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Environmental risk modeling of infrasttructure projects Wang, Yugui 2005

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ENVIRONMENTAL RISK MODELING OF INFRASTRUCTURE PROJECTS by YUGUI WANG B.Sc, The Tongji University, 1996 A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF APPLIED SCIENCE in THE FACULTY OF GRADUATE STUDIES (CIVIL ENGINEERING) THE UNIVERSITY OF BRITISH COLUMBIA May 2005 © Yugui Wang, 2005 Abstract Risk management is an important function for all c iv i l engineering projects, especially for P3 (Public Private Partnerships) projects, which are being widely considered as a procurement method for major c iv i l engineering infrastructure projects. One or more attributes of the natural and man-made environmental components of a project in concert with the attributes of a physical component and/or those of an activity or a group of activities can act as risk drivers for a risk event. The likelihood of the event's occurrence and its quantum of consequences G a n be dependent on whether or not the risk drivers share the same site location, participant responsibility, and time interval. A s modeling of a project's environment and related risks is very important for project risk management, knowledge-based constructs for representing a project's environmental and risk views are needed. These constructs should have capabilities to integrate a project's environmental view with its physical, process and organizational/contractual views to ensure thorough risk identification. This thesis work explores the robustness of constructs being developed as part of an extended research program on risk management to represent the environmental and risk views of a project. A comprehensive environmental component library that is applicable to c iv i l infrastructure projects is compiled by applying these constructs based on an extensive literature review and study of actual project documents. Mitigation measures for environmental impact and risks are identified. Strategies for visualizing environmental features and associated risks are discussed and illustrated. These strategies help project participants to gain insights on the ii confluence of environmental properties and associated risks in time, space and by project participants. Two case studies are conducted to explore the relationship between components of the environmental breakdown structure and risk issues/events, including relevant risk event mitigation measures. i i i Table of Contents Abstract . ii Table of Contents iv List of Tables vii List of Figures vii Acknowledgement x Co-Authorship Statement xi Chapter 1 Introduction 1 1.1 Research Motivation 1 1.2 Objectives 6 1.3 Methodology 7 1.4 Overview of Thesis 8 1.5 Bibliography 10 Chapter 2 Environment and Relevant Issues - State-of-the-Art 13 2.1 Project Environment and Environmental View 13 2.2 Representation of a Project's Environment - Classification Schema 16 2.2.1 Industry Classification Schema 16 2.2.2 Academic Classification Schema 20 2.2.3 Observations on Current Classification Schema 23 2.3 Environmental Risks 24 2.4 Environmental Impact 26 iv 2.5 Role of IT in Environmental Issues and Visualization 30 2.6 Bibliography 34 Chapter 3 Use of IT in Managing Environmental Risks in Construction Projects 42 3.1 Introduction 42 3.2 Overview of case study projects 45 3.3 Modeling the Environment 46 3.4 Knowledge Management 53 3.5 Integration with Risk Information 54 3.6 Conclusions 60 3.7 Acknowledgments 60 3.8 Bibliography 61 Chapter 4 Visualization of Construction Data 64 4.1 Introduction 64 4.2 Significance of Application of Visualization to Construction Environment 66 4.3 Visualization Technologies ..." 67 4.4 Applications of Visualization in Construction 70 4.5 Using Images to Model Environmental Risk Drivers 71 4.6 Applying Visualization Techniques for Change Order Management 76 4.7 Discussion and Conclusions 81 4.8 Acknowledgement 83 4.9 Bibliography 83 Chapter 5 Environment Modeling for Risk Management in Construction Projects 86 5.1 Introduction 86 5.2 Current Approaches for Representation of a Project's Environment 89 5.3 System Architecture for Modeling Project Environment 96 5.4 A Model of the Project Environment 99 5.5 Case Studies 105 5.6 Visualization of Environmental Components and Risks 112 5.7 Conclusions 117 5.8 Acknowledgements 118 5.9 Bibliography 118 Chapter 6 Conclusion 121 6.1 Summary 121 6.2 Contributions 124 6.3 Recommendations for Future Work 125 Appendices 127 I Components of Standard Environmental Breakdown Structure 127 II Attribute Definition of Standard EBS Entity Level Components 132 III Mitigation Measures for Environmental Impact and Risks 154 vi List of Tables 2.1 Environment Modeling in EIA Reports for Three Projects 19 2.2 Current Academic Approaches of Environment Classification 22 2.3 Works Contributive to Environmental Risk Identification 25 2.4 Works Investigating Specific Environmental Risks 27 2.5 Comparative Analysis of Visualization Techniques for Hierarchically Structured Data 33 4.1 Visualization Techniques, Working Principles and Sample Software Applications 69 4.2 Selected Properties of a Change Order 78 5.1 Environment Modeling in EIA Reports for Three Projects 91 5.2 Approaches to Environment Modeling from the Academic Literature .....93 5.3 Attribute Definition of Environmental Components 105 5.4 Extract from Floating Bridge Project Risk Register 109 Appendix I Components of Standard Environmental Breakdown Structure 127 AII.l Attribute Definition of Physical Components at the Entity Level of Standard EBS 132 AII.2 Attribute Definition of Social Components at the Entity Level of Standard EBS 146 All.3 Attribute Definition of Economic/Financial Components at the Entity Level of Standard EBS 149 AII.4 Attribute Definition of Political Components at the Entity Level of Standard EBS 152 AII.5 Attribute Definition of Regulartoty Components at the Entity Level of Standard EBS.... 153 Appendix III Mitigation Measures for Environmental Impact and Risks 154 List of Figures 3.1 Risk Drivers of Different Project Views 44 3.2(a) Environmental Breakdown Structure for Okanagan Lake Bridge Project 50 3.2(b) Attributes of "Archeological Site" Component 50 3.2(c) Specification of Attribute Values at Different Locations 50 3.3 Definition of Locations for Okanagan Lake Bridge Project 52 3.4(a) Project Risk Register for the Okanagan Lake Bridge Project.. 57 3.4(b) Selection of Appropriate Mitigation Measure from Master List of Mitigation Measures.. 57 3.5 Use of Standard Templates in Defining Environmental Breakdown Structure for the Sea to Sky Highway Improvement Project 59 4.1 Risk Drivers and Events 72 4.2(a) Environmental Breakdown Structure (EBS) 73 4.2(b) Environmental Component Attribute Definitions 73 4.2(c) Attribute Value 73 4.3 Distribution in Time and Space and by Responsibility of Environmental Risk Drivers 74 4.4(a) Hemispherical Hierarchy 76 4.4(b) Focused Hemispherical Hierarchy 76 4.5 CO History in Terms of CO ID, Timing and Value of the Work 79 4.6 History of COs by Location, Time, Responsibility and Number 81 5.1 Risk Drivers and Events 88 viii 5.2 Schematic of Partial System Architecture Linking Environmental and Risk Views of a Project with Supporting Knowledge Managament Features 97 5.3 Standard E B S - Class and Sub-class Level 101 5.4 Standard E B S - Entity Level Components of Physical Environment 102 5.5 Attributes for Habitat and Terrestrial Habitat Component 104 5.6 Floating Bridge Project E B S - Entity Level Components 107 5.7 Drivers for Archeology Risk Issue at Floating Bridge Project 110 5.8(a) Physical Location Definition 110 5.8(b) Attributes for Archeology Site Component 110 5.8(c) Assignment of Attribute Value for Acheology Site Component 110 5.9 Sea to Sky Highway (STS) Project E B S 113 5.10 Distribution in Time and Space and by Responsibility of Environmental Risk Drivers 115 5.11(a) 3-D Graph Viewer 116 5.11(b) Lateral V i e w of Distribution Graph after Rotation 116 5.12(a) Hemispherical Hierarchy 117 5.12(b) Focused Hemispherical Hierarchy 117 Acknowledgement I wish to express my sincere gratitude to Dr. Alan D. Russell, my supervisor, for his invaluable guidance, advice and support throughout my master's program. Most of the ideas presented in this thesis were developed through numerous discussions with Dr. Russell. This thesis would not exist without his patient efforts and intelligent comments. My special thanks to Dr. Sheryl Staub-French for the stimulating discussions and her efforts in reviewing this thesis. I am sincerely grateful to Sanjaya De Zoysa for his constructive criticism and feedback on the thesis work. The time I have spent with him working on the relevant topics has been very enjoyable. To Ming'en Li, Kehui Zhang, Zonghai Han, Tanaya Korde, Paul Tawiah, fellow colleagues and friends, many thanks for your encouragement, inspiration and moral support. My experience of the master's program at UBC has been more wonderful because of you. Finally, acknowledgement is gratefully extended to my parents, brothers and sister for their everlasting support. Chapter 1 Introduction 1.1 Research Motivation Awareness of the importance of the environment and attention to the human-induced changes to the environment has increased in recent years. The products and processes of the construction industry are considered to be significant contributors to changes in the environment. Many countries have established government authorities, and promulgated laws and regulations to oversee and assess respectively the environmental impact of construction projects. For example in Canada, the Canadian Environmental Assessment Agency (Canadian Environmental Assessment Agency 2003) provides leadership in environmental matters, serves as a center of expertise for federal environmental assessment, and is responsible for the overall administration of the federal environmental assessment process. The Canadian Environmental Assessment Act is the legal basis for the federal environmental assessment process. It sets out the responsibilities and procedures for carrying out the environmental assessments of projects which involve one or more federal authorities as project participants or jurisdictions. While a construction project can have an adverse impact on the environment, the environment can also have a significant adverse impact on a construction project. One reason for this is that project participants have to comply with government regulations and mitigate all adverse environmental impacts. This can adversely affect project performance metrics such as 1 safety, cost, time, revenue, scope and quality. For example, a passing-climbing lane system, a highway twinning strategy and other mitigation measures such as wildlife underpass and overpass structures have been applied to highways and roads within Canadian Rocky Mountain National Parks (McGuire and Morrall 2000). Such measures increase project cost and construction duration. In some instances, a project can be terminated in the feasibility study phase because of the detrimental impact it is likely to have on the environment. As an example of the impact of the natural environment on a project, a second reason performance metrics are affected, consider the transportation links in southwestern British Columbia. They cross rugged, mountainous terrain and are exposed to a large number of landslide hazards, particularly rock falls and rock slides. Rock falls can cause delays, damage, injury, and death to users of these routes. For example in 1982, a rock fell on a vehicle killing a woman and disabling her father while they were delayed in traffic on British Columbia (B.C.) Highway 99. The father successfully sued the provincial Ministry of Transportation and Highways for damages after pursuing his claim to the Supreme Court of Canada for the reason that the province owes a duty of care, which ordinarily extends to their reasonable maintenance, to those using its highways (Bunce et al. 1997). The expenditures on rock slope maintenance to reduce the risks to the traveling public and minimize costs and traffic disruptions by several agencies in British Columbia amount to approximately Canadian $10 million per year (Hungr et al. 1999). A third reason for impacts on project performance revolves around the significant uncertainty that exists in the project environment throughout the project life cycle. For example, the discovery of unforeseeable contaminated soil on the jobsite is frequently experienced by project participants during site work excavation. Impacts can range from minor to more than doubling the project cost and extending the project months past its original schedule depending on size of the project 2 and ability of the project team to properly respond (Tilford et al. 2000). As a special case, environmental uncertainty existing in environmental restoration projects is extremely significant during the construction phase. This is partially due to the facts that such projects are relatively new as compared with other types of construction project and technologies used in this type of project are often innovative. The impact of uncertainty on an environmental restoration project was addressed in a study by Independent Project Analysis, Inc. where they noted that the average cost overrun is about 25% for private sector environmental restoration projects while it is nearly 50% for similar projects conducted by the U.S. Department of Energy Office of Environmental Management (IPA 1993). Project environmental uncertainties lead to risks. It is noticeable that the literature uses the terms risk, uncertainty and hazard interchangeably (Boodman 1977; Faber 1979; CERL 1978; Lifson and Shaifer 1982; Hertz and Thomas 1983). Al-Bahar and Crandall (1990) used "uncertainty" to represent the probability that an event occurs while they defined risk as: "The exposure to the chance of occurrences of events adversely or favorably affecting project objectives as a consequence of uncertainty". To clarify the terms related to the topic of risk, the definitions of De Zoysa and Russell (2003a) are adopted in this thesis as follows: 1. The term risk issue is used to represent topics or keywords (e.g. short term inflation rate) of direct relevance to a project, around which uncertainty or a lack of predictability may exist, and which may result in risk events for one or more of the product, process, organizational, cost or quality views of a project and consequent uncertainty in one or more project performance measures; 2. The relevance of a risk issue for a project at a given point in time may be assessed, in some cases, through one or more risk issue drivers; 3 3. The term risk event corresponds to the potential variability in a project parameter (e.g. the average inflation rate during the construction phase), or one or more scenarios in which the possible states of nature that can be realized can be identified but which one will occur is not know with certainty (e.g. a slope failure occurs or not, and if it occurs, how extensive would it be); 4. The basic project performance measures which risk issues can impact include time, cost, revenue, quality, scope and safety; 5. Risk mitigation deals with how best to manage a risk using strategies such as redesign, alternative processes (procurement, construction, etc.), insurance, contingency allowances, contractual language, and so forth. In this thesis, our focus is on the negative or adverse consequences of a risk event. This corresponds to the focus in industry on the downside of a risk event. In addition to risks generated separately by a project's environment, one or more attributes of an environmental component (environmental view of a project) in concert with the attributes of a physical component (physical view of a project) and/or those of an activity or a group of activities (process view of a project) can act as risk drivers for a risk event, and the likelihood of the event's occurrence and its quantum of consequences can be dependent on whether or not they share the same site location and/or participant responsibility and at the same time. The benefits associated with integrating multiple views of a project to assist with the identification and treatment of risks that are project-specific are significant and have been addressed by several authors. Russell and Udaipurwala (2004) represented a project using nine views (physical, process, organizational /contractual, cost, quality, as-built, change management, environmental, and risk) integrated within a single system. Earlier findings on this subject can be traced back to 4 a 4-view representation by Russell and Froese (1997) and a 3-view representation by Fischer and Aalami (1996). A project's environment addressed here by way of an environmental view of a project consists of not only the natural environment but also the man-made environment. Both aspects of the environment could result in project risk events separately or in concert with other project views. However, emphasis will be put on the natural environment in this thesis. Knowledge management is a flourishing area that should be integrated with risk management. Both the public and private sectors of the construction industry face the scenario that experience gained by undertaking projects can easily be lost through downsizing, resignations and retirements because knowledge within organizations that resides primarily in the minds of experienced personnel is seldom documented in a consistent and accessible way. It is also difficult even for an experienced project team, especially for an infrastructure project with significant scale and complexity, to undertake risk management without reference to useful historical data from past similar projects. Historical project data needs to be collected, structured and reused on new projects so that the cost and time of starting up new projects could be significantly reduced. Knowledge management helps to solve the foregoing problems by storing valuable experience using information technology and making it available in easily accessible form to new projects. Work in this field has been done by Leung, Chuah, and Tummala (1998); Cox (1999); and De Zoysa and Russell (2003b). As of 2005, P3 (Public Private Partnerships) are more and more being widely considered as a procurement method for infrastructure and other public service projects in Canada and elsewhere. The private sector has the capability to finance, design, construct, and maintain projects with or without their transfer to government at the end of the concession period. A key issue in this kind of procurement is the allocation of risk among different participants. 5 Environrnental risks play important role in the selection of a concessionaire under this type of procurement arrangement. 1.2 Objectives The specific research objectives for this thesis are as follows: (a) To explore the robustness of constructs being developed to represent the environmental and risk views of a project, and participate in their refinement. As modeling of a project's environment and related risks is very important for project risk management (identification, quantification, mitigation, assignment, monitoring, and capturing lessons learned), De Zoysa and Russell (2004) developed constructs to represent a project's environmental and risk views. These constructs have been developed in concert with this thesis, thus allowing for timely feedback and refinement; (b) To use the constructs developed in order to compile a comprehensive environmental component library that is applicable to civil infrastructure projects, and to identify relevant mitigation measures. This work addresses the knowledge management aspect of modeling a project's environment and identifying associated risks; (c) To conduct two case studies using current transportation projects in British Columbia, and explore the relationship between components of the environmental breakdown structure and risk issues/events, including relevant risk event mitigation measures. The advantages offered by applying knowledge management should also be tested as part of these two case studies; and, (d) To develop strategies for visualizing environmental features and associated risks and apply these strategies to assist project participants to capture environmental risk information from existing construction projects. 6 Fulfillment of these objectives will help provide robust constructs for representing a project's environmental features and for environmental risk analysis of construction projects. Pursuit of these objectives will also assist practitioners to conduct environmental risk analysis and capture the relationship between the project environment and project risks in an efficient and effective way. 1.3 Methodology To achieve the objectives set for this thesis, the following methodologies were applied: (a) An extensive literature review related to project environment, risk, knowledge management, and visualization topics was conducted. Based on this review, the benefits and disadvantages of state-of -art techniques related to these topics were analyzed and a point of departure was determined for the research work. (b) A review of environment documents for actual projects was conducted in order to ensure that the work was responsive to the realities of actual projects. As a formal procedure, the Environmental Impact Assessment requirements for a project are the expression of opinions all project participants towards a construction project. (c) Interaction with industry participants and those focusing on related topics in the academic field was carried out. The interaction approach consisted of unstructured discussion, emails, and telephone calls. Through these interactions, direct and fresh ideas were obtained. (d) Case studies on two high profile transportation projects were developed. To explore the robustness of constructs and the fresh ideas developed by the author, two rather distinct case studies were performed: Okanagan Lake floating bridge construction project and Sea to Sky highway improvement project. The environment of the floating bridge project is tightly bounded 7 whereas the highway project traverses through several jurisdictions and through urban, coastal, and mountainous regions. Use of these two case studies allows us to assess the ability of the modeling methodology in representing a finite set of components, as well as a much larger number of components that are widely dispersed across several locations. 1.4 Overview of Thesis This thesis consists of an introduction chapter and a conclusion chapter to overview the research conducted and research contributions, and four chapters in the middle (Chapter 2, 3, 4 and 5) that focus on the specific contributions made. Three appendices are attached at the end. The description of each chapter and appendix are as follows: Chapter 2 provides an extensive literature review related to topics of representation of a project's environment, environmental risks, environmental impact and role of IT in environmental issues and visualization. Chapter 3 presents the constructs for modeling environmental risks on construction projects. A brief description of the components that make up the environmental breakdown structure is presented. Two case studies provide useful examples to show how these conducts are applied in practice to model project environmental risks. A version of this chapter has been published in the Proceedings of the Construction Research Congress 2005, American Society of Civil Engineering, April 5-7, 2005. San Diego, CA. The authorship for this chapter is Sanjaya De Zoysa, Yugui Wang, and Alan D. Russell. Chapter 4 presents an innovative data visualization strategy to help users gain insights about the environmental risk issues identified in the project risk analysis process. A brief overview of existing visualization technologies is also provided in this chapter. A version of this chapter will 8 be published in the Proceedings of the 2005 Annual Conference of the Canadian Society of Civil Engineering, June 2-4, 2005, Toronto, ON. The authorship for this chapter is Tanaya Korde, Yugui Wang, and Alan D. Russell. Chapter 5 focuses extensively on environment modeling and the association of environmental components with project risks. A master library of environmental components is provided in this chapter with all attributes defined. Two case studies are used to explore the richness of developed constructs. This chapter is a draft manuscript written for a journal paper. The authorship for this chapter is Yugui Wang and Alan D. Russell. Chapter 6 is a conclusion chapter which summarizes the research conducted and the contributions made. Appendix I contains all the components of a master Standard Environmental Breakdown Structure derived from literature review, study of various handbooks, and examination of documents describing the environmental characteristics of actual projects. The Standard Environmental Breakdown Structure is a hierarchical structure applied in this thesis to model a project's environment. It consists of five layers: environment, class, sub-class, entity, and sub-entity. Components at each level of this hierarchical structure are listed in this appendix. Appendix II contains the attribute definition of the components at the entity level in the Standard Environmental Breakdown Structure. Attributes are defined to describe the characteristics of each component. Appendix III contains a partial set of mitigation measures for environmental impact and risks. Mitigation measures for environmental issues with both certainty and uncertainty are included. ' 1.5 Bibliography Al-Bahar, J. and Crandall, K. (1990). "Systematic risk management approach for construction projects." Journal of Construction Engineering and Management, 116(3), 533-546. Boodman, D. (1977). "Risk management and risk management science: An overview." Paper presented at the Session of Risk Management, TIMS 23rd. Annual Meeting of Institute of Management Sciences, Athens, Greece, July. Bunce, C, Cruden, D., and Morgenstern, N. (1997). "Assessment of the hazard from rock fall on a highway." Canadian Geotechnical Journal, 34, 344-356. Canadian Environmental Assessment Agency (2003). "Basics of environmental assessment." http://www.ceaa.gc.ca/010/basics_e.htm (last accessed on 15 Jan.'05). CERL (1978). "Preliminary investigations of risk sharing in construction contracts." Interim Report No.88, Construction Engineering Research Laboratory, CERL, Apr. Cox, E. (1999). "Coping with the uncertainty principle: predictive project risk assessment and risk classification using a fuzzy case-based reasoning system." PC Al, 13, 37-40. De Zoysa, S. and Russell, A. (2003a). "Structuring of risk information to assist in knowledge-based identification of the life cycle risks of civil engineering projects." Proceedings of 5th Construction Specialty Conference of the Canadian Society for Civil Engineering. Moncton, Nouveau-Brunswick, Canada. De Zoysa, S. and Russell, A. (2003b). "Knowledge-based risk identification in infrastructure projects." Canadian Journal of Civil Engineering, 30, 511-522. De Zoysa, S. and Russell, A. (2004). "Reuse of knowledge in risk management - gaining a competitive advantages." Proceedings of World of Construction Project Management 2004, 1st International Conference. Toronto, Canada. May 27, 2004 - May 28, 2004. 10 Faber, W. (1979). "Protecting giant projects: a study of problems and solutions in the area of risk and insurance." Willis Faber, London, England. Fischer, M. and Aalami, F. (1996). "Scheduling with computer-interpretable construction method models." Journal of Construction Engineering and Management, ASCE, 22(4), 337-347. Hertz, D., and Thomas, H. (1983). "Risk analysis and its applications." John Wiley and Sons, Inc., New York, N.Y. Hungr, O., Evans, S., and Hazzard J. (1999). "Magnitude and frequency of rock falls and rock slides along the main transportation corridors of southwestern British Columbia." Canadian Geotechnical Journal, 36, 224-238 Independent Project Analysis, Inc. (IPA). (1993). "The Department of Energy Office of Environmental Restoration and Waste Management project performance study." DOE, Reston, Va. Leung, H., Chuah, K., and Rao Tummala, V. (1998). "A knowledge-based system for identifying potential project risks." International Journal of Management Science, 26(5), 623-638. Lifson, M., and Shaifer, E. (1982). "Decision and risk analysis for construction management." John Wiley and Sons, Inc., New York, N.Y. McGuire, T., and Morrall, J. (2000). "Strategic highway improvements to minimize environmental impacts within the Canadian Rocky Mountain National Parks." Canadian Journal of Civil Engineering, 27, 523-532. Russell, A. and Froese, T. (1997). "Challenges and a vision for computer-integrated management systems for medium-sized constractors." Canadian Journal of Civil Engineering, 24, 180-190. i i Russell, A. and Udaipurwala, A. (2004). "Using multiple views to model construction." CIB World Building Congress 2004, Toronto, Canada. 11 pages. Tilford, K., Jaselskis, E., and Smith, G. (2000). "Impact of environmental contamination on construction project." Journal of Construction Engineering and Management, 126(1), 45-51. 12 Chapter 2 Environment and Relevant Issues - State-of-the-Art While a large amount of work has been focused on environmental issues in general and on environmental health and protections in particular, little work has been focused in the literature on the linkage between the environment and construction. In this chapter, the work of others which is focused on construction and the environment are identified, summarized and evaluated as a key step in laying a solid foundation for the work described in this thesis. 2.1 Project Environment and Environmental View Seemingly starting in the 1970s, the term "environment" became widely popular and was coined as a concept particularly related to changes in the condition of regional or global surroundings. The Merriam-Webster Online Dictionary (2005) defines the term "environment" as: (1), the circumstances, objects, or conditions by which one is surrounded; (2) (a), the complex of physical, chemical, and biotic factors (such as climate, soil, and living things) that act upon an organism or an ecological community and ultimately determine its form and survival; (2) (b), the aggregate of social and cultural conditions that influence the life of an individual or community; and (3), the position or characteristic position of a linguistic element in a sequence. Carpenter (2001), in the context of construction, defined the environment as surroundings and their characteristics which affect human and other life forms that exist within these surroundings. He considered the environment as the existence of resources, which include both human and 13 natural resources, and their fragile quality. Based on the foregoing first and second definitions of environment and from the perspective of project management, project environment can be considered as surroundings and their characteristics which, at any phase of a project's life cycle, affect the performance of a project that exists within these surroundings. These surrounding can be both man-made and natural. Normally, they consist of physical, social, economic/financial, political and regulatory components. The environmental view of a project is considered to be an important project context dimension. Characterizing the context of a construction project through multiple views or models of a project is believed to be key to the identification and treatment of risks that are project specific. Russell and Udaipurwala (2004) defined a view as a data set which describes an abstraction of a significant facet or dimension of a project (e.g., process, product, physical or quality). Their representation of a project involves nine project views integrated within a single system, these being the physical, process, organizational/contractual, cost, quality, as-built, change management, environmental, and risk views. They considered representation, integration, interpretation and knowledge management as four central issues to this multi-view approach. The concept of views, either in explicit or implicit terms, has been pursued by a number of researchers. Fischer and Aalami (1996) developed three models, product, construction method and process models, which can be considered as three views, when they developed computer interpretable models to automatically generate realistic construction schedules. They considered the product model as WHAT to build which determines the scope of project, the construction method model as HOW to build (i.e., select appropriate construction methods and generate corresponding activities and their sequence or logic relations), and the process model as to determine WHEN activities will take place by calculating activity duration and timing and 14 project duration. Russell and Froese (1997) identified four major views which provided a useful framework for categorizing construction functions and supporting computer applications. These four major views are physical and environmental view, cost view, process view and as-built view. The physical and environmental view of the project describes what is to be built: its geometry, topology, physical systems, materials, etc., as well as the physical, economic, and sociopolitical environment in which the project will proceed (As described in this paper, the physical and environmental view was subsequently broken into two separate and distinct views: physical view representing what is to be built and where, and the environmental view representing the natural and man-made contexts in which the project will be constructed). The process view describes how the project will be constructed, who is responsible for different aspects of the work, when it will be done, and where. The cost view deals with the cost structure of individual parts as well as the overall project from various perspectives (subtrades, general, owner), and involves initial cost estimates and cost tracking throughout the construction phase. The as-built view describes what happened during the journey, why, and what actions were taken. Each of these four major views may be thought of as being comprised of a number of sub-views. Later, Russell and Chevallier (1998) added another two views, namely a quality and a change view, to this suite of four views. The quality view represents what standard must be achieved and the change view represents changes in scope. Consensus on what constitutes the complete set of views required to provide a holistic treatment of a project has yet to be achieved, in part because most researchers are focused on a subset of construction management functions. However, there appears to be consensus that at least two essential views correspond to the product and process models of a project. 15 2.2 Representation of a Project's Environment - Classification Schema Located in the interface between industry and academia, research on project environment classification schema can benefit from both industry documents and academic works. Compared to other fields in construction management, work done to date in the academic domain on project environment classification schema is very limited. However, voluminous industry documents are important sources of how a project's environment is characterized in practice. 2.2.1 Industry Classification Schema The first non-academic source is the environmental protection publications by international organizations. From the perspective of environmentalists, these publications consider how human life impacts the environment, how to assess that the environment is improved or degraded, and how to prevent degradation of the environment. Among these publications, construction activities are considered as important factors which degrade the environment. Comments on construction activities in these publications are important for this thesis research because they are helpful for extracting environmental components impacted by construction. The way in which these publications are structured reflects the environment classification schema of these international organizations. United Nations publications Africa Environment Outlook (UNEP 2002), Caribbean Environment Outlook (UNEP 1999) and GEO Latin America and Caribbean Environment Outlook (UNEP 2000) applied the same environment classification schema and presented the impact of human activities on the atmosphere (including climate variability, climate change and air quality), biodiversity, coastal and marine environment, forest, freshwater, land, and urban areas. Discussed in Asian Environment Outlook (ADB 2001) are the 16 environmental problems encountered in Asia with construction activities as important driving forces. Asian Development Bank (Asian Development Bank 2002) presented two examples of six-category environment classification schema. One is the classification of flora, fauna, atmosphere, water (fresh water and marine water), land/soil (surface and sub-surface) and human settlement while the other is the classification of air/climate, land/soil, water (fresh and marine water), other natural resources (biological resources, mineral include energy resources), waste and human settlement. OECD (OECD 2001) uses a two level hierarchy - with the first level encompassing two categories: natural environment and social-economic environment. The natural environment category includes climate change, ozone layer depletion, air quality, waste, water quality, water resources, forest resources, fish resources and biodiversity while the social-economic category consists of GDP and population, consumption, energy, transport, agriculture and expenditure. A second information source for current approaches to environmental classification schema is handbooks written by construction industry organizations. The Environmental Handbook for Transportation Operations (NYSDOT 2001) is a summary of environmental requirements for maintaining highway and transportation systems. The structure of this handbook reflects categories of maintenance activities, which include general work, highway maintenance and operations, facility-based operations and waste management. The environmental components that should be considered under each of these headings are described in detail. Although no environment classification schema per se is presented in this handbook, the environmental concerns mentioned are a significant source for identifying environmental components. Many countries and international organizations have produced manuals or directives for environmental impact assessment that are reflective of their own regulations. Consider, for example the 17 reference, Roads and the Environment - a Handbook (Tszmokawa and Hoban 1997). The environmental impact part of this handbook classifies the project environment into eleven categories: soil, water resources, air quality, flora and fauna, communities and their economic activities, land acquisition and resettlement, indigenous people, culture heritage, aesthetics and landscape, noise environment, and human health and safety. Each category has sub-categories and some sub-categories have sub-sub-categories. The Environmental Impact Assessment (EIA) reports for individual projects are a third source of reference for project environment classification. Legislated guidelines often determine the scope of EIA studies which mostly relate to natural environmental components, economic conditions, social and health components, and cultural and heritage components (Canadian Environmental Assessment Agency 2003). An EIA report describes in detail what impact the project will have on the environment, what mitigation measures should be taken and what monitoring program should be implemented. The way in which the project environment is classified can be different in each EIA project report. Here, use is made of examples of EIA reports for three projects - two from British Columbia and one from Europe to illustrate how a project's environment is classified, as shown in table 2.1. In this table, Project 1 is the Sea to Sky highway improvement project in British Columbia, Canada (EAO 2004a). This project involves widening and straightening a 94.7 km section of highway through urban, coastal, and mountainous regions and environmentally sensitive areas. The road sections cross 67 roadside •drainage ditches, 191 creeks and streams, 7 lakes, 1 pond, 24 wetlands, and 1 estuarine tidal marsh. The highway also traverses several municipalities that profess varying degrees of support for the proposed improvements, and have different bylaws regarding construction, traffic management, etc. Project 2 is the New Fraser River Crossing project in British Columbia, 18 Table2.1 Environment modeling in EIA reports for three projects Project 1 Project 2 Project 3 1. Land requirements 1. Environmental effects 1. Hydrography 2. First Nations interest 1.1 Fisheries & aquatic 2. Dredging and reclamation 3. Archeological effects resources 3. Sediment spreading and 4. Environmental effects 1.2 Wildlife & vegetation sedimentation 4.1 Water quality 1.3 Contaminated site 4. Water quality 4.2 Fisheries & aquatic 2. Economic, social, heritage and 4.1 Heavy metals & toxic resources health effects substances 4.3 Wildlife & vegetation 2.1 Agricultural resources 4.2 Waste water & hygienic 4.4 Geochemical 2.2 Community and Socio- water quality 4.5 Contaminated site economic effects 4.3 Release of nutrients 4.6 Air quality 2.2.1 Neighborhoods 4.4 Oxygen 5. Socio-Economic effects 2.2.2 Transportation 5. Benthic vegetation 5.1 Project design issues 2.2.3 Construction 5.1 Eelgrass 5.2 Transportation demand 2.2.4 Navigation 5.2 Ruppia 5.3 Noise 2.3 Air quality and health 5.3 Macro algae 5.4 Emergency services 2.4 Noise 6. Benthic fauna 5.5 Recreation 2.5 Archeological resources 6.1 Common mussels 5.6 Aesthetics 3. First Nations Interests 6.2 Others 5.7 Economic 3.1 Fishing 7. Fish 5.8 Land use impacts 3.2 Hunting 7.1 Spawning and nursery 6. Navigation 3.3 Gathering grounds 7. Permits, licenses, 3.4 Cultural heritage sites 7.2 Migratory routes & authorizations 3.5 Privacy distribution 3.6 Noise 8. Birds 3.7 Air quality & health 8.1 Breeding eiders 3.8 Other community effects 8.2 Moulting greylag geese 4. Permits, licenses, authorizations 8.3 Moulting mute swans 8.4 Other breeding species 8.5 Staging migrants 9. Mammals 9.1 Seals 9.2 Movement of foxes, cats and rats 10. Beach and coast 10.1 Coastal morphology 10.2 Beach & bathing water quality 11. External environment 11.1 Noise 11.2 Industrial & sanitary water 11.3 Fuel 11.4 Waste & residual products 11.5 Transportation 11.6 Groundwater 19 Canada (EAO 2004b). The Project entails approximately 13.4 kilometers of new roadway including the construction of a new six-lane tolled bridge crossing the Fraser River, new controlled access four-lane arterial roads on both sides of the. river, two overpasses and relevant road upgrades. The project is located in an urban area with several communities, including First Nations communities. Social and economic impacts are the major environmental concerns along with fisheries and wildlife habitats. Project 3 is the Oresund Fixed Link project (Oresundskonsortiet 2000) between the Swedish and Danish coasts. It is a combined railway and motorway with a length of 16.4 km consisting of an immersed tunnel, two approach bridges and a high bridge. Oresund is a strait connecting the Baltic Sea and the Kattegat/North Sea. The artificial peninsula and the artificial island constructed for connecting tunnel and bridges along with the bridge piers have a blocking effect and a potential regional impact on the water exchange in the Baltic Sea, in addition to a local environmental impact in Oresund. 2.2.2 Academic Classification Schema Work done in the academic domain on classification schema for a project's environment is valuable since there are so few references as compared with the vast literature on other aspects of construction. Among the very few works identified, nine of them are described herein. Leopold et al. (1971) proposed a matrix system as a checklist to assist in developing a uniform environmental impact statement. One axis of the matrix is for actions which cause an environmental impact and the other axis is for the existing environmental components that might be affected. A sample matrix provided involves 100 actions on the horizontal axis and 88 environmental components on the vertical axis giving a total of 8,800 possible interactions. Although the authors did not provide information on what constituted the 88 environmental components, they demonstrated the importance of identifying environmental components using a 20 reduced matrix. In this reduced matrix, they identified 13 environmental components: water quality, atmospheric quality, erosion, deposition and sedimentation, shrubs, grasses, aquatic plants, fish, camping and hiking, scenic views and vistas, wilderness qualities, rare and unique species, and health and safety. The actions of this reduced matrix consist of 9 components: industrial sites and buildings, highways and bridges, transmission lines, blasting and drilling, surface, excavation, mineral processing, trucking, emplacement of tailings, and spills and leaks. The interaction between these environmental components and actions represents the environmental impact. Although it is implicit, the interaction of environmental components and actions in this matrix model has the similar philosophy as the integration of the environmental, process and physical views of a project proposed by Russell and Udaipurwala (2004). In selecting a highway route, McHarg (1968) classified a project's environment for a proposed highway alignment into four categories. The first category deals with components directly relative to construction saving and costs. It consists of two components: topographic corridor and land value, difference of which reflects the variation of cost for different highway alignments. The second treats social values. It consists of urbanization, residential quality, historic value, agriculture value, recreation values, wildlife value, water values, and susceptibility to erosion. The third category is scenic value and the fourth is physiographic obstructions. Examples for each of these components are described by McHarg (1968). The five most valuable environment classification schemas identified in the academic literature are summarized in table 2.2. The schema of Week (1977) was developed for environmental impacts of transportation projects. He applied a "synthesis of the environmental impacts" category to present a summary of overall environmental impacts, both beneficial and adverse, which have been identified as a result of the technical studies and investigation of a 21 Table2.2 Current academic approaches of environment classification Week, T. (1977) Wilson, F. and Stonehouse, D . (1983) Hughes, W. (1989) Marmoush, Y. (1999) Underhill, J . & Angold, P . (2000) Economic environment Physical environment Cultural Physiography Pollution Biological environment Water regime Economic Geomorphology Foreign material Plant & animal diseases Erodibility Political Sedimentology Dust Human disease Woodlands Social Hydrography De-icing salt Aquatic ecology Unique ecological areas Physical Tides Exhaust output Terrestrial ecology Wildlife Aesthetic Current Hydrology Social environment Agriculture Financial Waves Runoff pollution Community & tribal Social environment Legal Sediment transport Stream flow change structure Development Institutional Water quality Disturbance effects Cultural resources Noise Technological Pollution source Gust of wind Synthesis of environmental Utilities Policy Pollution ambient levels Human access impact Recreation Marine ecology Noise Unique cultural features Phytoplankton Physical barriers to the Aesthetic scenic areas Zooplankton movement of animal Seaweed species Benthic microfauna Ecological habitat & Intertidal macrofauna corridors Fish Shrimp Bird fauna „ ^ . , For highway location „ , . . . . . „ For coastal development For road network For transportation proiect . , r J For building project . ^ r selection ° v J project 22 project. The environmental classification schema of Wilson and Stonehouse (1983) originated from the master's thesis of Stonehouse (1979). They identified environmental concerns for highway location and classified them into two categories: physical environment and social environment. Detailed components were further classified for these two categories. Hughes (1989) defined the environment in terms of eleven environment factors. He defined these factors to ensure that any observable environmental phenomena may be classified into one or more generic groups of factors. He considered each of these environmental factors as being subject to degrees of variability. The extent to which these factors vary was classified in terms of their degree of definition, stability in terms of time, certainty, simplicity and ease with which they can be mitigated. Marmoush (1999) classified the major environmental aspects considered by coastal development into four categories, as shown in table 2.2. He described the^ mpact of these environmental concerns which occurred both during construction and after construction. The former was considered to be short-term impact while the later was considered to be long-term impact. As compared to the others, the work of Underhill and Angold (2000) is from a very unique perspective. Instead of focusing on the environmental impact of a highway at the preliminary phase of a project as was done by other authors, they worked on how a road network causes habit loss, habit fragmentation and habit degradation and thus impacts wildlife in an intensively modified landscape during the operating phase of a road network. Their classification schema, shown in table 2.2, was used to describe the ecological impacts of extant roads upon local biota. 2.2.3 Observations on Current Classification Schema Lessons can be learned from the environment classification schemas reviewed in the previous section. A very obvious observation is that most schemas used a hierarchical structure 23 to model the environment. Although some work, such as the one of Hughes (1989) only classified the environment into several categories without any further break down, they can still be considered as a one layer hierarchical structure. It is also noted that all of the hierarchical structures used are very shallow. Most of them are less than three layers deep while only a very few of them such as the New Fraser River Crossing project (EAO. 2004b) used a four layer hierarchical structure. The third observation is that only modest consistency, at best, exists amongst the classification schemas proposed. To date, we have not found an international, national or even regional standard which can be used on a consistent basis to describe the environment of most projects. For all of the sources examined, both the classification schema and the definition of each environmental component were different, even for projects of a similar type. The fourth observation is that most of the environmental classification schemas identified are for certain types of project only. For example, Marmoush's (1999) classification is only for coastal development projects. No master library of environmental components organized in a well defined structure which is applicable to all types of infrastructure projects was found to exist. The last observation is that no emphasis has been given in the literature to the reuse of environmental experience gained on past projects for future projects. Although knowledge management is flourishing in most research domains, it seems still quiet in this corner of construction research. 2.3 Environmental Risks Risk management of a civil engineering project includes risk identification, qualification, quantification, allocation, mitigation and monitoring. Effective and thorough risk identification is the first and most important step of risk management, in that unidentified risks tend to cause 24 the most negative consequences for projects because of a lack of planned mitigation measures. Existing tools for identifying risks include the use of check lists, prompt lists, brainstorming, literature review, interviews and knowledge-based identification (De Zoysa and Russell 2003). A vast literature is focused on risk identification. Six sources identified as being the most relevant to environmental risk identification are summarized briefly in table 2.3. Table2.3 Works contributive to environmental risk identification Authorship Contribution to Environmental Risk Identification Appendix 5 of this book provides information to aid risk identification focusing on river and estuary issues. The information has been presented in two formats: a list that contains words or phrases likely to prompt thought or discussion around risk issues, and a number of tables listing likely hazards, consequences, impacts and possible risk mitigation measures. Morris & Simm (2000) Arndt (2000) Aklncl & Fischer (1998) Tummala & Burchett(1999) Chua et al. (2003) Fang et al. (2004) A hierarchical risk framework consisting of project phase, category, sub-category and risk layers is defined. A detailed list of risks with definitions is provided. This list contains many identified economic, political and natural environmental risk issues. Construction-specific risk factors which include natural environmental risks and economic and political environment-specific factors are described in detail with specific examples. Risks for transmission construction projects are considered with respect to six categories: financial & economic, political & environmental, design, site construction, physical, and Acts of God. Twelve factors identified in the financial & economic, political & environmental, and Acts of God categories correspond to project environment risks. Five political risks and four economic risks are identified and described in detail for East Asian cross-border construction projects. 45 risks in the Chinese construction market are identified from the perspective of contractors. These risks are ranked according to the importance. Many of these risks can be included in the category of project environmental risks. How environmental risks common to projects are handled can be unique to the specific context of a project. For example, pollution is an environmental risk that occurs on most projects. 25 However, the source of the pollution and the mitigation measures can vary significantly from project to project. A lot of literature is focused on a single environmental risk and investigates the spectrum of issues relevant to that specific risk. Examples of works considered to be significant in this regard are described in table 2.4. 2.4 Environmental Impact Environmental impact is legally required to be assessed for civil engineering projects in most jurisdictions. The issue of environmental impact is always intertwined with that of environmental risks. An environmental impact issue is also an environmental risk issue if uncertainty exists. For example, contaminated soil is an environmental impact issue while an unforeseeable contaminated soil is an environmental risk issue. Mitigation measures for environmental impact can also be mitigation measures of environmental risks (i.e., they can reduce the likelihood of the risk being realized). A substantial body of literature explores environmental impact assessment methods, environmental management, environmental screening, and so on. Some of literature describes innovative mitigation measures of environmental impact over the project life cycle. These works are very helpful for environmental risk management. An Environmental Management System (EMS) is used to address a project's impact on the environment. It is a formal approach that describes the goal, policy, implementation, strategy, specific tasks, monitoring and reporting. ISO 14001 serves as the standard for developing an EMS in the ISO 14000 series. The characteristics of EMS, components of the ISO 14000 series and their application in construction are described in detail by Christini et al. (2004). Chen et al. (2000) proposed that major Chinese construction firms should obtain ISO 14001 EMS 26 Table2.4 Works investigating specific environmental risks Authorship Risks Description Tilford et al. (2000) Contamination The cost-impact, schedule-impact, remediation approach, guidelines for mitigation and the legal framework that contractors work in are provided for unforeseen environmental contamination. Trenter (2003) Geotechnical risk The natural of geotechnical risk is seen to comprise three interrelated categories: design risk, below-ground contract risk and project management risk. Details for each of these categories are discussed. Benedetto and Cosentino (2003) Water pollution for road systems Four possible circumstances for the dispersion of pollutants when road accidents occur are considered: surface water, ground water, natural soil, and urban soil. The risk function is computed with regard to the objective evaluation of severity of the events and to the stochastic calculation of the associated probability. Dalziell and Nicholson (1999) Natural hazards The risks to close the Desert Road section of State Highway 1 in New Zealand caused by snow & ice, volcanic eruption & lahars, earthquakes, and traffic accidents were evaluated in terms of their expected frequency of occurrence, duration of road closure, economic impact and mitigation measures. Sayers et al. (2002) Flood hazard Risk-based techniques from high level planning based on outline analysis to detailed designs using high resolution simulation models are applied to flood hazard management. Bunce et al. (1997) Rock fall & rock slide Rock fall impact-mark mapping supplemented by documented rock fall records was used to establish a rock fall frequency. A risk analysis methodology is applied to assess the probability of loss of life due to rock fall. Hungr et al. (1999) Rock fall & rock slide Magnitude-cumulative frequency relationships were derived for two corridors in BC. A risk analysis method using the slope of the magnitude-frequency relationships is outlined. Diekmann and Featherman. (1998) Risk of environmental restoration projects This paper examined using both influence diagramming and Monte Carlo simulation to model the uncertainties associated with environmental restoration projects. An approach for identifying, classifying and incorporating uncertainty into standard cost estimating procedures is provided to quantify the risk of large-scale cost growth. 27 certification and integrate the concept of environmental management into construction management practice when they present a systematic approach to environmental management of pollution and/or hazards caused by urban construction projects in China. Environmental screening of projects is considered an important part of EMS. Innes and Pugh (1996) developed a standardized screening model for highway projects to evaluate the project from a variety of environmental aspects. Mitigation of environmental impact should start with the planning and design phase of a project. To a significant degree, mitigation measures taken in the planning and design phase are more effective than those that can be taken in the construction and maintenance phase of a project. This is especially true for highway projects. Being aware of this, some highway designers provide innovative design solutions that also meet rising environmental demands in a cost-effective and timely way. McGuire and Morrall (2000) presented three levels of strategic highway improvement to mitigate the unique environmental impact highways and roads have within Canadian Rocky Mountain national parks, which are also World Heritage Sites. The first level of this strategic highway improvement is the rehabilitation of existing park roads in ways to reduce terrain impacts. The second is the development of passing lanes to defer twinning of lanes. The third is the twinning of lanes. Also included in this paper are mitigation measures of fencing and animal crossing structures, addressing wildlife movement, biodiversity, and mortality as well as stream, terrain, and vegetation disturbance minimization techniques. A feature article in World Highways (2005) addressed many mitigation measures taken in the Deerfoot Trial Extension highway project in Alberta. These mitigation measures include shifting the highway alignment to avoid impacting a side channel in the Bow River, forming 30 meter wide strips as a wildlife corridor, providing wildlife underpasses and long span bridges, constructing a pond to 28 catch the sediment-laden runoff, and an environmental lighting system with minimized light pollution escaping upwards and drastically reduced glare. The third example for mitigation of highway environmental impact is taken from an article addressing rigorous environmental controls of NSW Roads (1999) between the towns of Bulahdelah and Coolongolook, Australia. This highway passes through environmentally sensitive areas of state forest, grazing country, six river crossings, a large resident fauna population, and downstream oyster-growing tourist aquatic environment. Mitigation measures for impact on all of these environment features and description of erosion and sediment control techniques are provided1 in this article. In addition to the literature addressing global environmental impact of a project, some literature is focused on specific environmental impact issues and contains more detailed information. Steele et al. (2003) reports on a life-cycle assessment method developed to factor environmental impact into bridge engineering strategy. From an environmental perspective, they identified four aspects for bridge engineering. These are: 1. design and durability, 2. material choice, 3. maintenance, refurbishment and strengthening, and 4. adaptability, reuse, recycling and waste minimization. Dadson et al. (2002) contributed on the issue of determining the effects of the environment on the deterioration of steel bridge components. The Virginia State Climatology Office had identified six regions within the state as having different topography and climate. Using bridge inspection field data, Dadson et al. (2002) proposed a methodology using statistical analysis to determine the effects of environment in each of these six regions on mean service life estimates of paint on steel girder bridges. In this methodology, they also identified factors affecting bridge element service life. The practice of incorporating certain waste products into highway construction and repair materials, such as the use of ground tire rubber in bituminous construction and as a crack sealer, has become more popular. Azizian et al. (2003) investigated the possible impact of these materials on the quality of surface and ground water. 2.5 Role of IT in Environmental Issues and Visualization Advances in information technology play a more and more important role in environmental issues, as they do in other fields. Most IT applications in the environmental domain achieve their goals by visualizing the environment or make environmental visualization as part of its function. This is partially because representing the environment involves huge data sets and it is not easy for users to extract information from them if they are portrayed using text and tabular formats alone. It is also because current software and hardware technologies make the visualization of such huge data set possible. Many computer-based tools, models and expert systems that combine computer graphics, simulation, artificial intelligence and other advanced information technologies have been developed for environmental modeling and understanding complex environmental processes. Wilson and Stonehouse (1983) applied a computer aided overlay technique to represent the environment of highways in order to consider the environmental impact of different highway location options. Although this is a very simple model and is not integrated with other relevant issues as compared to the technology we have today, it demonstrates the strength of computer aided overlay techniques for examining environmental issues. Rapant and Kordik (2003) applied a similar idea to integrate separately evaluated assessments of environmental risks for soil, groundwater and stream sediments in a comprehensive environmental risk assessment map. Fedra (1990) investigated the existing computer tools and methods for the assessment of environmental impacts and implemented a rule-based expert system using hierarchical checklists 30 to perform an environmental impact assessment. This system used simulation models coupled with geographical data bases and dedicated GIS functions. A Geographic Information System (GIS) is an organized collection of computer hardware, software, geographic data, and personnel designed to efficiently capture, store, update, manipulate, analyze, and display all forms of geographical referenced information (ESRI 1990). It represents the real world consisting of many geographical features as a number of related data layers. These layers can be overlapped according to the requirements of users when they carrying out spatial analysis and modeling. GIS holds great potential for environment modeling, analysis, and visualization. A very substantial literature investigates using GIS as an environmental framework. Karimi and Houston (1996) grouped these applications into two general approaches: loosely coupled and tightly coupled. Current trends and future needs were discussed in their work which is very valuable for capturing the broad spectrum of integrating environmental models with GIS. The environmental simulation model and its process developed by Huang and Claramunt (2004) can be visualized, controlled and tuned through interactive steering in a 3D virtual environment. This virtual environment can also run on a web browser and allows users to assemble modeling and visualization components with flexibility (Huang 2003). In addition to the visualization capabilities incorporated in environmental modeling technologies, an enormous amount of work has been done on information visualization in other disciplines, especially in computer science. Although the techniques resulting from this work are not currently applied to environmental issues, they hold great potential for the construction domain, including the treatment of project related environment issues. Taxonomies by Qin et al. (2003) and Chi (2000) are very helpful for the implementers to grasp the key techniques of visualization, so that they can be applied to specific domains of interest. Visualization of 31 hierarchical data structures is an important category for construction projects among these taxonomies, because a lot of construction data can be structured hierarchically. For example, a hierarchical work breakdown structure is widely used for project scheduling; a project's physical component can be represented using a hierarchical structure (Russell and Chevallier 1998); and a hierarchical structure can provide a mechanism to manage knowledge about methods and resources available for constructing a particular physical component (Udaipurwala and Russell 2002). Considering the great potential for applying hierarchical structure data visualization techniques to the construction domain, several important hierarchical structure data visualization techniques are described and compared in table 2.5. Exploration of visualization techniques to cope with the sheer volume of construction management data has hardly been treated in the literature (This does not include work directed at visualizing the physical artifact to be built for purposes of constructability reasoning or workability of the methods selected for its construction (e.g. Staub and Fischer 1998)). Three works have been identified as significant precursors in this research domain. Liston et al. (2000) developed a prototype using two visualization techniques, highlight and overlay, to enable the project team to focus on the relevant information, productively interact with the information and visually relate information. The process of highlighting has two parts: the interaction that defines the task/context and the visualization of the specific project content. Highlighting involves selection of an object (building component, construction activity, etc.), highlighting of project information related to a spatial region or within a temporal region, and application of a highlighting filter. Overlaying is the process of placing one set of information onto another set of information that results in one "merged" view. Overlaying actions to be implemented can be document to document of same type (e.g., placing a Gantt chart onto another Gantt chart), object 32 Table2.5 Comparative analysis of visualization techniques for hierarchically structured data Authorship Technique Size of Name Data Set Interaction Dimension Algorithm Description Huffaker et al. (1998) Plankton Large Web-based, zoom, focus 3D It is a system of nodes and links. The size of the data sel dictates an automated placement algorithm that can leverage the hierarchical nature of the data. It supports a focus function. Carriere and Wilson and Bergeron (1999) Fsviz Kazman (1995) (Cone tree) Kreuselerand Magic Eye Schumann (2002) View Jankun-Kelly and MoireGra-Ma (2003) phs Large Large Medium Filter, zoom, focus Filter, UNHIDES Medium zoom, focus Filter, zoom, focus Filter, zoom, focus 3D 2D 3D 2D It is a modified cone tree method consisting of nodes and links. The radii of the subcones based on the depth of the parent node in the tree. It supports a focus function. It uses a hyperbolic tree for its main display which requires that all locations be calculated in a radial fashion along an arc with respect to depth in the tree and to an interior poinl where the root node resides. It supports four other layout algorithms: leaf-based, subnode-based, range-based and density based. It supports a focus function. It maps a hierarchy graph onto the surface of a hemisphere. It then applies a projection in order to change the focus area interactively by moving the center of projection. It displays a spanning tree induced upon a visual node graph using a radial focus + context graph layout. The distortion due to focus and rotation applies to both the tree levels and the sizes of the visual nodes. HCIL (2005) Treemap Medium Filter, zoom, focus 2D It is a space-constrained technique using a 2-D space filling approach in which each node is a rectangle whose area is proportional to some attribute such as node size. 33 to document of same type (e.g., placing a set of activities onto another Gantt chart), document to document of different type (e.g., placing a 3D model onto a Gantt chart) and object to document of different type (e.g., placing a building component onto a Gantt chart). Focusing on the execution phase of a project, Songer and Hays (2003) developed a visual framework considering a possible representation of project control data. They used the visual framework to analyze current graphical representations of several typical construction project control processes and the associated data-type represented by the graphic. Four layout strategies including scatterplot, linked histogram, hierarchical tree and treemap layouts were applied to represent cost control data in this work. Assisted by a multi-view representation of a project and the integration of these views within a single system, Russell and Udaipurwala (2000) used visual images to assess initial schedule quality in terms of accuracy and completeness and aid project management for project control. They demonstrated the effectiveness of visual images to extract information of resource distribution in time and space, identify problems encountered on a project, and assist with reasoning about productivity loss. 2.6 Bibliography Aklncl, B. and Fischer, M. (1998). "Factors affecting contractor's risk of cost overburden." 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In some instances, the realization of such risks can lead as far as to termination of a project, while in other instances it can have detrimental impacts on performance measures such as cost, revenue, duration, scope, and quality. While experience and knowledge gleaned on past projects is very useful in identifying and managing risks for new projects, such expertise resides primarily in the minds of project personnel and is seldom documented by organizations in a consistent, accessible, and reusable manner. Therefore, it is easily lost through retirements, resignations, and downsizing. Described in this paper is work by the authors directed at developing an IT-based methodology that allows users to capture their knowledge in a re-usable format and apply it to managing environmental risks of specific project * This chapter formed part o f the Proceedings for the Construction Research Congress 2005, American Society o f C i v i l Engineering. A p r i l 5-7, 2005. San Diego, C A . The authorship is: Sanjaya De Zoysa, P h D Candidate and Graduate Research Assistant, Department o f C i v i l Engineering, University of Bri t ish Columbia , dezoysa@civil.ubc.ca, Y u g u i Wang, M A S c student and Graduate Research Assistant, Department o f C i v i l Engineering, University o f Brit ish Columbia , yugui_wang@hotmail.com, and A l a n D . Russell, Professor and Chair, Computer Integrated Design and Construction, Department o f C i v i l Engineering, University of Bri t ish Columbia, adr@civil .ubc.ca. 42 contexts. Motivation for this work stems in part from the pursuit of alternative procurement modes by government (e.g. Public-Private Partnerships) wherein much greater emphasis is placed on risk identification and assignment in the early phases of a project. The authors have participated in the risk identification phase for several large scale projects, and have applied in paper-format several of the concepts espoused in this paper. These concepts have proved very helpful in adding structure to the process and in identifying the drivers or sources of risk that arise from the various dimensions within and surrounding a project. What distinguishes our work from that of others, especially in the risk modeling domain, is the attempt to integrate within a single computer environment the range of dimensions needed to capture the essence of a project. Typical current practice involves the use of a risk register to catalogue the risks associated with a project (Department of Premier and Cabinet, Tasmania 2002, Hal l et al. 2001) that are identified through processes such as brainstorming and the use of prompt lists. The strengths of such a tool, which is generally in the form of an elaborate spreadsheet, lies in the ease of use offered by its format, and its partial facilitation of knowledge management by allowing the simple use of a risk register from a past similar project (assuming one exists) as the starting point for the new project at hand. However, the contents of the register have no direct connectivity to the description of a project, which poses significant difficulties for updating as a project's definition unfolds and risk drivers change. It is our belief that characterizing the context of a construction project through multiple views or models of a project (e.g. Russell and Udaipurwala 2004 - 9 views, Russell and Froese 1997 - 4 views, Fischer and Aalami 1996 - 3 views) is key to the identification and treatment of risks that are project-specific. The concept of views, either in explicit or implicit terms has been pursued by a number of researchers. Consensus on what constitutes the complete set of views 43 required to provide a holistic treatment of a project has yet to be achieved, in part because most researchers are focused on a subset of construction management functions. However, there appears to be consensus that at least two essentiahviews correspond to the product and process models of a project. Physical components of the project, its processes, project participants, and the components of the environment in which the project is located in, can either on their own or in concert act as sources or drivers of risks on a given project as shown in figure 3.1. In developing an IT-based methodology for risk management we have characterized these sources of risk drivers through 4 project views: the Physical V i e w (what w i l l be built - the product model), the Process V i e w (how it w i l l be procured and constructed), the Organizational / contractual V i e w (who w i l l design and build it), and the Environmental V i e w (natural and man-made environments in which it w i l l be built). In this paper, the primary focus is on the environmental view, i.e. how we model the environment in a manner that enables knowledge re-use, and its integration with risk information modeled through a Risk V i e w in order to identify and manage environmental risks on a given project. Environmental drivers Organizational / contractual drivers 1 L Physical drivers r Process drivers Risk Drivers Risk Events Figure 3.1 Risk drivers of different project views In illustrating aspects of the IT-based approach for managing environmental risks, use is made of examples from two rather distinct case studies, one a floating bridge construction 44 project, and the other a highway improvement project that spans in excess of 90 km. Thus, in terms of structuring the paper, we first provide a brief overview of the two projects, and then present details of our approach. Information presented about the case studies have been derived from public domain documents and represents the author's interpretation of information contained within these documents. 3.2 Overview of case study projects The environment of the floating bridge project is tightly bounded ( M O T 2003) whereas, the highway project traverses through several jurisdictions and through urban, coastal, and mountainous regions ( M O T 2004). Use of these two case studies allows us to assess the ability of the modeling methodology in representing a finite set of components, as well as a much larger number of components that are widely dispersed across several locations. A brief description of the two projects follows. The 3 lane Okanagan lake floating bridge on Highway 97 serves as the first case study. It is one of British Columbia's most congested sections of highway having been in service for 46 years. The province is seeking a contractor to design, build, finance, and maintain a new 5 lane crossing, while operating, maintaining, and then decommissioning the existing 880m long bridge. The approach on the eastern side is adjacent to the city park o f Kelowna, while the possibility o f unearthing archaeological artifacts is a primary concern on the west side, with two unexamined archaeological resource areas being present in the area. The Sea to Sky highway improvement project in British Columbia serves as the second case study. The project involves widening and straightening a 94.7 km section of highway in a mountainous and environmentally sensitive area. The expansion involves 5 road sections 45 including bridges and viaducts. Moving south to north, the configuration consists of a 12.2 km 4 lane section, a 10.5 km 2 lane section, a 19.7 km 3 lane section, a 9.9 km 4 lane section, and a 42.4 km 3 lane section. The road sections cross 67 roadside drainage ditches, 191 creeks and streams, 7 lakes, 1 pond, 24 wetlands, and 1 estuarine tidal marsh. The highway also traverses several municipalities that profess varying degrees of support for the proposed improvements, and have different bylaws regarding construction, traffic management, etc. Throughout the construction phase, traffic w i l l have to be maintained on the existing 2 lane road (which does have some 3 and 4 lane sections already), and the desire is to minimize the number of scheduled road closures. Our primary perspective with respect to these projects is that of government carrying out an analysis of project risks in order to provide input to a value for money analysis (Akintoye et al. 2003, H M Treasury 1998) aimed at determining the appropriate procurement method, and assisting in the development of risk allocation and mitigation strategies. A t this stage in the project lifecycle, detailed design solutions are not available nor are construction methods known with any certainty. Based on various specialist studies commissioned by government, however, what is largely known is the spectrum of project participants and stakeholders and their respective agendas, the likely form that design solutions w i l l take, and the environmental characteristics (natural and man-made) that w i l l shape the project. It is noted that the methodology described in the paper is applicable to any phase of the project lifecycle and is equally usable by both public and private sectors. 3.3 Modeling the Environment Presently, in most parts of the world, the environment of large construction projects is characterized mainly from the standpoint of carrying out Environmental Impact Assessment 46 (EIA) studies as part of the approval process for a project. Legislated guidelines determine the scope of these studies which mostly relate to natural environmental components, economic conditions, social and health components, and cultural and heritage components (Canadian Environmental Assessment Agency 2003). Hughes (1989) in recognizing the implications of the project environment on the organizational structure of the project identifies 11 types of environmental factors. Among these are political factors, legal, financial, institutional, technological, and policy factors in addition to the categories that are covered by E I A studies. Other researchers (e.g. Underhill and Angold 2000, Week 1977, and Wilson and Stonehouse 1983) have explored how aspects of the natural environment can be characterized. To date, however, we have not found an international, national or even regional standard that can be used to describe or model the environment of most projects. Based on an extensive review of environmental assessment reports for major projects in Canada and elsewhere, it is observed that in terms of the classification schema and the semantics used to describe the environment for individual projects, while there can be similarities amongst projects, there are always notable differences. From a practical point of view, what this means is that any computer-based structure developed for representing the environment of projects should possess considerable flexibility, both in terms of allowing the capture of one or more environmental breakdown structures in order to facilitate the development of standards at the level o f the organization while allowing tailoring of a standard or bottom up definition of a environmental breakdown structure for a unique project. We also observed that most environmental descriptions used in practice adopt a three-level hierarchical structure, with the very odd exception being up to a maximum of five levels. For purposes of developing our methodology, we have defined the project environment as the physical, social, economic / financial, political, and regulatory surroundings of a project, thus encompassing the dimensions considered in E I A studies as well as well as other surroundings that can be of significance for project risks. It is noted that the user is not restricted to adopting this particular classification and can readily adopt another such as a scheme used in E I A studies. However, the importance of adopting a single, consistent classification within an organization is strongly emphasized as it is critical in ensuring the portability of information between projects. A hierarchical structure has been adopted in modeling the environmental context to reflect actual practice and with the aim of allowing flexibility in the level of detail at which the environment can be represented. For example, in a preliminary assessment of project feasibility and risks, a coarse model that makes use of a shallow hierarchy may be used for representing the environment. A s more information becomes available regarding the project's environmental, physical and process views, and as decisions are made as to the pricing of risks and their allocation, a more detailed and slightly deeper environmental hierarchy would be required to assist the risk management process. A hierarchical model also facilitates inheritance and aggregation of properties. These are desirable for allowing the speedy setup of an environmental model and in ensuring consistency and adherence to standard terminology, in defining the properties of its components. However, a hierarchical representation is not devoid of drawbacks. Difficulties can arise in ensuring that components are organized such that the collections are mutually exclusive. Additionally, deep hierarchies are not commensurate with the quality of environmental data available, and the resources available for building up such a model. A s stated previously, a three-level hierarchy is typically used in E I A studies to model components of the environment. In implementing our approach, up to a five-level hierarchy termed the 48 Environment Breakdown Structure (EBS) has been used. A s demonstrated through two extensive case studies, this number of levels provides sufficient flexibility for modeling at the level of detail indicative of day-to-day practice as reflected by E I A studies, while allowing the user leeway of incorporating additional details i f desired. Finally, in terms of supporting the risk identification process, a shallow hierarchy for modeling a project's environment is preferred. Risk identification sessions normally involve a considerable number of individuals, and visibility of as much of the E B S structure as possible and the ability to navigate it quickly is imperative. These sessions often involve not only identifying risks as a function of a project's environment, but often result in teasing out additional features of the environment that are relevant to a project's risk profile. The component types in the hierarchy are described below, with examples drawn from figure 3.2(a) that shows the E B S structure for the Okanagan lake bridge project. The five component types that comprise the E B S hierarchy are: Environment: The global environment of the project under which all other components can be defined and described. Class: The main classes of the environment, in our case physical, social, political, regulatory, and economic/financial. However, the users can define classes as they see fit. Sub-class: A subset of environmental components within a class, such as geological components within the physical environment class, and macro economic factors within the financial/economic category. . Entity: A n environmental component that can be identified distinctly from other components - e.g., inflation, archaeological resource, fish. Sub-entity: In some cases it might be necessary to characterize the environment in more 49 1H-[):WI H'.i :iovtii UNI WAI its F-ile " . :t_View Standards:.: ::EBS.:: iWtndow. Help ft, __ r_3 © ^Bfl % t i 4 - OL8E Environment Example Floating Bridge Project Environment a- PHY Class Physical Environment j Bfi-HYD Sub-class Hydrography j j 4 -CREK Entity Creek j j -i- LAKE Entity Lake j • TPGP Sub-class Topography \ f - G E O Sub-class Geology i + BOTN Sub-class Botany j * HABT Sub-class Habitat j 4 - 2 0 L G - Sub-class Zoology ! j i ' A W B Entity Amphibian i { j- RPTL Entity Reptile S j i - MAML Entity Mammals j j 4 - B I R D Entity Birds j j f GULL Sub-entity California'r, j j j 5 SWAN Sub-entity Trumpete i j i - F I S H Entity Fish j .• ATMP Sub-class Atmosphere i ;4-CLMT Sub-class Climatology j i - P L U T Sub-class Pollution S - S C L Class Social Environment ! B3--ABOG Sub-class Aboriginal j i - C M L F Sub-class Community j A - M S F T ' Sub-class Micro Social Facto j S - A C H T Sub-class Archeological and i 3-ARCH Entity Archeology Attributes : Values, standard EBS Records \ Risk Issues j:; Prciect Records. |: Memo. j Path: OLBE.SCL.ACHT.ARCH. Code: if AST E Description: jArcheotogtcai Stte Type:. J-oMB ry Attribute Values Description Name ol resource Land area of site Creation Era Current State Inherited attribute i 8/QA. I tins! YES L YES Q sqm YES L YES L JTHS Aiilici (b) Si-ECO k POL -REG ASTE 5ub-entit/. Archtolcg.TSTSWe' Class Economic / Financial Environment Class Political Environment Class Regulatory Environment < Ready:.: (a) PatK OLBE.SCL.ACHT.ARCH.. Attribute:'Name of resource" Value Type: Linguistic ,••• (c) Location Ranges location Range •:• .= v•>, Value > • H i C)Qv43 23*_24»_-23»_24» D10v38 24«O0_10-24-.aCL10 D!Qv42 24*10 50-24-.10 SO DIQv45 Cancel i Figure 3.2 (a) Environmental Breakdown Structure for Okanagan lake bridge project; (b) Attributes of 'Archeological site' component; (c) Specification of attribute values at different locations detail. For example, a composite inflation rate is made up of labor rates, material rates, etc., while birds may be made up individual species such as trumpeter swan and gull. Components that make up the E B S can be further described in terms of user-defined attributes that allow the properties of a component to be comprehensively described (see figure 3.2(b)). The risk issues that are driven by an environmental component are in most instances dependent upon the component's attribute values and not simply on the presence of the 50 component itself. For example, bird species within the project boundary that are classified as endangered (e.g. attribute value T R U E for attribute definition endangered? at project locations x, y, z) could lead to uncertainties in project duration as bird nests encountered during construction would have to be relocated prior to the continuation of construction. A s shown in figure 3.2(b), functionality has been provided for defining Quantitative (Q), Linguistic (L), as well Boolean (B) attributes in order to accommodate the variety of characteristics that may be used to describe environmental components. Allowance has also been made for E B S components to be associated with project records such as photographs of the project site, documents detailing site investigations and so forth. A s described later, associations can also be made with components of the project risk register consisting of a project-specific listing of risks. In addition to defining the characteristics or attributes of a component, the identification of the locations at which the environmental component is present is also necessary from a risk management perspective, as the intersection of environmental components with other project components at the same location (e.g. environmental, physical and/or process) can heighten the relevance of a risk issue for the project. A n example would be the intersection of the archaeological resource site at location chainage 23+_23+ that has been assigned the name DIQv43 (see figure 3.2(c)) with the activity 'clear embankment area' at the same chainage location. We use a set of location constructs consisting of a location set, location, sub-location hierarchy to describe either a physical project location (e.g. chainage of a highway project) or a temporal location (e.g. step in a procedure). In implementing the methodology, the set of location constructs defined in the physical view (called the P C B S for physical component breakdown structure) is used to represent the locations corresponding to the physical, process, and environmental views in order to ensure consistency of definition. The set of locations used 51 for modeling the Okanagan lake bridge project is shown in figure 3.3. Components of the E B S structure are associated with project locations by way of assigning values for component attributes that are relevant to each project location. For example, six rather ill-defined archaeological sites fall within the project corridor. Values of attributes such as the name that has been assigned to each archeological site during environmental studies, the approximate area of the site (measured in square meters), and the current state of the site, i.e. whether it is 'destroyed', 'unexplored' and so on, can be assigned to the six sites based on their location as shown in figure 3.2(c). Fie Project_vtew * Standards PCBS Window Help S X - OIBE Project Okanagan Late floating 6 : Chainage 23+00 - 23+10 : Chainage 23+10 - 23+50 : Chainage 23+SO - 24+00 : Chainage 24+00 - 24+10 : Chainage 24+10 - 24+50 GPRJ Location Qobal Project 23+G0_l0 Location Roadway ( 23+10_50 Location Roadway r. >•• 23+_24+_ Location Roadway: < : 24+G0_l0 Location Roadway < 1 24+10_50 Location Roadway < > 24+_25+ Location Interchange: Chainage 24+SO - 25+25 2S+25J35 Location Roadway: Chainage 25+25 - 25+35 25+_28+ Location Roadway: 25+35 - 28+00 : r~ 28+_29+ Location Approach Bnfaankment: Chainage 26+00 - 29+44 29+J32+ Location Ramp & Transition Span: Chainage 29+44 - 32+80 32+_39+ Location Floating Bridge: Chainage 32+68 - 39+64 38+_40+ Location Bev Deck/ TransBon Span: Chainage 38+64 - 40+12 !• 40+_45+ Location Roadway: Chaaiage 40+12 - 45+84 DRYDOCK1 Location Dryctaf&fcfr Pontoon Constr,-8ear Creek South r"DRyDOOC2 Location Drydockfor Pontoon Constr.-Kelowna City Park DRYDOCK3 Location Drydock for Pontoon Corstr. - Hghway 97 PgBout DRYDOCK4 Location Drydock for Pontoon Corstr. - Penticton : :• LAKE Location Lake i i - rCAKE Location North shore -SLAKE Location South shore J 152 Location Set Procedural Location Set Ready Figure 3.3 Definition of locations for Okanagan lake bridge project In defining component attributes, the user has the option of entering the definition at a higher level o f the hierarchy and allowing components at lower levels to inherit common attribute definitions. This reduces the burden of re-defining attributes and also ensures consistency. A s a further step towards bringing about the consistent use of terminology, we 52 allow the user to build up a standard set of linguistic values based upon common terms used within the user's organization, which can be assigned as values to linguistic variables. A s described later, standard use of terms can greatly facilitate the encoding and re-use of knowledge especially regarding conditions under which a risk issue is likely to be relevant for a certain project context. 3.4 Knowledge Management Knowledge management is a relatively new, yet flourishing area of research. Effective management of knowledge typically requires a combination of organizational, social, technological, and managerial initiatives. The use of information technology is therefore only a segment, albeit an important one, of a larger strategy that is required to manage knowledge within an organization. Several authors have proposed utilizing IT in the form of knowledge-based systems for risk management. These include a rule-based risk identification system for high voltage transmission line projects (Leung, Chuah, and Tummala 1998) and a fuzzy case-based reasoning system for risk assessment in software development projects (Cox 1999). A comprehensive analysis of such approaches is provided in De Zoysa and Russell (2003). While acknowledging the pioneering work carried out by previous researchers, we believe that further success depends on developing an approach that treats the environmental, physical, process and organizational/contractual context dimensions of a project, an aspect that is not comprehensively dealt with in existing approaches. Consideration of these project dimensions is extremely important as their attributes and likely values are the determinants of risks that could arise on a project - i.e. it is often as important i f not more so to manage the risk drivers as compared to the risk event itself. 5 3 One of the main barriers to creating a model of the environment (as well as the other project views) in support of risk management is the effort required to create it, particularly i f each component and its attribute definitions are to be defined anew each time a project is defined. The strategy that has been adopted to enable the re-use of information and knowledge that is gained on a project, involves use of two domains that are referred to as the Standards side and the Project side. The Standards side contains information that is independent of any one project, whereas the project side contains information that is relevant to an individual project. A project's E B S structure stripped of attribute values and location assignments can be saved as a template on the Standards side, allowing knowledge about the environmental component structure for a particular project to be stored in a re-usable format. Thus, in executing projects in similar environments the user would extract the standard template or parts of it and define the E B S structure for the current project. A template can describe a certain type of environment, for example, mountainous or coastal, or refer to a specific part of the environment such as a stream. The notion of using standard templates is not unique to the authors, and shares parallels with the concept of reusable ontologies (Annamalai and Sterling 2003), while also being somewhat reflective of case-based reasoning schema (Brandon and Ribeiro 1998). 3.5 Integration with Risk Information A s described previously, the lack of integration of risk registers with a definition of the project context in current practice inhibits the identification of risk issues that are relevant to the project context, and precludes leverage that could be gained by such integration including allowing the user the option of viewing risks that are applicable to upcoming time windows, the distribution of risks over project participants and so forth. 54 In developing a methodology that treats integration amongst the project views and the risk view, we duplicate for the risk view the concept of a standards domain and a project domain. On the standards side, a Standard Risk Issue Register (SRR) is used to identify a repository of risk issues that is built up over time by a particular organization. We use the term risk issue to denote potential sources of uncertainty or unpredictability that could generate one or more risk events. A potential risk issue is "first nation artifacts" that could create a risk event such as "discovery of artifacts on road alignment". Realization of this event could lead to one or more discrete scenarios depending on the significance of the archeological find. Our treatment of risk events in general allows for up to three scenarios corresponding to low, medium and high consequences, with associated probabilities and outcome measured in terms of scope, time, cost, etc. Risk issues are categorized and organized as a hierarchy within the S R R that also includes details on whether the effect of the risk issue is local (e.g. is individual work package related) or global in nature (affects many work packages or the entire project), the type(s) of project stakeholders affected by the risk as well as the stakeholders who are best suited to manage the risk, appropriate mitigation measures, and suitable ways of incorporating the risk into the economic analysis of the project. A s part of our philosophy of allowing the user to build up knowledge, we allow master lists of risk mitigation measures, methods for estimating likelihoods and impacts of risk events, and methods of incorporating the risk into the economic analysis of the project, to be built up on the standard side of the system. We use the concept of risk drivers in creating associations between components of the S R R and components of the environmental templates in the standards domain. A component of the environmental view, the presence of which makes the risk issue relevant is defined as a risk driver. Risk issues that are driven by a particular E B S component can be listed as part of the 55 encoded information of that component. Knowledge regarding conditions under which the risk is likely to occur, expressed in terms of the risk drivers that correspond to the attributes of environmental components (e.g. for a bird species of type x, is it an endangered species?), can also be encoded within the system by the user. On an individual project, we use a Project Risk Register (PRR) that contains risk issues that are relevant to the project context, such as the one shown in figure 3.4 that relates to the Okanagan lake bridge project. Figure 3.4(a) shows part of the project risk register while figure 3.4(b) shows aspects of the mitigation folder for the risk event 'Discovery of Artifacts on Road Alignment.' Note that relevant performance measures affected by the event have been identified as time and scope. Other properties that can be associated with a risk event correspond to the folder names shown in figure 3.4(b). Users can choose among several modes of use in building up a P R R as described below. The 1 st mode of use lends itself to instances where the environmental definition is at a very coarse level or in instances when the project environment's uniqueness precludes the use of standard E B S structures that set out a pre-defined relationship between risk issues and E B S components. In this mode the S R R is used as a mnemonic device. The user can browse through the hierarchy of risk issues and extract risk issues that are thought to be relevant to the current project context. The user can then manually create associations between risk issues and E B S components as well as other project views such as the physical view. The 2nd mode of use makes use of the associations between E B S components of standard templates and risk issues of the SRR. A s a user builds up an environmental definition of the project environment by copying over standard E B S templates or parts of templates onto the project side, the risk issues that have been associated with the E B S components are 56 :Fite: :Pro)ect:View -' . Standards RISK Window Help _ 3> X 1 BliE|tflfe|/bl&|fl|®| M ^ N & l g l ' f 1 .-Re; L t • --,•••«. r • il.ansg.sn Puck.-1 - - r -(a) TECH Category Technical Risk Issues PHY Category Enwonmertal Risk Issues s NAT Subcategory Natural Environmental Risks i CONT Issue Contaminated Sotl '- ENDG Issue Endangered Species 1 3-rou. Issue Polution ACC Event Major accident on bridge release; - STAKE Subcategory Third Party Stakeholder Risks I 3 FIRST Class First Nations ! S ARTIF Issue First Nations Artifacts I f ; s-OtSC Event Discovery of Artifacts on Roar i s RE5ERV Issue First nations reservations NOISE Event Objections to construction nc i * SPCLINT Class Special Interest Group Risks a ECON Subcategory Economic Risks | 3 LAB Class Labour Market Risks \ \ S SKILL Issue SHed labor \ ;SHORT Event Shortage of skilled labor due i l INF Class Inflationary Risks * FIN Subcategory Financial Environment S REG Subcategory Regulatory Risks i REGS Class Regulations m E1AREG Issue EIA Regulations ORGCOHT Category Organizational / Contractual Risk 1$ rf-OIPft Issue Lackof experience of member a BANK Issue Bankruptcy of concession member FORCEMAJ Category Force Majeure Ready; Description | Risk Dirvers j Performance measures | values Mfcgabon j Standard RIR Records j Memo] •• P * PRR.rfW.STAKE.FIRST ARTIF Code [DISC ..^ Description jDiscovetv of Arriacts on RoadASo^menl Ri:k Isiue Specific Ltsk ; Appropriate rtutigalion sliatetyes fa: 7 me .-:• Studies Ewerrane past history of woik site Pretabiieation Appropriate mitigation strategies for: Scope Modify] Modsyj -MftigatKfft Master List] Edit Afjpropoaio (ratigafoon jfcaiegws tor. Scope • (b) ~ s T l Hedges / Guarantees v : Q 8uy (Owes on volaliie prqecl r©uts (e.g mate • - QQbtawpicegua(anle«fromsa3plieistoiasp^ a - • Studies Figure 3.4 (a) Project Risk Register for the Okanagan lake bridge project (b) Selection of appropriate mitigation measure from Master List of Mitigation Measures automatically copied over to the P R R . The user can further augment the P R R by copying over additional risk issues from the S R R manually. In the 3rd mode of use, we make use of conditions specified in terms of the attributes of E B S components to gain further insights as to the relevance of the risk issue to the project context. A s described previously, a risk driver acts as the catalyst for a risk issue. However, the relevance of the risk issue might be determined further by evaluating the characteristics of the risk driver. For example the risk issue "bird nest relocation" would be driven by the E B S component "birds". However, the importance of the risk issue becomes magnified when the value of the Boolean attribute "Endangered?" of the E B S component "Birds" takes on the value 57 " T R U E " . In the 3rd mode of use, we allow conditions to be specified on the standard side that need to be met by attributes of the E B S component for the risk issue(s) to be relevant. Once imported to the project side, and values assigned against its attributes, the user can run a check against the conditions specified for each associated risk issue. The system w i l l then match the conditions against the attribute values specified and signify risk issues that satisfy the conditions. The use of any one or a combination of the modes of use described above w i l l result in the P R R containing a context specific listing of risk issues. Use can be made of the risk issues to then define the risk events that could potentially occur on the project. The risk events pertaining to a project such as the risk issue "Work stoppages on the western approach embankment to allow removal of artifacts" tend to be very project specific, and we envisage only very general risk event definition w i l l be stored on the S R R as re-usable knowledge. In defining risk events for a particular project, the user armed with general risk event descriptions would examine the locations at which the components driving the risk issue are present. Considering each location separately, the user w i l l have the ability to examine other components that share the same locations. A n example would be the risk issue "archaeological artifacts" that is driven by the E B S component "archaeological artifacts" located in Roadway chainage 23+00 - 24+50. If the process of "Bu i ld approach roadway" is also present at the same location then it is likely that risk events such as the one described could occur on the project. The ability to envision the juxtaposition of risk issues, environmental components, and components of other project views places the user in a position of advantage to identify project risk events and their significance. A s shown in figure 3.4(b), use can also be made of encoded knowledge to select the most appropriate mitigation measure(s) for a risk event. 58 As described before, a project EBS structure such as the one for the Okanagan lake bridge project can be saved as a template on the standard side of the system along with information on the attributes that are of importance in modeling components, as well as the risk issues that are driven by the components. Similarly, the Standard Risk Register can be enhanced with risk issues that were identified during the course of the project and not previously recorded within it. Information contained within the master list of risk mitigation strategies, and information on methods of estimating the impact of risk event and of incorporating risk into the economic analysis can also be enhanced in this manner. S-STSE Erwironment Sea to Sky Highway =-PHY Class Physical Environment ; SHYD Sub-class Hydrography . i f-fPGP Sub-class Topography ; k GEO Sub-class Geology j s-BOTN Sub-class Botany ' s-HABT Sub-class Habitat • :* ZOLG Sub-class Zoology ; s LWOG Sub-class Lower Organisms I :* ATMP Sub-class Atmosphere ; :+: CLHT Sub-class Climatology ; s-DESE Sub-ctess Disease Control i i PLUT Sub-class Pollution * SCL Class Social Environment i ECO Qass Economic / Financial Environment +: POL Class Political Enwonment jf.-REG Class Rectory Environment Ready Project i+; Coastal Envirorareni '+ Lake Envkonment Economfc Class L-i Stream f OK Figure 3.5 Use of standard templates in defining Environmental Breakdown Structure for the Sea to Sky highway improvement project Now, assume that the Sea to Sky highway project is undertaken subsequent to the bridge project. Building up the EBS and identifying the risks on this project anew would be an onerous task. However, this process is expedited with the use of standard templates built up from the 59 floating bridge project. While the projects themselves might be fairly distinct, as a whole they share several components of a similar nature such as streams, economic components, and First Nations artifacts. In building up the EBS the user can copy over standard descriptions of components such as streams as shown in figure 3.5. While actual attribute values are absent, the attributes of importance are already defined for the standard components. Information on risk issues driven by the environmental component is also present which is copied over to the project side. These risk issues can be used in building up the PRR for the project. Once the user assigns values for the attributes that are reflective of the current project, they can also be matched against the risk issue conditions to determine the relative importance of the risk issue. 3.6 Conclusions We have described an IT-based approach for managing environmental risks that makes use of a hierarchical representation of a project's environment. The methodology allows components of the environmental model to be integrated with risk information, and also facilitates the development of standard templates geared towards knowledge and information re-use. Application to two full-scale projects has demonstrated the usefulness of the approach. Among areas of future research is the development of visualization strategies that allow an analysis of the spread of risks over components of the environmental and other project views including project locations and participants along with their concentration in time. 3.7 Acknowledgments The authors would like to express their appreciation for the financial support provided by The British Columbia Ministry of Transportation in the form of a grant-in-aid for research on environmental risk identification for P3 projects. 60 3.8 Bibliography Akintoye, A . , Hardcastle, C , Beck, M , . Chinyio, E . , and Asenova, D . (2003). "Achieving best value in private finance initiative project procurement." Construction Management and Economics, 21, 461-470. Annamalai, M . , and Sterling, L . (2003). "Guidelines for constructing reusable domain ontologies." Proceedings, Workshop on Ontologies in Agent Systems: 2nd International Joint Conference on Autonomous Agents and Multi-Agent Systems, Melbourne, Australia. Brandon, P. and Ribeiro, F. (1998). " A knowledge-based system for assessing applications for house renovation grants." Construction Management and Economics, 16, 57-69. Canadian Environmental Assessment Agency (2003). "Basics of Environmental Assessment." http://www.ceaa.gc.ca/010/basics_e.htm (1 Nov. '04). Cox, E . (1999). "Coping with the uncertainty principle: Predictive project risk assessment and risk classification using a fuzzy case-based reasoning system." P C A l , 13, 37-40. De Zoysa, S. and Russell, A . (2003). "Knowledge-based risk identification in infrastructure projects." Canadian Journal of C i v i l Engineering, 30, 511-522. Department of Premier and Cabinet, Tasmania (2002). "Project Management." http://www.projectmanagement.tas.gov.au/k_base/examples/pagerisk.htm (1 Nov. '04) Fischer, M . and Aalami , F. (1996). "Scheduling with computer-interpretable construction method models." Journal of Construction Engineering and Management, A S C E , 22(4), 337-347. Hal l , J., Cruickshank, I., and Godfrey, P. (2001). "Software-supported risk management for the construction industry." Proceedings of the Institute of C i v i l Engineering, 42-48, Paper 12272. 61 H M Treasury (1998). "Public Sector Comparators and Value for Money." H M Treasury, London, U . K . Hughes, W . (1989). "Identifying the environments of construction projects." Construction Management and Economics, 7(1), 29-40. Leung, H . , Chuah, K . , and Rao Tummala, V . (1998). " A knowledge-based system for identifying potential project risks." International Journal of Management Science, 26(5), 623-638. Ministry of Transportation, British Columbia (2003). "Environmental Impact Assessment synopsis report, Okanagan lake bridge project." Ministry of Transportation, Environmental Management Section, Victoria, B C . Ministry of Transportation, British Columbia (2004). "Environmental assessment of Sea-To-Sky highway improvement project." Ministry of Transportation, Environmental Management Section, Victoria, B C . Russell, A . and Froese, T. (1997). "Challenges and a vision for computer-integrated management systems for medium-sized contractors." Canadian Journal of C i v i l Engineering, 24, 180-190. Russell, A . , and Udaipurwala, A . (2004). "Using multiple views to model construction." Proc.CIB World Building Congress, Toronto, National Research Council o f Canada. Underhill, J. and Angold, P. (2000). "Effects of roads on wildlife in an intensively modified landscape." Environment Review, 8, 21-39. Week, T. (1977). "Environmental impact of transportation project." Environmental Impacts of International C i v i l Engineering Projects and Practices. Proceedings of a session of the A S C E National Convention, San Francisco, 1-28. 62 Wilson, F. and Stonehouse, D . (1983). "Environmental impact assessment: highway location." Journal of Transportation Engineering, 109(6), 759-768. 63 Chapter 4 Visualization of Construction Data* 4.1 Introduction Construction project participants are confronted with the need to make high quality and timely decisions based on the information content that can be deduced from the very large data sets required to represent the various facets of a project through its development life cycle. H o w best to extract information from large data sets is a question that fascinates researchers and practitioners alike across a number of disciplines, including construction. One line of inquiry deals with data visualization, which the authors believe has special appeal to the construction industry because of its visual orientation, and because data visualization tools are directly usable by construction practitioners without the requirement for expert assistance, a potential impediment to the adoption of other reasoning schema being examined by the research community. Described in this paper is work directed at exploring how data visualization strategies, in concert with a multi-view representation of construction projects can aid decision making and provide valuable insights into reasons for construction performance. Data visualization has applicability to a broad range of management functions, and, supported by a * This chapter formed part o f the Proceedings of the 2005 Construction Specialty Conference o f the Canadian Society o f C i v i l Engineering. June 2-4, 2005. Toronto, O N . The authorship is: Tanaya Korde, M A S c student and Graduate Research Assistant, Department o f C i v i l Engineering, University o f Bri t ish Columbia , tpk08@yahoo.com, Y u g u i Wang, M A S c student and Graduate Research Assistant, Department o f C i v i l Engineering, University o f Brit ish Columbia, yugui_wang@hotmail.com, and A l a n D . Russell, Professor and Chair, Computer Integrated Design and Construction, Department o f C i v i l Engineering, University o f Bri t ish Columbia, adr@civil .ubc.ca. 64 holistic representation of a project, important learning can take place on cause-effect relations that might otherwise go undetected and/or hypotheses on reasons for performance to date proved or disproved. The representation of a project adopted herein involves nine project views integrated within a single system. These views are: physical, process, organizational/contractual, cost, quality, as-built, change management, environmental, and risk (Russell and Udaipurwala 2004). Examples of data visualization as they relate to the environmental and change management views are provided in the paper. In general, visualization can be defined as the art of representing data using suitable visual formats and/or graphical images such that it simplifies and facilitates its interpretation by the intended target audience. In the construction world, there can be multiple target audiences, and the type of visual image used may vary from one audience to another depending on their comfort with 2-D, 3-D, and more complex images. For example, while construction personnel tend to be very visually oriented, often their clients are not. Studies have revealed that the visual perceptive system o f humans is much faster than the human cognitive system. Hence humans can derive information from data better and faster i f it is presented in a suitable visual format. Data and information can be distinguished from one another, with information corresponding to the message(s) extracted from data. Interestingly, in the visualization literature, often the term information visualization is used, although the emphasis is in fact on the visualization of data. Representing data in a visual format "makes the human brain use more of its perceptual system for the initial processing of any data than relying completely on its cognitive abilities"' (Geisler 1998). A s stated by Brautigam (1996), visualization techniques "exploit the human perceptual system" as opposed to the human cognition system. Various attributes of the data of interest are mapped against certain features 65 like color, size, shape, location or position thereby reducing the need for explicit selection, sorting and scanning operations within the data (Tufte 1990, Shneiderman 1994). These techniques thus tailor the data to be retrieved, such that the eye can quickly distinguish salient features of the data before the brain begins to process it (Brautigam 1996). This helps the target audience achieve insights faster and better as to the information content of a data set that may otherwise be concealed or not easy to comprehend from its representation in tabular or text form. For the current state-of-the-art of computerized visualization techniques, data representation is often coupled with real time interactive tools like zooming and filtering, details-on-demand windows and setting dynamic query fields, which allow users to browse through and study the represented data. Emphasis is placed on the rapid filtering of data to reduce the result sets (Ahlberg and Shneiderman 1993). This is called visual data exploration. Thus, visualization can be described as a two-fold process of data presentation and data exploration. 4.2 Significance of Application of Visualization to Construction Environment Construction projects involve voluminous data sets. A project's database may contain data varying from textual form such as drawing specifications and contractual clauses, to quantitative data like number of change orders and related properties dealing with value, timing, number or participants, etc., RFIs issued and turn around times, drawing control data, schedule information pertaining to dates and activity durations (planned and actual), weather conditions on site, and cost breakdowns. The data is generally time and location variant and originates from multiple project participants. The sheer volume and nature of the data pose significant management challenges. Further complicating these challenges is the observation that construction data is 66 often poorly organized because it lacks proper grouping and sub grouping which can lead to missed opportunities to associate related data or facts. For effective management of a project, efficient handling, monitoring and control of all project data is essential. Buried within this data are important messages which relate to the reasons for performance to date, but extracting this information from any database, especially a poorly organized one can be very difficult (even i f a database is well organized, linkages amongst different data items may not be obvious - data visualization may in fact help one forge relevant links). A s a consequence, explaining different aspects of construction project performance often qualifies as a classic case of "data rich -information poor" problems (Songer and Hays 2003). Thus, the massive amount of data available to management personnel results in information overload (Songer and Hays 2003) unless it is accompanied by a high level of organization and accompanying reporting mechanisms. Effective visual representation schema assist the efficient scanning of different parts of a project's database, allowing users to instantly "identify the trends, jumps or gaps, outliers, maxima and minima, boundaries, clusters and structures in the data" (Brautigain 1996). Exploration tools allow continuous interaction between users and the graphic displays by offering scope for "constant reformulation" of search goals and parameters as new insights into the data are gained (Ahlberg and Shneiderman 1993). It provides a continuously updated information platform to users, thereby aiding the decision making process from project conception to completion of construction, the timeline of interest in this paper. 4.3 Visualization Technologies Based on a literature review, it is observed that the field of visualization has evolved tremendously from classical graphs and diagrams to the current array of computerized interactive 67 visual aids. Over the past decade, a number of visualization techniques have been developed and enhanced to achieve a range of objectives and increased scope of application. In this section the authors provide a brief overview of the current state-of-the-art of these techniques, their working principles and sample software applications, although this treatment is not exhaustive. Several authors have tried to classify visualization techniques using various schema. Earliest amongst these was. classification by the data type(s) that they can represent, proposed by Shneiderman (1996), who further proposed another classification framework on the basis of the type of user interactive tools offered by a given technique like overview, zoom and filter, details-on-demand, etc. The intent of proposing this latter classification was to identify techniques that could fulfill a specific analytical task desired by the user. Different interactive tools offer different analytic capabilities like clustering, comparing, and identifying patterns within the data, thereby assisting users to gain deeper insights into the data. In selecting a visualization technique for a certain application, users need to resolve two predominant issues: the data type(s) the technique can represent; and, the kind of user interaction it offers for analytic purposes. In order to satisfy both of these fundamental user concerns, Qin et al. (2003) combined the two classification frameworks proposed by Shneiderman to put forth a matrix framework (Table 4.1) where visualization techniques are situated in a cell depending upon which data type they are applicable to and what analytical tasks they offer to users for interaction. The two-dimensional classification framework shown in Table 4.1 has data type ( ID, 2D, 3D, Multi-dimensional, Hierarchical, Graph and Text/hypertext) as one dimension and analytical tasks (overview-query, comparison, cluster-classification, distribution pattern and dependency-correlation analysis) as the other. 'Outlier analysis i.e. identifying outliers in a data set forms a part of cluster classification as clusters and outliers are cross problems' (Qin et al. 2003). 68 Table 4.1 Visualization techniques, working principles and sample software applications (Qin et al. 2003) Analytical Overview- Comparison Cluster- Distribution Dependency-Task query classification pattern correlation Data Type analysis I D Animation; Pie plot; Line Color map; Curve Value bar; Li feLine ; Line graph; Color map; Curve graph density plot Curve density plot; Histogram density plot 2D A V i z Geographic map; Scatter plot; Color map Geographic map; Scatter plot Color map Isogramplot 3 D Vis ib le Human Volume rendering; Scatter Scatter plot Color map plot Multi- GrandTour W i n V i z ; H D - E y e GrandTour; dimensional Project pursuit, FastMap Table Lens; n- Andrews Parallel Circ le Scatterplot V i s ion ; Curve; Star Coordinates; Segments; Matr ix; Scatterplot Matr ix; Star glyphs glyphs InfoCrystal InfoCrystal Dimension Stacking Hierarchical Hyperbolic view; Magic Eye V i e w ; Treemap; Information Cone Tree; Disk Cube Tree -Graph WebBook WebForager Ne tMap W e b V i e w D A - T u ; Fisheye view Text/hypertext NetMap Perspective W a l l ; Document Lens TileBars InfoCrystal TileBars; InfoCrystal Visualization techniques and/or software applications are grouped in cells depending upon which data type they can represent and the corresponding analytical task they offer to users. Some visualization techniques like 'Perspective wal l ' or 'Cone trees' are suitable for only a specific data type and a specific analytic task and hence occur only in a single cell in the table, while other techniques like 'Colormaps', 'Scatter plots' are applicable to several data types or analytic tasks and hence appear in several cells. For clarity, each cell is divided into two sections: the top section lists names of specific software applications where appropriate, while the lower section contains the names of visualization techniques. A n interesting observation made by Qin et al. (2003) is that techniques for deeper analysis are much fewer than those for overview-query and comparison. 4.4 Applications of Visualization in Construction In carrying out the literature review on visualization techniques, the authors also undertook to identify the extent to which they have been applied to the field of construction, with the focus being primarily on the visualization of contruction management data as opposed to visualizing the physical artifact to be built for purposes of constructability reasoning or workability of the methods selected for its construction (e.g. Staub and Fischer 1998). Somewhat surprisingly, there is very little literature that addresses visualization of construction data, either using conventional representations or some of the more avant-garde techniques developed and advocated by computer scientists. Songer and Hays (2003) addressed the issue of managing project control data using Treemaps and other visual aids like scatterplots and histograms. They described an iterative process of structure-filter-communicate while considering level of detail, density, and efficiency of data representation. Russell and Udaipurwala (2000a) (2000b), (2002) used linear planning charts to help with assessing schedule quality and schedule updating strategies, 2-D and 3-D graphs to represent the distribution of resources in time and space, stacked 2-D graphs to assist with explaining activity performance to date as a function of site conditions encountered, and 3-D graphs to portray problems encountered in time and space and their consequences. 70 For the remainder of this paper, the authors treat two different phases of a project and participant viewpoints to illustrate the types of insights that can be achieved through data visualization. The thought processes described and accompanying images for these scenarios can be readily adapted to the exploration of other mangement functions and project data types. For the first combination, the authors examine the client's perspective on decision making as to the most suitable procurement mode and formulation of contractual terms. For the second, the authors examine the contractor's perspective on change order management during project execution, and possible impacts on project performance. The two examples given are illustrative of the kinds of situations often encountered on capital projects, and which can be missed because of a preoccupation with individual items as opposed to the collection of many items and related patterns of occurrence - i.e. there can be a failure to see the big picture. This in turn can lead to several undesirable situations, including an underestimation of consequences, failure to initiate corrective action in a timely way, delays, management burnout, loss of entitlement, and loss of reputation, to name a few. 4.5 Using Images to Model Environmental Risk Drivers The identification and management of risks arising from a project's environmental context is vital to project success. Failure to manage such risks can lead to adverse impacts on performance measures such as cost, duration, revenue, scope, safety and quality. In extreme circumstances, it can even lead to the termination of a project. One or more attributes of an environmental component (environmental view of a project) separately or in combination with the attributes a physical component (physical view of a project) and/or those of an activity or a group of activities (process view of a project) can act as risk drivers for a risk event, and the 71 likelihood of its occurrence and quantum of consequences can be dependent on whether or not they share the same site location and/or participant responsibility at the same time, as shown in Figure 4.1. The challenge becomes how to detect the confluence of these attributes. Environmental drivers contractual drivers Organizational / What Where When Physical drivers U—M Process drivers Risk Drivers Risk Events Figure 4.1 Risk drivers and events A projects' environmental context is comprised of the natural and man-made environments. Here the focus is on the natural environment. In most jurisdictions, the requirement exists to carry out an Environmental Impact Assessment (EIA) prior to undertaking a construction project, and a wide array of environmental components must be examined, as illustrated in the hierarchical environmental breakdown structure (EBS) depicted in figure 4.2(a). Each component of this structure can be described in terms of a number of attributes, and depending on the presence of these attributes and their value at a specific location, the potential for one or more risk events may result (figures 4.2(b) and 4.2(c)). Visualization techniques can be very helpful for comprehending the distribution of environmental risk drivers in time and space and assignment of responsibility for their management. The resulting images can be augmented by superimposing additional data in terms of the timing and placement of physical components and related construction activities, thereby assisting in the identification, quantification, mitigation and assignment of risks. Overviewed 72 : Standards £85 . ;&mdow .;;Hel i OL8E Environment Example Floating Bridge Project Environment ^ PH¥ Class Physical Environment 1 3-HYD Sub-dass Hydrography I ; & CREC Entity Creek I ( 1- MJLLC Sub-entity Mi creek i I BEARC Sub-entity Bear creek FENTC Sub-entity Penticton Creek • i-lAKE Entity Lake j i- OKNG 5ub-en«y Okanagan Lake H-TPGP Sub-dass topography Hi-GEO Sub-dass Geology Wi BOTN Sub-class Botany i BHA8T Sub-class Habitat j i-TRST Entity Terrestrial Habitat I ! S-AQTH Entity Aquatic Habitat row Sub-dass Zoology IS ATMP Sub-class Atmosphere ffl-aMT Sub-class Ctovatology iS-PLUT Sub-dass Pollution SCL Class Social Environment t-8 A80G Sub-class Aboriginal \M CMIF Sub-dass Community Life * MSET Sub-class Micro Social Factors S ACHT Sub-class Arctieotooicai and Historic Resources 3- ARCH Entity Archeology ECO Class Economic / Financial Environment POL Class Poftlcal Environment REG Class Regulatory Environment Attributes- Values | standard EBS Records j Risk Issues | Protect Records) Memo I Path OLBE;WY,HABTAQTH.-; • • OxfevJMILC Type p . . Oescrtfon (Mi Creek Hetwat '3 I Description s Ansa l l ' S ''Idnnccl AtlrihutL V J I U L * Inhered.:. l Ptamed.. i Plarirjed. Actual ' Actual Class B A R Unn YES NO YES NO NO Q YES NO YES NO NO B YES NO YES NO NO B YES NO YES NO NO B YES NO YES NO NO B (a) Ready.. Path: OLBE.PHY.HABT.AQTH. Attnbu*e:. Poten&al fot Habitat Lass Value Type: Boolean . Inned Values \ Eniei fictuaSValues Location Range ; Value 4Q+„45+ 40+^45+ True II3T (b) (c) Figure 4.2 (a) Environmental Breakdown Structure (EBS); (b) Environmental component attribute definitions; (c) Attribute value. here is current work by the authors directed at developing a detailed specification as to how best to represent various aspects of the environmental view of a project in visual form. Shown in figure 4.3 is an innovative 3 -D histogram that depicts the number of environmental risk drivers in time and space and by assigned responsibility. Each of its two horizontal axes represents respectively, the project location and time, both of which are treated as intervals instead of specific instances. The interval of these location and time could be reduced or increased as necessary. The vertical axis from the origin point of the three axes represents the number of total drivers while the other two vertical axes at the end of their respective horizontal axes represent the number of drivers by responsibility (e.g. owner, consultant, general contractor) integrated across time and space, respectively. 73 Figure 4.3 Distribution in time and space and by responsibility of environmental risk drivers One common issue in risk identification is the need to know how many risk drivers exist within a specific time interval and at a specific location. This information is readily available by examining each tower shaped column in a time/location cell. The number of organizational drivers for different project participants is represented using different colors, thereby capturing an additional dimension within the 3-D graphs. For example, focusing on the intersection of time T4 and location L 9 , reveals a tower shaped column with three colors: red for drivers managed by the owner, green for drivers managed by the consultant and blue for drivers managed by the general contractor (in fact for this example, a combination o f color and different shaped/sized icons is used). If precise information about these numbers is needed, they can be made to appear in a small information box as shown on the graph by briefly suspending the mouse on the 74 column of interest. A second issue of interest to users is the distribution of the total number of drivers according to time and location, with a further breakdown by project participant. This information is given on the two "side walls" of the graph. Distributions for the number of organizational drivers are shown in different colors while the distribution for total number of drivers is shown by the heavy black lines. For the case when many columns exist making it difficult to scrutinize the distribution information put to the side walls, a 3-D view control box is provided so that the graph can be rotated and the required information made completely visible. Users are interested in not only how many drivers exist in a specific time and location cell , but also the identity of these drivers and their attributes. To get this information, users should be able to click the hyperlinked text in the small information box being shown in figure 4.3. This wi l l result in a separate window popping up with a hierarchical structure for drivers visualized as shown in figure 4.4(a) using the Magic Eye V i e w technique (Kreuseler and Schumann 2002), a method by which all o f the hierarchical nodes are distributed on the surface of a hemisphere. For example, i f you click "Total: 33" in the box in figure 4.3, a hierarchical structure with total of 33 drivers w i l l pop up while i f you click "Owner: 9" a hierarchical structure with a total of 9 drivers for which the owner is responsible w i l l pop up. If the responsibility for a driver is shared amongst two or more project participants, the driver w i l l be included in the count for each organization but it w i l l only be counted once in terms of the total number of drivers for its corresponding time and locations interval. This hemispherical hierarchy could also be rotated so that nodes of special interest are focused on, as shown in figures 4.4(a) and 4.4(b). B y suspending the mouse on one of these nodes for a second, the attributes for that specific driver would pop up in a small information box giving attribute name, value, and location (e.g. 7 5 archeological site area within a section of a highway corridor or potential = degradation within a stream bed). ' T R U E ' for habitat Figure 4.4 (a) Hemispherical hierarchy; (b) Focused hemispherical hierarchy (From Kreuseler and Schumann 2002) 4.6 Applying Visualization Techniques for Change Order Management In this section, an example is provided of the kind of insights that data visualization can offer for the function of change-order management from the perspective of the general contractor or construction manager. Changes and change orders are an inevitable part of any construction project. They can have a significant effect on a project and its participants in terms of productivity, and overall project performance. Further, they can give rise to contentious disputes because of their cumulative impact on the efficient execution of other work, and the additional load placed on management staff. Various researchers (e.g. Hanna et al. 2004, Ibbs 1997, Thomas and Napolitan 1995) in the past have tried to quantify these impacts as well as the 76 properties of change orders that have the most adverse consequences for performance. Interestingly, however, the subject of change order management is seldom discussed in the literature. The focus in this paper is on demonstrating the value of visualization in helping to determine i f clustering of change orders is occurring in one or more of time and space or by project participant, which could in turn explain in whole or in part performance difficulties at different levels of the project (e.g. trade level, overall project level). This focus forms part of a larger ongoing research effort directed at a change order management view of a project and its relationship with other project views. A change order may be regarded as a separate information entity that can be tracked in an information system. It has a number of properties, including associations with components or information entities that define other project views. Some of these properties are specified by system users, others are derived by the system based on information provided (e.g. durations). A partial list of change order properties is provided in Table 4.2. A s indicated previously, rather than focus on the properties of an individual change order, here the authors show how data visualization can provide a 'b ig picture' o f what is happening to a project in the way of changes during its construction phase. A n implicit causal model underlying the images given is that the possible impact of change orders is likely to be highest i f they are clustered simultaneously in time, space and by project participant. In presenting these images, use has been made of an actual data set in terms of number of change orders (122), value, timing and location. Further, to ensure clarity of the image, coarse definitions of time and space have been used. Time is measured in months. In terms of monthly count of active COs, a C O is counted for as many months as it is active. In terms of its value, it is distributed uniformly over its duration. Locations have been aggregated into three: on site, off site, and both on and off site, 77 Table 4.2 Selected properties of a change order Change order (CO) property View Data type Source CO ID (identity) CO Mgmt alphanumeric User Date CO process initiated CO Mgmt date User Date CO approved (cancelled) CO Mgmt date User Duration of CO initiation/approval process CO Mgmt number Derived Reason for CO (client initiated, design error/omission, ...) CO Mgmt alphanumeric User Date CO work started As-built date User Date CO work completed As-built date User Duration of executing CO work As-built number Derived Number of consultants involved with CO CO Mgmt number Derived Identity of consultants involved (e.g. Architect, structural CO alphanumeric User engineer, ...) Mgmt Number of trades involved with CO CO Mgmt number Derived Identity of trades involved (e.g. GC, mechanical, electrical, ...) CO Mgmt alphanumeric User Basis for payment (lump sum, unit price, time & materials, ...) CO Mgmt alphanumeric User Base cost of CO and cost breakdown, exclusive of impact costs CO Mgmt numbers User Estimate of impact costs of CO if applicable CO Mgmt number User Physical component(s) of project affected by CO and locations Physical alphanumeric User Long lead time procurement items associated with CO Physical alphanumeric User Procurement item procurement sequence Process alphanumeric User Association with existing schedule activities Process alphanumeric User Number of existing activities affected Process number Derived Association with new activities as a consequence of CO Process alphanumeric User Number of new activities as a consequence of CO Process number Derived As-built problems associated with CO As-built alphanumeric User Identity of existing drawings revised due to CO Physical alphanumeric User Identity of new drawings due to CO Physical alphanumeric User Number of RFI's associated with CO As-built number Derived Identity of RFI's associated with CO As-built alphanumeric User with the reasoning being that offsite C O ' s would not contribute to productivity loss or congestion on site. From the viewpoint of developing visualization schema, it is observed that it is important to allow for different granularities in the definition of time (e.g. day, week, month), location (individual, group of locations, class of locations), project participants (individual, by group, by class - e.g. consultants, trades, suppliers), and so on. Figure 4.5 provides a visual representation of the change order history of a project in terms of C O identity ( a simple number in this case), the months in which it was executed, and the monthly expenditure in terms of base costs (no impact costs included). A l l the change orders executed during a month are mapped against one color to add clarity to the image. The resulting image demonstrates that most of the change orders are clustered in the latter stages of the project, although a significant share of the total value of C O work was performed earlier and was associated with just a few COs. 1 0 0 9 4 ) 4 • 104)4 0 114)4 • 1 2 - 0 4 0 0 1 - 0 5 « 0 2 4 ) 5 » 0 3 4 > 5 0 04-05 11054)5 1 0 0 6 4 ) 5 « 0 ? 4 ) 5 1350000 $ » , 0 0 B „ $250,000 m © <-> $200,000 _> $150,000 CD 3 $100 AGO $0 Figure 4.5 CO History in terms of CO ID, timing and value of the work Figure 4.6 provides a deeper insight into the project's set of COs and perhaps tells a more compelling story than figure 4.5. In this image, each project participant is mapped onto its own 79 colour. The participants are stacked over one another in a predefined order. In this case we have dealt with five participants in total, three on-site trades, Trade A , Trade B and Trade C, and two fabricators, namely Fab X and Fab Y . The vertical axis represents the number of COs active for a specific participant in a given month (a dollar value axis could also have been used). The COs have also been sorted according to their location along X-axis . This makes the available information easier to assimilate. A single cell in the horizontal plane of the graph yields the project participants involved, the number of COs active per participant, the active month and the location of the COs. For instance, the arrow in the figure indicates that in the month May-05, Trade B had 7 active 'On-site' COs. Figure 4.6 highlights one of the challenges involved in formulating visual images which maximize the clarity and visibility of the data represented. For larger datasets such as this, i f vertical columns had been used, the taller columns in the front of the image would obstruct the view of the bars in behind, thereby hiding much of the content of the image. To avoid this problem, we experimented with the use of cones and pyramids, and found the latter provided the most pleasing and useful image. For the visual images in figures 4.5 and 4.6 various C O attributes were mapped against colour and location in 3D space, thereby allowing significant insights to be derived form the C O data. However coupling the current images with interactive tools like 'zooming and filtering', 'details-on-demand windows' or setting 'dynamic query fields' would increase the scope for data analysis and provide deeper insights into the data. For example, clicking on a particular C O in figure 4.5 would pop up a 'detail-on-demand window' with C O properties selected from the list in table 4 .2 and contained in a user defined content profile. Figure 4.6 illustrates a very basic example of such a pop-up window displaying the trade name (Trade B) , the month of interest 80 and the Number of COs associated with the trade. Further, by introducing filtering techniques, users would have the flexibility to view only data of current interest: e.g a time window of September-04, 'Off-site' COs only, and work by Fab X only. Such selection and filtering capabilities help management pinpoint specific issues and help with decision making directed at resolving existing or emerging problems. 8 p ^ i j 2 S <p 2 8 8 ° 8 8 8 8? 8 Time (in Months) Figure 4.6 History of COs by location, time, responsibility and number 4.7 Discussion and Conclusions A number o f challenges exist when implementing visualization techniques to represent construction data. Two of them are described here. First, it is important to provide a number of visualization techniques for the same data. Different users have different preferences and capabilities for the visual format that yields the greatest insights or most information content. For 81 example, 2-D drawings are still preferred by most people working in industry, with growing interest in 3-D model being shown in a few organizations - thus both formats should be treated. These formats should also be supplemented by being able to view simultaneously more traditional formats, such as data tables. Additionally, impediments to using visual images such as color-blindness need to be considered, and compensated for by using different shapes to represent data components instead of just relying on colour coding. A second challenge is the loss of interaction when moving from the screen to hard copy form. A s stated previously, interaction is a vital tool for exploring efficiently large data sets on screen using different formats, viewing angles, and so on. Effectively, the screen interactive mode should be used to explore the data in order to determine its information content and then determine which format (2-D, 3-D, colour, scaling, rotation, etc) portrays the information context most clearly. It is this image that should then be produced in hard copy format. Unfortunately, some of the benefits of data visualization are lost when moving from interactive to hard copy mode. In conclusion, a brief overview of the current state-of-the-art of data visualization techniques and several of the advantages of data visualization that relate to the perceptive as opposed to cognitive processes of humans is provided. Two distinctly different decision/reasoning contexts illustrated the value that data visualization techniques offer in terms of extracting information from the large data sets that characterize construction projects. B y combining such techniques with a holistic representation of a project and related data, the potential exists to develop a potent tool for assisting construction management personnel and other project participants improve their decision making and their understanding of the reasons for project performance to date. In the near term, the authors w i l l be focusing on developing a number of causal models or hypotheses for explaining construction performance (e.g. 82 productivity, delays) and how aspects of these models can be represented in one or more visual images to assist in determining the validity of the hypothesis put forward about performance levels achieved. Further images relevant to other management functions as they relate to quality and risk management wi l l also be explored. The most promising of these w i l l be fully implemented and field-tested on actual projects. 4.8 Acknowledgement The authors would like to express their appreciation for the financial support provided by N S E R C Strategic Grant S T P G P 257798-02, and a British Columbia Ministry of Transportation Grant-in-Aid. 4.9 Bibliography Ahlberg, C. and Shneiderman, B . (1993). "Visual information seeking: Tight coupling of dynamic query filters with starfield displays." Human Factors in Computing Systems, Conference Proc. CHI '94 , 313-317. Brautigam, M . (1996). "Applying information visualization techniques to web navigation." Thesis proposal, U C Santa Cruz, U S A . Geisler, G . (1998). "Making information more accessible: a survey of information visualization applications and techniques." http://www.ils.unc.edu/~geisg/info/infovis/paper.html. (03 Feb., 2005) Hanna, A . ; Camlic, R.; Peterson, P.; and Lee, M . (2004). "Cumulative effect of project changes for electrical and mechanical construction." J. of Const. Engrg. & Mgmt., 130(6), 762-771. 83 Ibbs, W . (1997). "Quantitative impacts of project change: size issues." J. of Const. Engrg. & M g m t , 123(3), 308-311. Kreuseler, M . , and Schumann, H . (2002). " A flexible approach for visual data mining." I E E E Transactions on Visualization and Computer Graphics, Institute of Electrical and Electronics Engineers Computer Society, 8(1): 39-51. Qin, C ; Zhou, C ; and Pei, T. (2003). "Taxonomy of visualization techniques and systems -Concerns between users and developers are different." The State Key Lab of Resources and Environmental Information System, Institute of Geographic Science and Resources Research, Chinese Academy of Sciences, Beijing, China, http://www.hku.hk/cupem/ asiagis/fall03/Full_Paper/Qin_Chengzhi.pdf (03 Feb. 03, 2005). Russell, A . and Udaipurwala, A . (2004). "Using multiple views to model construction." C IB World Building Congress 2004, Toronto, Canada. 11 pages. Russell, A . and Udaipurwala, A . (2002). "Construction schedule visualization." Proc. of the International Workshop on Information Technology in C i v i l Engrg., 2002, Washington D . C . , U S A , 167-178. Russell, A . and Udaipurwala, A . (2000b). "Visual representation of project planning and control data." Proc. of the 8th International Conference ( ICCCBE-VII I ) , Stanford University, U S A , (1): 542-549. Russell, A . and Udaipurwala, A . (2000a). "Assessing the quality of a construction schedule." Proc. of A S C E Construction Congress V I , 2000, Orlando, Florida, U S A , 928-937. Shneiderman, B . (1994). "Dynamic queries for visual information seeking." I E E E Software, 11(6): 70-77. 84 Shneiderman, B . (1996). "The eyes have it: a task by data type taxonomy for information visualization." Proc. of the I E E E Symposium on Visual Languages, 1996, Los Alamitos, U S A , 336-343. Songer, A . and Hays, B . (2003). " A framework for multi-dimensional visualization of project control data." Construction Research Congress 2003, Honolulu, Hawaii, U S A , 121-130. Staub, S. and Fischer, M . (1998). "Constructability reasoning based on a 4D facility model." Structural Engineering World Wide, T191-1 (CD R O M Proceedings), Elsevier Science Ltd. Thomas, R. and Napolitan, C. (1995). "Quantitative effects of construction changes on labor productivity." J. o f Const. Engrg. & Mgmt., 121(3), 290-296. Tufte, E . (1990). "Envisioning information." Graphics press, Cheshire, Connecticut, U S A . 85 Chapter 5 Environment Modeling for Risk Management in Construction Projects* 5.1 Introduction The worldwide boom of c iv i l engineering projects arises, in part, from a huge demand for new and upgraded public infrastructure while at the same time increasing the pressure for funds from already overextended government budgets. Procurement modes, such as Public-Private Partnerships (P3's) which seek to maximize involvement of the private sector, are being adopted more and more by governments around the world to reduce their allocation of funds to such projects, while providing infrastructure to the public in a timely way. Risk management plays an important role at the procurement mode decision making phase (e.g., traditional delivery vs. P3) for the reason that both the public and private sectors need to explicitly identify the complete spectrum of project risks and which project party is best suited to manage individual risks, so that they can be allocated in a way that maximizes value-for-money. Both the natural and man-made environments, in which a project w i l l be designed, constructed and operated are significant sources of risk. Risk events can impact project * This chapter is a draft manuscript prepared for submission to a journal. The authorship is: Yugu i Wang, M A S c student and Graduate Research Assistant, Department o f C i v i l Engineering, University o f Bri t ish Columbia , yugui_wang@hotmail.com, and Alan D . Russell , Professor and Chair, Computer Integrated Design and Construction, Department o f C i v i l Engineering, University o f Brit ish Columbia , adr@civil .ubc.ca. 86 performance (cost, time, quality, scope, revenue and safety) either directly or indirectly. For example, a natural hazard such as a landslide or an unexpected contaminated underground condition can directly extend project duration and increase project cost, while a change in government regulations during the course of a project may require project participants to follow a more stringent environmental policy and conduct more costly mitigation measures, thereby impacting project performance. A project's context can be usefully described in terms of nine dimensions or views: physical, process, organizational/contractual, cost, quality, as-built, change management, environmental, and risk (Russell and Udaipurwala 2004). O f particular interest at the outset of a project for risk management are the following four views: the environmental view which treats the natural and man-made environments in which the project w i l l be executed; the physical view which treats what w i l l be built; the process view which describes how the project w i l l be procured and constructed; and, the organizational/contractual view which states who is responsible for what. One or more attributes of an environmental view component, separately or in combination with the attributes of a physical view component, and/or those of an activity or a group of activities from the process view can act as risk drivers for a risk event, and the likelihood of its occurrence and quantum of its consequences can be dependent on whether or not they share the same site location and/or participant responsibility in the same time frame, as shown in Figure 5.1. In this paper, a flexible, computer-based approach for modeling a project's environment and which supports knowledge management and various project management functions, with emphasis on risk identification and management is described. The approach is applicable to any and all project types. The paper is organized as follows. A review of past classification and modeling approaches for describing a project's environment is presented in section 5.2 along 87 Environmental drivers Organizational / contractual drivers H i ^ r Physical drivers Process drivers Risk Drivers Risk Events Figure 5.1 Risk drivers and events with the features desired of a comprehensive, computer-based representation schema for modeling a project's environment and interfacing it with a range of project management functions. This is followed in section 5.3 by an overview description of the system architecture adopted for modeling a project's environment, with emphasis placed on the environmental and risk views of a project, how they are integrated, and on the role knowledge management can play in populating these views. Also treated are the modeling constructs used within the environmental view. Contents of a master environmental breakdown structure (EBS) are then presented in section 5.4. The authors believe these contents, which have been gleaned from a number of sources to be an important contribution of the paper. Two case studies are then presented in section 5.5 to demonstrate application of the system architecture and supporting prototype system to full scale projects. A reality that accompanies the modeling of actual projects is the potentially massive scale of the data sets required for their representation. H o w insights can be derived from such data sets through data visualization strategies is briefly described in section 5.6. Finally, section 5.7 treats conclusions of the paper. 88 5.2 Current Approaches for Representation of a Project's Environment Carpenter (2001) defined the environment as surroundings and their characteristics which affect human and other life forms that exist within these surroundings. He stated that the environment represents both the existence of resources (human and natural) and their easily degraded quality. From the perspective of project management, we consider a project's environment as its surroundings and their characteristics which, at any phase of a project's life cycle, affect its performance within these surroundings. We use the notion of an environmental view of a project as the mechanism for capturing and representing a project's environmental context. A n environmental impact assessment (EIA) or similar study is the approach routinely used and indeed required for most c iv i l engineering projects in order to consider the .interaction between a project and its environment. Legislated guidelines determine the scope of such a study which mostly relates to natural environmental components, economic conditions, social and health components, and cultural and heritage components (Canadian Environmental Assessment Agency 2003). A hierarchical structure is frequently applied to certain E I A studies as the method to model a project's environment and as a means for structuring the E I A report. Use has been made herein of E I A reports for three.projects, two from British Columbia, Canada and one from Europe to illustrate how a project's environment is modeled in industry, as shown in table 5.1. Project 1 corresponds to the Sea to Sky highway improvement project in British Columbia, Canada ( E A O 2004a). This project involves widening and straightening a 94.7 km section of highway in a mountainous and environmentally sensitive area. Other details for this project are provided in the case studies section of this paper. Project 2 in table 5.1 is the New Fraser River 89 Crossing project in British Columbia, Canada ( E A O 2004b). This project entails approximately 13.4 kilometers of new roadway including the construction of a new six-lane tolled bridge crossing the Fraser River. Project 3 is the 0resund Fixed Link project (0resundskonsortiet 2000) between the Swedish and Danish coasts. It is a combined railway and motorway of length 16.4 km consisting of an immersed tunnel, two approach bridges and a high bridge. Handbooks issued by individual industrial organizations are another source for how to model the environment. These handbooks (e.g. N Y D O T 2001; Tszmokawa and Hoban 1997; and A D B 2002) apply somewhat similar classification schemes as shown in table 5.1, but without great consistency. It is observed from table 5.1 that although many environmental components, such as fish and noise, are common across different projects, in terms of the classification schema and the semantics used to describe the environment for individual projects, there are notable differences! We observe that most environmental descriptions used in practice adopt a three-level hierarchical structure, with the very odd exception being up to a maximum of five levels. It is also noted that risks that arise from the environmental components are normally hidden among voluminous documents, and are not easy to identify and assess. Typically, environmental issues are separated from risk analysis. Limited work appears to have been done by academics on project environment modeling. Among the works identified, five of them were found to be directly relevant. They are listed in table 5.2. Week's (1977) schema was developed for the environmental impact of transportation projects and represents some of the earliest work found. The schema of Wilson and Stonehouse (1983) was applied to highway location selection considering environmental impact. Hughes (1989), in recognizing that building projects can be seen as a response to the environment 9 0 Table 5.1 Environment modeling in EIA reports for three projects Project 1 Project 2 Project 3 1. Land requirements 1. Environmental effects 1. Hydrography 2. First Nations interest 1.1 Fisheries & aquatic 2. Dredging and reclamation 3. Archeological effects resources 3. Sediment spreading and 4. Environmental effects 1.2 Wildlife & vegetation sedimentation 4.1 Water quality 1.3 Contaminated site 4. Water quality 4.2 Fisheries & aquatic 2. Economic, social, heritage and 4.1 Heavy metals & toxic resources health effects substances 4.3 Wildlife & vegetation 2.1 Agricultural resources 4.2 Waste water & hygienic 4.4 Geochemical 2.2 Community and Socio- water quality 4.5 Contaminated site economic effects 4.3 Release of nutrients 4.6 Air quality 2.2.1 Neighborhoods 4.4 Oxygen 5. Socio-Economic effects 2.2.2 Transportation 5. Benthic vegetation 5.1 Project design issues 2.2.3 Construction 5.1 Eelgrass 5.2 Transportation demand 2.2.4 Navigation 5.2 Ruppia 5.3 Noise 2.3 Air quality and health 5.3 Macro algae 5.4 Emergency services - 2.4 Noise 6. Benthic fauna 5.5 Recreation 2.5 Archeological resources 6.1 Common mussels 5.6 Aesthetics 3. First Nations Interests 6.2 Others 5.7 Economic 3.1 Fishing 7. Fish 5.8 Land use impacts 3.2 Hunting 7.1 Spawning and nursery 6. Navigation 3.3 Gathering grounds 7. Permits, licenses, 3.4 Cultural heritage sites 7.2 Migratory routes & authorizations 3.5 Privacy distribution 3.6 Noise 8. Birds 3.7 Air quality & health 8.1 Breeding eiders 3.8 Other community effects 8.2 Moulting greylag geese 4. Permits, licenses, authorizations 8.3 Moulting mute swans 8.4 Other breeding species 8.5 Staging migrants 9. Mammals 9.1 Seals 9.2 Movement of foxes, cats and rats 10. Beach and coast 10.1 Coastal morphology 10.2 Beach & bathing water quality 11. External environment 11.1 Noise 11.2 Industrial & sanitary water 11.3 Fuel 11.4 Waste & residual products 11.5 Transportation 11.6 Groundwater 91 identified 11 types of environmental factors. He proposed that the environment should be defined in a structured way and that the list o f criteria should be examined to ensure that any observable environmental phenomena may be classified into one or more generic groups o f environmental forces. Marmoush (1999) focused on establishing an environmental classification schema for coastal development limiting its usefulness for a broad range of project types. Underhill and Angold (2000) looked at representing a project's environment from a specific perspective of how roads w i l l impact wildlife. Environmental components for the corresponding column in table 5.2 appear, to be much different from those in other columns for this reason. However, it provides useful information as to what environmental components should be considered from this viewpoint. In all o f the literature surveyed, minimal emphasis was placed on how representation of the environment could be assisted by computer-based approaches, or on the interface between a model of the environment and project management functions. Nevertheless, existing classification schemas provide a backdrop for more generalized modeling of a project's environment. The hierarchical structures used by others and the components identified are helpful for characterizing the environmental context of a project. Based on our work on modeling a project's environment and participation in risk identification processes for actual projects, we believe that a comprehensive, computer-based representation schema for a project's environment should have the following characteristics: 1) It should be a generic modeling structure that can be applied to most project types. A s described previously, most environment modeling schemas proposed to date are for a specific type of project, such as a highway or coastal development project. Table 5.2 Approaches to environment modeling from the academic literature Week, T . (1977) Wilson, F. and Stonehouse, D. (1983) Hughes, W. (1989) Marmoush, Y. (1999) Underhill, J. & Angold, P. (2000) Economic environment Physical environment Cultural Physiography Pollution Biological environment Water regime Economic Geomorphology Foreign material Plant & animal diseases Erodibility Political Sedimentology Dust Human disease Woodlands Social Hydrography De-icing salt Aquatic ecology Unique ecological areas Physical Tides Exhaust output Terrestrial ecology Wildlife Aesthetic Current Hydrology Social environment Agriculture Financial Waves Runoff pollution Community & tribal Social environment Legal Sediment transport Stream flow change structure Development Institutional Water quality Disturbance effects Cultural resources Noise Technological Pollution source Gust of wind Synthesis o f environmental Utilities Policy Pollution ambient levels Human access impact Recreation Marine ecology Noise Unique cultural features Phytoplankton Physical barriers to the Aesthetic scenic areas Zooplankton movement o f animal Seaweed species Benthic micro fauna Ecological habitat & Intertidal macro fauna corridors Fish Shrimp Bird fauna For transportation project For highway location selection For building project For coastal development project For road network 93 2) It should be comprised of a range of environmental component types so as to ensure that any observable environmental phenomena can be classified into one or more generic groups. 3) The modeling schema should assist with the management of environmental risks, and provide support for different stages of risk management including the tracking of risks throughout the project life cycle. Current approaches to modeling a project's environment see risk management as a separate function and seldom consider changes in the environment and related environmental risks throughout the project life cycle. 4) The approach used for modeling the environment should integrate with the physical, process and organizational views of a project and to the extent possible, use consistent modeling constructs across all of these views. Attributes of environmental components can act as risk drivers in concert with attributes of physical and process components because they share one or more of the same physical location, the same project participants or the same time interval. Only by integrating these views, can the full range of environmental risks be thoroughly identified. A s well , integration of the environmental view with other project views assists with other management functions, including planning and scheduling, change management, and explaining reasons for performance to date. 5) The modeling approach adopted should allow users to define attributes and assign attribute values for each environmental component, thus assisting with a comprehensive understanding of a project's environmental profile and the integration of a project's environmental, physical, process and organizational views for risk management. Provision should also be made for treating other information relevant to the project's environment, including links to multi-media information that portrays various aspects of the environment (e.g. digital photographs), environmental regulations, etc. 6) Knowledge management should form an integral part of the approach adopted. Thus, reuse of environmental knowledge gained in past projects for new ones should be facilitated. Two important objectives of knowledge management are to assist with the development of a standard and consistent vocabulary, so that knowledge is transferable both amongst projects and within the organization, and to ease the burden associated with developing an initial description of a project's environment. 7) The knowledge management feature should be sufficiently flexible that help can be offered to users i f it is wanted, but users should be allowed to define a model of the environment as they see fit i f help is not required or wanted. 8) The ability to visualize environmental data should be treated to help deal with the large volume of data involved and to assist decision makers in generating insights into the environmental features of a project, including related risks. 9) Extensive screen and hard copy reporting capabilities, including the ability to track changes in time should be an essential part of the approach adopted. The schemas reviewed in the literature seldom reflect even a subset of the foregoing requirements, and none embodied all o f these requirements. We have sought to address all o f them in terms of a system architecture and a corresponding prototype system that is capable of treating full-scale projects in order to demonstrate the usefulness and practicality of the approach adopted. 95 5.3 System Architecture for Modeling Project Environment Figure 5.2 depicts part of the system architecture in schematic form developed for representing the environmental and risk views of a project in support of an array of project management functions (see DeZoysa et al. 2005 for more details). These views in turn link with other project views, including the physical, process and organizational/contractual views of a project to create a holistic and integrated representation of a project. Features of note include the following. There are two 'sides' to the system - the Project Side where an instance of each project view resides for the project at hand. The second side, formally called the Standards Side, is where user-defined knowledge or standards is stored (i.e. the knowledge management side of the system). On the Project Side, the model used for describing the project environmental view, called the Environmental Breakdown Structure (EBS), takes the form of a hierarchical model as described later, while the model used for describing the project risk view, called the Project Risk Register (PRR), also takes the form of a hierarchical model. Parallel constructs reside on the Standards Side of the system in terms of a Standard E B S which is a library of user defined templates and a Standard Risk Issue Register (SRR) which also consists of a library of risk issue templates. Direct access to both sets of templates allows users to capture knowledge for future use, and for importing this knowledge for creating the E B S and P R R for a new project on the Project Side of the system. Various modes of use are facilitated, from direct definition of E B S and P R R structures with no reference to any standards (Mode 1), copying of standards structures to the project side to generate a starting point for defining the environmental and risk views of a project (Mode 2), and lastly, some intelligence to allow the partial automation of the identification of potential risk issues as a function of the environmental features for the project of 96 interest. In the remainder of this section, we focus on the constructs used to model the environmental view, both on the project and standards side of the system. To accommodate the characteristics desired of a comprehensive approach to modeling of the environment and linkage with the risk management function, as already observed, use is made of a hierarchical modeling structure. This is consistent with actual practice and provides flexibility in the level o f detail with which the environment can be represented. For example, at the early decision making phase of a project when broad project parameters are being examined, a detailed description of the environment is not likely to be available and thus only a coarse representation of its main features is possible. A s the project unfolds, and more and more detailed environmental information becomes available, the hierarchical representation of the environment can be readily expanded. A s noted previously, in the academic literature and in industry practice as well , a three-level hierarchy is typically applied. In our approach, up to a five-level hierarchy structure termed the Environmental Breakdown Structure (EBS) has been used. A maximum of five levels is allowed to help ensure visibility of the model structure for purposes of group discussion and decision making, and for ease of navigation. Standard Risk Issue Register • • B - g -Xi m CTQ ft) 1= , o T O ; -CD Mode 2, Association Standards Side Project Side Standard E B S Cu CD Mode 3. Condition P. td * so b £*! X) CD a-era fD Project Risk Register ode 1. Association Project E B S Figure 5.2 Schematic of partial system architecture linking environmental and risk views of a project with supporting knowledge management features 97 The five component types that correspond to the five levels that comprise the E B S hierarchy are: Environment: The global environment of the project under which all other components can be defined and described. This is the root node. Class: The main classes of the environment, by which various dimensions of the project environment can be grouped or classified (e.g. physical, social, economic/financial, political and regulatory environment). Definition of the classes is left to the model users, although a specific class structure is suggested on the knowledge management side. Sub-class: A subset of environmental components within a class, such as geological components within the physical environment class, and macro economic factors within the financial/economic class. Entity: A n environmental component that can be identified distinctly from other components - e.g., inflation, archaeological resource, fish. Sub-entity: In some cases it might be necessary to characterize the environment in more detail. For example, a composite inflation rate is made up of labor rates, material rates, etc., while birds may be made up of individual species such as trumpeter swan and gull. Environmental components located within the E B S can be further described in terms of user defined attributes and their values at specific project locations, thus allowing the properties of a component to be described in a comprehensive manner and in a way which helps with a number of project management functions. For example, from a risk management perspective, risk issues that are driven by an environmental component are in most instances dependent upon one or more of the component's attribute values and not simply on the presence of the component itself. For example, bird species within the project boundary that are classified as endangered (e.g. 98 attribute value T R U E for attribute definition endangered? at project locations x, y, z) could lead to uncertainties in project duration as bird nests encountered during construction would have to be relocated prior to the continuation of construction. Three types of attribute value, Quantitative (Q),, Linguistic (L) and Boolean (B) values are provided to accommodate the variety of characteristics that may be used to describe environmental components. Use of a hierarchical structure facilitates inheritance of attributes and aggregation of attribute values allowing the speedy setup of an environmental model and ensuring consistency and adherence to standard terminology in defining the properties of components. In addition to defining the attributes of a component, allowance has also been made for associations to be made between E B S components and various types of project records and documents (e.g. photos, meeting minutes, regulations) as well as with the risk management function. The intersection of environmental components with other project components (e.g. organizational/contractual, physical and/or process) at the same location can heighten the relevance of a risk issue for the project. For the system prototype developed, the set of location constructs is defined in the physical view modeling structure and associated with the physical, process and environmental views in order to ensure complete integration of the various views. On the project side of the system, components of the E B S structure are associated with project locations by way of assigning values for component attributes that are relevant to each project location. 5.4 A Model of the Project Environment Although the system architecture allows users to adopt any classification schema to model environment as they see fit, a single and consistent classification is believed to be critical to 99 ensuring the portability of information at the very least between projects of similar type. This is achieved by allowing the user to develop a series of templates on the standards or knowledge management side of the system. Preferably, a master E B S template is first constructed (see figure 5.3), from which subsets of the master are extracted for projects of specific types such as highway, bridge, tunnel, rapid transit, airport runway and water supply projects (see the left hand side of figure 5.3). Here we discuss the contents of a master E B S compiled from an extensive examination of the literature, government regulations, handbooks and environmental assessment statements of actual projects. The first level of Standard Infrastructure Project E B S is the global environment. It is then classified into five classes as shown in figure 5.3. They are physical, social, economical/financial, political and regulatory environments. The physical environment corresponds to the natural environment in which the project is located, and it is represented using the eleven sub-classes shown in figure 5.3. The collection of entities suggested for each of these sub-classes is shown in figure 5.4 - they capture the majority, i f not all , of the natural environmental components that can accompany an infrastructure project. A s this representation is soft coded, it can be enriched and modified as desired. The social environment represents the environment created by social requirements and social activities (e.g. aesthetics and community life). A s populated, it consists of the seven categories shown in figure 5.3. The financial/economic environment represents the local and national economic and financial conditions that surround the project and which have an impact on both the front-end decision making and execution phases of a project, respectively. This class is further broken down into eleven sub-classes. The political environment represents the political atmosphere in which the project is located. Political factors can be a significant risk source for a c iv i l engineering project, 100 R I P C O N b .30 -L : \ IH f .S ISWORKVOKANAGANLAKI . I3Ri r jGL \Mf .KGI . [ )PHOJ[ .C File Project_View _ Standards Standard £8$ Window Help 3 X Template Tree Structure Description Standard Infrastructure Project EBS Standard Highway Project EBS _ Standard Bridge Project EBS Standard Tunnel Project EBS Standard Rapid Transit Project EBS t~l- ROOT Environment Standard Infrastructure Project EBS El-PHY Class Physical Environment i •' Standard Airport Runway Project EBS \ S WD Sub-class Hydrography Standard Water Supply Project EBS I ErTPGP Sub-class Topography iSlii&ndatd Infrastructure Project EBS | t GEO Sub-class Geology ) (fj-BOTN Sub-class Botany ' \ ijr HABT Sub-class Habitat | l*!"ZOLG Sub-class Zoology j i -LWOG Sub-class Lower Organisms \ © ATMP Sub-class Atmosphere | lii-CLMT Sub-class Climatology ) Ifl-DESE Sub-class Disease Control i IB-PLUT Sub-class Pollution B SCI Class Social Environment i E-ABOG Sub-class Aboriginal . ' ! B-CMLF Sub-class Community Life \ il-UBEV Sub-class Urban Environment ! ShMSFT Sub-class Micro Social Factors • "I \ ill-OHMS Sub-class Other Human Settlements I • El-ACHT Sub-class Archeological and Historic Resourct \ EB-'ASTH Sub-class Aesthetics S ECO Class Economic / Financial Environment i SI- ECID Sub-class Economic Indicators 1 i -MECN Sub-class Macro Economic ; ' j $ - MRSC Sub-class Market Resources I G3-FNAC Sub-class Finance j $-MKP.T Sub-class Market Potential i SI- AGRC Sub-class Agriculture j fil- FRST Sub-class Poresty I i i - TRSM Sub-class Tourism 1 S-COMC Sub-class Commerce j i - R S C S Sub-class Resources 1 Itl-CLAM Sub-class Claims _ , : !+:•• POL Class Political Environment + REG Class Regulatory Environment v < .1 . > Ready , Figure 5.3 Standard EBS-Class and sub-class level especially when a P3 procurement mode is adopted. For example, a change in government which can happen overnight as the result of an election might make some projects die. The political environment can be further classified into the following five sub-classes: government, military, anarchy, government authority and legal policy. The regulatory environment represents the 101 kll'CON >j jl) I MIIISISWOKKUIKANAGANI FileProjectView Window Help-Standards Standard EBS FJe Project_View Standard IBS Wjndow' _ a x K I Holshi|4 Help File Projertjfew _ Standards Standard EBS Window h i ! * Tree Structure Standard Infrastructure Project EBS a-ROOT -PHY Environment Standard Infrastructure Project EBS Class Physical Environment HYD' Sub-class Hydrography j - DRNA Entty Drainage Systems CREK Entity Creek i- STRE Entty Stream RIVE Entity River {-WELL Entity Well ')•••• RSER Entity Reserviors LAKE Entity Late LAGN Entity Lagoon i-SEA Entity Sea 1CFD Entity Icefield i-GRWA Entity Groundwater L RUOF Entity Runoff Water TPGP Sub-class Topography L- MOTN Entity Mountain HILL Entity HII PLAN Entity Plain j ESTR Entity Estuary SHAL Entity Shallow i CANY Entity Canyon PAIR Entty Pasture l-WTLD Entity Wetland j "SAVN Entity Savanna SCRU Entity Scrubland FRST Entity Forest j— TAND Entity Tundra DSET Entty Desert j-SESO Entity Seashore j BAY Entity Bay GULF Entity Gulf SRAT Entity Strait CH- GEO Sub-class Geology Tree Structure _ _ •• Standard Infrastructure Project EBS L-J GEO Sub-class Geology j I- SOIL Entty Soil i \ ESO Entity Inland Sand j CSAD Entity Coastal Sand j j ROCK Entity Rock I CORF Entity Coral Reef j SDMT Entity SerjimenUoad \ I D8SF Entity Debris Ftow ! GPMO Entty Ground Movement j i - S E S W C Entty Seismic Zone j ' VLCN Entity Volcanic Active Place Q - B O T N Sub-class Botany j TREE Entity Trees SHRB Entity Shrubs j 5 OWS Entity Grasses j f-FERN Entty Fern \ f—EMS. Entity Emblement AQ!C Entity Aquatic Plants j VGTD Entity Vegetation Debris $ HABT Sub-class Habitat ] TRST Entity Terrestrial Habitat \~ AQTH Entity Aquatic Habitat MCHT Ertity Marine and Coastal Habtat f '-MSRZ Emty Migration Zone fi-ZOLG Sub-class Zoology (a) Tree Structure Standard Infrastructure Project E B S tei ATMP Sub-class Atmosphere i -AMPB Entity Amphibia ; RPTL Entty Reptilia j MAM. Entity Mammalia AVES Entity Aves ;'• • ITSY Entity Ichthyology IVTB Entity Invertebrate LWOG Sub-class Lower Organisms i BCTR Entity Bacteria FUG! Entty Fungai ATMP Sub-class Atmosphere (b) < Ready NUM < Ready.?: AQUT Entity Lower Air Layer • UAOL Entity Upper Air Ozone Layer CLMT Sub-class Climatology i -GUTW Entty Gust of Wind j-TONO Entity Tornado l-TPON Entty Typhoon HRCM Entity Hurricane l-FOS Entity Fog FRST Entity Frost 5NFL Entity Snowfall f-STORM Entty Storms i-AVLC Entity Snow Avalanche h-RNa Entity Rainfal i FOOD Entty Flood l-TUNM Entity Tsunami DROT Entity Drought FRE1 Entity Severity of Freezing THAW Entty Thawing Cycles I-TEMP Entity Temperature i - H U M D Entity Relative Humidity ATPS Entity Atmospheric Pressure (c) iNUM < Ready S DESE Sirb-class Disease Control j~6TNC Entity Botanical Disease ZOIC Entity Zoic Disease fe 1 -HUMN Entty Human Disease | e-PLUT Sub-class Polution | PAGM Entty Potentially Acid Generating (PAG) Material *' i • ML - Entty Metal Leachate (ML). : CNTM Entity Toxic Contaminated Site i SLWT Entty SoW Toxic Waste r-LQWT Entity Liquid waste drscharges and sewages ] BIWT Entity BtoUc Waste i DPLF Entity Dumping and Larrfiings - SCL Class Social Environment & :Us2ih\. Ifllil J^SM^W^SSSSd if' i" NUM , Figure 5.4 Standard EBS- Entity level components of physical environment 102 regulatory regime under which the project w i l l be designed, built and operated. In total, 165 components at the entity level of the Standard Infrastructure Project E B S have been identified to date as being relevant to infrastructure projects (see Wang 2005). Wang (2005) has also identified important attributes for each of these 165 entity level components, many of which are helpful for environmental risk management. Attribute definitions for three components, habitat, creek and archeology are illustrated here as examples. Five attributes have been defined for the habitat sub-class component, independent of habitat type, as shown in figure 5.5(a). For example, area is a quantity attribute defining the area of the habitat. The other attributes for habitat component are four Boolean attributes which describe the potential for habitat loss, habitat degradation, habitat fragmentation and the potential for bio-structure change of habitat. If the value for one of these four Boolean attributes is T R U E for a specific location of a project, the potential exists for a risk event to be realized, which could take the form of a requirement to take unplanned special precautions in order to comply with government regulations to protect the habitat. These attributes for habitat can be inherited to the entity components which are one layer below the habitat component, such as the terrestrial habitat as shown in figure 5.5 (b) (see figure 5.4 (b) for the four habitat entities listed under the habitat sub-class component). The use of inheritance facilitates consistency in the definition of attributes as well as the speedy development of the environment model. Users can either inherit attributes from the next highest level in the hierarchy or add new attributes at the same level as necessary. A s shown in figure 5.5(b), attribute "major wildlife species of the habitat" is defined at the "terrestrial habitat" level while the other attributes are inherited from the "habitat" level. A creek is a very environmentally sensitive component as it has implications for habitat, pollution and many other issues which can be a source of project risks. Thirteen attributes have been identified as being 103 relevant to characterizing the creek component as shown in table 5.3. Attribute values and their seasonal variation, when they apply, can have significant consequences for construction method selection and project planning. Ignoring one or more of these attributes can lead to the realization of a risk event, such as wash out of bridge abutment forms during the construction phase. Other attributes of a creek component deal with the chemical aspect which might be a risk source for pollution. Four attributes are defined for the archeology component as shown in table 5.3: the name of the resource, the area of the resource, the current status of the resource (Is it destroyed or partially destroyed?) and the era when the resource was created. These attributes define the value of the resource and how it can impact the project such as the intersection of potential archeological areas with project locations. Also shown in figure 5.5 are other properties that can be associated with a standard environmental component in the form of Standard E B S Records (photographs, sketches, regulations) and links with risk issues identified in the Standard Risk Issue Register that apply for usage modes 2 and 3 shown in figure 5.2. SiS3ffli2 Aitubutes | Standard EBS Records | Risk Issues | Memo I Template: Slarefatd Master Highway Protect ESS. ••• PathROOT.PHY. Code; |HABT Ijrpe [ ~~ Attribute Descrpoort [Habitat Desarptorv Potential l a HaWat Loss Potential for Habitat Degradation Potential for Habitat to be Fragmentated Potential for fib-Structure Change Inherited Attribute-jiCldai. HB/Q/L 3 Uj NO Q NO e NO 8 NO 8 NO 8 (a) inherit attnbuie definition from above level Add Alrtuies |siandard£BSRscoids| Risk Issues |:Man>| Template: Standard Mastei Highway Proiec-t EBS, Path. ROOT PHY HAST Code: jTRST . Descnptai Terrestrial HaMat •AttoMe-Description .-IrheotedAttakte. i Class JAM.. Ur« Area YES Q sgm Potential for Habitat Loss YES B Potential to Habitat Degradation YES S Potential to HaHat to be Fragmetttted YES B Potential to Bio-Structure Charrjp YES 8 iMajcf Wrte'SjecS'i'the Hattat] NO L (b) iV :lnherrt attribute detrton fan above level • Add Delete i Eda OK Cancel Figure 5.5 Attributes for Habitat and Terrestrial Habitat component 1 0 4 Table 5.3 Attribute definition of environmental components Components Attributes Type Definition Creek 1. Name of the waterbody L The name of creek. 2. Seasonal B Whether the creek is seasonal. 3. P H value Q The P H value of water in the creek. 4. The highest temperature Q The highest temperature of the water in the creek. 5. The lowest temperature Q The lowest temperature o f the water in the creek. 6. Suspended solids L A list o f suspended solids. 7. Dissolved organic L A list of dissolved organic compound. compound 8. Dissolved mineral L A list of dissolved mineral. 9. Cross section shape L The cross section shape of the creek. 10. Cross section area Q The cross section area of the creek. 1.1. Water table level Q The water table level of the creek. 12. Water depth Q The water depth in the creek. 13. Velocity Q The water velocity in the creek. Archeology 1. Resource name L What's the name of this resource? Site 2. Creation era L When was it created? 3. Site area Q The area occupied by this archeology site. 4. Current state L Is it destroyed, partially destroyed or well protected? 5.5 Case Studies To illustrate aspects in use of the project environment modeling approach presented in the previous sections, use is made of two rather distinct case studies, the Okanagan Lake floating bridge project and the Sea to Sky highway improvement project, both projects being in British Columbia, Canada, with the former in the interior of the province and the latter on the coast. The geographical and environmental contexts of the floating bridge project are tightly bounded ( M O T 2003), whereas the highway project traverses through several jurisdictions and through urban, coastal, and mountainous regions ( E A O 2004a). Use of these two case studies allows us to assess the ability of the modeling methodology to represent a compact and relatively small number of components, as well as a much larger number of components that are widely dispersed across several locations. The existing 3-lane Okanagan Lake floating bridge was completed in 1958 and is 880 meters long with a lift span for marine traffic at the east end as well as a small f i l l abutment area, and a causeway at the west end. It "is the only bridge that crosses Okanagan Lake and it is an essential part of the Okanagan regional transportation system. This key link for traffic to and from the Lower Mainland is the most congested section of highway in the interior of British Columbia operating well over its capacity during peak periods with "Summer Average Daily Traffic" exceeding 50,000 vehicles per day. The province is seeking a private sector consortium to design, build, finance, and maintain a new 5 lane crossing, while operating, maintaining, and then decommissioning the existing 880m long bridge. A full risk analysis is particularly important for this project due to the choice of a P3 procurement mode and the need for great clarity regarding the assignment of risks. The major characteristics of the natural environment of this project are the lake itself with steep hills on the west side of the lake, Kelowna City on the east side of the lake with a city park located beside the existing bridge, and a politically savvy First Nations community on the west bank of the lake. Archeology, fish and wildlife, lake sediment and noise constitute the major environmental concerns. The environment of this project was modeled using the Project E B S structure shown in figure 5.6. The physical, social, economic/financial, political and regulatory environments were initially defined by copying over relevant components from the master template of standard templates (i.e. Standard Infrastructure Project E B S - figure 5.4). Attributes defined as part of the standard components were automatically copied over as part of the standards copying process. Using the copied components as the starting point, the 106 3(1 I HHI^ .SWtlRKWKANACiANIAKIIMOMUAIR Standards EJ3S Wndow Help - 3 X E Environment Example bating Bridge Project Environment PHY Class Physical Ermonment B-HYD Sub-class Hydrography ; SCREk Entity Owk HIllC Sutervtity MI creek 8EARC Sub-entity Bear creek PENTC Sub-entity Penfctcm Creek I- LAKE Entity Late ! :-OKNG Sub-ertty Okanagan Lake [-!• TP5P Sub-class Topography :-MOTN Entity Mountain ? ran Entity m HWSO Sub-entity tfl on west side lake HESD Sub-entity t i on east side late WTID Entity Wetland ; 1 SCIP Sub-entity Scirpus Marsh and Adjacent Hablats -' SCRU Entity Scrubland ; :-SESU Sub-entity Grassed and Shrub Areas on East Side Upsbpe. - FRST Entity Forest WBFT Sub i^ty West Bank Forest H- GEO Sub-class Gectogy £ 5DHT Entity Sediment Load SE5HJC Entity Seismic Zone fcvBOTN Sub-class Botany TREE Entity Trees ; :-SHRB Entity Shrubs i : GRAS Entity Grasses ; '-AQTC Entity Actuate Plants - HABT Sub-dass Habitat TRST Entity Terrestrial Habitat .- AQTH Entity Aquatic Habitat i --MH.C Sutwntity Hi Creek Habitat M'ZOIS Sub-class Zoology AHPB Entity Amphibian RPTL Entity Repute (a) MAM. Entity Mammals - BIRD Entity Birds n mm KIP!ON') id , MillSi'-WHRKUIKANAdAN!AKlMlilDGfWll\ SWAN Sub-entity Trumpeter swan j § FISH Entty Fish MLFS Sub-entity Fish in Ml Creek . FLAKE Sub-entity Fish to Okanagan Lake Ei-ATMP Sub-class Atmosphere ; AQUT Entity tower layer* B'CLMT Stir-class Ctoatoiogy rm Entity Rainfall • TEW Entity Temperature 61 PlUT Sub-dass Pcfction 1- DDCPW Entity Dry Dock Contained Polluted Water ;• DRWTP, Enbty Dredging Polluted Water !~ML Entity Metal Leachate (ML) CNW Entity Toxic Contaminated Site SCI Class Social Erwronment 3 ABOG Sub-class Aboriginal FNTR Entity First Nation Interest - CHIP Sub-class Community Life I j-NCHS Entity Norse \ RCRA Entity Recreation I SPARK Entity Parks M K K Sub-entity Ketema City Park BCPP Sub-entity Bear Creek Provincial Park L- CSPW Enlty Cemeteries, Schools and Mace of Worship B MSFT Sub-class Mwo Social Factors 1 PtDM Entity Population and Demography E-ACHT Sub-class Archeological and Historic Resources 6 ARCH Ertty Archeology ASTE43 Sub-entity Archeological Site OIQv 43 Sub-entity Archedogical Site OIQv 38 Sub-entity Archeotegical Site DIQv 42 Sub-entity Archeological Site DIQv 45 Sub-entity Arcrreokrgical Site DIQv 3 Sub-entity Archedorjcal Site DIQv 37 Class Et««/Frnarda)Erwironm«nt Class Political Enwonment Class Regulatory Environment (b) ASTE38 A5TE42 ASTE45 ASTE3 A5TE37 a-ECO • PCX £ REG 'Ready MUM Figure 5.6 Floating Bridge Project EBS- Entity level components environmental model was then edited to reflect the specific features of the project. For the project at hand, a few sub-entity components were added, these being the three creeks ( M i l l Creek, Bear Creek and Penticton Creek) which are defined as sub-entities under the entity Creek. These creeks are important habitats for fish and are potential risk sources for the project. Other additions include the Archeological Site sub-entities under the Archeology entity component. Shown in figure 5.6 are all o f the components for the physical and social dimensions of the 107 project's environment. Once the components of the environmental model or E B S are defined, values and their corresponding locations can be assigned to component attributes. A Project Risk Register for this project was then developed by associating the environmental components modeled in the Project E B S with the physical, process and organizational views of the project. Due to space limitations, a limited number of examples of potential risk events excerpted from the project risk register are summarized in tabular form, as shown in table 5.4. Additional information contained in the system but not shown in table 5.4 includes risk drivers, performance measures impacted, and applicable mitigation measures. To illustrate some of the foregoing, we use the archeology risk issue as shown in figure 5.7. It illustrates how environmental components in concert with components from other views act as risk drivers for a risk issue. In this example, the sub-entity environmental component archeological sites together with the entity component First Nations interests are the environmental drivers for archeology risk issues because of the religious significance of these sites. These sites occupy the same location as the West Bank causeway (the road alignment in the physical view). Should an archeological site be encountered during the construction phase, very significant time and cost consequences could result. The locations for the project, as defined in the physical view of the project, are shown in figure 5.8(a). Locations are assigned to attribute definitions and their values of each environmental component, such as archeology site DIQv43 as shown in figure 5.8(b) and (c), where the value for the attribute, land area of site, is assigned. Integration within a single system of a project's environmental, process, physical and organizational views aids in the identification of relevant risk issues and related risk events and their significance through the sharing of one or more of the same location, time frame or project participants. 108 Table 5.4 Extract from Floating Bridge Project Risk Register Category Sub-Category Issue Event Physical Geology Sediment Load Bridge pier becomes inclined because of unbalanced sediment load. Erosion Safety of bridge pier foundations impaired by erosion. Habitat Terrestrial Habitat Habitat not previously identified as terrestrial habitat designated as such during construction -construction interrupted, compensation required. Aquatic Habitat A n unexpected loss of aquatic habitat occurs due to construction process. Zoology Fish Unexpected loss of valuable species due to a construction mishap interrupts construction process. Atmosphere A i r Quality Unacceptable levels of air pollution to local residents from construction process results in order from authorities to alter the construction process. Acts of God Seismic Zone A n earthquake occurs during construction phase creates Tsunami in lake - damages/sinks bridge. Pollution Toxic Contaminated Site Unknown/unexpected contaminated materials identified during excavation phase. Solid Toxic Waste Unexpected waste disposal conditions imposed on treatment of construction waste. Liquid waste discharges and sewages Pollution in runoff water from construction process for building bridge pontoons at the dry dock site exceeds allowable levels. Spi l l Contamination A n unexpected spill of potentially toxic materials into the lake occurs during construction/operation. Social Aboriginal First Nations Interest First Nations employment threshold requirements cannot be met. Community Life Noise Noise level of construction work exceeds allowable threshold, leading to reduced working hours or need for alternative methods. Navigation Navigation collision occurs under the bridge and damages bridge components. Archeology Archeology Unknown archaeological resources discovered, requiring realignment of route or restrictions on construction area. 109 Environmental Drivers 1. Sub-entity: Archeological Sites 2. First Nations Interests Process Drivers 1. Road embankment construction Physical Drivers 1. Road alignment Organizational Drivers 1. Owner for site investigation. 2. Concessionaire for road alignment selection and embankment construction. 3. Westbank First Nations Location: West bank causeway Archeology Risk Issues Project phase: Design and construction phase Figure 5.7 Drivers for archeology risk issue at floating bridge project §^::fjle PjrOJKt_'»1*V« _ JO I :MIIISISW(fiWU)KANACjANL AKIilRIDdl V XT-it Standards PCJ3S Window Help - ? X < s Ready Project Risk Example: Floating Bridge & Approachways I- LSI Location Set Physical Location Set |-GPR3 location Global Project 23+_24+ location Roadway: Chainage 23+00 - 24+50 r 24+_2S+ location Interchange: Chainage 24+50 - 25+50 !- 25+_28+ Location Roadway: Chainage 25+50 - 23+00 i 2S+.29+ location Approach Bnbantaert: Chainage 28+00 • 29+44 l~ 29+J2+ location Ramp & Transtion Span: Chainage 29+44 - 32+80 i 32+_39+ Location Floating Bridge- Chahaga 32+68 - 35+64 f-38+_40+ Location ElevDecMTransitlonSpan:Chainage38+64-40+12 }•• 40+_45+ location Roadway: Chainage 40+12 - 45+84 r-DRYDOCK Location Orydc«kfwPcrtocmCorisUuctton j- LAKE Location Late (both sides) | rUAKE Location North Skte of late ^ SLAKE location South Side of late J-LS2 location Set Procedural location Set }• RDWAYJ Subproject Roadway; Chainage 23+00 - 24+50 I 1NTERCH Subproject Interchange I- R0WAY_2 Subproject Roadway: Chainage 25+50 - 28+00 i EM8AMC Subproject Approach Embankment j-RAMPJS Subproject Ramp8t Transition Span , i-BRIDGE Subproject Floating Bridge * ' i DECK.TS Subproject East Transition Span j- RDWAYJ Subproject Roadway: Outage 40+12 - 45+84 i-DRYDOCK Subproject Drydod HUM . / . Attributes' Values j Standard EBS Record!! Bsk Issues/Events [ Prowl Records | M e m j Pari. O IK SrXACHT ARCH OA'fSSr™ • DesccfAorr |bch*olsgca1 Site DIQv 43 * — " Tfpe I r -AttnbuteVakies =:  J Oe!d()Wri_ ! Name of resource i Land area ol site : CreabonEra : Cuient Stale I, A A. A Aj ( Y N. Y.. N. Y.. V.. N. »' N. N. Y N Y„ N. N. V. N. Y . N. N. i Anticipated Allribute Value p.? Path; 01BE.SCI.ACHT.ARCH Attribute::Land area of site VabeTjipe: Quantitative. >.,; Unit: sqm P pujnvakjesfotayocatoni... Location Range t,: •• Location Range >: Value: 23*_24+-23.=24+ 25 (C) Add! Delete Edit • i t - Cancel. J / Q A U«t L L t (b) •:• Enter Actual Values OK Cancel Figure 5.8 (a) Physical location definition, (b) Attributes for Archeology Site component, (c) Assignment of attribute value for Archeology Site component no The Sea to Sky highway improvement project in British Columbia serves as the second case study. This highway links the communities from West Vancouver to Whistler, climbing from Horseshoe Bay to a spectacular mountain landscape in an environmentally sensitive area. This project is accompanied by many complex engineering and construction challenges. The project involves widening and straightening a 94.7 km section of highway with 5 road sections including bridges and viaducts. Moving south to north, the finished configuration consists of a 12.2 km 4 lane section, a 10.5 km 2 lane section, a 19.7 km 3 lane section, a 9.9 km 4 lane section, and a 42.4 km 3 lane section. A l l these sections requires upgrades to address current deficiencies in safety, reliability and mobility, and to serve future travel needs, including transportation demands during the 2010 Winter Olympics. The Province has adopted a P3 procurement mode to design, build, finance and operate this project. A s a consequence, a great deal of effort was and is being expended on risk identification and management. The environment for this project is rather complex. The road sections cross 67 roadside drainage ditches, 191 creeks and streams, 7 lakes, 1 pond, 24 wetlands, and 1 estuarine tidal marsh. The highway also traverses several municipalities that profess varying degrees of support for the proposed improvements, and have different bylaws regarding construction, traffic management, etc. Throughout the construction phase, traffic w i l l have to be maintained on the existing 2 lane road (which does have some 3 and 4 lane sections already), and the desire is to minimize the number of scheduled road closures. The first outstanding environmental issue for this project is First Nations because the project falls within the asserted traditional territory o f four First Nations groups. The interest of First Nations has to be considered within the project life cycle. Community noise is also an important issue especially during night time when the traffic is still busy. Geography is the third in important issue because the existing highway is notorious for falling rock and slope slides. Because the highway crosses many water systems, water quality and aquatic life are also key concerns. A Project E B S for this project was developed as shown in figure 5.9 to incorporate the full range of environmental components. Given the focus of this paper, only the physical and social environmental components are provided in this figure. This Project E B S was developed by selecting and copying components from the Standard E B S and assigning values to their attributes. A s compared to the E B S for the floating bridge case study, the Sea to Sky E B S involves many more components and its complexity is obvious. Carrying out these two case studies allowed us to demonstrate the following: the environmental modeling structure developed is sufficiently rich and flexible to cope with full scale projects and diverse environmental components; the notion of developing a knowledge management facility greatly eases the burden of developing an initial environmental breakdown structure for the most complex of projects; the contents of the master environmental breakdown structure developed through extensive examination of the literature and actual project documents capture the diversity of components that describe the natural and man-made dimensions of a project's environment; and finally, the attributes and their values for environmental components are of great assistance in identifying potential environmentally driven project risk events. 5.6 Visualization of Environmental Components and Risks • The complexity of the environment in which a large scale infrastructure project is located makes difficult the tasks of developing a comprehensive understanding of a project's environmental features, identifying related environmental risks and quantifying their potential impact on the project. This difficulty is further compounded because of the voluminous data sets 112 Window Help - o X STSE Environment Sea to Sky Highway Project El-PHY. Class Physical Environment - HYD Sub-class Hydrography (a) mm Entity Drainage Systems CREK Entity Creek STRE Entity Stream RIVE Entity River LAKE Entity Lake SEA Entity Sea GRWA Entity Groundwater RUOF Entity Runoff Water TPSP Sub-dass Topography - HOTN Entity Maintain HILL Entity HI ESTR Entity Estuary WILD Entity Wetland SCRU Entity Scrubland FRST Entity Forest SESO Entity Seashore -BAY Entity Bay GEO Sub-class Geology SOE Entity Sol 1LSD Entity Hand Sand CSAO Entity Coastal Sand R o a Entity Rock i cm Entity Coral Reef SDMT Entity Sediment Load D8SF Ertty Debris How GRMO Entity Ground Movement SESMC Entity Seismic Zone BOTN Sub-dass Botany TREE Entity Trees SHRB Entity Shrubs GRAS Entity Grasses , FERN Entity Fern i-EHH. Entity Emblement AQ'C 'Entity Aquati:Plants • < y Ready ; VGTD Entity Vegetation Debris i-HABT Sub-class Habitat r-TRST Entity Terrestrial Habitat j-AQTH Entity Aquatic Habitat HCHT Entity Marine and Coastal Hal I ZOLG Sub-dass Zoology l-AMPB Entity Amphibia RPTl Entity Reptita i- MAML Entity Mammalia I AVES Entity Aves 4--ITGV Entity Ichthyology 1YTB Entity Invertebrate : LWOG Sub-class Lower Organisms i-ecm Entity Bacteria i FUG! Entity Fungal ATMP Sub-class Atmosphere \ AQUT Entity Lower Ar Layer I l - UAOL Entity Upper Air Ozone Layer j I- CLMT Sub-dass Climatology GUTW FOG FRST (b) Entity Gust of Wind Entity Fog Entity Frost Entity Snowfall Entity Snow Avalanche Entity Rainfal Entity Storms Entity Flood Entity Severity of Freezing Entity Thawing Cycles j-AVLC RNFl |" STORM j--FLOOD J FREI \ THAW f-HUMO Entity Relative Humidity ' ATPS Entity Attwspheric Pressure OESE Sub-class Disease Control -HUMN Entity Human Disease PLUT Sub-class Pollution ; PAGM Entity PoterWIy Add Generj;^  i l i i i i l l iMlii ffi I AjlReady Window. .Help tuni^  j * i j - 8 X \-ML Enfty MetalLeachate(ML) f CNTM Entity Toxic Contaminated Sit SLWT Entity Solid To* Waste •:-LQWT Entity Liquid waste discharge DPIF Entity Dumping and LaraHing: SCI Oass Soda! Environment - A80G Sub-class Aboriginal ; FN1R Entity First Nation Interest a-CMLF Sub-dass ComminityUfe (cj NOIS Entity Noise Y8TF Entity vibration from Traffic j-TTCG Entity Traffic / Transport™ C i-CMAC Enfty Community Access i-RCRA Entity Recreation PARK Enfty Parks j-EMRC Enbty Emergency Services i PBCH Enfty Public Health i-ACMF Entity Accidents and Malfunct ; -CSPW Entity Cemeteries, Schools ar CEVT Entity Community Events i-CEDS Entity Community Education S CSTY Entity CMC Safety i-UTLT Entity Utities SLUi Entity Space and Land Use tat BUBEV Sub-dass Urban Efftironment j CMAR Enfty Commercial Area ' EVIF Entity Environmental Infrastrui 8-M5FT Sub-dass Micro Social Factors 'MM Enfty Population and Demogi B-OHMS Sub-dass Other HunianSettremei OCAT Entity Other Construction Ad IUOS Entity Land Use in Other Setti 3 ACHT Sub-class ArcheologicaiaraiHstoi | ! HRTG Entity Heritage • - ARCH Entity Archeology ;-> ASTH Sub-dass Aesthetics \ r e -I* Ii File Pro)8Ct_Vw \ Standarcts Window Help. 1 BlJek teUtoiaiojo •ARCH Entity Archeology (d) LOSC Enfty landscape • fflSC Ertty Townscape L S W T Entty S e e * Views | ECO Class 4 POL Class PifalEnvirctrront E E REG Class Re^atoryEnwonmert < Ready • Figure 5.9 Sea to Sky Highway (STS) Project EBS 113 required to represent a project. A s a result, members of the project management team can become lost or drown when confronted with so much data and information. The ability to visualize environmental and other related data can assist management in gaining valuable insights into the messages buried in such massive data sets. In this.section, we provide a brief overview of ongoing work directed at developing formats and strategies for visualizing environmental data, with emphasis on the clustering of risks driven by a project's environmental features. While details of a number of formats that have been found to be useful have been worked out, these formats have yet to be implemented in the prototype system. Figure 5.10 shows an innovative 3-D interactive histogram which can assist the project team to recognize important project environmental and risk information. In this figure, the x axis corresponds to the time interval while the y axis corresponds to location interval. (As an aside, in implementing data visualization capabilities, it is important to include the ability to define different level of coarseness or granularity for the x and y axes - e.g. time measured in days, weeks, months, seasons and years.) The vertical or z axis sitting in the middle of the figure, represents the number of total drivers while the two vertical axes at the two sides is for number of organizational drivers, which indicate the number of drivers for which each organization is responsible. In this figure, three organizations, general contractor, consultant and owner, are used as examples. The number of organization can be more than three and they are represented by different colors. The drivers can be drawn either from only the environmental view or from other views such as physical, process and organizational/contractual views. Four types of information can be obtained from this interactive figure. Firstly, users can determine how many risk drivers exist in a specific time and location interval, and how many drivers for which each project participant has been assigned responsibility. For example, from 114 Locat ion In t e rva l Figure 5.10 Distribution in time and space and by responsibility of environmental risk drivers figure 5.10 we can identify that a total of 33 drivers exist in the time interval T4 and location interval L9 . The owner is responsible for 9, the consultant for 11, and the general contractor for 13 of these drivers. This detailed information appears in a small pop up information window when a user suspends the mouse on the tower-shaped columns, as shown in figure 5.10. Secondly, information regarding the distribution of the total number of drivers according to time and location, with a further breakdown by project participant, can be obtained from the two "side walls" of the graph. Distributions for the number of organizational drivers are shown in different colors while the distribution for total number of drivers is shown by the heavy black line. For the case that the presence of many columns in the three dimensioned space prevents users from scrutinizing the distribution on the side wall , a 3-D view control box is provided as shown in 115 figure 5.11(a) so that the graph can be rotated and the required information made completely visible, as shown in figure 5.11(b). Thirdly, users are provided with the information of what drivers comprise the total set of drivers and the set of drivers each organization responsible for, including the hierarchical structure with which these drivers are organized. This can be achieved by clicking on the hyperlinked text in the small information box shown in figure 5.10, which activates a separate pop up window. This window displays a hierarchical structure for the drivers, as shown in figure 5.12(a) using the Magic Eye V i e w technique (Kreuseler and Schumann 2002), a method by which all o f the hierarchical nodes are distributed on the surface of a hemisphere. Chart FX Properties General Series Axes P Rotated view X Angle J45 ~jj i*Angle: |45~Jj[| Shadows | Feted angle Eerapeotjve: ). (a) OK | Cancel | Help Number Of Distribution rotal Drivers for Number of Org. Drivers Distribution for Number of Total Drivers Number of Org. Drivers L2 1.3 \J- L8 L9 1.10 Location Interval Figure 5.11 (a) 3-D graph viewer; (b) Lateral view of distribution graph after rotation For example, i f you click "Total: 33" in the box in figure 5.10, a hierarchical structure with a total of 33 drivers w i l l pop up while i f you click "Owner: 9" a hierarchical structure with a total of 9 drivers for which the owner is responsible w i l l pop up. If the responsibility for a driver is shared amongst two or more project participants, the driver w i l l be included in the count for each organization but it w i l l only be counted once in terms of the total number of drivers for its corresponding time and location interval. Lastly, attribute values for each of these drivers can be 116 popped up as shown in figure 5.12 (b) once the user rotates and focuses on the intended driver and suspends the mouse on it. T Component Attributes Value Table 2 Name Inherited B/q/L Location Planned Value Actual Value 3 1 4 2 „ 5 3 6 4 5 (b) Figure 5.12 (a) Hemispherical hierarchy; (b) Focused hemispherical hierarchy (Revised from Kreuseler and Schumann 2002) 5.7 Conclusions Described in this paper is a comprehensive approach for modeling a project's natural and man-made environments in support of the functions associated with project management, with special reference to risk management. It builds on the past work o f others for characterizing the environment of a project. Integral to the approach developed is the integration of the environmental view of a project with other project views such as the physical, process, organizational/contractual and risk views, and the ability to capture and reuse knowledge gained from past projects and other sources. Equally important is what should be the contents of an environmental view. Thus, a master library of environmental components along with examples of relevant component attributes for infrastructure projects is provided. Use is made of two real 117 projects to demonstrate features of the approach and its applicability and usefulness for modeling full-scale projects. H o w to extract messages from the masses of data that describe the environmental and risk views of a project using data visualization strategies is also discussed. Ongoing work is focused on implementing these data visualization strategies and seeking input from practitioners. 5.8 Acknowledgements We gratefully acknowledge financial support for this work by N S E R C Strategic Grant S T P G P 257798-02, Decision Support System and Knowledge Management Concepts for the Construction Industry, and the British Columbia Ministry of Transportation Grant-in-Aid, Assessing P3 Risk Management for Public Sector Projects. The project team consists of Alan Russell, project leader, Sanjay DeZoysa, PhD candidate and graduate research assistant responsible for developing the risk and environmental modeling constructs and supporting system architecture, Yugui Wang, M A S c student and graduate research assistant, responsible for validating the environmental modeling constructs, developing a master environmental model template, conducting case studies on actual projects and visualizing environmental data, Asad Udaipurwala, PhD candidate and graduate research assistant, a key participant in the development of the overall prototype system as well as with the process view, and Wi l l i am Wong, senior programmer responsible for development and maintenance of the prototype system. 5.9 Bibliography Asian Development Bank (2002). "Handbook on environment statistics." Development Indicators and Policy Research Division, Economics and Research Department, Asian Development Bank. 118 Canadian Environmental Assessment Agency (2003). "Basics of Environmental Assessment." http://www.ceaa.gc.ca/010/basics_e.htm (1 Nov. '04). Carpenter, T. (2001). "Construction in a fragile world." Environment, Construction, and Sustainable Development, V I . Edited by T. G . Carpenter. John Wiley & Sons Ltd. 2001. DeZoysa, S., Wang, Y , and Russell, A . D . (2005). "Use of IT in Managing Environmental Risks in Construction Projects." Proceedings for the A S C E Construction Research Congress, Apr i l 5-7, 2005, San Diego. Environmental Assessment Office (EAO) (2004a). "Sea to Sky highway improvement project assessment report." http://www.eao.gov.bc.ca/epic/output/html/deploy/epic_document_l 92 _18995.html (16 Feb. '05) Environmental Assessment Office (EAO) (2004b). "New Fraser River Crossing project assessment report." http://www.eao.gov.bc.ca/epic/output/html/deploy/epic_document_214 _19086.html (16 Feb. '05) Hughes, W . (1989). "Identifying the environments of construction projects." Construction Management and Economics, 7(1), 29-40. Kreuseler, M . , and Schumann, H . (2002). " A flexible approach for visual data mining. " I E E E Transactions on Visualization and Computer Graphics, Institute of Electrical and Electronics Engineers Computer Society, 8(1): 39-51. Marmoush, Y . (1999). "Environmental management of coastal development, state of Kuwait ." Water science Technology, 40(7), 47-53. 119 Ministry of Transportation, British Columbia (MOT) (2003). "Environmental Impact Assessment Synopsis Report, Okanagan Lake Bridge Project." Ministry of Transportation, Environmental Management Section, Victoria, B C . New York Department of Transportation ( N Y D O T ) (2001). "Environmental handbook for transportation operations." N Y S D O T Environmental Analysis Bureau ( E A B ) , N e w York. Russell, A . and Udaipurwala, A . (2004). "Using multiple views to model construction." C I B World Building Congress 2004, Toronto, Canada. 11 pages. Tszmokawa, K . , and Hoban, C. (1997). "Roads and the environment- a handbook." The World Bank technical paper No . 376. The World Bank, Washington D . C . Underhill, J. and Angold, P. (2000). "Effects of roads on wildlife in an intensively modified landscape." Environment Review, (8) 21-39. Wang, Y . (2005). "Environmental Risk Modeling of Infrastructure Projects." M A S c . thesis, Department of C i v i l Engineering, the University of British Columbia. Week, T. (1977). "Environmental impact of transportation project." Environmental Impacts of International C i v i l Engineering Projects and Practices. Proceedings of a session of the A S C E National Convention, San Francisco, 1-28. Wilson, F. and Stonehouse, D . (1983). "Environmental impact assessment: highway location." Journal of Transportation Engineering, 109(6), 759-768. Oresundskonsortiet (2000). "Environmental impact of the construction of the Oresund Fixed Link ." M a y 2000. Printed by: Fihl Jensen. I S B N : 87-89881-23-0. 120 Chapter 6 Conclusion 6.1 Summary A project's environment is surroundings and their characteristics which, at any phase of the project life cycle, have a direct impact on project performance. These surroundings can be both man-made and natural, and relate to the physical, social, economic/financial, political and regulatory surroundings. Characterizing the context of a construction project through multiple views or models of a project plays an important role in identifying and treating environmental risks that are project-specific. The environmental and physical components of the project, along with its processes and project participants, can either on their own or in concert act as sources or drivers of risks. For these reasons, modeling of the environment for the purpose of risk management is significant for construction projects. These research motivations are described in Chapter 1 along with research objective, methodology and thesis overview. A thorough literature review is necessary and an effective way to understand and evaluate current approaches for representing a project's environment. The most valuable works identified from such a search are described in Chapter 2. A working definition of project environment is given in the beginning of this chapter to clarify the scope of the research. The notion of an environmental view and other views of a construction project are described to help the reader 121 understand how this concept assists with the approach adopted for environmental risk modeling as described in Chapters 3, 4 and 5. Valuable observations from environment modeling approaches used both in the industrial and academic domains are presented and they form an important foundation for part of the approach developed in this research. Other aspects of the literature search dealt with environmental risks, environmental impacts and mitigation measures, and approaches to data visualization, which could prove useful for dealing with the large volumes of data required for representing a project. Chapter 3 presented the constructs developed for representing and integrating the environmental, risk, physical, process and organizational views of a project for the purpose of environmental risk management. These constructs are based on an IT-based methodology that allows users to capture their knowledge in a re-usable format and apply it in managing environmental risks for specific project contexts. In the computer-based methodology developed, a hierarchical representation structure that allows inheritance and aggregation of user-defined properties is used to model the environment. User-defined hierarchical environmental models for different project types (e.g. coastal highway, bridge, dam, etc.) can be stored as templates on the knowledge management side of the computer system. Risks are modeled through a structure termed the Standard Risk Issue Register (SRR) on the knowledge management side of the system, and the Project Risk Issue Register (PRR) on the project side of the system. Both of them are also organized as hierarchies. The SRR serves as an organization's repository of risk-related knowledge gained over time. Components of the SRR can be associated with components of the environmental templates on the knowledge management side. For a specific project context, the user builds up the representation for the environment on the project side of the system, using as applicable the standard templates on the knowledge management side of the 122 system. Accompanying this process, risks can be simultaneously added to the Project Risk Register (PRR), which is a project specific repository of risks, either from environmental component associated risks on the knowledge management side or from manual risk identification due to the integration of environmental, process, organizational and physical views. Two case studies are briefly applied to these constructs in this chapter to illustrate the philosophy of these constructs. As seen from Chapter 3, the data for risk drivers identified for a specific project can be numerous and the diverse attributes of each driver make the data sets even more complex. Presented in a traditional format such as table or in text mode, it is hard for a project team to extract information quickly and to gain the insights necessary for effective management. Visual representation of data holds great potential for reducing both communication difficulties between data sets and project teams and communication difficulties among project team members. Chapter 4 investigates current visualization techniques, especially those which have already been applied to construction management data. It also includes some important visualization techniques which are not currently applied to but hold great potential for the construction field. An interactive 3-D histogram is provided in this chapter to visualize four dimensions of risk information. This innovative 3-D histogram depicts the number of environmental risk drivers in time and space and by assigned responsibility. A hierarchical risk structure is visualized in a focus + content method and combined with this 3-D histogram by linking. Attributes of each risk driver are also linked to the visualized hierarchical structure. This visualization scheme presents data pertaining to environmental risks in effective formats which facilitate decision making, risk identification, and choice of mitigation measure. 123 Chapter 5 focuses on illustrating and validating aspects of the IT-based approach for managing environmental risks. B y applying the constructs developed in Chapter 3, a master library of environmental factors is established and attributes are defined to describe the characteristics of these environmental factors on the knowledge management side. The environmental profile of two projects, one for the Sea to Sky highway project and one for the Okanagan Lake floating bridge project, are developed. Identifying risk issues and associated risk events that arise from the environmental profile is demonstrated for the floating bridge project. Application of the constructs developed in Chapter 3 to these two case studies demonstrates that the constructs are sufficiently 'rich' that they can be used to represent what one needs to know about the environment for purpose of project management, and in particular, risk management. 6.2 Contributions Contributions resulting from this thesis are: 1. A structured literature review is provided in Chapter 2 with observations. This literature review identifies the most important works related to project environment. Both researchers and practitioners working on this topic or relevant topics can benefit from this literature review. 2. A comprehensive master library consisting of 165 environmental factors is developed, which treats most i f not all of the environmental factors associated with infrastructure projects. Relevant mitigation measures for these environmental factors are also included. 3. Attributes are defined for each o f the environmental factors to describe their characteristics. These attributes are important for environmental risk identification in 124 that it is the value of the attribute that acts as a risk driver. These attributes are also helpful for project practitioners to understand why these environmental factors are important for project performance. 4. The robustness of the constructs developed to represent the environment is explored by applying them to two rather distinct case studies. These constructs have proved to be sufficiently rich to model the complete spectrum of environmental components and related risks encountered on infrastructure projects. 5 . Visualization strategies for environmental risks have been explored. These strategies have the potential to provide project practitioners with an effective way of capturing environmental risk information quickly. They also demonstrated the potential to reduce communication difficulties encountered amongst project participants. 6.3 Recommendations for Future Work The research in this thesis has lead to several areas for future work, as follows: 1. A methodology should be developed for applying the environmental factors and attributes defined for them to generate an environmental impact assessment statement. Not all environmental issues are uncertain and relevant to project risks. However, certain environmental factors are also need to be mitigated and project performance can also be impacted by them. IT technologies are seldom used in environmental impact assessment procedure, and knowledge gained from the past projects is seldom structured for re-used for future projects. A system with such characteristics is needed by industry. 125 2. Strategies for visualization of project environment data in a generic way are still needed. The strategies developed in this research for visualization of environmental risks should be extended to embrace all o f environmental risk management, environmental impact assessment, and environmental management. 3. A risk library with identified environmental risks that can be stored on the knowledge management side needs to be established. Association of these risks with environmental factors on the knowledge side should also be affected so that this can be applied to future projects. 4. A more comprehensive set of mitigation measures of both environmental risks and environmental impacts need to be identified. 126 Appendix I Components of Standard Environmental Breakdown Structure Environment Class Sub-Class Entity Sub-Entity Project Environment Physical Hydrography Drainage Systems Creek Stream River Well Reservoirs Lake Lagoon Sea Icefield Groundwater Runoff Water Topography Mountain H i l l Plain Estuary Shallows Canyon Pastures Wetlands Savannas Scrubland Forest Tundra Desert Seashore Bay Gul f Strait Geology Soil Inland Sand Coastal Sand Rock Coral Reef Sediment Load Debris Flow Area Ground Movements To be Continued 127 Continued Environment Class Sub-Class Entity Seismic Area Sub-Entity Volcanic Active Area Botany Trees Shrubs Grasses Fern Emblement Aquatic Plants Vegetation Debris Habitat Terrestrial Habitat Aquatic Habitat Marine and Coastal Habitat Migration Zone Zoology Amphibia Reptilia Mammalia Bird Fish Invertebrate Lower Organisms Bacteria Fungi Atmosphere A i r Quality Upper A i r Ozone Layer Climatology Gust of Wind Fog Frost Snowfall Rainfall Severity of Freezing Thawing Cycles Temperature Relative Humidity Atmospheric Pressure Storms Snow Avalanche Floods Drought Tornado Typhoon Hurricane Tsunamis To be Continued 128 Continued •Environment Class Sub-Class Diseases Control Entity Botanical Disease Sub-Entity Zoic Disease Human Disease Pollution Potentially Ac id Generating (PAG) Material Metal Leachate ( M L ) Toxic Contaminated Site Solid Toxic Waste Liquid Waste Discharges and Sewages Biotic Waste Dumping and Landfdlings Social Aboriginal First Nation Interest Community Life Noise Vibration from Traffic Traffic / Transportation Congestion Community Access Recreation Parks Emergency Services Public Health Accidents and Malfunctions Cemeteries, Schools, Place of Worship Community Events Community Education Service Civic Safety Utilities Space and Land Use Impact (Surface and Sub-surface) Urban Environment , Commercial Area Slums Environmental Infrastructure Micro Social Factors Population and Demography Social Instability Wealth Distribution Other Human Other Construction Activities Settlements Land Use in Other Settlements Archeological and Heritage Historic Resources Archeology Site Aesthetics Landscape Townscape To be Continued 1 2 9 Continued Environment Class Sub-Class Entity Scenic Views and Vistas Sub-Entity Economic / Financial Economic Indicators G D P CPI Private and Government Consumption Special Construction Index Macro Economic Monetary Inflation Economic Growth Foreign Exchange Rate and Reserves Capital Movement Restriction Market Resources A / E / C firms Client or Owner Relationship Competition Construction Materials Skilled and Unskilled Workers Labor Cost/ Productivity Construction Equipment Logistics Finance Medium and Long Term Financing. Tax and Nontax Incentives Market Potential Market Volume Bidding Project Volume Agriculture Agriculture Land Reserve Agriculture Operations Aquaculture Foresty Economic Loss Due to Deforestation Tourism Tourism Boom Commerce Trade Resources Natural Resources Residential and Community Property Offices and Public Buildings Claims Third Party Claims Political Government Political Continuity Enforceability of Contract Government Incentives Military Military Occupied Area Military Restriction Anarchy Strike Riot Terrorist Act C iv i l Strife and Armed Conflict To be Continued 130 Continued Environment Class Sub-Class Entity War Sub-Entity Government Authority Federal Government Authority Province Government Authority Local Government Authority Legal Policy Procedure for Bidding and Design Approval Livable Region Strategic Plan Labor and Strike, Repatriation Restriction. Regulatory Regulatory Change Permits, Licenses and Authorizations Changes in Regulations, Rules, Guidelines Formulated and Programs Taken. New Regulatory New Regulatory 131 Appendix II Attribute Definition of Standard E B S Entity Level Components Standard Environmental Breakdown Structure is classified into physical, social, economic/financial, political, and regulatory classes. Attribute definition for entity level components in each of these classes are listed from Table A I I . l to Table A I L 5. The letter L , B or Q represents that the attribute is either linguistic, boolean or quantity respectively. The letter I represents that this attribute is inherited from upper level. Table A I L 1, Attribute definition of physical components at the entity level of Standard E B S . Components Attributes Type Definition Drainage System Name of the Waterbody L , I The name of drainage system. Role of the Drainage System L The drainage system is used for waste water, water supply for the purpose of irrigation or drinks, or other purpose. Seasonal B , I Whether the drainage system is seasonal used or all year round used P H Value Q , I The P H value of water in the drainage. The Highest Q , i The highest temperature of the water in Temperature the drainage. The Lowest Q , i The lowest temperature of the water in the Temperature drainage. Suspended Solids L , I A list of suspended solids. Dissolved Organic L , I A list o f dissolved organic compound. Compound Dissolved Mineral L , I A list of dissolved mineral. Cross Section L The cross section shape o f the drainage. Shape Cross Section Q The cross section area of the drainage. Area Water Table Level Q The water table level of the drainage. Water Depth Q The water depth in the drainage. 132 Velocity Q The water velocity in the drainage. Creek Name of the < Waterbody L , I The name of creek. Seasonal B , I Whether the creek is seasonal. P H Value Q , I The P H value of water in the creek. The Highest Q , I The highest temperature of the water in Temperature the creek. The Lowest Q , I The lowest temperature of the water in the Temperature creek. Suspended Solids L , I A list of suspended solids. Dissolved Organic L , I A list o f dissolved organic compound. Compound Dissolved Mineral L , I A list of dissolved mineral. Cross Section L The cross section shape of the creek. Shape Cross Section Q The cross section area of the creek. Area Water Table Level Q The water table level of the creek. Water Depth Q The water depth in the creek. Velocity Q The water velocity in the creek. Stream Name of the Waterbody L , I The name of Stream. Seasonal B , I Whether the stream is seasonal. P H Value Q , l The P H value of water in the stream. The Highest Q , l The highest temperature of the water in Temperature the stream. The Lowest Q , i The lowest temperature of the water in the Temperature stream. Suspended Solids L , I A list o f suspended solids. Dissolved Organic L , I A list o f dissolved organic compound. Compound Dissolved Mineral L , I A list o f dissolved mineral. Cross Section L The cross section shape of the stream. Shape Cross Section Q The cross section area of the stream. Area Water Table Level Q The water table level of the stream. Water Depth Q The water depth in the stream. Velocity Q The water velocity in the stream. River Name of the Waterbody L , I The name of river. Seasonal B , I Whether the river is seasonal. P H Value Q , l The P H value of water in the river. The Highest Q , I The highest temperature of the water in Temperature the river. The Lowest Q , i The lowest temperature of the water in the 133 Temperature river. Suspended Solids L , I A list o f suspended solids. Dissolved Organic L , I A list o f dissolved organic compound. Compound Dissolved Mineral L , I A list of dissolved mineral. Cross Section L The cross section shape of the river. Shape Cross Section Q The cross section area of the river. Area Water Table Level Q The water table level o f the river. Water Depth Q The water depth in the river. Velocity Q The water velocity in the river. W e l l N a m e o f t h e Waterbody L , I The name of well . Seasonal B , I Whether the well is seasonal. P H Value Q , I The P H value of water in the well . The Highest Q J The highest temperature of the water in Temperature the well . The Lowest Q , l The lowest temperature of the water in the Temperature well . Suspended Solids L , I A list of suspended solids. Dissolved Organic L , I A list of dissolved organic compound. Compound Dissolved Mineral L , I A list of dissolved mineral. Cross Section L The cross section shape of the well . Shape Cross Section Q The cross section area of the well . Area Water Table Level Q The water table level of the well . Water Depth Q The water depth in the well . Ground Level Q The ground level where the well is. Reservoir Name of the L , I The name of reservoir. Waterbody Seasonal B , I Whether the reservoir is seasonal. P H Value Q , I The P H value of water in the reservoir. The Highest Q, I The highest temperature of the water in Temperature the reservoir. The Lowest Q , i The lowest temperature of the water in the Temperature reservoir. Suspended Solids L , I A list of suspended solids. Dissolved Organic L , I A list o f dissolved organic compound. Compound Dissolved Mineral L , I A list of dissolved mineral. Geometric Shape L The shape of the reservoir. Area Q The area of the reservoir. Water Table Level Q The water table level o f the reservoir. 134 Water Depth Q The water depth in the reservoir. Bank Level Q The ground level at the top of the bank of the reservoir. Lake Name of the Waterbody L , I The name of lake. Seasonal B , I Whether the lake is seasonal. P H Value Q . I The P H value of water in the lake. The Highest Q , l The highest temperature of the water in Temperature the lake. The Lowest Q , i The lowest temperature of the water in the Temperature lake. Suspended Solids L , I A list of suspended solids. Dissolved Organic L , I A list of dissolved organic compound. Compound Dissolved Mineral L , I A list of dissolved mineral. Geometric Shape L The shape of the lake. Area Q The area of the lake. Water Table Level Q The water table level of the lake. Water Depth Q The water depth in the lake. Bank Level Q The ground level at the top of the bank of the lake. Name of the L a g 0 0 n Waterbody L , I The name of lagoon. Seasonal B , I Whether the lagoon is seasonal. P H Value Q , i The P H value of water in the reservoir. The Highest Q , i The highest temperature of the water in Temperature the lagoon. The Lowest Q , I The lowest temperature of the water in the Temperature lagoon. Suspended Solids L , I A list o f suspended solids. Dissolved Organic L , I A list o f dissolved organic compound. Compound Dissolved Mineral L , l A list o f dissolved mineral. Geometric Shape L The shape of the lagoon. Area Q The area of the lagoon. Water Table Level Q The water table level of the lagoon. Water Depth Q The water depth in the lagoon. Bank Level Q The ground level at the top of the bank of the lagoon. g e a Name of the Waterbody L The name of the sea. Circulation Pattern L The circulation pattern of the sea. Current Velocity Q The average velocity of the current. Tide Table L The tide table for the sea. M a x i m Wave Q The maxim wave height in a year. Height 135 Sea Level Rising Q The average sea level rising per year. Icefield Name of the L The name of the icefield. Waterbody Area Q The area of the icefield. Deflate Rate Q Deflate Rate of Icefield per Year Ice Depth Q The thickness of the ice. Hardness of Ice Q The hardness of the ice. Ground Water Name of the Waterbody Seasonal L , I B , I The name of ground water at the location. Whether the ground water is seasonal. P H Value Q , i The P H value of water. The Highest Q , i The highest temperature of the water. Temperature The Lowest Q , i The lowest temperature of the water. Temperature Suspended Solids Dissolved Organic L , I L , I A list o f suspended solids. A list o f dissolved organic compound. Compound Dissolved Mineral L , I A list o f dissolved mineral. Geometric Shape L The shape of the ground water. Area Q The area of the ground water. Water Table Level Q The water table level of the ground water. Water Depth Water Velocity Water Pressure Q Q Q The water depth of the ground water. The ground water velocity. The pressure of the ground water. Runoff Water P H Value Q The P H value of water. Suspended Solids Dissolved Organic L L A list o f suspended solids. A list o f dissolved organic compound. Compound Dissolved Mineral L A list o f dissolved mineral. Area Q The area where the runoff water impact. Water Velocity Infiltration Rate Q Q The runoff water velocity. The infiltration rate for the runoff water to infiltrate in the soil. Mountain Name L , I The name of the mountain. Average Altitude Q The average altitude of the mountain. Summit Altitude Q The altitude of summit. Length Q The length of the mountain. Slope of Fal l Q The average slope of fall o f the mountain. Surface Stability B Whether the surface layer is stable. Surface Erodibility B Whether the surface can be easily eroded. H i l l Name L , I The name of the hi l l . Average Altitude Q The average altitude of the h i l l . Summit Altitude Q The altitude of summit. Slope of Fal l Surface Stability Q B The average slope of fall o f the hi l l . Whether the surface layer is stable. 136 \ Surface Erodibility B Whether the surface can be easily eroded. Plain Name L , I The name of the plain. Average Altitude Q The average altitude of the plain. Area Q The area of the plain. Surface Erodibility B Whether the surface can be easily eroded. Estuary Name L , I The name of the estuary. Average Altitude Q The average altitude of the estuary. Area Q The area of the estuary. Geometric Shape L The geometric shape of the estuary. M a x i m Width Q The maxim width of the estuary. Min imum With Q ' The minimum width of the estuary. Surface Erodibility B . Whether the surface can be easily eroded. Shallows Name L , I The name of the shallows. Average Altitude Q The average altitude of the shallows. Area Q The area of the shallows. Geometric Shape L The geometric shape of the shallows. Surface Erodibility B Whether the surface can be easily eroded. Canyon Name L , I The name of the canyon. Length Q The length of the canyon. Average Width Q The average width of the canyon. M a x i m Width Q The maxim width of the canyon. Min imum With Q The minimum width of the canyon. Average Depth Q The average depth of the canyon. M a x i m Depth Q The maxim depth of the canyon. Min imum Depth Q The minimum depth of the canyon. Surface Erodibility B Whether the surface can be easily eroded. Pasture Name L , I The name of the pasture. Average Altitude Q The average altitude of the pasture. Area Q The area of the pasture. Geometric Shape L The geometric shape of the pasture. Enclosure B Whether the pastures has enclosure. Wetland Name L , I The name of the wetland. Average Altitude Q The average altitude of the wetland. Area Q The area of the wetland. Geometric Shape L The geometric shape of the wetland. Savanna Name L , I The name of the savanna. Average Altitude Q The average altitude of the savanna. . Area Q The area of the savanna. Scrubland Name L , I The name of the scrubland. Area Q The area of the scrubland. Geometric Shape L The geometric shape of the scrubland. Average Scrub Q The average height of the scrub. Height Forest Name The name of the forest. Area Q The area of the forest. Species Diversity B Whether there are diverse species. 137 Forest degradation B Whether the forest has degradation. Tundra Name L , I The name of the tundra. Average Altitude Q The average altitude of the tundra. Area Q The area of the tundra. Freeze-up L The period of freeze up in a year. Desert Name L , I The name of the desert. Average Altitude Q The average altitude of the desert. Area Q The area of the desert. Surface Stability B Whether the surface layer is stable. Seashore Name L , I The name of the seashore. Average Width Q The average width of the seashore. M a x i m Width Q The maxim width of the seashore. Min imum With Q The minimum width of the seashore. Surface Erodibility B Whether the surface can be easily eroded. Bay Name L , I The name of the bay. Area Q The area of the bay. Gu l f Name L , I The name of the gulf. Area Q The area of the gulf. Strait Name L , I The name of the strait. Length Q The length of the strait. Average Width Q The average width of the strait. M a x i m Width Q The maxim width of the strait. Min imum With Q The minimum width of the strait. Soil Topsoil Depth Q The depth of topsoil. Top Bedrock Q The level of top of bedrock. Level Water-Solubility B Whether it's water soluble. Inland Sand Area Q The area of the sand source. Depth Q The depth of the sand source. Sand Quality L Is the sand quality good, bad or medium? Sand Color L The color of sand. Coastal Sand Area Q The area of the sand source. Depth Q The depth of the sand source. Sand Quality L Is the sand quality good, bad or medium? Sand Color L The color of sand. Adverse Mining B Whether there is any adverse impact i f Impact mine the sand from coastal sand source. Rock Rock Layer Area Q The area of the rock layer. Rock Layer Depth Q The depth of the rock layer. Rock Hardness Q The hardness of the rock. Rock Color L The color of the rock. Coral Reef Area Q The area of the coral reef. Bleach B Whether the coral reef is bleached. Sediment Load Sediment Area Q The area of sediment. Sediment Depth Q The depth of the sediment. Firmness B Whether the sediment is firm enough. 138 Debris Flow Area Period L The period in a year debris flow occurs. Ground Movement Land Subsidence B Whether the land can subside. Seismic Area Seismic Zone B Whether it is located within seismic zone. Volcanic Activity Existing Volcanic B Whether there are any existing volcanic Area Activities activities. Number of Q , I The number of endangered species of Trees Endangered trees existing in the location. Species Number of Project Q , I The number of project threatened species Threatened of trees which need to be mitigated. Species Number of Q , i The number of project threatened Threatened endangered species of trees which need to Endangered be mitigated. Species Al i en Invasive B , I Whether it's possible to induce alien Species species of trees to invade. Degradation of B Whether there w i l l be Mangroves Mangroves degradation. Number of Trees Q The number of trees which need to be Need Transplant transplanted because of the project. Number of Q , l The number of endangered species of Shrubs Endangered shrubs existing in the location. Species Number of Project Q , l The number of project threatened species Threatened of shrubs which need to be mitigated. Species Number of Q J The number of project threatened Threatened endangered species of shrubs which need Endangered to be mitigated. Species Al i en Invasive B , I Whether it's possible to induce alien Species species of shrubs to invade. Shrub Area Q The area of the shrubs. Number of Q , I The number of endangered species of Grasses Endangered grasses existing in the location. Species Number of Project Q , I The number of project threatened species Threatened of grasses which need to be mitigated. Species Number of Q , i The number of project threatened Threatened endangered species of grasses which need Endangered to be mitigated. Species Al i en Invasive B , I Whether it's possible to induce alien Species species of grasses to invade. 139 Area Q The area of the grasses. Number of Q , i The number of endangered species of Ferns Endangered ferns existing in the location. Species Number of Project Threatened Q , i The number of project threatened species of ferns which need to be mitigated. Species Number of Q , i The number of project threatened Threatened endangered species of ferns which need to Endangered be mitigated. Species A l i en Invasive B , I Whether it's possible to induce alien Species species of ferns to invade. Number of Q The number of emblement species. Emblement Emblement Species List of Emblement Q The name list of the emblement species. Species Area of Q The area of the emblement Emblement Number of Q , i The number of endangered species of Aquatic Plants Endangered aquatic plants existing in the location. Species Number of Project Threatened Q , i The number of project threatened species of aquatic plants which need to be Species Number of Q , i mitigated. The number of project threatened Threatened Endangered endangered species of aquatic plants which need to be mitigated. Species Al i en Invasive B , I Whether it's possible to induce alien Species species of aquatic plants to invade. Vegetation Debris Vegetation Debris Disposal B Whether there is vegetation debris disposal. Terrestrial Habitat Area Q , i The area of the habitat. Habit Loss Habitat B , I Whether there is habitat loss because of B , I the project. Whether there is habitat degradation Degradation because of the project. Habitat Fragment Structure and B , I B , I Whether the habitat is fragmented by the project. Whether the project w i l l change the Characteristic biological structure and characteristics of Change the habitat. Aquatic Habitat Area Q J The area of the habitat. Habit Loss B,T Whether there is habitat loss because of 140 the project. Habitat B , I Whether there is habitat degradation Degradation because of the project. Habitat Fragment B , I Whether the habitat is fragmented by the project. Structure and B , I Whether the project w i l l change the Characteristic biological structure and characteristics of Change the habitat. Marine and Coastal Area Q , I The area of the habitat. Habitat Habitat Loss B , I Whether there is habitat loss because of the project. Habitat B , I Whether there is habitat degradation Degradation because of the project. Habitat Fragment B , I Whether the habitat is fragmented by the project. Structure and B , I Whether the project w i l l change the Characteristic biological structure and characteristics of Change the habitat. Migration Zone Area Q The area of the migration zone. Migration Species L The name of the migration species in the Name zone. Area Loss B Whether there is migration area loss because of the project. Migration Zone B Whether there is migration zone Degradation degradation because of the project. Migration Zone B Whether the migration zone is fragmented Fragment by the project. Structure and B , I Whether the project w i l l change the Characteristic biological structure and characteristics of Change the migration zone. Number of Q , I The number of endangered species of Amphibia Endangered Species amphibia existing in the location. Number of Project Q , I The number of project threatened species Threatened of amphibia which need to be mitigated. Species Number of Q , I The number of project threatened Threatened endangered species of amphibia which Endangered need to be mitigated. Species Al i en Invasive B , I Whether it's possible to induce alien Species species of amphibia to invade. Number of Q , I The number of endangered species of Reptilia Endangered Species reptilia existing in the location. 141 Number of Proj ect Q J The number of project threatened species Threatened of reptilia which need to be mitigated. Species Number of Q J The number of project threatened Threatened endangered species of reptilia which need Endangered to be mitigated. Species Al i en Invasive B , I Whether it's possible to induce alien Species species of reptilia to invade. Number of Q J The number of endangered species of Mammalia Endangered mammalia existing in the location. Species Number of Proj ect Q J The number of project threatened species Threatened of mammalia which need to be mitigated. Species Number of Q J The number of project threatened Threatened endangered species of mammalia which Endangered need to be mitigated. Species Al i en Invasive B , I Whether it's possible to induce alien Species species of mammalia to invade. Number of Q J The number of endangered species of Bird Endangered birds existing in the location. Species Number of Project Q J The number of project threatened species Threatened of birds which need to be mitigated. Species Number of Q J . The number of project threatened Threatened endangered species of birds which need to Endangered be mitigated. Species A l i en Invasive B J Whether it's possible to induce alien Species species of birds to invade. Migration Table L The migration table shows the migration period of each species of birds. Number of Q J The number of endangered species of fish Fish Endangered existing in the location. Species Number of Project Q J The number of project threatened species Threatened of fish which need to be mitigated. Species Number of Q J The number of project threatened Threatened endangered species of fish which need to Endangered be mitigated. Species A l i en Invasive B J Whether it's possible to induce alien 142 Species species of fish to invade. Migration Table L The migration table shows the migration period of each species of fish. Number of Q , I The number of endangered species of Invertebrate Endangered invertebrates existing in the location. Species Number of Project Q . I The number of project threatened species Threatened of invertebrates which need to be Species mitigated. Number of Q . I The number of project threatened Threatened endangered species of invertebrates which Endangered need to be mitigated. Species Al i en Invasive B , I Whether it's possible to induce alien Species species of invertebrates to invade. Number of Q , I The number of endangered species of Bacteria Endangered bacteria existing in the location. Species Number of Project Q , i The number of project threatened species Threatened of bacteria which need to be mitigated. Species Number of Q , i The number of project threatened Threatened endangered species of bacteria which Endangered need to be mitigated. Species Al i en Invasive B , I Whether it's possible to induce alien Species species of bacteria to invade. Number of Q , i The number of endangered species of Fungi Endangered fungi existing in the location. Species Number of Project Q , I The number of project threatened species Threatened of fungi which need to be mitigated. Species Number of Q , l The number of project threatened Threatened endangered species of fungi which need Endangered to be mitigated. Species A l i en Invasive B , I Whether it's possible to induce alien Species species of fungi to invade. A i r Quality Temperature Q The temperature of the air. Humidity Q The humidity of the air. Gaseous Pollutants L The name of gaseous pollutants in the air. Suspended L The name of suspended particulate matter Particulate Matter in the air. Odors L The odors of the air. Upper A i r Ozone Greenhouse Effect B Whether there is any gas emission with Layer Gas Emission greenhouse effect. Ozone-depleting Substances B Whether there are any ozone-depleting substances in the upper air zone. Gust of Wind Wind Speed Q The velocity of the wind. Wind Direction L The direction of the wind. Fog Visibi l i ty Q The visible distance in the fog. Frost Frost Period L The period in a year during which there is frost. Snowfall Annual Average Snowfall Q The average snowfall in a year. Snowfall Period L The period in a year during which there is snowfall. Month with L The month in a year in which it has Maximum maximum snowfall. Snowfall Snowfall in Q The snowfall in the month which has Maximum maximum snowfall. Snowfall Month Rainfall Annual Average rainfall Q The average rainfall in a year. Month with L The month in a year in which it has Maximum Rainfall maximum Rainfall. Rainfall in Q The rainfall in the month which has Maximum Rainfall maximum rainfall. Month Month with L The month in a year in which it has Min imum Rainfall minimum rainfall. Rainfall in Q The Rainfall in the month which has Min imum Rainfall minimum rainfall. Month Severity of Freezing Severity of Freezing L In what degree is it frozen? Thawing Cycles Start Time L The start time of the thawing. End Time L The end time of the thawing. Temperature Average Temperature in Jan Q The average temperature in January. Average Temperature in Jul Q The average temperature in July. j Average Annual Temperature Q The average temperature in a year. Relative Humidity Average Annual Relative Humidity Maximum Annual Relative Humidity Min imum Annual Relative Humidity Q Q Q The average annual relative humidity in a year. The maximum relative humidity in a year. The minimum relative humidity in a year. 144 Annual Average Q The average annual atmospheric pressure Atmospheric Pressure Atmospheric Pressure in a year. Maximum Annual Q The maximum atmospheric pressure in a Atmospheric Pressure year. Min imum Annual Q The minimum atmospheric pressure in a Atmospheric Pressure year. Storm Annual Storm Period L The period in a year during which there is storm. Snow Avalanche Annual Avalanche Period L The period in a year during which there is snow avalanche. Floods Annual Flood L The period in a year during which there is Period floods. Drought Drought Existing B Whether drought is existing. Tornado Annual Tornado Period L The period in a year during which there is tornado. Typhoon Annual Typhoon Period L The period in a year during which there is typhoon. Hurricane Annual Hurricane Period L The period in a year during which there is hurricane. Hurricane Zone B Is the location in the hurricane zone? Tsunamis Tsunami Zone B Is the location in the tsunami zone? Botanical Disease Invasion of Al i en B J Whether there are alien disease invading? Disease Disease Name The name of the disease. Infector Name L,I What species are the infectors? Contagion Means L,I How the diseases are. Susceptible Species U What species are susceptible to these diseases? Zoic Disease Invasion of Al i en B,I Whether there are alien disease invading? Disease Disease Name L,I The name of the disease. Infector Name L,I What species are the infectors? Contagion Means L J H o w the diseases are. Susceptible Species L, I What species are susceptible to these diseases? Human Disease Invasion of Al i en B,I Whether there are alien disease invading? Disease Disease Name U The name of the disease. Infector Name U What species are the infectors? Contagion Means U How the diseases are. Susceptible Species L,I What species are susceptible to these diseases? Potentially A c i d Volume Q , I The volume of the potentially acid 145 Generating (PAG) Material Name L generating material. The name of potentially acid generating material. Metal Leachate ( M L ) Volume Name Q , i L The volume of the metal leachate. The name of metal. Toxic Contaminated Site Site Name Toxic Material Name Contaminated Volume Contaminated Area L L Q Q The name of the contaminated site. What's name of the toxic material? The volume of the contaminated material. The area of the contaminated area. Solid Toxic Waste Volume Recyclable Q , l B The volume of the solid toxic waste. Is this solid toxic waste recyclable? Liquid waste discharges and sewages Volume Liquid Name Recyclable Q , i L B The volume of the liquid waste discharges and sewages. What's the name of the liquid? Is this liquid waste recyclable? Biotic Waste Volume Waste Name Q , i L The volume of the biotic waste. What's the name of the biotic waste? Dumping and Landfillings Volume Q , i The volume of the dumping and landfillings. Table A I L 2, Attribute definition of social components at the entity level of Standard E B S . Components Attributes Type Definition First Nation Interest First Nation Name Interest Description L L The name of the first nation. The description of the first nation interest. Noise Noise Level Q The level of the noise. Vibration from traffic Frequency Vibration Swing Q Q The frequency o f the vibration from traffic nearby. The vibration swing of the vibration from traffic nearby. Traffic / Transportation Congestion Rush Hour Average Waiting Time Per km in Rush Hour L Q The table of rush hour in a day in this community. Average waiting time per km in rush hour in this community. Community Access Community Severance B Whether the project w i l l create a barrier to movements between different parts of 146 previously integral units like residential communities, farms or golf courses. Recreation Recreation L What are the recreation activities? Activities Area Occupied Q The area occupied by the recreation activities. Average Number Q Average number of people who attend of People Attended these recreation activities simultaneously. Parks Name of Park L The name of the park. Area Q The area occupied by the park. Emergency Services Availabili ty Efficiency B B Whether the emergency service is available in this community? ' Is the emergency service efficient? Public Health Existing Epidemic Frequently Occurred Disease B L Is there any existing epidemic? What's the frequently occurred disease? Accidents and Malfunctions Frequency of Accidents and Malfunction L What's the frequency of accidents and malfunction? Cemeteries, Schools, Place of worship Area Age Q Q The area occupied by the cemeteries, schools and place of worship. What's the age of the cemeteries, schools, and place of worship? Community Events Community Education Service Important Event Date Professional Training L B The important event data in this community. Whether the community has professional training program which can be available to the project. Civ ic Safety Safety B Is it safe enough in this community? Utilities Drink Water B Is drink water available in this Availability Drink Water Price Q community? What's the price of drink water? Industrial Water B Is industrial water available in this Availabili ty Industrial Water Q community? What's the price of industrial water? Price Electricity Power Availability Electricity Price Gas Station Gas Price B Q B Q Is electricity power available in this community? What's the price of electricity? Is there gas station in this community? What's the price of the gas? Telephone Line Telephone Rate Internet Cable B Q B Is telephone line available in this community? What's the price of the telephone call? Is internet cable available in this 147 community? Internet Cable Rate T V Cable T V Cable Rate Q B Q What's the price of internet cable service? Is T V cable available in this community? What's the price of T V cable service? Space and Land Use Impact (Surface and Sub-surface) Degradation of Soil Structure Desertification Soil Loss Land Reclamation B B B B Whether the soil structure w i l l be degraded by space and land use. Whether there is desertification due to the space and land use. Whether there is any soil loss due to the space and land use. Whether there is land reclamation. Commercial Area Area Q The area occupied by the commercial area. Population Density Q What's the population per square meter? Slums Area Population Density Q Q The area occupied by the slums. What's the population per square meter? Environmental Infrastructure Availability of Sewage Facility Availability of Sanitation Facility Availability of Solid Waste Management Emissions and Waste Discharge B B B B Is there any sewage facility? Is there any sanitation facility? Is there any solid waste management program? Is there any emissions and waste discharge? Population and Demography Local Population Q What's the local population? Social Instability Instability B Is there any unstable social factors? Wealth Distribution Uniform B Is the wealth distributed uniformly in the society? Other Construction Activities Construction Project Name Type of Construction Activi ty Start Date of the Construction Activity End Date of the Construction Activi ty L L L L The name of the construction project nearby. What type of projects is it? The start date of the project nearby. The end date o f the project nearby. Land Use in other Settlements Name of Settlement Type of Settlement Area L L Q The name of the settlement nearby. What type is this settlement? The area occupied by this settlement. 148 Heritage Resource Name Creation Era Site Area Current State L L Q L What's the name of this resource? When was it created? The area occupied by this heritage. Is it destroyed, partially destroyed or well protected? Archeology Site Resource Name Creation Era Site Area Current State L L Q L What's the name of this resource? When was it created? The area occupied by this archeology site. Is it destroyed, partially destroyed or well protected? Landscape Townscape Scenic Views and Vistas Evaluation of Landscape Evaluation of Townscape Evaluation of Scenic and Vistas L L L Is it an excellent, good or bad landscape? Is it an excellent, good or bad townscape? Are they excellent, good or bad scenic and vistas? Table A I L 3, Attribute definition of economic/financial components at the entity level of Standard E B S . Components Attributes Type Definition G D P G D P Value Q The G D P value for this economic area. CPI CPI Value Q The CPI value for this economic area. Private and Government Consumption Annual Private Consumption Annual Government Consumption Q Q Annual private consumption amount in this economic area. Annual government consumption amount in this economic area. Special Construction Index Name of Index Value of Index L Q The name of the special index for construction economics.. The value of the special index. Monetary Inflation Current Annual Inflation Rate Current Monthly Inflation Rate Q Q The current annual inflation rate in this economic area. The current monthly inflation rate in this economic area. Economic Growth Current Annual G D P Growth Rate Current Monthly G D P Growth Rate Q Q The current annual G D P growth rate in this economic area. The current monthly G D P growth rate in this economic area. Foreign Exchange Rate and Reserves Current Foreign Monetary Reserves Exchange Rate Q Q The amount of current foreign monetary reserves. The foreign exchange rate. 149 Capital Movement Restriction L , The description of the restriction of Restriction Description capital movement by government. A / E / C firms client or Average Archi . Q The average ratio of architecture tender owner relationship Tender Number / number versus project number. competition Project Quality of Architecture L The assessment of architecture firm. Is it good or not so good? Average Eng. Q The average ratio of engineer tender Tender Number / number versus project number. Project Quality of L The assessment of engineer firm. Is it Engineer good or not so good? Average Contr. Q The average ratio of contractor tender Tender Number / number versus project number. Project Quality of L The assessment of contractor firm. Is it Contractor good or not so good? Construction Availability of B Can all o f the construction material be Materials Material procured at local market? Quality of Material L Do the materials have good quality? Skilled and Unskilled Availability of B Are the unskilled workers available at the Workers Unskilled Workers local market? Quality of Unskilled Workers L What's the quality of the unskilled workers available? Availability of B Are the skilled workers available at the Skilled Workers local market? Quality of Skilled L What's the quality of the skilled workers Workers available? Labor Cost/ Productivity Average Skilled Q The average ratio of labor cost versus Labor Cost/ Productivity Average Unskilled L / Cost Productivity Q productivity for skilled workers. The average ratio of labor cost versus productivity for skilled workers. Construction Equipment Availability of Construction Equipment Quality of Construction Equipment B L Are the construction equipments available at the local market? What's the quality of the construction equipments available? Efficiency of B Is the logistics system efficient for Logistics Constr. Material Logistics procurement of construction material? Efficiency of Con. B Is the logistics system efficient for Equipment procurement of construction machinery? 150 Logistics Medium and Long Term Financing Abi l i ty for Medium Term L Is it very difficult, difficult or easy to obtain medium term financing? Financing Abi l i ty for Long Term Financing L Is it very difficult, difficult or easy to obtain long term financing? Tax and Non-tax Incentives Tax Incentives Non-Tax Incentives L What tax incentives the government issued for financing? What non-tax incentives exist for financing? Market Volume Current Market Volume Q H o w many projects are available for construction? Bidding Project Volume Bidding Project Volume Q H o w many projects are available for construction through bidding process? Agriculture Land Reserve Area for Agriculture Land Q The area for agriculture land reserve which is a limited source. Reserve Agriculture Operations Impact of Pesticides Nitrogen Phosphate Fertilizers Impact Impact of Dense Livestock L . L L What's the impact of pesticides used by agriculture operations? What's the impact of Nitrogen Phosphate Fertilizers used by agriculture operations? What's the impact of dense livestock? Aquaculture Number of Aquarium Q The number of aquarium in this area. Economic Loss due to Lost Value Q The amount of economic loss because of Deforestation the deforestation. Annual Tourist Q The annual tourist population increase Tourism Boom Population Increase Rate rate in the area where the project is. Trade Market Flourish B Is the local market flourishing? Natural Resources (coal, oi l , gas, wind power, etc.) Natural Resources Availability Natural Resource B L Are there any natural resources in this area? What are the available natural resources Supply Structure in this area? Price of Natural L What's the price of these natural Resources resources? Residential and Community Property Name of Property Property Owner Property Value L L Q What's the name of the property? Who is the owner of the property? What's the value of the property? Offices and Public Name of Building L What's the name of the building? Buildings Owner of Building L Who is the owner of the building? Building Value Q What's the value of the building? 151 Third Party Claims (Such as claim due to remediation) Name of Claimant Amount Claimed Reason for Cla im Result L Q L L The name of the claimant. The amount the claimant claimed. The reason for claim. The result of the claim. Table A l l . 4, Attribute definition of political components at the entity level of Standard E B S . Components Attributes Type Definition Political Continuity Political Continuity L The assessment of the government and governmental policy's continuity. Is it good, normal or bad? Enforceability of Contract Contract Enforceability L The assessment of the enforceability of contract in the society. Is it good, normal or bad? Government Incentives Government Incentives for Construction L What are the government incentives for construction industry? Military Occupied Area Area Q The area occupied by the military in the area where the project is. Military Restriction Mili tary Restriction L What the restriction the project has from military? Strike Occurrence Frequency Q The average times of strikes in a year. Riot Occurrence Frequency Q The average times of riots in a year. Terrorist act Occurrence Frequency Q The average times of terrorist act in a year. C i v i l Strife and Armed Conflict Occurrence Frequency Q The average times of c iv i l strife and armed conflict in a year. War Existing War B Whether there is existing war. Federal Government Authority Name of Authority Impact of Authority L What's the name of this authority? What impact w i l l this authority has on the project? Province Government Authority Name of Authority Impact of Authority L What's the name of this authority? What impact w i l l this authority has on the project? Local Government Authority Name of Authority Impact of Authority L What's the name of this authority? What impact w i l l this authority has on the project? Procedure for Bidding and Design Approval Description of Procedure L Description of bidding and design approval procedure stipulated by the law. Livable Region Description of L The description of the regional strategic 152 Strategic Plan Plan Labor and Strike, Description of L Repatriation Related Juristic Restriction Rules plan which is important for project plan. The description of related juristic rules for labor and strike, repatriation, and restriction of these issues. Table A I L 5, Attribute definition of regulatory components at the entity level of Standard E B S . Components Attributes Type Definition Permits, Licenses and Permit Name L The name of issued permit. Issuing Permit Issuing L The authority which issued the permit. Authorizations Authority License Name L The name of issued license. License Issuing L The authority which issued the license. Authority Authorization L The name of issued authority. Name Authorization Issuing Authority L The authority which issued the authority. Changes in L The description of the changes in regulations, rules, Description of regulations, rules, guidelines and guidelines formulated Changes programs. and programs taken. New Regulatory Description of N e w Regulations L The description of new regulatory. 153 Appendix III Mitigation Measures for Environmental Impact and Risks Note: 1, This table contains some of mitigation measures for some environmental impact and risks. It neither contains the full list of mitigation measures for each issue, nor does it contain the full list of environmental impact and risks. 2, This table contains the name of the environmental issues, the description of environmental issue, whether they affect part of the project (local) or overall project (global), in which project phase they w i l l affect a project, what performance measures they w i l l affect a project, and their mitigation measures. NO. E N V I R O N M E N T A L I S S U E D E S C R I P T I O N O F E N V I R O N M E N T A L ISSUE L O C A L / G L O B A L P R O J E C T P H A S E P E R F O R M A N C E M E A S U R E S A F F E C T E D M I T I G A T I O N M E A S U R E S 1 Potentially A c i d Generating ( P A G ) Material Assess the potential for acid generating material. A c i d generating material can adversely affect freshwater and marine systems. Normally, it results from (i) blasting and exposure of rock cut faces and (ii) disposal of surplus rock. Local Construction, Maintenance Time, Cost, Safety Preconstruction investigation; minimize rock excavation; reuse P A G material for construction; shortcrete final rock cut surface; encapsulate it and treat any groundwater leachate generated from it; disposed of to designated site. 2 Metal Leachate ( M L ) Metal leachate loading, such as Aluminum and Copper loadings, resulting from blasting and exposure of rock cut faces can impact sensitive waterbodies. The severity of impact depends on the loading levels, physical pathways and the sensitivity of receptors. Local Construction, Maintenance Time, Cost, Safety Conduct a surface water monitoring program; preconstruction investigation; minimize rock excavation; shortcrete final rock cut surface; collect and treat runoff; line ditches with lime. To be Continued 1 5 4 Continued NO. 3 E N V I R O N M E N T A L I S S U E Flood D E S C R I P T I O N OF E N V I R O N M E N T A L ISSUE Problems associated with flood and insufficient design for flood mitigation. L O C A L / G L O B A L Local P R O J E C T P H A S E Design, Construction, Maintenance P E R F O R M A N C E M E A S U R E S A F F E C T E D Safety, Cost, Time M I T I G A T I O N M E A S U R E S Detailed peak flow estimation and detailed design; evaluate all the results from both rainfall-based methods and regional data methods to finally estimate a suitable design flow based on the reliability of input data, past events, historic high flow records, and professional experience. Construction dams as necessary. 4 Downstream Channel Processes Constructing new infrastructure or changes to existing infrastructure such as highway, bridge and culvert can potentially alter downstream channel processes by increasing channel erosion, increasing overbank flow, and increasing bedload movement in alluvial channels. Local Design, Construction, Maintenance Safety, Cost, Time Detailed investigation and design; assessment of the impact resulting from downstream channel processes. 5 Hydraulic Connectivity Improper hydraulic connectivity between upslope and downslope areas of the construction site can cause serious erosion and other damages to infrastructure. Proper connectivity measures have to be adopted to reduce adverse impacts. Local Design, Construction, Maintenance Safety, Cost, Time Permeable embankment; use of retention ponds and constructed wetlands to attenuate runoff rate from impervious area. Specifically for highway: direct highway runoff to bio-filtration swales along the road side thus ensuring water quality to lowland areas; and use of porous asphalt pavement. To be Continued 155 Continued NO. 5 E N V I R O N M E N T A L ISSUE Hydraulic Connectivity D E S C R I P T I O N OF E N V I R O N M E N T A L ISSUE Improper hydraulic connectivity between upslope and downslope areas of the construction site can cause serious erosion and other damages to infrastructure. Proper connectivity measures have to be adopted to reduce adverse impacts. L O C A L / G L O B A L Local P R O J E C T P H A S E Design, Construction, Maintenance P E R F O R M A N C E M E A S U R E S A F F E C T E D Safety, Cost, Time M I T I G A T I O N M E A S U R E S Permeable embankment; use of retention ponds and constructed wetlands to attenuate runoff rate from impervious area. Specifically for highway: direct highway runoff to bio-filtration swales along the road side thus ensuring water quality to lowland areas; and use of porous asphalt pavement. 6 Erosion and Sedimentation Erosion at the inlet and outlet of structures, at the base of abutments or foundations and at the road embankment; marine sediment transport dynamics at proposed barge-loading facility sites. Creek sedimentation can also induce problems. Local Design, Construction, Maintenance Safety, Cost, Time Open-bottom culvert; adequate erosion protection; berm drain outlets on cut batters could be designed to tail out into adjacent vegetated areas and disperse run off at non-erosive velocities; reduce the steepness of the major cut batters; timber windrows act as sediment barriers. 7 Strata Succession The impact on structure due to unexpected change in soil strata Local Construction, Maintenance Safety, Cost, Time Detailed site investigation; avoid locating the structure at the area where unexpected change in strata can easily happen. 8 Differing Site Conditions (DSC) Risk that the subsurface geology differs from the assumptions made in the initial design and cost estimation stages of the project. Local Construction Safety, Cost, Time Detailed site investigation. To be Continued 1 5 6 Continued NO. 9 E N V I R O N M E N T A L ISSUE Contaminated Soil D E S C R I P T I O N OF E N V I R O N M E N T A L ISSUE A n y contaminated soil which is found existing at the original construction site during construction. L O C A L / G L O B A L Local P R O J E C T P H A S E Construction P E R F O R M A N C E M E A S U R E S A F F E C T E D Safety, Cost, Time M I T I G A T I O N M E A S U R E S Monitoring construction activities especially the excavation of the original ground and replacing any contaminated soil found. 10 Highway Runoff Highway runoff contains the contaminated water due to winter maintenance (mainly road salt) and the continued use of the roadway where deposits of a wide variety of products are placed on the road surface from passing vehicles. The runoff flows along highway ditches, which may be directed to streams or lakes without treatment. Global Maintenance Safety, Cost Removal of roadside soils which have received runoff for a number of years and therefore may be contaminated. Sediment basins that capture all run-off and prevent it from flowing into local waterways. 11 Spillage Spillage of fuels, oils and chemicals through vehicular accident during project life cycle. Global Construction, Maintenance Safety, Cost Craft a dangerous goods spill response plan; appoint an environmental emergency response officer; construct sediment basins as necessary to capture spillage polluted run-off and prevent it from flowing into local waterways.. To be Continued 157 Continued NO. 12 E N V I R O N M E N T A L ISSUE Debris Torrents D E S C R I P T I O N O F E N V I R O N M E N T A L ISSUE The occurrence of debris torrents can damage or destroy the infrastructure. L O C A L / G L O B A L Local P R O J E C T P H A S E Construction, Maintenance P E R F O R M A N C E M E A S U R E S A F F E C T E D Time, Cost, Scope, Safety M I T I G A T I O N M E A S U R E S Construction of barrier walls at selected locations with ongoing management of debris torrent risk through continuation of progressive alert program; inlet gratings; high flow culverts; debris basins; protective structures and creek channelization works. 13 Bedload Movement The frequent conveyance of channel material during significant flow events. Local Construction, Maintenance Cost and Safety Maintaining a stable flow regime consistent with natural conditions. 14 Earthquakes Infrastructure destroyed by earthquakes. Global A l l Phases Time, Cost, Scope, Safety N e w earthquake resistant design and construction; retrofit existing infrastructures. .15 Slope Stability This risk can arise from global (slip) failure, undercutting (scour) of slopes by water, or total collapse of structures due to failure of underlying soils. Local Construction, Maintenance Time, Cost, Scope, Safety Application of conservative design standards; attention to, or alteration of, drainage regimes during design; appropriate hydraulic and hydrologic analyses; localized redirection of drainage away from scour-susceptible areas; weak or soft soils identified during geotechnical investigation and treated during construction; temporary shoring of slopes, using techniques such as soil anchoring, shotcrete, mesh, temporary retaining walls and other methods; smooth blasting techniques in the tunnel. To be Continued 158 Continued NO. 16 E N V I R O N M E N T A L I S S U E Rock Fal l D E S C R I P T I O N OF E N V I R O N M E N T A L ISSUE Problems associated with rock fall from rock cut. L O C A L / G L O B A L Local P R O J E C T P H A S E Construction, Maintenance P E R F O R M A N C E M E A S U R E S A F F E C T E D Cost, Safety M I T I G A T I O N M E A S U R E S A program of rock slope stabilization; innovative construction practice. 17 Snow Avalanche A n avalanche wi l l block, impair or destroy the infrastructure. Local Construction, Maintenance Time, Cost, Safety Relocate project location away from sloughing snow area; design steep rock and soil cuts that tend to slough regularly thus reducing the likelihood of larger accumulations of snow affecting infrastructure. 18 Wildl i fe Habitat and Vegetation Wildlife habitat loss, fragmentation and degradation due to a project. The removal of vegetation. Local Construction, Maintenance Time, Cost Minimize construction areas; use suitable construction time window; manage interactions between project personnel and wildlife; minimize the duration of construction; re-vegetate with native species; create rock pile habitat; verifiably survey rare and sensitive species; compensate for loss of rare ecosystem habitat. 19 Fisheries and Aquatic Habitat Fisheries and aquatic habitat loss, fragmentation and degradation due to a project. Local Construction, Maintenance Time, Cost Compensation for loss of rare ecosystem habitat; careful planning and early design changes in combination with a reduced project scope. To be Continued 159 Continued NO. E N V I R O N M E D E S C R I P T I O N O F L O C A L / P R O J E C T P E R F O R M A N C E M E A S U R E S A F F E C T E D M I T I G A T I O N M E A S U R E S Minimize quantities handled on stockpiles N T A L I S S U E E N V I R O N M E N T A L ISSUE G L O B A L P H A S E A i r quality degradation due to exhaust and transferred between construction equipment; minimize the time that surface areas are exposed; water or cover exposed surfaces and stockpiles; cover the load of haul/dump trucks; ensure that opacity levels 20 A i r Quality output, dust, Greenhouse Gases (GHGs) and emitted air contaminants from construction material manufacturers. Global Construction, Maintenance Cost, Safety from exhaust are within acceptable levels; and assess air quality near residences. Ground movement due to demolition, pile driving, and forced ramming. Use static crushing; chemical breaking; 21 Ground Local Construction Time, Cost hydraulic/ static press in pile equipment; electric machine, static compacting. Concentrate the noisiest activities (e.g., rock drilling, pile driving) within the shortest daytime construction period; possible 22 Noise Noise exposures at sensitive locations including the noise from both Global Construction, Maintenance Cost, Safety application o f noise shed, noise-control earth berms, and noise barriers; construction scheduling measures that minimize noise impacts on local residents; quiet construction material (e.g., open-graded asphalt for highway); operation control (e.g., low speed zone of a highway). construction and operation activities. To be Continued 160 Continued NO. 23 E N V I R O N M E N T A L ISSUE Traffic / Transportation D E S C R I P T I O N OF E N V I R O N M E N T A L ISSUE The impact of traffic disruptions and traffic jams during the construction phase. L O C A L / G L O B A L Local P R O J E C T P H A S E Construction P E R F O R M A N C E M E A S U R E S A F F E C T E D Safety, Cost, Time M I T I G A T I O N M E A S U R E S Use detours to provide a by-pass route around construction areas; schedule construction works to avoid times when traffic volumes are higher, including seasons, day-of-week and hours of the day. 24 Community Access (Connectivity) Potential impacts on current road access to, from and across the community by a project. Local Construction, Maintenance Cost, Safety Consult and work closely ;with key stakeholders and community advisory groups to ensure that adverse impacts are identified and design features are developed to provide safe pedestrian, cyclist and vehicular movement to, from and across the community. 25 Archaeology Adverse impact on the archaeology and heritage site. Local Design, Construction Cost, Time Thorough investigation; change o f project locations; compensation measures. 26 First Nations Interest The adverse impact of First Nation's interest on a project. Local A l l Phases Time, Cost, Scope Specific and directed consultation program; participation in the project by First Nations; stakeholder consultation program. 27 Changes in Regulations Changes in environmental regulations. Global Construction, Maintenance Cost, Time, Scope Investigate and predict any changes of environment regulations attributable to a project; scrutinize how change to be handled in contractual language. 161 

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