1982 404 14573 150 DI 3 1982 408 A H I J K L M N 405 14574 250 Dl 3 1994 406 14575 150 AC 1 1975 407 14576 150 Dl 3 1982 408 14577 200 Dl 3 1991 409 14578 200 Dl 3 1980 410 14579 150 Dl 3 1994 411 14580 200 Dl 3 1982 412 14581 200 Dl 3 1982 413 14582 150 Dl 3 1991 414 14583 150 Dl 3 1991 415 14584 150 Dl 3 1991 1988 2 416 14585 150 Dl 3 1991 417 14586 250 Dl 3 1974 418 14587 250 Dl 3 1974 419 14588 250 Dl 3 1974 420 14589 150 Dl 3 1981 421 14590 250 Dl 3 1974 422 14591 150 Dl 3 1991 423 14592 150 Dl 3 1991 424 14593 150 Dl 3 1991 425 14594 150 Dl 3 1991 426 14595 150 Dl 3 1992 427 14721 200 Dl 3 1991 428 14754 200 Dl 3 1986 429 14756 200 Dl 3 1988 430 14768 250 Dl 3 1978 431 432 433 434 435 436 437 409 0 P • Q R S T U Has pipe been Number replaced Number Under Years In Length of breaks since soil zone of soil boulevard 1 Ground (metres) to 1999 break type zones or road 2 24 9.6 30 1 B 3 5 11.0 40 1 B 4 24 143.9 1 no 30 B 5 16 95.4 30 1 B 6 16 131.9 30 1 B 7 25 7.3 40 1 R 8 35 2.1 40 1 B 9 35 10.6 40 1 B 10 35 4.0 1 no 40 1 B 11 17 11.7 40 1 B 12 26 87.3 1 no 40 1 B 13 2 60.3 40 1 R 14 40 388.8 1 no 30 1 B 15 40 9.5 30 1 B .16 40 89.0 30 1 B .17 14 101.6 30 B 18 15 83.7 30 1 R ' 19 40 142.3 30 1 B 20 40 82.1 30 1 B 21 17 150.7 30 1 R 22 21 13.0 30 1 B 23 17 3.4 30 1 B 24 40 79.7 1 no 30 1 B 25 26 36.9 30 > 1 B 26 26 50.2 40 1 B 27 13 3.5 40 1 B 28 26 187.1 40 1 B 29 24 37.2 30 1 B 30 35 6.9 1 no 30 1 B 31 0 96.3 60 B 32 4 81.5 30 1 R 33 18 73.1 40 1 R 34 0 12.0 . 30 1 R 35 4 100.0 30 1 R 36 16 3.2 30 1 B 37 25 88.0 30 1 B 38 18 59.0 40 1 B 39 4 12.9 30 1 R 40 24 3.5 30 1 R 41 4 29.4 30 1 R 42 4 32.6 30 1 R 43 15 59.8 . 30 1 B 44 0 50.6 30 1 B 45 0 151.9 40 1 B 46 0 80.2 1 replaced 60 2 B 47 0 49.7 60 2 B 410 0 P Q R S T U 48 0 48 .8 30 2 B 49 0 92 .9 30 1 B 50 15 141.8 30 1 B 51 23 76.7 40 1 R 52 35 7.6 30 1 B 53 35 387.8 1 no 60 B 54 8 21.8 30 1 B 55 27 309.0 30 B 56 40 81.2 40 1 B 57 7 171.0 40 1 B 58 8 91 .5 40 1 R 59 8 95.1 40 1 R 60 19 156.3 70 B 61 5 150.3 40 1 R 62 17 5.7 40 1 B 63 22 10.7 40 1 B 64 22 77.7 40 1 B 6 5 22 149.3 40 1 B 66 24 143.7 40 1 B 67 9 14.7 40 1 B 68 8 118.6 40 1 B 69 8 86 .5 40 1 B 70 9 7.0 40 1 R 71 8 113.1 40 1 B 72 8 98.4 40 1 R 73 17 93 .5 40 1 B 74 17 44 .2 40 1 B 75 17 90.0 40 1 B 76 35 358 .9 40 1 B 77 2 3.5 40 1 B 78 17 156.2 40 1 B 79 17 15.5 40 1 B 80 19 17.1 30 1 . R 81 19 133.8 30 1 B 82 8 3.4 30 1 B 83 28 339.9 1 no 30 1 B 84 12 110.9 30 1 R 85 17 3.5 30 1 B 86 17 85.8 30 1 R 87 24 73.2 30 1 B 88 24 79.0 1 no 30 1 B 89 24 15.5 30 1 B 90 24 66.1 60 B 91 24 5.6 30 1 B 92 13 5.5 30 R 93 13 50.3 1 B 94 24 17.4 1 B 95 13 43.1 30 2 B 96 24 41 .0 30 2 B 97 24 24 .3 30 1 B 98 24 66 .5 30 2 B 411 0. P Q R S T U 99 16 32.4 30 1 B 100 24 142.3 1 no 60 2 B 101 24 53.3 30 1 B 102 24 1.4 30 1 B 103 22 184.3 40 1 B 104 22 19.8 40 1 B 105 22 15.6 40 1 B 106 24 64.8 60 B 107 16 125.4 30 1 B 108 16 46.0 30 1 R 109 16 121.5 30 1 B 110 24 61.1 30 1 B 111 23 286.8 60 R 112 23 4.8 40 1 R 113 23 93.4 30 1 R 114 23 336.4 30 R 115 26 9.6 40 1 B 116 28 10.4 40 1 R 117 26 6.1 40 1 R 118 26 238.5 1 no 40 1 B 119 26 95.1 40 1 R 120 8 8.7 30 1 B 121 40 15.0 40 1 R 122 4 235.4 40 1 B 123 4 2.0 40 1 R 124 2 7.0 40 1 B 125 2 22.5 40 1 B 126 17 28.8 1 no 40 1 R 127 4 3.1 40 1 R 128 1 77.4 40 1 R 129 35 50.2 40 1 B 130 2 11.8 40 1 R • 131 1 14.3 40 1 R 132 1 7.2 40 1 R 133 5 142.4 40 1 R 134 30 165.0 2 no 30 R 135 30 259.8 1 no 30 R 136 17 20.6 30 1 R 137 30 231.1 1 no 30 1 B 138 8 5.6 30 1 B 139 4 139.5 30 B 140 4 7.6 30 1 B 141 30 162.0 2 no 30 1 B 142 27 206.7 1 no 30 1 B 143 27 6.8 30 1 B 144 27 10.9 30 1 R 145 30 95.5 30 1 B 146 30 94.7 30 •1 B 147 27 7.4 30 1 B 148 30 175.6 30 1 B 149 13 52.6 30 1 R 4 7 2 0 P Q R S T U 150 27 53.2 40 1 B 151 5 19.4 30 1 B 152 5 66.2 30 1 R 153 5 20.4 30 1 B 154 5 25.9 40 1 R 155 34 32.3 30 1 B 156 5 42.4 30 1 R 157 27 150.3 1 no 30 1 B 158 27 137.1 2 no 30 1 R 159 27 11.3 30 1 B 160 27 68.7 30 1 B 161 4.8 30 1 B 162 24 5.4 30 1 B 163 27 76.9 1 no 30 1 B 164 27 149.2 30 1 B 165 2.1 30 1 B 166 43 3.5 30 - 1 R 167 40 385.2 30 1 B 168 35 6.6 30 1 B 169 31 69.4 1 no 30 1 R 170 3.5 30 1 R 171 9 11.1 40 1 R 172 9 96.9 40 1 R 173 9 12.4 40 1 R 174 4.7 40 1 B 175 9 114.2 40 1 R 176 9 22.4 40 1 • R 177 2 20.7 40 1 R 178 24 135.7 40 ,1 B 179 27 54.9 40 1 B 180 27 61.3 40 1 B 181 19 34.8 40 1 B 182 21 195.2 30 1 B 183 5 100.6 30 1 R 184 35 85.4 40 1 B 185 26 4.2 40 1 B 186 26 17.4 40 1 R 187 26 113.6 40 1 R 188 13 96.3 40 1 B 189 14.3 40 1 R 190 26 141.8 40 1 B 191 26 7.7 40 1 B 192 26 63.0 30 1 B 193 26 76.3 60 B 194 40 7.4 30 1 R 195 26 15.9 30 1 R 196 26 15.7 30 1 R 197 40 3.4 30 1 R 198 43 2.5 30 1 R 199 9 161.3 30 1 B 200 9 69.1 60 2 R 4/5 0 P Q R S T , U 201 35 388.9 1 no 60 2 B 202 17 2.0 30 1 R 203 24 19.0 30 1 R 204 21 199.8 30 1 B 205 21 13.1 30 1 R 206 21 87.7 30 1 B 207 30 3.5 30 1 R 208 8 87.8 30 1 R 209 8 82.6 1 replaced 30 1 B 210 8 160.1 30 1 B 211 8 40.9 30 1 R 212 35 3.6 30 1 B 213 21 41.0 30 1 B 214 17 41.5 60 . B 215 17 51.6 30 1 B 216 7 73.0 30 1 B 217 7 19.0 30 B 218 7 75.3 30 1 B 219 7 139.4 2 replaced 30 1 B 220 5 98.1 30 1 R 221 15 81.9 30 1 R 222 13 72.2 30 ' 1 . R 223 14 68.7 30 1 R 224 14 93.4 30 1 B 225 10 62.7 30 1 R 226 10 81.9 30 1 R 227 10 63.4 30 ^ 1 R 228 13 89.5 1 no 30 1 B 229 14 91.5 30 1 B 230 9 5.0 30 1 B 231 9 97.9 30 1 R 232 5 75.6 30 1 R 233 13 71.1 30 1 R 234 9 7.1 30 1 R 235 13 16.6 30 1 R 236 13 20.3 30 1 R 237 6 25.8 30 1 B 238 20 121.4 30 1 B 239 13 8.5 30 1 R 240 13 4.1 40 1 R 241 13 112.4 1 replaced 30 1 R 242 13 75.1 30 R 243 13 65.5 30 1 R 244 13 104.1 60 R 245 13 8.1 1 no 40 1 R 246 13 6.3 40 1 R 247 35 17.0 30 1 R 248 21 17.0 30 1 R 249 21 7.1 30 1 R 250 17 3.5 30 1 R 251 6 6.3 30 1 R 474 0 P Q R S T U 252 6 13.4 30 1 R 253 21 35.6 30 1 B 254 6 66.3 30 1 R 255 6 169.6 30 1 R 256 2 18.9 40 1 R 257 35 58.1 40 3 (closed roac 258 24 113.8 40 1 B 259 27 208.8 30 1 B 260 13 30.8 30 1 B 261 13 134.1 30 B 262 6 2.9 30 1 R 263 6 119.2 60 R 264 6 33.1 30 1 R 265 6 28.7 30 1 R ?66 35 53.1 30 1 B 267 6 1.7. 30 1 R 268 6 23.4 30 1 R 269 6 31.8 30 1 R 270 14 ;102.2 30 1 B 271 14 90.3 1 replaced 60 R 272 6 59.5 30 1 R 273 6 42.6 30 1 B 274 35 88.7 30 1 R 275 3 112.2 40 1 B 276 3 139.2 40 1 B 277 21 10.8 30 1 R 278 4 129.4 40 1 B 279 4 166.6 30 1 R 280 17 54.4 30 1 R 281 35 13.2 1 no 30 1 B 282 35 139.8 30 1 B 283 35 37.4 30 1 B 284 6 107.9 60 R 285 13 187.6 30 B 286 6 431.4 30 1 B 287 9 50.9 30 1 B 288 9 131.0 30 B 289 5 68.7 30 1 B 290 13 173.8 1 no 30 1 B 291 15 4.5 30 1 R 292 15 129.4 30 1 R 293 13 133.7 30 R 294 13 232.3 30 1 R 295 15 169.5 60 B 296 15 202.3 60 B 297 15 91.5 30 1 R 298 15 70.2 30 1 R 299 11 105.9 30 1 R 300 13 53.6 30 1 R 301 10 109.9 30 1 B 302 10 20.3 30 1 B 415 0 P Q R S T U 303 11 127.2 30 1 B 304 14 77.3 30 1 B 305 14 101.5 30 1 B 306 14 84.5 30 1 B 307 5 164.2 1 replaced 60 R 308 5 6.8 30 1 R 309 5 92.2 30 R 310 5 26.2 30 R 311 5 145.0 30 1 R 312 5 45.1 30 1 R 313 5 97.3 1 replaced 30 1 R 314 26 113.4 1 no 30 B 315 26 34.6 30 1 B 316 16 58.1 30 1 B 317 16 104.7 30 1 B 318 17 46.5 30 1 R 319 11 169.8 60 B 320 21 15.2 30 1 R 321 17 76.6 30 1 B 322 16 85.7 60 B 323 9 163.9 30 1 B 324 0 4.2 30 1 B 325 28 206.7 30 1 B 326 12 133.0 30 1 B 327 35 265.2 60 B 328 35 140.6 40 1 B •329 35 362.5 40 1 B 330 35 4.6 40 1 5 (closed roac 331 35 6.6 40 1 R 332 35 23.7 40 1 R " 333 35 9.7 40 1 B 334 9 27.1 40 1 B 335 9 58.9 40 1 B 336 9 19.6 40 1 R 337 9 80.8 40 1 B 338 9 50.2 40 1 B 339 9 137.2 40 1 B 340 35 75.1 40 1 B 341 35 73.5 60 R 342 35 266.3 3 no 40 1 B 343 20 58.4 30 1 R 344 20 138.9 30 R 345 35 18.2 30 1 R 346 35 1.5 30 1 B 347 5 30.6 30 1 R 348 5 113.3 1 replaced 30 1 R 349 5 164.0 60 R 350 8 23.6 30 1 B 351 8 163.5 30 B 352 8 18.1 30 1 B 353 27 18.0 30 1 B 416 0 P Q R S T U 354 30 120.1 1 no 30 2 B 355 30 102.2 30 1 B 356 13 63.3^ 30 1 R 357 13 74.0 30 1 R 358 27 79.8 30 1 B 359 27 230.5 30 B 360 4 9.2 30 1 B 361 25 72.2 . 40 1 R 362 5 12.1 40 1 R 363 2 143.0 40 1 R 364 2 1.3 40 1 R 365 2 32.3 40 1 R 366 2 99.5 40 1 R 367 2 98.5 40 1 R 368 2 19.8 40 1 R 369 2 115.6 40 1 R 370 3 85.3 40 1 B 371 3 8.6 40 1 R 372 3 8.8 40 1 R 373 17 37.9 40 1 B 374 3 6.0 40 1 R 375 2 73.7 40 1 R 376 40 397.3 1 no 40 1 B 377 2 118.4 40 1 R 378 2 9.2 40 1 R 379 2 28.6 40 1 B 380 25 82.8 40 1 R 381 4 118.4 40 1 R 382 8 14.3 30 1 R 383 18 124.9 40 1 R 384 26 147.0 1 no 40 1 B 385 26 78.4 40 1 R 386 25 252.3 1 no • 40 1 R 387 25 155.2 40 1 R 388 1 5.5 40 1 R 389 13 161.0 30 B 390 13 23.0 30 1 B 391 16 48.4 30 1 B 392 24 178.0 30 1 B 393 24 16.5 30 1 R 394 24 73.1 30 1 B 395 24 16.2 30 1 R 396 24 38.0 30 . 1 B 397 24 21.3 30 1 R 398 13 12.3 30 1 B 399 13 151.4 30 R 400 13 173.1 30 B 401 13 91.9 30 1 B 402 13 30.0 30 1 B 403 17 51.4 30 2 R 404 17 8.9 30 1 R 417 0 P Q R S T U 405 5 22.5 40 1 R 406 24 152.3 60 2 B 407 17 9.4 30 1 R 408 8 259.8 30 1 B 409 19 189.8 30 1 B 410 5 20.3 40 1 B 411 17 158.0 40 1 B 412 17 81.7 40 1 B 413 8 177.6 40 1 R 414 8 217.5 40 1 R 415 8 16.8 1 replaced 40 1 R 416 8 193.4 40 1 R 417 25 52.5 40 1 R 418 25 44.4 40 1 R 419 25 51.1 40 1 R 420 18 113.4 40 1 B 421 25 47.8 40 1 R 422 8 141.1 40 1 B 423 8 46.4 40 1 B 424 8 74.3 40 1 B 425 8 123.9 40 1 B 426 7 156.8 40 1 B 427 8 70.0 30 B 428 13 30.0 40 1 R 429 11 126.9 30 1 R 430 21 2.1 30 1 R s 431 total breaks 47 432 433 434 435 436 • 437 418 V W X Y Z AA AB Surface traffic Pipe Pipe 1 material classification lining Bedding Backfill protection C factor 2 asphalt local unlined sand sand none 105 3 asphalt local CML gravel crush gravel wrapped 136 4 gravel/grass no traffic unlined sand sand none 105 5 gravel/grass no traffic CML gravel crush gravel wrapped 113 6 gravel/grass no traffic CML gravel crush gravel wrapped 111 7 asphalt collector unlined sand sand none 118 8 asphalt local unlined sand sand none 115 9 . asphalt local unlined sand sand none 115 10 asphalt local unlined sand sand none 115 11 asphalt local unlined sand sand none 122 12 asphalt local unlined sand sand none 115 13 asphalt collector CML gravel crush gravel wrapped 136 14 gravel/grass no traffic nil native native none 95 15 asphalt local unlined sand sand none 122 16 asphalt local unlined sand sand none 122 17 gravel/grass no traffic CML gravel crush gravel wrapped 116 18 asphalt local CML gravel crush gravel wrapped . 121 19 asphalt local unlined sand sand none 115 20 asphalt local unlined sand sand none 115 21 asphalt local CML gravel crush gravel wrapped 111 22 gravel/grass no traffic CML gravel crush gravel wrapped 118 23 asphalt local CML gravel crush gravel wrapped 132 24 asphalt local unlined sand sand none 115 25 concrete local unlined sand sand none 115 26 concrete local unlined sand sand none 115 27 gravel/grass no traffic CML gravel crush gravel wrapped 28 asphalt local unlined sand sand none 115 29 gravel/grass no traffic unlined sand sand none 105 30 concrete local unlined sand sand none 115 .31 gravel/grass no traffic CML gravel crush gravel wrapped 124 32 asphalt collector CML gravel crush gravel wrapped 105 33 asphalt local CML gravel crush gravel wrapped 114 34 asphalt local CML gravel crush gravel wrapped 111 35 asphalt collector CML gravel crush gravel wrapped 105 36 asphalt . local CML gravel crush gravel wrapped 113 37 gravel/grass no traffic unlined sand sand none 115 38 gravel/grass no traffic CML gravel crush gravel wrapped 39 asphalt local CML gravel crush gravel wrapped 118 40 asphalt collector CML gravel crush gravel wrapped 105 41 asphalt collector CML gravel crush gravel wrapped 132 42 asphalt collector CML gravel crush gravel wrapped 121 43 gravel/grass no traffic CML gravel crush gravel wrapped 114 44 gravel/grass no traffic CML gravel crush gravel wrapped 111 45 gravel/grass no traffic CML gravel crush gravel wrapped 138 46 gravel/grass no traffic CML gravel crush gravel wrapped 105 47 gravel/grass no traffic CML gravel crush gravel wrapped 105 419 \ V W X Y Z AA AB • 48 gravel/grass no traffic CML gravel crush gravel wrapped 105 49 gravel/grass no traffic CML gravel crush gravel wrapped 105 50 gravel/grass no traffic CML gravel crush gravel wrapped 132 51 asphalt collector CML gravel crush gravel wrapped 118 52 gravel/grass no traffic unlined sand sand none 126 53 gravel/grass no traffic unlined sand sand none 115 54 gravel/grass no traffic CML gravel crush gravel wrapped 100 55 gravel/grass no traffic unlined sand sand none 105 56 gravel/grass no traffic unlined sand sand none 57 gravel/grass parking CML gravel crush gravel wrapped 127 58 asphalt local CML gravel crush gravel wrapped 126 59 asphalt local CML gravel crush gravel wrapped 126 60 gravel/grass no traffic CML gravel crush gravel wrapped 61 asphalt local CML gravel crush gravel wrapped 110 62 asphalt local CML gravel crush gravel wrapped 110 63 gravel/grass no traffic nil native native none 106 64 gravel/grass no traffic nil native native none 99 65 gravel/grass no traffic nil native native none 106 66 gravel/grass no traffic unlined sand sand none 105 67 gravel/grass no traffic CML gravel crush gravel wrapped 124 , 68 gravel/grass no traffic CML gravel crush gravel wrapped 124 , 69 gravel/grass no traffic CML gravel crush gravel wrapped 124 70 asphalt local CML gravel crush gravel wrapped . 124 71 gravel/grass no traffic CML gravel crush gravel wrapped 124 72 asphalt local CML gravel crush gravel wrapped 126 73 gravel/grass parking CML gravel crush gravel wrapped 118 74 gravel/grass parking CML gravel crush gravel wrapped 136 75 gravel/grass parking CML gravel crush gravel wrapped 136 . 76 gravel/grass no traffic unlined sand sand none 105 77 gravel/grass parking CML gravel crush gravel wrapped 136 78 gravel/grass parking CML gravel crush gravel wrapped 136 79 gravel/grass parking CML gravel crush gravel wrapped 136 80 asphalt arterial CML gravel crush gravel wrapped 128 81 gravel/grass no traffic CML gravel crush gravel wrapped 128 82 asphalt local CML gravel crush gravel wrapped 110 83 gravel/grass no traffic unlined sand sand none 105 84 asphalt local CML gravel crush gravel wrapped 85 asphalt local CML gravel crush gravel wrapped 111 86 asphalt collector CML gravel crush gravel wrapped 111 87 gravel/grass no traffic unlined sand sand none 105 88 gravel/grass no traffic unlined sand sand none 105 89 gravel/grass no traffic unlined sand sand none 105 90 gravel/grass no traffic unlined sand sand none 91 concrete local unlined sand sand none 105 92 asphalt local CML gravel crush gravel wrapped 118 93 gravel/grass no traffic CML gravel crush gravel wrapped 118 94 gravel/grass no traffic unlined sand sand none 95 gravel/grass no traffic CML gravel crush gravel wrapped 118 96 gravel/grass no traffic unlined sand sand none 105 97 gravel/grass no traffic unlined sand sand none 105 98 gravel/grass no traffic unlined sand sand none 108 420 V W X Y Z AA AB 99 gravel/grass no traffic CML gravel crush gravel wrapped 118 100 gravel/grass no traffic unlined sand sand none 108 101 gravel/grass no traffic unlined sand sand none 102 gravel/grass no traffic unlined sand sand none 105 103 gravel/grass no traffic unlined sand sand none 108 104 gravel/grass no traffic unlined sand sand none 108 105 gravel/grass no traffic unlined sand sand none 108 106 gravel/grass no traffic unlined sand sand none 105 107 gravel/grass no traffic CML gravel crush gravel wrapped 118 108 asphalt local CML gravel crush gravel wrapped 109 gravel/grass no traffic CML gravel crush gravel wrapped 118 110 gravel/grass no traffic unlined sand sand none 105 111 asphalt collector CML gravel crush gravel wrapped 114 112 asphalt collector CML gravel crush gravel wrapped 118 113 asphalt collector CML gravel crush gravel wrapped 114 114 asphalt collector CML gravel crush gravel wrapped 116 115 asphalt local unlined sand sand none 115 116 asphalt collector unlined sand sand none 115 117 asphalt local unlined sand sand none 115 118 concrete local unlined sand sand none 115 119 asphalt local unlined sand sand none ' 115 120 asphalt local CML gravel crush gravel wrapped 129 121 asphalt local unlined sand sand none 115 122 gravel/grass no traffic CML gravel crush gravel wrapped 110 123 asphalt local CML gravel crush gravel wrapped 124 gravel/grass no traffic CML gravel crush gravel wrapped 100 125 gravel/grass no traffic CML gravel crush gravel wrapped 136 126 asphalt local CML gravel crush gravel wrapped 136 127 asphalt local CML gravel crush gravel wrapped 128 asphalt local CML gravel crush gravel wrapped 129 gravel/grass no traffic nil native native none 99 130 asphalt local CML gravel crush gravel wrapped 127 131 asphalt collector CML gravel crush gravel wrapped 132 asphalt collector CML gravel crush gravel wrapped 133 asphalt collector CML gravel crush gravel wrapped 133 134 asphalt local unlined sand sand none 105 135 asphalt local unlined sand sand none 105 136 asphalt collector CML gravel crush gravel wrapped 129 137 Dncrete sidewa no traffic unlined sand sand none 115 138 gravel/grass local CML gravel crush gravel wrapped 129 139 gravel/grass no traffic CML gravel crush gravel wrapped 100 •140 gravel/grass no traffic CML gravel crush gravel wrapped 100 141 gravel/grass no traffic unlined sand sand none 105 142 gravel/grass no traffic unlined sand sand none 143 gravel/grass no traffic unlined sand sand none 105 144 asphalt local unlined sand sand none 105 145 concrete no traffic unlined sand sand none 105 146 gravel/grass no traffic unlined sand sand none 105 147 concrete no traffic unlined sand sand none 105 148 concrete no traffic unlined sand sand none 105 149 asphalt local CML gravel crush gravel wrapped 421 V W X Y Z AA AB 150 gravel/grass no traffic unlined sand sand none 130 151 gravel/grass no traffic CML gravel crush gravel wrapped 130 152 asphalt collector CML gravel crush gravel wrapped 133 153 gravel/grass no traffic CML gravel crush gravel wrapped 100 154 asphalt collector CML gravel crush gravel wrapped 132 155 gravel/grass no traffic nil native native none 156 asphalt collector CML gravel crush gravel wrapped 133 157 gravel/grass no traffic unlined sand sand none 105 158 asphalt local unlined sand sand none 105 159 gravel/grass no traffic unlined sand sand none 105 160 gravel/grass no traffic unlined sand sand none 105 161 gravel/grass no traffic unlined sand sand none 162 gravel/grass no traffic unlined sand sand none 105 163 gravel/grass no traffic unlined sand sand none 164 gravel/grass no traffic unlined sand sand none 105 165 gravel/grass local nil native native none 166 asphalt local nil native native none 105 167 gravel/grass local nil native native none 105 168 asphalt no traffic unlined sand sand none 105 169 asphalt parking lot nil native native none 129 170 asphalt parking lot CML gravel crush gravel wrapped 171 asphalt local CML gravel crush gravel wrapped 124 172 asphalt local CML gravel crush gravel wrapped 124 173 asphalt local CML gravel crush gravel wrapped 130 174 gravel/grass no traffic nil native native none 175 asphalt local CML gravel crush gravel wrapped 124 1.76 asphalt local CML gravel crush gravel wrapped 130 177 asphalt local CML gravel crush gravel wrapped 126 178 gravel/grass no traffic unlined sand sand none 115 179 gravel/grass no traffic unlined sand sand, none 180 gravel/grass no traffic unlined sand sand none 105 181 gravel/grass no traffic unlined sand sand none 182 gravel/grass no traffic CML gravel crush gravel wrapped 100 183 asphalt local CML gravel crush gravel wrapped 184 gravel/grass no traffic unlined sand sand none 105 185 asphalt local unlined sand sand none 115 186 asphalt local unlined sand sand none 115 187 asphalt local unlined sand / sand none 115 188 gravel/grass no traffic CML gravel crush gravel wrapped 189 asphalt local CML gravel crush gravel wrapped 190 concrete local unlined sand sand . none 115 191 asphalt local unlined sand sand none 115 192 concrete local unlined sand sand none 115 193 concrete local unlined sand sand none •115 194 asphalt local unlined sand sand none 115 195 asphalt local unlined sand sand none 115 196 asphalt local unlined sand sand none 115 197 asphalt local unlined sand sand none 115 198 asphalt local nil native native none 105 199 gravel/grass no traffic CML gravel crush gravel wrapped 100 200 asphalt local CML gravel crush gravel wrapped 100 422 V W X Y Z AA AB 201 gravel/grass no traffic unlined sand sand none 105 202 asphalt local CML gravel crush gravel wrapped 132 203 asphalt local nil native native none 204 gravel/grass no traffic CML gravel crush gravel wrapped 114 205 asphalt local CML gravel crush gravel wrapped 114 206 gravel/grass no traffic CML gravel crush gravel wrapped 114 207 asphalt local unlined sand sand none 105 208 asphalt commercial CML gravel crush gravel wrapped 134 209 gravel/grass no traffic CML gravel crush gravel wrapped 129 210 gravel/grass no traffic CML gravel crush gravel wrapped 129 211 asphalt commercial CML gravel crush gravel wrapped 134 212 gravel/grass parking unlined sand •sand none 105 213 gravel/grass no traffic CML gravel crush gravel wrapped 114 214 gravel/grass no traffic CML gravel crush gravel wrapped 215 gravel/grass no traffic CML gravel crush gravel wrapped 111 216 gravel/grass no traffic CML gravel crush gravel wrapped 95 217 gravel/grass no traffic CML gravel crush gravel wrapped 95 218 gravel/grass no traffic CML gravel crush gravel wrapped 95 219 gravel/grass no traffic CML gravel crush gravel wrapped 95 220 asphalt collector CML gravel crush gravel wrapped 133 221 asphalt local CML gravel crush gravel wrapped .130 222 asphalt local CML gravel crush gravel wrapped 223 asphalt local CML gravel crush gravel wrapped 224 gravel/grass no traffic CML gravel crush gravel wrapped 225 asphalt local CML gravel crush gravel wrapped 226 asphalt local CML gravel crush gravel wrapped 121 227 asphalt local CML gravel crush gravel wrapped 228 gravel/grass no traffic CML gravel crush gravel wrapped 130 229 gravel/grass no traffic CML gravel crush gravel wrapped 130 230 gravel/grass no traffic CML gravel crush gravel wrapped 118 231 asphalt local CML gravel crush gravel wrapped 114 232 asphalt local CML gravel crush gravel wrapped 233 asphalt local CML gravel crush gravel wrapped 124 234 asphalt local CML gravel crush gravel wrapped 124 235 asphalt local CML gravel crush gravel wrapped 236 asphalt local CML gravel crush gravel wrapped 237 gravel/grass no traffic CML gravel crush gravel wrapped 132 238 gravel/grass no traffic nil native native none 105 239 asphalt 224th CML gravel crush gravel wrapped 123 240 asphalt 224th CML gravel crush gravel wrapped 132 241 . asphalt 224th CML gravel crush gravel wrapped 123 242 asphalt 224th CML gravel crush gravel wrapped 123 243 asphalt 224th CML gravel crush gravel wrapped 123 244 asphalt 224th CML gravel crush gravel wrapped 123 245 asphalt 224th CML gravel crush gravel wrapped 128 246 asphalt local CML gravel crush gravel wrapped 128 247 asphalt 224th unlined sand sand none 105 248 asphalt local nil nil nil nil 249 asphalt local nil nil nil nil 122 250 asphalt local CML gravel crush gravel wrapped 114 251 asphalt local CML • gravel crush gravel wrapped 129 423 J V W X Y Z AA AB 252 asphalt lane CML gravel crush gravel wrapped 134 253 gravel/grass no traffic CML gravel crush gravel wrapped 114 254 asphalt Brown Ave. CML gravel crush gravel wrapped 132 255 asphalt Brown Ave. CML gravel crush gravel wrapped 132 256 asphalt collector CML gravel crush gravel wrapped 136 257 asphalt no traffic unlined sand sand none 119 258 gravel/grass no traffic unlined sand sand none 115 259 gravel/grass no traffic unlined sand sand ; none 118 260 gravel/grass no traffic CML gravel crush gravel wrapped 118 261 gravel/grass no traffic CML gravel crush gravel wrapped 118 262 asphalt local CML gravel crush gravel wrapped 132 263 asphalt Brown Ave. CML gravel crush gravel wrapped 132 264 asphalt 224th CML gravel crush gravel wrapped 132 265 asphalt 224th CML gravel crush gravel wrapped 132 266 gravel/grass no traffic unlined sand sand none 115 267 asphalt Brown Ave. CML gravel crush gravel wrapped 132 268 asphalt commercial CML gravel crush gravel wrapped 118 269 asphalt local CML gravel crush gravel wrapped 120 270 gravel/grass no traffic CML gravel crush gravel wrapped 113 271 asphalt local CML gravel crush gravel wrapped 272 asphalt Brown Ave. CML gravel crush gravel wrapped 114 273 gravel/grass no traffic CML gravel crush gravel wrapped 120 274 asphalt lane unlined sand sand none 105 275 gravel/grass no traffic CML gravel crush gravel wrapped 130 276 gravel/grass no traffic CML gravel crush gravel wrapped 130 277 asphalt local CML gravel crush gravel wrapped 114 278 gravel/grass no traffic CML gravel crush gravel wrapped 124 279 asphalt local CML gravel crush gravel wrapped 123 280 asphalt local CML gravel crush gravel wrapped 126 281 gravel/grass local unlined sand sand none 115 282 gravel/grass no traffic unlined sand sand none 115 283 gravel/grass no traffic unlined sand sand none 115 284 asphalt collector CML gravel crush gravel wrapped 128 285 gravel/grass no traffic - CML gravel crush gravel wrapped 118 286 gravel/grass no traffic CML gravel crush gravel wrapped 126 287 gravel/grass no traffic CML gravel crush gravel wrapped 118 288 gravel/grass no traffic CML gravel crush gravel wrapped 118 289 gravel/grass no traffic CML gravel crush gravel wrapped 132 290 lawns . no traffic CML gravel crush gravel wrapped 118 291 asphalt local CML gravel crush gravel wrapped 121 292 asphalt local CML gravel crush gravel wrapped 121 293 asphalt local CML gravel crush gravel wrapped 100 294 asphalt local CML gravel crush gravel wrapped 100 295 gravel/grass no traffic CML gravel crush gravel wrapped 114 296 gravel/grass no traffic CML gravel crush gravel wrapped 114 . 297 asphalt local CML gravel crush gravel wrapped 123 298 asphalt local CML gravel crush gravel wrapped 123 299 asphalt local CML gravel crush gravel wrapped 123 300 asphalt local CML gravel crush gravel wrapped 123 301 gravel/grass no traffic CML gravel crush gravel wrapped 121 302 gravel/grass no traffic .CML gravel crush gravel wrapped 121 424 V W X Y Z AA AB 303 gravel/grass no traffic CML gravel crush gravel wrapped 100 304 gravel/grass no traffic CML gravel crush gravel wrapped 116 305 gravel/grass no traffic CML gravel crush gravel wrapped 118 306 gravel/grass no traffic CML gravel crush gravel wrapped 126 307 asphalt collector CML gravel crush gravel wrapped 121 308 asphalt collector CML gravel crush gravel wrapped 133 309 asphalt collector CML gravel crush gravel wrapped 133 310 asphalt local CML gravel crush gravel wrapped 121 311 asphalt collector CML gravel crush gravel wrapped 133 312 asphalt collector CML gravel crush gravel wrapped 133 313 asphalt collector CML gravel. crush gravel wrapped 133 314 gravel/grass no traffic unlined sand sand none 315 gravel/grass no traffic unlined sand sand none 133 316 gravel/grass no traffic CML gravel crush gravel wrapped 111 317 gravel/grass no traffic CML gravel crush gravel wrapped 111 318 asphalt local CML gravel crush gravel wrapped 111 319 gravel/grass parking CML gravel crush gravel wrapped 116 320 asphalt local CML gravel crush gravel wrapped 321 gravel/grass no traffic CML gravel crush gravel wrapped 322 gravel/grass no traffic CML gravel crush gravel wrapped 323 gravel/grass no traffic CML gravel crush gravel wrapped 100 324 gravel/grass local nil native native none 95 325 gravel/grass no traffic unlined sand sand none 105 326 gravel/grass no traffic CML gravel crush gravel wrapped 122 327 gravel/grass no traffic unlined sand sand none 105 328 gravel/grass no traffic unlined sand sand none 105 329 gravel/grass parking unlined sand sand none 105 330 asphalt no traffic unlined sand sand none 331 asphalt local unlined sand sand none 105 332 asphalt local unlined sand sand none 105 333 gravel/grass local unlined sand sand none 105 334 gravel/grass . no traffic CML gravel crush gravel wrapped 105 335 gravel/grass no traffic CML gravel crush gravel wrapped 118 336 asphalt collector CML gravel crush gravel wrapped 127 337 gravel/grass no traffic CML gravel crush gravel wrapped 124 338 gravel/grass no traffic CML gravel crush gravel wrapped 124 339 gravel/grass no traffic CML gravel crush gravel wrapped 124 340 asphalt parking unlined sand sand none 105 341 asphalt local unlined sand sand none 105 342 gravel/grass no traffic unlined sand sand none 105 343 asphalt local CML gravel crush gravel wrapped 122 344 asphalt parking lot CML gravel crush gravel wrapped 100 345 asphalt local unlined sand sand none 105 346 gravel/grass no traffic unlined sand sand none 105 347 asphalt local CML gravel crush gravel wrapped 100 348 asphalt collector CML gravel crush gravel wrapped 133 349 asphalt collector CML gravel crush gravel wrapped 133 350 gravel/grass no traffic CML gravel crush gravel wrapped 100 351 gravel/grass no traffic CML gravel crush gravel wrapped 100 352 gravel/grass no traffic CML gravel crush gravel wrapped 100 353 gravel/grass no traffic unlined sand sand none 105 425 V W X Y Z AA AB 354 gravel/grass no traffic unlined sand sand none 105 355 gravel/grass no traffic unlined sand sand none 105 356 asphalt local CML gravel crush gravel wrapped 122 357 , asphalt local CML gravel crush gravel wrapped 122 358 gravel/grass no traffic unlined sand sand none 359 gravel/grass no traffic unlined sand sand none 100 360 gravel/grass no traffic CML gravel crush gravel wrapped 100 361 asphalt collector CML gravel crush gravel wrapped 114 362 asphalt collector CML gravel crush gravel wrapped 136 363 asphalt collector CML gravel crush gravel wrapped 136 364 asphalt local CML gravel crush gravel wrapped 365 asphalt collector CML gravel crush gravel wrapped 136 366 asphalt collector CML gravel crush gravel wrapped 136 367 asphalt collector CML gravel crush gravel wrapped 136 368 asphalt collector CML gravel crush gravel wrapped 136 369 asphalt collector CML gravel crush gravel wrapped 136 370 gravel/grass no traffic CML gravel crush gravel wrapped 134 371 asphalt local CML gravel crush gravel wrapped 134 372 asphalt local CML gravel crush gravel wrapped 135 373 gravel/grass no traffic CML gravel crush gravel wrapped 374 asphalt local CML gravel crush gravel wrapped 110 375 asphalt collector CML gravel crush gravel wrapped 136 376 gravel/grass no traffic unlined sand sand none 105 377 asphalt collector CML gravel crush gravel wrapped 114 378 asphalt collector CML gravel crush gravel wrapped 133 379 gravel/grass no traffic CML gravel crush gravel wrapped 135 380 asphalt collector CML gravel crush gravel wrapped 114 381 asphalt local CML gravel crush gravel wrapped 382 asphalt arterial CML gravel crush gravel wrapped 129 383 asphalt local CML gravel crush gravel wrapped 114 384 concrete local unlined sand sand none 115 385 asphalt local unlined sand sand none 115 386 asphalt collector CML gravel crush gravel wrapped 110 387 asphalt collector unlined sand sand none 118 388 asphalt collector CML gravel crush gravel wrapped 114 389 gravel/grass no traffic CML gravel crush gravel wrapped 113 390 gravel/grass no traffic CML gravel crush gravel wrapped 113 391 gravel/grass no traffic CML gravel crush gravel wrapped 113 392 gravel/grass no traffic unlined sand sand none 132 393 asphalt local unlined sand sand none 132 394 gravel/grass local unlined sand sand none 105 395 asphalt local unlined sand sand none 105 396 gravel/grass no traffic unlined sand sand none 105 397 asphalt local unlined sand sand none 398 gravel/grass no traffic CML gravel crush gravel wrapped 113 399 asphalt local CML gravel . crush gravel wrapped 400 gravel/grass no traffic CML gravel crush gravel wrapped 111 401 gravel/grass no traffic CML gravel crush gravel wrapped 118 402 gravel/grass no traffic CML gravel crush gravel wrapped 111 403 asphalt collector CML gravel crush gravel wrapped 111 404 asphalt collector CML gravel • crush gravel wrapped 111 426 V W X Y Z AA AB 405 asphalt collector CML gravel crush gravel wrapped 130 406 gravel/grass no traffic unlined sand sand none 105 407 asphalt local CML gravel crush gravel wrapped 118 408 gravel/grass no traffic CML gravel crush gravel wrapped 115 409 gravel/grass no traffic CML gravel crush gravel wrapped 128 410 gravel/grass no traffic CML gravel crush gravel wrapped 100 411 gravel/grass parking CML gravel crush gravel wrapped 118 412 gravel/grass parking CML gravel crush gravel wrapped 118 413 asphalt local CML gravel crush gravel wrapped 126 414 asphalt local CML gravel crush gravel wrapped 126 415 asphalt local CML gravel crush gravel wrapped 126 416 asphalt local CML gravel crush gravel wrapped 134 417 asphalt collector CML gravel crush gravel wrapped 114 418 asphalt collector CML gravel crush gravel wrapped 114 419 asphalt collector CML gravel crush gravel wrapped 114 420 gravel/grass no traffic CML gravel crush gravel wrapped 110 421 asphalt collector CML gravel crush gravel wrapped 114 422 gravel/grass no traffic CML gravel crush gravel wrapped 126 423 gravel/grass no traffic CML gravel crush gravel wrapped 424 gravel/grass no traffic CML gravel crush gravel wrapped 126 425 gravel/grass no traffic CML gravel crush gravel wrapped 126 426 gravel/grass no traffic CML gravel crush gravel wrapped 127 427 gravel/grass no traffic CML gravel crush gravel wrapped 428 asphalt collector CML gravel crush gravel wrapped 429 asphalt local CML gravel crush gravel wrapped 430 asphalt local CML gravel crush gravel wrapped 431 432 433 434 435 436 437 427 AC AD AE AF AG AH 1 Roughness Q J p s V m p s C_hazen HGL_M MDD P PSI 2 120 1.1071 0.06 110 91.43 93.78 3 110 1.1846 0.02 . 120 91.46 83.57 4 120 0.1501 0.01 110 91.43 99.74 5 110 0.2895 0.01 120 .91.43 111.83 6 110 0.489 0.02 120 91.43 112.69 7 120 3.4243 0.07 110 91.45 84.84 8 120 4.7193 0.15 110 91.50 86.62 9 120 6.8822 0.21 110 91.50 86.33 10 120 6.8822 0.19 120 91.50 86.19 11 120 6.8822 0.21 110 91.49 85.90 12 120 2.1733 0.07 110 91.50 84.77 13 110 3.8701 0.07 120 91.46 80.17 14 90 1.5892 0.09 90 91.74 79.29 15 120 14.9009 0.29 110 91.77 78.61 16 120 9.1198 0.18 110 91.77 ,78.61 17 110 0.8437 0.04 120 91.47 '94.55 18 110 2.4353 0.07 120 91.51 113.65 19 120 8.8245 0.17 110 91.73 78.84 20 120 11.435 0.23 110 91.73 78.84 21 110 1.6043 0.08 120 91.67 88.00 22 110 6.1248 0.11 120 91.70 79.79 23 110 3.8281 0.07 120 91.68 84.31 24 120 6.7853 0.21 110 91.74 79.29 25 120 4.8998 0.15 110 91.65 79.29 26 120 1.061 0.03 110 91.59 78.35 27 91.54 78.86 28 120 2.9552 0.14 120v 91.51 80.66 29 120 0.4502 0.02 110 91.43 97.76 30 120 4.9614 0.1 110 91.67 81.31 31 110 1.1072 0.05 120 91.68 86.88 32 120 2.1949 0.06 120 91.55 103.19 33 1.10 1.7867 0.09 120 91.48 84.32 34 110 3.386 0.06 120 91.68 84.31 35 120 3.5227 0.17 120 91.58 101.95 36 110 1.1173 0.05 120 91:69 77.64 37 120 2.9637 0.06 110 93.49 79.21 38 91.48 84.32 39 110 1.2098 0.06 120 91.55 102.48 40 120 2.1949 0.06 120 91.55 102.48 41 120 5.2512 0.25 120 91.55 103.19 42 110 3.7218 0.1 120 91.53 102.88 43 110 0.9815 0.05 120 91.51 104.13 44 110 0.8153 0.04 120 91.68 85.31 45 90 0 0 120 91.43 86.24 46 120 0.5066 0.01 120 91.68 86.88 47 120 3.2157 0.06 120 91.68 84.17 428 AC AD AE AF AG AH 48 120 0.3303 0.02 90 91.68 84.17 49 120 1.2259 0.02 120 91.68 81.47 50 110 3.0612 0.08 120 91.52 121.78 51 110 3.2905 0.09 120 91.45 85.69 52 120 5.7334 0.11 110 91.66 81.31. 53 120 6.3895 • 0,13 110 91.62 102.00 54 110 0.8051 0.04 120 91.46 100.50 55 120 0.3031 0.02 , 110 91.47 92.26 56 91.50 80.64 57 110 0.7394 0.04 120 91.46 80.17 58 110 0.3845 0.02 120 91.46 80.73 59 110 0.4648 0.02 120 91.46 80.58 60 91.47 82.30 61 110 1.2489 0.06 120 91.45 83.42 62 110 1.2489 0.06 120 91.46 80.44 63 90 0.0189 0 90 91.45 84.84 64 90 1.0823 0.06 90 91.45 83.42 65 90 0.0189 0 90 91.45 83.42 66 120 1.0356 0.06 110 91.44 82.41 67 110 0.5388 0.03 . 120 91.46 80.58 68 110 0.5388 0.03 120 91.46 80.45 69 110 0.5388 0.03 120 91.46 80.45 70 110 0.5388 0.03 120 91.46 80.58 71 110 0.5388 0.03 120 91.46 80.58 72 110 0.4155 . 0.02 120 91.46 80.73 73 110 0.5985 0.02 120 91.46 80.73 74 110 0.4756 0.01 120 91.46 80.73 75 110 0.4756 0.01 120 91.46 80.73 76 120 0.9964 0.05 110 91.44 82.41 77 110 0.4756 0.01 120 91.46 80.73 78 110 0.4756 0.01 120 91.46 81.58 79 110 0.4756 0.01 120 91.46 81.58 80 110 1.0068' 0.03 120 91.42 121.07 81 110 1.0068 0.03 120 91.42 121.07 82 110 0.2288 0.01 120 91.43 118.23 83 120 0.2288 0.01 110 91.43 118.23 84 91.43 108.56 85 110 0.4779 0.02 120 91.43 108.56 86 110 0.4779 0.02 120 91.43 105.01 87 120 0.4408 0.02 110 91.43 97.76 88 120 0.5804 0.03 110 91.43 93.91 89 120 0.1945 0.01 110 91.43 93.91 90 91.43 93.35 91 120 0.4408 0.02 110 91.43 94.20 92 110 0.0776 0 120 91.43 106.86 93 110 0.2576 0.01 120 91.43 106.86 94 91.43 93.91 95 110 0.2576 0.01 120 91.43 99.74 96 120 0.5236 0.03 110 91.43 101.17 97 120 0.5236 0.03 110 91.43 101.17 98 120 0.7474 0.04 110 91.43 101.45 429 AC AD AE AF AG AH 99 110 0.1077 0.01 120 91.43 104.15 100 120 0.8306 0.05 110 91.43 101.45 101 91.43 101.45 102 120 0.0851 0 110 91.43 101.17 103 120 0.8306 0.05 110 91.44 92.65 104 120 0.8306 0.05 110 91.45 83.42 105 120 0.8306 0.05 110 91.45 83.42 106 120 0.5236 0.03 110 91.43 88.08 107 110 0.1077 0.01 120 91.43 110.98 108 91.43 108.56 109 110 0.1077 0.01 120 91.43 104.15 110 120 0.5992 0.03 110 91.43 104.15 111 110 2.4234 0.07 120 91.44 92.65 112 . 110 3.2905 0.09 120 91.44 92.65 113 110 2.4234 0.07 120 91.43 111.69 114 110 1.7236 0.05 120 91.43 112.69 115 120 2.1733 0.07 110 91.50 86.62 116 120 6.1161 0.17 120 91.51 81.22 117 120 1.9733 0.06 110 91.51 81.08 118 120 1.1851 0.04 110 91.50 83.92 119 120 1.9733 0.06 110 91.50 83.92 120 110 0.9353 0.03 120 91.43 118.23 121 120 3.5309 0.11 110 91.51 81.22 122 110 0.6787 0.02 120 91.47 81.32 123 91.47 81.32 124 110 0.4584 0.02 120 91.48 80.04 125 110 0.4584 0.01 120 91.48 80.04 1.26 110 0.4756 0.01 120 91.46 81.58 127 91.47 81.32 128 91.44 82.41 129 90 1.0823 0.06 90 91.44 82.41 130 110 0.7394 0.04 120 91.46 80.17 131 91.46 81.44 132 91.46 81.58 133 110 0.8097 0.02 120 91.46 87.84 134 120 0.0634 0 110 91.43 97.76 135 120 0.3316 0.02 110 91.43 98.32 136 110 0.8527 0.04 120 91.43 104.44 137 120 - 1.2445 0.07 110 91.45 104.89 138 110 2.4291 0.07 120 91.43 118.23 139 110 0 0 120 91.45 91.81 140 110 0.602 0.03 120 91.45 94.66 141 120 0.602 0.03 110 91.45 93.95 142 91.47 109.76 143 120 0.3031 0.02 •110 91.47 105.77 144 120 1.5164 0.08 110 91.47 105.77 145 120 1.2132 0.07 110 91.46 104.77 146 120 0.2848 0.02 110 91.46 104.77 147 120 1.353 0.07 110 91.45 104.89 148 120 1.353 0.07 110 91.46 104.77 . 149 91.47 107.06 430 AC AD AE AF AG AH 150 110 0.1904 0.01 110 91.46 86.56 151 110 1.1084 0.05 120 91.46 91.25 152 110 3.0086 0.08 120 91.46 91.83 153 110 1.068 0.05 120 91.47 91.41 154 120 0.298 0.01 120 91.46 87.84 155 91.46 90.98 156 110 4.1294 0.11 120 91.47 89.71 157 120 2.5283 0.14 110 91.52 96.32 158 120 2.5283 0.14 110 91.62 84.51 159 120 2.5283 0.14 110 91.62 84.51 160 120 2.5283 0.14 110 91.62 84.51 161 91.62 84.51 162 120 2.5283 0.14 110 91.62 84.51 163 91.62 84.51 164 120 3.2735 0.18 110 91.62 84.51 165 91.68 81.47 166 90 2.1304 0.07 90 91.68 81.61 167 90 2.1304 0.07 90 91.71 79.66 168 120 1.4798 0.08 110 91.50 85.48 169 90 2.2795 v 0.06 . 120 91.50 84.62 170 91.50 84.62 171 110 2.0341 0.1 120 91.48 81.04 172 110 2.0341 0.1 120 91.46 83.30 173 110 0.8769 0.04 120 91.46 83.30 174 91.46 83.01 175 110 0.3858 0.02 120 91.46 83.30 176 110 0.9671 0.05 110 91.49 84.90 177 110 0.4534 0.02 120 91.46 81.72 178 120 0 0 120 91.46 84.71 179 91.46 86.56 180 120 0.335 0.02 120 91.46 86.56 181 91.46 86.98 182 90 1.6621 0.08 120 91.47 89.71 183 91.51 94.02 184 120 4.2194 0.23 110 91.53 79.97 185 120 0.4455 0.01 110 91.59 78.49 186 120 2.6099 0.08 110 91.51 81.22 187 120 3.0467 0.15 120 91.57 79.18 188 91.54 78.86 189 91.54 78.86 190 120 3.2654 0.1 110 91.57 79.18 191 120 0.4455 0.01 110 91.59 78.63 192 120 5.2187 0.25 120 91.70 79.93 193 120 4.7481 0.26 110 91.59 78.49 194 120 8.7533 0.27 110 91.71 79.52 195 120 6.038 0.19 110 91.71 79.66 196 120 6.038 0.19 110 91.70 79.93 197 120 8.87 0.27 110 91.74 79.29 198 90 2.1304 0.07 90 91.71 79.66 199 110 2.8532 0.14 120 91.76 78.46 200 110 2.8532 0.14 120 91.68 86.45 431 AC AD AE AF AG AH 201 120 1.7252 0.09 110 91.68 86.88 202 110 3.8281 0.07 120 91.68 84.31 203 91.69 81.76 204 110 4.0012 0.07 120 91.69 81.76 205 110 6.0425 0.11 120 91.69 80.77 206 110 6.0425 0.11 120 91.69 80.77 207 120 . 1.7252 0.09 110 91.73 78.84 208 110 1.9234 0.05 120 91.69 77.64 209 110 2.0784 0.06 120 91.69 78.49 210 110 2.0784 0.06 120 91.68 82.61 211 110 1.9234 0.05 120 91.69 78.49 212 120 1.6847 0.09 110 91.67 81.59 213 1.10 4.4151 0.08 120 91.69 81.76 214 91.67 88.00 215 110 1.4272 0.07 120 91.67 88.00 216 90 3.0563 0.15 120 91.62 84.66 217 90 3.0563 0.15 120 91.62 84.66 218 90 3.0563 0.15 120 91.62 84.66 219 90 3.0563 0.15 120 91.55 103.19 220 110 2.6037 0.07 120 91.47 89.71 221 110 1.4629 0.07 120 91.52 98.30 222 91.47 104.22 223 91.47 101.23 224 91.47 94.55 225 91.48 104.93 226 110 0 0 120 91.48 104.93 227 91.48 104.93 228 110 0 0 120 91.49 108.37 229 110 0 0 120 91.49 110.93 230 110 1.2098 0.06 120 91.55 107.45 231 110 1.9252 0.09 120 91.55 108.17 232 91.51 113.94 233 110 0 0 120 91.55 111.02 234 110 0 0 120 91.55 108.17 235 91.55 111.02 236 91.55 111.02 237 110 3.2251 0.09 120 91.55 118.97 238 90 3.2498 0.1 90 91.57 119.28 239 110 3.2498 0.09 120 91.57 119.28 240 110 6.3895 0.17 120 91.61 102.00 241 110 3.425 0.09 120 91.59 110.07 242 110 4.531 0.12 120 91.60 107.66 243 110 4.681 0.13 120 91.60 107.66 244 110 3.45 0.09 120 91.61 102.00 245 110 9.6998 0.26 120 91.61 102.00 246 110 6.1446 0.17 120 91.61 102.00 247 120 1.6847 0.09 110 91.66 81.31 248 93.50 83.46 249 100 0 0 100 91.70 79.79 250 110 3.386 0.06 120 91.68 84.31 251 110 2.0784 0.06 120 91.69 78.49 432 AC AD AE AF AG AH 252 110 1.9234 0.05 120 91.69 78.49 253 110 4.4151 0.08 120 91.69 80.77 254 110 1.7401 0.05 120 91.69 77.92 255 110 2.4767 0.04 120 91.69 80.20 256 110 0.8741 0.02 120 91.47 79.75 257 120 0.9362 0.05 110 91.48 80.04 258 120 0 0 120 91.46 81.72 259 110 0.5766 0.03 120 91.47 107.62 260 110 1.2098 0.06 120 91.55 107.45 261 110 1,2098 0.06 120 91.55 102.62 262 110 2.0553 0.04 120 91.68 77.92 263 110 2.5847 0.05 120 91.69 78.35 264 110 2.9637 0.05 120 91.68 77.92 265 110 4.6401 0.08 120 91.68 77.06 266 120 4.6401 0.09 110 91.68 77.20 267 110. 1.5757 0.03 120 91.69 78.35 268 110 1.1173 0.03 120 91.69 77.50 269 110 0 0 120 91.69 77.92 270 110 1.1173 0.05 120 91.69 77.50 271 91.69 77.92 272 110 1.4861 0.03 120 91.69 80.20 273 110 1.0633 0.03 120 91.69 79.21 274 120 1.0633 0.06 110 91.69 79.21 275 110 0.4198 0.02 120 91.46 80.59 276 110 0.4198 0.02 120 91.46 83.01 277 110 0 0 120 93.49 79.21 278 110 1.1189 0.05 120 91.50 81.64 279 110 0.0927 0 120 91.68 82.89 280 110 0.2009 0.01 120 91.68 82.61 281 120 6.3895 0.13 110 91.66 81.31 282 120 4.9614 0.1 110 91.67 81.31 283 120 4.9614 0.1 110 91.68 77.20 284 110 6.1446 0.17 120 91.58 101.95 285 110 3.3337 0.09 120 91.57 116.73 286 110 3.1851 0.09 120 91.52 121.78 . 287 110 2.3992 0.12 120 91.58 101.95 288 110 2.3992 0.12 120 • 91.55 108.17 289 110 0 0 120 91.51 112.81 290 110 2.7733 0.13 120 91.55 107.45 291 110 0.1132 0 120 • 91.51 112.81 292 110 3.1278 0.08 120 91.50 111.94 . 293 110 1.5294 0.07 120 91.53 102.88 294 110 1.5294 0.07 120 91.51 113.65 295 110 0.9815 0.05 120 91.51 104.13 296 110 0.9815 0.05 120 91.50 111.94 297 110 3.9726 0.11 120 91.50 111.94 298 110 3.5263 0.1 120 91.49 110.93 299 110 3.5263 0.1 120 91.48 108.64 300 110 2.4397 0.07 120 91.47 107.06 301 110 0.2161 0.01 120 91.48 103.65 302 110 0.6187 0.03 120 91.48 105.79 433 AC AD AE AF AG AH 303 110 0.6187 0.03 120 91.48 106.07 304 110 0.3952 0.02-, 120 91.47 101.23 305 110 0.3952 0.02 120 91.47 106.21 306 110 0.8437 0.04 120 91.47 94.55 307 110 3.7218 0.1 120 91.52 98.30 308 '110 1.8562 0.05 120 91.52 98.30 309 110 4.3845 0.12 120 91.51 94.02 310 110 2.5283 0.12 120 91.52 96.32 311 110 4.23 0.11 120 91.51 94.02 312 110 4.23 0.11 120 91.48 89.29 313 110 4.23 0.11 120 91.48 89.29 314 91.62 84.66 315 120 3.89 0.21 110 91.64 85.11 316 110 3.9278 0.19 120 91.64 85.11 317 110 2.5708 0.12 120 91.66 86.00 318 110 1.4272 0.07 120 91.66 86.00 319 110 1.6847 0.08 120 91.67 81.59 320 91.69 80.77 321 91.69 80.77 322 91.69 81.76 323 110 2.8532 0.14 120 91.68 86.45 324 90 1.5892 0.09 90 91.68 81.47 325 120 0 0 , 110 91.50 82.50 326 110 0 0 120 91.66 81.58 327 120 1.4798 0.08 110 91.53 79.97 328 120 2.2682 0.12 110 91.50 81.64 329 120. 1.1493 0.06 110 91.50 81.64 330 91.48 80.04 331 120 1.1493 0.06 110 91.48 80.04 . 332 120 1.4798 0.08 110 91.53 79.97 333 120 4.2194 0.23 110 91.53 79.97 334 110 0.3768 0.02 120 91.46 80.02 335 110 0.7627 0.04 120 91.46 80.31 336 110 0.7197 0.03 120 91.46 80.02 337 - 110 0.3858 0.02 120 91.46 80.02 338 110 0.3858 0.02 120 91.46 84.71 339 110 0.3858 0.02 120 91.46 80.59 340 120 2.8197 0.14 120 91.49 84.90 341 120 1.9387 0.09 120 91.50 85.48 342 120 0.2982 0.02 110 91.48 81.04 343 90 0.5254 0.03 120 91.50 85.48 344 90 1.6621 0.08 120 91.50 84.62 345 120 1.4798 0.08 1.10 91.50 85.48 346 120 1.4798 0.08 110 91.50 85.48 347 110 0 0 120 91.46 90.98 348 110 2.8325 0.08 120 91.46 91.83 349 110 1.5309 0.04 120 91.46 87.84 350 110 . 0.8051 0.04 120 91.47 92.26 351 110 0.8051 0.04 120 91.47 , 92.26 352 110 0.8051 0.04 120 91.46 100.50 353 120 1.068 0.06 110 91.47 92.26 434 AC AD AE AF AG AH 354 120 1.1084 0.06 110 91.45 94.09 355 120 0.602 0.03 110 91.45 104.89 356 110 2.0517 0.06 120 91.47 106.21 357 ' 110 2.1664 0.06 120 91.47 105.63 358 91.47 109.76 359 110 0.066 0 120 91.47 109.76 360 110 0.9089 0.04 120 91.45 94.66 361 110 4.1153 0.07 120 91.46 81.58 362 110 2.181 0.04 120 91.46 83.57 363 110 2.181 0.04 120 91.46 81.58 364 91.46 81.58 365 110 4.5277 0.08 120 91.46 80.45 366 110 3.8411 0.07 120 91.46 80.45 367 110 4.7134 0.08 120 91.47 80.03 368 110 5.0581 0.14 120 91.47 79.75 369 110 5.5165 0.15 120 91.50 80.07 370 110 1.5417 0.04 120 91.47 82.17 371 110 1.5417 0.04 120 91.47 81.03 372 110 1.0539 0.03 120 91.47 81.03 373 91.47 82.17 374 110 1.5417 0.07 120 91.47 82.17 375 110 5.8588 0.1 120 91.47 80.03 376 120 0.4052 0.02 110 91.48 80.04 377 110 5.9162 0.1 120 91.50 80.07 378 110 6.1161 0.17 120 91.50 81.08 379 110 0 0 120 91.50 80.64 380 110 4.2474 0.07 120 91.46 81.58 381 91.46 81.58 382 110 0.9353 0.03 120 91.43 118.23 383 110 1.7867 0.09 120 91.50 84.77 384 120 1.1851 0.04 110 91.50 84.34 385 120 0.0337 0 110 91.50 84.34 386 110 6.3969 0.11 120 91.49 85.90 387 120 3.6812 0.07 110 91.45 84.84 388 110 3.937 0.07 120 91.46 81.58 389 110 0.2901 0.01 120 91.43 109.70 390 110 0.2901 0.01 120 91.43 108.56 391 110 0.2901 0.01 120 91.43 108.56 392 120 0.3314 0.02 110 91.43 93.91 393 120 0.3314 0.02 110 91.43 99.74 394 120 0.1501 0.01 110 91.43 101.17 395 120 0 0 110 91.43 93.35 396 120 0 0 110 91.43 93.91 397 91.43 93.91 398 110 0.2901 0.01 120 91.43 109.70 399 91.43 106.86 400 110 0.366 0.02 120 91.43 107.28 401 110 0.2901 0.01 120 91.43 109.70 402 110 0.366 0.02 120 91.43 105.01 403 110 0.3735 0.02 120 91.43 104.44 404 110 1.2262 0.06 120 91.43 104.44 435 AC AD AE AF AG AH 405 110 1.9001 0.03 120 91.46 83.85 406 120 1.9001 0.1 110 91.46 84.42 407 110 0.4779 0.02 120 91.43 108.85 408 110 1.1314 0.03 120 91.43 118.23 409 110 1.0068 0.03 120 91.42 120.08 410 110 0.9964 0.05 120 91.45 83.57 411 110 0.2405 0.01 120 91.46 80.44 412 110 1.4644 0.04 120 91.46 80.44 413 110 1.0055 0.05 120 91.46 80.45 414 110 0.0821 0 120 91.46 80.45 415 110 0.0821 0 120 91.46 81.59 416 110 1.3869 0.07 120 91.46 80.45 417 110 4.7829 0.08 120 91.46 81.59 418 110 5.8808 0.1 120 91.47 82.30 419 110 5.7859 0.1 120 91.47 82.30 420 110 1.5874 0.08 120 91.48 84.32 421 110 5.2991 0.09 120 91.47 82.74 422 110 0.9823 0.05 120 91.46 80.73 423 91.46 80.73 424 110 0.9823 0.05 120 91.47 80.03 425 110 0.9823 0.05 120 91.47 80.03 426 110 0.7394 0.04 120 91.46 80.73 427 91.42 120.08 428 91.61 102.00 429 91.48 108.64 430 91.70 79.79 431 432 433 434 435 436 437 436 APPENDIX H 437 Degree of accuracy of time-linear and time-exponential predictions for material groups Material Breaks to 1999 Breaks (1999-2004) Breaks to 2004 1999 Break rate (breaks/km) 2004 Break rate (breaks/km) A C 29 3 32 2.524 2.785 CI 2 3 5 1.514 3.785 DI 16 1 17 0.750 0.797 Linear Exponential Actual 2004 Breaks (cumulative) Predicted 2004 Breaks (cumulative) Predicted - Actual Percentage difference R-Squared ~ Predicted 2004 Breaks (cumulative) Predicted-Actual Perccnta ge . diffcrcnc c AC 32 41.3058 9.3058 29.08% 0.9218 99.11865 67.11865 210% CI 5 2.789 -2.211 -44.22% 0.8138 3.08255 -1.91745 ' -38% DI 17 22.8023 5.8023 34.13% 0.9155 40.1167 23.1167- 136% Average RA2= 0.8837 Statistics Linear Exponential Mean 6.33% SD 43.85% Mean 102.46% SD 127.40% Median 29.08% Median 135.98% 438 Degree of accuracy of time-linear and time-exponential predictions for material and diameter groups 1999 Break 2004 Break Breaks to Breaks (1999- Breaks to rate rate Material Diameter 1999 2004) 2004 (breaks/km) (breaks/km) A C 150 21 3 24 2.406 2.759 A C 200 5 0 5 3.253 3.253 A C 250 3 0 3 2.459 2.459 CI 150 2 2 4 2.506 5.013 DI 150 7 2 9 0.597 0.767 DI 200 7 0 7 1.023 1.023 DI 250 2 0 2 0.727 0.727 Linear Exponential Actual 2004 Breaks (cumulative) Predicted 2004 Breaks (cumulative) Predicted-Actual Percentage difference R A 2 Predicted 2004 Breaks .'. (cumulative) Predicted - Actual Percentage difference AC 150 24 30.24 6.24 26.00% 0.9505 . 80.737 56.737 236% AC 200 5 7.2476 2.2476 44.95% 0.8063 18.07 13.07 AC 250 3 3.9982 0.9982 33.27% 0.7526 5.56 2.56 85% 5 ' ; CI 150 4 . 2.789 -1.211 -30.28% 0.8138 3.08 -0.92 -23% •••••• DI 150 9 10.01 1.01 11.22% 0.9268 21.27 12.27 136% , '. DI .200 7 9.6832 2.6832 38.33% 0.8193 11.725 4.725 68% DI 250 2 3.1053 1.1053 55.27% 0.7837 • 3.232 1.232 62% . • Avg R A 2= 0.8361 Statistics Linear Exponential Mean 25.54% SD 28.30% Mean 117.94% SD 101.32% Median 33.27% Median 85.33% Mode Mode 439 Degree of accuracy of time-linear and time-exponential predictions for material, diameter and age groups Material Diameter Age cohort Breaks to 1999 Breaks (1999-2004) Breaks to 2004 1999 Break rate (breaks/km) 2004 Break rate . (breaks/km) AC 150 ' 1960-1969 11 1 12 3.002 3.275 AC 150 1970-1974 7 0 7 2.975 2.975 AC 150 1975-1984 3 2 5 1.463 2.438 AC 200 1970-1974 - 3 0 3 2.14 2.14 AC 250 1960-1969 3 0 3 4.644 4.644 DI 150 1980-1989 3 1 4 0.492 0.656 DI 200 1980-1989 2 1 3 0.782 1.174 Linear Exponential Actual 2004 Breaks (cumulative) Predicted 2004 Breaks (cumulative) Percentage difference * R A 2 Predicted 2004 Breaks (cumulative) Percentage difference* AC 150 1960-1969 12 15.346 28% 0.8956 : 36.5 204% AC 150 1970-1974 7 10.99 57% 0.94 20.41' 192% AC 150 1975-1984 5 3.93 -21% 0.8802 5.69 ' 14% AC 200 1970-1974 3 4.3 43% 0.82 7.6 ' 153% AC 250 1960-1969 3 4 33%~ 0.753 5.6 , 87% Dl 150 1980-1989 4 4.1 2% 0.84 1 9.19 • • 130% DI .200 1980-1989 3 3.1 3% 0.78 3.232 • •- 8% - ' • / • Avg R A 2= 0.8441 * Based on predicted minus actual Statistics Linear Exponential Mean 20.71% SD 27.15% " Mean 92.90% SD 84.69% Median 28.00% Median 87.00% 440 Degree of accuracy of time-linear and time-exponential predictions for material, diameter, soil and age groups Breaks 1999 Break 2004 Break Breaks to (1999- Breaks to rate rate Material Diameter Soil type Age cohort 1999 2004) 2004 (breaks/km) (breaks/km) AC 150 Clayey soil 1960-1969 6 1 7 3.883 4.531 AC 150 Clayey soil 1970-1974 7 0 7 2.959 2.959 AC 150 Clayey soil 1975-1984 2 0 2 2.083 2.083 AC 250 Clayey soil 1960-1969 2 0 2 7.752 - 7.752 DI 150 Clayey soil 1980-1989 3 1 4 0.650 0.867 AC 150 Silty soil 1960-1969 3 0 . 3 2.155 2.155 AC 200 Silty soil 1970-1974 3 0 3 2.513 2.513 DI 200 Silty soil 1980-1989 2 0 2 2.793 2.793 Linear Exponential Actual 2004 Breaks (cumulative) Predicted 2004 Breaks (cumulative) Percentage difference* R A 2 Predicted 2004 Breaks (cumulative) Pcrcciilagc difference* AC 150 Clayey soil 1960-1969 7 7.6 9% 0.6594 32 5 364% AC 150 Clayey soil 1970-1974 7 10.95 56% 0.9409' . 20.4 191% AC 150 Clayey soil 1975-1984 2 2.2 . 10% 0.625 ' - - 2.54 27% AC 250 Clayey soil 1960-1969 2 2.4 20% 0.6875 •2.85 4 DI 150 Clayey soil 1980-1989 4 4.11 3% 0.8356 9.19 13"".. AC 150 Silty soil 1960-1969 3 4.5 50% 0.6927 5.21 7. AC 200 Silty soil 1970-1974 3 4.3 43% 0.82 • 7.63 \i-DI 200 Silty soil 1980-1989 ' 2 3.1 55% 0.7837 '3.23 61-. Avg RA2= 0.75566 * Based on predicted minus actual Linear Exponential Mean 30.76% SD 22.67% . Mean 130:56% •; SD 110.44% Median 31.67% Median 101.71% 441 Degree of accuracy of time-linear and time-exponential predictions for material, diameter, age and surface material groups Breaks 1999 Break 2004 Break Surface Breaks to (1999- Breaks rate rate Material Diameter Age cohort Material 1999 2004) to 2004 (breaks/km) (breaks/km) AC 150 1970-1974 Asphalt 2 0 2 13.514 13.514 AC 150 1960-1969 Gravel/grass 7 0 7 2.964 2.964 AC 150 1970-1974 Gravel/grass 5 0 . 5 2.101 2.101 AC 150 1975-1984 Gravel/grass 3 5 8 1.514 4.038 AC 200 1970-1974 Concrete 2 0 2 2.653 2.653 AC 250 1960-1969 Gravel/grass 2 0 2 3.13 3.13 DI 150 1980-1989 Gravel/grass 3 1. > 4 0.732 0.732 DI 200 1980-1989 Asphalt 2 0 2 1.584 1.584 Linear Exponential Actual 2004 Breaks (cumulative) Predicted 2004 Breaks (cumulative) Percentage difference* R A 2 Predicted 2004 Breaks (ciimiilatiw) Percentage difference* AC 150 1970-1974 Asphalt 5 3.164 -37% 0.827 3."') -24»;. AC 150 1960-1969 . Gravel/grass 7 10.03 43% 0.950 19 US 173% AC 150 1970-1974 Gravel/grass 5 ' 7.625 53% 0.926 10 2(. 105 AC 150 1975-1984 Gravel/grass 3 3.926 31% 0.880 5.<." 90% AC 200 1970-1974 Concrete 2 2.94 47% 0.820 4. 132% AC 250 1960-1969 Gravel/grass 2 2.56 28% 0.729 3.12 56% DI 150 1980-1989 Gravel/grass 4 4.11 3% 0.836 9.1') ' 130% DI 200 1980-1989 Asphalt 2 3.11 56% 0.780 v.- - 62% . Avg RA2= 0.843 * Based on predicted minus actual Statistics Linear - Exponential Mean 27.90% SD 31.13% Mean 9.0.25% SD 60.19% Median 37.08% Median 97.43% 442