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Rainwater recycling on green roofs for residential housing : case studies in Richmond, British Columbia;… Kong, Yuewei 2008

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RAINWATER RECYCLING ON GREEN ROOFS FOR RESIDENTIAL HOUSING - Case Studies in Richmond, British Columbia; San Antonio, Texas; and Toronto, Ontario  by  YUEWEI KONG  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER of ADVANCED STUDIES in LANDSCAPE ARCHITECTURE  in  THE FACULTY OF GRADUATE STUDIES  THE UNIVERSITY OF BRITISH COLUMBIA Vancouver April 2008 © Yuewei Kong  Abstract Stormwater is the component of runoff that is generated by human activities, and has gradually become a key issue in achieving sustainability in urban environments. When vegetation and soils are replaced with roads and buildings, less rainwater infiltrates into the ground or is taken up by vegetation, and more becomes surface runoff. A greater area of impervious surfaces leads to increased stormwater runoff volume and velocity, and consequently increases the risk of flooding and erosion. Being able to reduce stream flows and pollution of surface flows, green roofs are one technology that may help in alleviating this storm water crisis. This thesis developed a different and effective methodology for quantifying the effects of green roofs on stormwater runoff and calculating the runoff volume and rate for residential housing communities before and after applying green roofs. The method utilizes local climate data like rainfall and evapotranspiration rate, the water use properties of vegetation like crop coefficients of plants, and the areas of impervious surfaces; and then compares the different effects of green roofs in different locations having disparate climatic conditions. It was found that the best way to achieve zero runoff was to green a portion of the total rooftop area and disconnect all impervious surfaces. Implications of this methodology on city planning and site design and for future research are then discussed.  ii  Table of contents Abstract ^ Table of Contents ^  iii  List of Tables ^ List of Figures ^  vii  List of Equations ^  ix  Acknowledgements ^ Part A: Calculation of Stormwater Runoff for Green Roofs Chapter 1 Introduction of Green Roofs 1.1 Introduction ^ 2 5 1.2 Classification of green roofs ^ 6 1.3 Benefits of green roofs ^ 6 1.3.1 Stormwater management ^ 1.3.2 Amenity and aesthetic improvement 7 1.3.3 Building envelope protection and life extension ^ 7 1.3.4 Creating habitat for plants, birds, and insects ^ 9 1.3.5 Effects on microclimate ^ 10 Chapter 2 Calculation Methods and Examples 2.1 Calculation objects ^ 2.2 Calculation methodology ^ 2.2.1 Methods to compute runoff ^ 2.2.2 Calculation methods for sites with connected impervious surfaces and disconnected impervious surfaces ^  13 14 14 20  2.3 Calculation examples ^ 23 2.3.1 Data input for calculations ^ 23 2.3.2 Calculations for sites with connected impervious surface ^ 23 2.3.3 Calculations for sites with disconnected roofs ^ 25 2.3.4 Calculations for sites with disconnected impervious surfaces ^ 26 2.3.5 Calculations for sites with green roof systems ^ 28 2.3.6 Calculations for sites with green roof systems and 33 disconnected impervious surfaces ^ Chapter 3 Selected Sites for Calculations 3.1 Introduction of Transect Zone ^ 3.2 Analysis of selected sites ^  36 37  iii  Chapter 4 Calculation Results for Stormwater Runoff Quantity and Quality 4.1 Calculation results — Quantity of stormwater runoff ^ 4.1.1 Storm water runoff calculation results for Richmond, BC ^ 4.4.2 Storm water runoff calculation results for San Antonio, TX ^ 4.1.3 Storm water runoff calculation results for Toronto, ON ^  52 52 62 71  4.2 Calculation results — Quality of stormwater runoff ^ 80 4.2.1 Reduction in Concentration of Contaminants ^ 81 4.2.2 Reduction in Runoff Volume ^ 84 4.3 Summary for Green Roofs 1, 2, 3 and 4 ^  88  4.4 Conclusions for maximum deficits ^ 91 4.4.1 Relationship between maximum deficits and soil type 91 4.4.2 Maximum deficits and substrate design for green roofs ^ 92 4.5 Calculated Runoff vs. Real Runoff^ 94 4.5.1 Calculated Evapotranspiration (ET) vs. real ET ^ 94 4.5.2 Impacts of roof pitch ^ 95 4.5.3 Impacts of soil materials ^ 96 Chapter 5 Conclusions for Calculation Results 5.1 Effects of precipitation and impervious surfaces ^ 100 5.2 Conclusions for Green Roofs 1, 2, 3 and 4 ^ 101 5.3 Conclusions for Richmond, BC; San Antonio, TX; and Toronto, ON ^ 102 Part B: Tools, Strategies, Solutions for Designers  Chapter 6 Best Case Scenarios for the Rezoning Site in Richmond, BC 6.1 Objectives ^ 6.2 Analysis of the selected rezoning site in Richmond ^ 6.2.1. Location map and site context ^ 6.2.2. Concept development plan ^ 6.2.3. Best case scenario ^  106 106 106 107 110  6.3 Summary ^  119  Part C: Conclusions and Discussions  Chapter 7 Conclusion and Discussion 7.1 Conclusion ^ 122 7.2 Discussion ^ 124 7.2.1. Implications for the practice of city planning for site design ^ 124 7.2.2 Gaps and future research opportunities ^ 124 125 7.2.3. Shortcomings of the research ^ References ^  127  iv  Lists of tables Table 1-1: Median daily temperature fluctuation of the roof membranes on Field Roofing Facility in Ottawa ^  9  Table 1-2: Rooftop temperature measured at noon on a typical summer day on Field Roofing Facility in Ottawa ^  11  Table 2-1: Runoff curve numbers for urban areas ^  16  Table 2-2: Hydrologic Soil Groups ^  17  Table 2-3: Procedure for calculating stormwater runoff (Q) ^  17  Table 2-4: Calculation example of runoff rate for sites with connected ^24 impervious surfaces ^ Table2-5: Calculation examples of runoff rates for sites with disconnected roofs ^ 25 Table2-6: Calculation examples of runoff rates for sites with disconnected impervious surfaces ^  27  Table2-7: Plants used for the calculation of stormwater runoff on green roofs 29 Table2-8: Kc of green roofs ^  30  Table2-9: Calculation examples of runoff rates for sites with green roofs ^ 31 Table2-10: Calculation examples of 10-day water balance for green roofs ^ 32 Table 4-1: Selected residential sites in Richmond, BC ^  53  Table 4-2: Runoff rates by cover types in Richmond, BC ^  53  Table 4-3: Total runoff rates from selected residential sites in Richmond, BC (Average year) ^  55  Table 4-4: Runoff rates from traditional roof and green roofs, Richmond, BC ^  56  Table 4-5: Total runoff rates when applying green roofs: selected residential sites in Richmond, BC in an average year ^ 58 Table4-6: Calculation of water balance for Green Roof 1, Richmond, BC ^ 59 Table4-7: Calculation of water balance for Green Roof 2, Richmond, BC ^ 60 Table4-8: Calculation of water balance for Green Roof 3, Richmond, BC ^ 61 Table4-9: Calculation of water balance for Green Roof 4, Richmond, BC ^ 62 Table 4-10: Selected residential sites in San Antonio, TX ^  63  Table 4-11: Runoff rates by cover types in San Antonio, TX ^  64  Table 4-12: Total runoff rates from selected residential sites in San Antonio, TX (Average year)  65  Table 4-13: Runoff rates from traditional roof and green roofs, San Antonio, TX ^  66  Table 4-14: Total runoff rates when applying green roofs- selected residential sites in San Antonio, TX (average year) ^  67  ^  Table4-15: Calculation of water balance for Green Roof 1, San Antonio, TX ^ 68 Table4-16: Calculation of water balance for Green Roof 2, San Antonio, TX ^ 69 Table4-17: Calculation of water balance for Green Roof 3, San Antonio, TX ^ 70 Table4-18: Calculation of water balance for Green Roof 4, San Antonio, TX ^ 71 Table 4-19: Selected residential sites in Toronto, ON ^  72  Table 4-20: Runoff rates by cover types in Toronto, ON ^  73  Table 4-21: Total runoff rates from selected residential sites in Toronto, ON (Average year) ^  74  Table 4-22: Runoff rates from traditional roof and green roofs, Toronto, ON ^ 75 Table 4-23: Total runoff rates when applying green roofs- selected residential sites in Toronto, ON (average moist year) ^ 76 Table 4-24: Calculation of water balance for Green Roof 1, Toronto, ON ^ 77 Table 4-25: Calculation of water balance for Green Roof 2, Toronto, ON ^ 78 Table 4-26: Calculation of water balance for Green Roof 3, Toronto, ON ^ 78 Table 4-27: Calculation of water balance for Green Roof 4, Toronto, ON ^ 80 Table 6-1: The areas of impervious and pervious surfaces for the redevelopment plan ^  109  Table 6-2: Calculated runoff rates and runoff volume from sites with connected impervious surfaces — rezoning area (average moist year 2004) ^ 111 Table 6-3: Calculated runoff rates and runoff volume from sites with Green Roofs 1, 2, 3, and 4 and connected impervious surfaces — rezoning area (average moist year 2004) ^ 112 Table 6-4: Table 6-4: Total evapotranspiration (ET) volume — Green Roofs 1, 2, 3, and 4 (average moist year 2004) ^ 114 Table 6-5: Calculated runoff rates and runoff volume from sites with Green Roofs 1, 2, 3 and 4, and disconnected impervious surfaces — rezoning area (average moist year 2004) ^ 115 Table 7-1: Collective summaries  122  vi  Lists of figures Figure 1-1: Comparison of the daily maximum and minimum membrane temperatures on Field Roofing Facility in Ottawa ^  8  Figure 2-1: Runoff process from sites with connected impervious surfaces ^  20  Figure 2-2: Runoff process from sites with disconnected roof surfaces ^ 21 Figure 2-3: Runoff process from sites with disconnected roof surfaces ^ 21 Figure 2-4: Runoff process from green roofs ^  22  Figure 3-1: Selected residential sites in Richmond, BC, San Antonio, TX and Toronto, ON ^  38  Figure 4-1: Precipitation (1995-2004) in Richmond, BC ^  52  Figure 4-2: Precipitation (1997-2006) in San Antonio, TX ^  63  Figure 4-3: Precipitation (1997-2006) in Toronto, ON ^  72  Figure 4-4: Recommended event mean concentrations by land use for pollutant types ^  83  Figure 4-5: Recommended event mean concentrations by land use for heavy metals ^  83  Figure 4-6: Stormwater runoff from the selected high-density Urban Core Zone in the average moist year ^  86  Figure 4-7: Stormwater runoff from the selected medium-density Urban Center Zone in the average moist year ^  86  Figure 4-8: Stormwater runoff from the selected low- to medium-density General Urban Zone in the average moist year ^  87  Figure 4-9: Stormwater runoff from the selected low-density Suburban Zone in the average moist year ^  87  Figure 4-10: Annual rooftop runoff reduction - Green Roof 1 ^  88  Figure 4-11: Maximum deficits - Green Roof 1 ^  88  Figure 4-12: Annual rooftop runoff reduction - Green Roof 2 ^  89  Figure 4-13: Maximum deficits - Green Roof 2 ^  89  Figure 4-14: Annual rooftop runoff reduction - Green Roof 3 ^  90  Figure 4-15: Maximum deficits - Green Roof 3 ^  90  Figure 4-16: Annual rooftop runoff reduction - Green Roof 4 ^  91  Figure 4-17: Maximum deficits - Green Roof 4 ^  91  Figure 4-18: Saturation, Field Capacity, and Wilting Point. ^  92  Figure 4-19: (a) Crushed building rubble; (b) LECA -- Light expanded clay granules) ; (c) Performance of plants in summer ^  97  Figure 5-1: Stormwater runoff vs. precipitation — Richmond, BC ^  100  vii  Figure 5-2: Stormwater runoff vs. precipitation — San Antonio, TX ^ 100 Figure 5-3: Stormwater runoff vs. precipitation — Toronto, ON ^  100  Figure 6-1: Location map and site context ^  107  Figure 6-2: Concept development plan for area "B" ^  108  Figure 6-3: Development plan for area "B" ^  109  Figure 6-4: Perspective rendering of development plan for area "B" ^ 109 Figure 6-5: Model of site with connected impervious surfaces ^  110  Figure 6-6: Model of site with connected impervious surfaces with green roofs ^  112  Figure 6-7: Typical build-up for sloping extensive green roofs ^  113  Figure 6-8: Model of site with disconnected impervious surfaces with green roofs ^  116  Figure 6-9: Direction of runoff — green roofs ^  117  Figure 6-10: Direction of runoff — pathways ^  117  Figure 6-11: Direction of runoff —parking lots and cul-de-sacs ^  118  Figure 6-12: Permeable paving for parking stalls ^  118  viii  Lists of equations 1. The Runoff Curve Number (CN) equation (Q) ^  15  2. Initial abstraction (la) ^  15  3. Potential maximum retention after runoff begins (S) ^  15  4. Evapotranspiration (ET) ^  19  5. Reference evapotranspiration (ETref) ^  19  ix  Acknowledgements Foremost, I would like to thank my supervisor, Daniel Roehr, who has been very patient with me, always encouraging me and pushing me forward. He has given me an enormous amount of help and teaching from the earliest stages of this work. Daniel has provided me valuable advice, keeping me on the right track by helping me be more precise and specific, and teaching me how to focus on the major questions and dig deeply into them to work out the answers. The first step is always hard. Thanks go to Patrick Mooney, the MASLA program director and also my major advisor. He gave me good suggestions in the beginning of my MASLA program, helping me come up with the thesis topic, introducing me to Daniel, my supervisor, and providing me with sound advice and important contacts in Richmond, BC, for developing a crucial part of the thesis. I would also like to thank Cynthia Girling, my committee member, for her patience and good advice, and Ronald Kellett, who helped me a lot in the beginning phase of the thesis and gave me very good suggestions about the methodologies that I later employed. I also appreciate Cecilia Achiam (Senior Coordinator) and Sara Badyal (planner) at the City of Richmond, for providing me the valuable information of a rezoning site in Richmond as a case study. Special thanks to Don Burger, who proofread this thesis and made it more comprehensive and explicit. I appreciate and won't forget your help. Thank you to my fellow graduate students Jon Laurenz, Jone Belausteguigoitia, and Vikas Tanwar, for all their help and encouragement during my MASLA studying. The last but not the least, I want to thank all my family and friends for their love and support, especially Jessica. For me, your support and encouragement are always my motivation, and I will keep going forward.  PART A.  CALCULATION OF STORMWATER RUNOFF FOR GREEN ROOFS  Chapter 1  Introduction of^kook  .  1.1 Introduction of green roofs Due to population growth and urban development, open space and undisturbed lands have given way to encroachment from buildings and roads. Sealed with concrete and asphalt, these areas no longer experience water infiltration into the soil. Dark-colored rooftops and pavement absorb and store energy from the sun during the day and reflect it at night. The results are increased stormwater runoff; greater temperature differences between urban areas and open, undisturbed land (known as the urban heat island effect); altered weather patterns; and a loss of greenery in metropolitan areas leading to an overall loss in biodiversity and reduced sustainability. An increase in impervious cover area results in a greater amount of runoff, because there are fewer natural places that can collect rainwater and allow it to soak into the ground; and the use of curbs and gutters, storm sewers and concrete channels can accelerate the velocity of surface flows. The increased volume and velocity of the water increases the risk of flooding downstream and erosion. Flooding and erosion can cause both economic and social losses, as they will result in damage to properties and infrastructure, a loss of land resources such as arable land, and injury or death to people living in and around floodplain. (Stephens, K. A., 2002.) Increased urban temperatures can affect public health, the environment, and the amount of energy that consumers use for summertime cooling. Higher temperatures can accelerate the chemical reaction that produces ground-level ozone, or smog, while summertime heat islands increase energy demand for air conditioning, raising power plant emissions of harmful pollutants (Frumkin, H., 2001). The urban heat island may also increase cloudiness and precipitation in the 2  city and result in altered weather patterns, as a thermal circulation sets up between the city and surrounding region. Altered weather patterns bring changes in rainfall; increases in crop vulnerability to infection, pest infestations, and choking weeds; and eventually be detrimental to agricultural interests. (Rosenzweig, C. 2001). Green roofs can provide a partial solution to these problems. Vegetation on green roofs can reduce peak stormwater runoff by reducing the rate at which rainwater reaches the ground level, and vegetated surfaces can be highly permeable, which further reduces the amount of stormwater runoff generated. Evapotranspiration from rooftop vegetation potentially cools the rooftop surface, reducing the amount of heat flow into the building via the roof. Vegetation can also alleviate air and water quality problems by filtering pollutants through the leaves and roots. Furthermore, vegetation in urban areas has been shown to increase mental well being, biodiversity and residential property values. (Bass, B. 2003) As a result, green roofs can simultaneously reduce stormwater runoff, improve runoff quality, building energy performance, air quality, aesthetics and urban ecosystem function, by taking advantage of the unused roof space available in many urban areas. In European countries such as France, Switzerland and Germany, green roofs are viewed as an effective strategy for increasing green space in cities, reducing stormwater runoff, and achieving other environmental benefits. (Bass, B. 2003) In cities like Vancouver (BC), Toronto (ON), and Guangzhou, China, with moderate to high land-use density and relatively low reserves of green infrastructure, green roofs should be widely used. Unfortunately for many cities in China, South America, and other developing regions, little research into green roofs has been conducted. Therefore, it is difficult to quantify the impacts of green roofs in regions where climatic conditions are disparate. 3  The present research focuses on the impacts of green roofs on stormwater runoff for residential housing, as residential housing usually makes up the largest portion of a city's land use map, excluding agricultural lands and undeveloped natural and open space; they consequently can provide the largest potential for identifying and applying the benefits of green roofs. The effects of green roofs will vary with different local climates. Different geographic locations have different climatic conditions, such as temperature, rainfall, wind velocity, solar radiation, relative humidity, and evaporation rate. These factors will influence the functioning of green roofs. The intensity and frequency of rainfall events can influence the stormwater runoff volume and the peak runoff rate; summer precipitation rates can influence the performance of green roof vegetation; and temperature, solar radiation, wind speed, and relative humidity can influence the water that plants transfer into the air via evapotranspiration. By analyzing the functioning of green roofs, we can determine the factors that influence total runoff. It will then be possible to calculate the runoff volume with local climatic data, water use by vegetation type and water capacity of soils. This will ultimately lead to an evaluation of the potential benefits green roofs provide within the context of varying climatic conditions. This thesis will attempt to determine the effects that different climatic conditions have on green roof functioning. This thesis will also attempt to determine an appropriate methodology for quantifying the benefits of green roofs. This methodology will be evaluated under different climatic models to determine the relative benefits green roofs provide in a variety of scenarios. This will allow developers and designers to maximize the potential benefits of green roofs while minimizing the costs, thus creating a more efficient and attainable intervention. The refined methodology will finally be applied to a rezoning site in Richmond, BC. A range of green roofs will be tested on the same site to determine the most 4  appropriate application. The anticipated best case scenario for the rezoning site will be a higher-density building footprint that creates a minimum of stormwater runoff and improves stormwater runoff quality.  1.2 Classification of green roofs Green roofs can be divided into two categories: extensive and intensive. a. Extensive green roofs: Extensive green roofs are designed with minimal planting medium profiles and sometimes only a mineral substrate. The plants- normally mosses, succulents, herbaceous plants and grasses- are chosen for their ability to regenerate and maintain themselves over long periods of time, in addition to being able to withstand the harsh conditions of cold, heat, drought and wind. Native species are often preferred. Extensive green roofs do not necessarily require irrigation, and as they are often not accessible to the public, they have fewer human requirements, such as guardrails or aesthetic design. Extensive green roofs are the least expensive form of roof greening to implement and maintain. An extensive green roof is usually a single-layer system, with a soil depth between 5 and 15 cm and a weight increase of 72.6 to 169.4 kg per m 2 . (Peck, S. W., 1999.) b. Intensive green roofs: Intensive green roofs have greater planting medium depths in which any type of vegetation may grow, from turf and groundcovers to shrubs and trees. They are often accessible to people and activities and are often built in downtown areas where green space is limited. An intensive green roof can be considered a type of open space. They represent highly artificial environments compared to ground-based  5  gardens, requiring more irrigation, fertilizer, and care. Intensive green roofs are also more costly than extensive green roofs to build and maintain. They require a deeper layer of soil, typically 20 to 60 cm deep, with a weight increase of 290 to 967.7 kg per m 2 . (Peck, S. W., 1999.) Deeper soil allows more plant diversity, which leads to higher maintenance requirements than those for an extensive green roof. There are greater social and psychological benefits associated with intensive green roofs, however.  1.3 Benefits of green roofs Studies of green roofs have shown that both extensive and intensive green roofs can provide benefits for residential neighbourhoods such as stormwater management, amenity and aesthetic improvements, building envelope protection and lifetime extension, habitat creation for plants, birds and insects, and positive microclimatic effects.  1.3.1. Stormwater management a. Peak flow reduction: A study conducted on the Vancouver Public Library's green roof with a 350mm (14") soil layer- plus vegetation- showed that the green roof was able to reduce peak flows by over 80% during the summer months when the roof is dryer and the rainfall events are typically smaller (<2 mm/ hr). The green roof reduced rainwater runoff by approximately 30% during smaller winter rain events (2-6mm/hr) and by less than 5% for larger, more severe events (>6mm/hr). (Johnston, C., 2004.) b. Delay in peak flow of runoff: A study at Michigan State University was 6  conducted on a simulated green roof platform with a 25mm(1") soil layer growing with Sedum, plus a 15mm(5/8") Xero Flor XF108 drainage layer and a 7.5mm Xero Flor XF158 water retention fabric. During a 14-month period, there were 26 light (<2 mm/hr) rain events, 30 medium (2-6mm/hr) rain events and 27 heavy (>6mm/ hr) rain events. On average, green roof watersheds detained runoff for 55 minutes after inception of the storm during a light rain event (<2mm/hr), 15 minutes during an average rain event (2-6mm/hr), and 5 minutes during a heavy rain event (>6mm/hr). (VanWoert, N.D., 2005.)  1.3.2. Amenity and aesthetic improvement a. Provision of recreational space: Green roofs can be developed on residential housing to provide children's play areas or recreational spaces for the exclusive use of residents. b. Increasing the value of the property and the marketability of the building as a whole, particularly for accessible green roofs: Trees can improve air quality by absorbing CO2, and can provide cooling shade, habitat for birds and windbreaks. American and British studies show that good tree cover increases the value of a home by 6-15%. (Peck, S. W., 1999.) c. Satisfying the aesthetic needs of people looking down upon the roof from adjacent buildings  1.3.3. Building envelope protection and life extension An exposed roof membrane absorbs solar radiation during the day and its temperature rises. The effects of UV radiation can accelerate the 7  aging process of the waterproofing membrane; this can compromise the quality of the waterproofing and the durability of the membrane. The green roof can protect the waterproofing membrane from exposure to UV radiation and extreme temperature fluctuations. (Scholz-Barth, K., 2004.)  Figure 1-1: Comparison of the daily maximum and minimum membrane temperatures on Field Roofing Facility in Ottawa (Nov. 2000 to Sep. 2001) Reference roof vs. Green roof -- Membrane Temperature (Nov 22, 2000 -- Sep 31. 2001) 8C 6C  -4C  Nov Dec Jan  ^  Feb  ^  Mar Apr May^Jun^Jul^Aug Sep 4.-4,--AT  max (Green Roof) (Green Roof)  --'--AT min  Source : Bass. B. and Baskaran, B. 2003.  Figure 1-1 compares the median daily membrane temperature fluctuation (daily maximum temperature - daily minimum temperature) of the Reference Roof and the Green Roof on (National Research Council Canada) NRC's Field Roofing Facility in Ottawa over a 22-month observation period. The exposed membrane in the Reference Roof experienced high daily temperature fluctuations, with a median fluctuations of 42-47°C (76-85°F). However, Table 1-1 shows that the  8  Green Roof experienced a reduced temperature fluctuation in the roof membrane to a median fluctuation of 5-7°C (9-11°F) throughout the year. (Liu, K. 2004.)  Table 1-1: Median daily temperature fluctuations of the roof membranes on Field Roofing Facility in Ottawa during the observation period (Nov 22, 2000 — Sep 30, 2002). (Liu, K. 2004.)  Median Daily Temperature Fluctuation (daily maximum temperature — daily minimum temperature) Observation^ period^Reference Roof^Green Roof^Ambient Membrane^Memberane Winter 2001  9^C (16^F)  6°^C (11^F)  10^C (18^F)  Spring 2001  46° C (83° F)  6°^C (11'^F)  13° C (23^F)  Summer 2001  47^C (84^F)  7° C (13° F)  12'^C (22°^F)  Fall 2001  23' C (41'^F)  5^C (9° F)  8^C (14^F)  Winter 2002  9°^C (16'^F)  7^C (13°^F)  9° C (16^F)  Spring 2002  42^C (76^F)  6° C(11 ^F)  10°^C (18°^F)  Summer 2002  47° C (84" F)  6^C (11'^F)  12^C (22° F)  1.3.4. Creating habitat for plants, birds, and insects  Green roofs can provide food, habitat, shelter, nesting opportunities and a safe resting place for animals, as this elevated urban ecosystem can afford protection from traffic noise, human intervention, and preying animals. (Scholz-Barth, K., 2004.) A study in Switzerland showed that green roofs can provide a beneficial habitat for animals. Spiders, beetles 9  and bird species using green roofs in Basel and Lucerne were surveyed over four years. 254 species of beetles, 74 species of spiders and 25 species of birds were recorded, including many rare species. (Boscoe, A. 2003.)  1.3.5. Effects on microclimate The evaporation and oxygen-producing effects of vegetation on rooftops can contribute to the improvement of the microclimate. a. Cooling the ambient air temperature: Through evaporation and transpiration, green roofs cool the surrounding air. Table 1-2 shows the rooftop temperatures measured at noon on a typical summer day at different levels between the Reference Roof and the Green Roof. The ambient air temperature on the green roof was much lower than the Reference Roof.  10  Table 1-2: Rooftop temperatures measured at noon on a typical summer day on Field Roofing Facility in Ottawa (Liu. K. 2006.)  600mm  Height Above  Reference Roof  Green Roof  Roof  Temperature  Temperature  600 mm (24 in  25°C  25°C  300mm  300 mm (12 in  26°C  23°C  200mm  200 mm (8 in)  28°C  25°C  100 mm (4 in)  32°C  28°C  50 mm (2 in)  37°C  27°C  100mm 50mm  Rooftop  b. Air quality improvement: Air is cleaned through the increased production of oxygen. Plants also tend to filter out fine airborne particles as air passes over them and settles on their leaf and stem surfaces. (Peck, S. W., 1999.) Studies show that treed urban streets have 10-15% fewer dust particles than similar streets without trees. In Frankfurt, Germany, a street without trees had an air pollution count of 10,000-20,000 dirt particles per litre of air and a treed street in the same neighbourhood had an air pollution count of less than a third of that amount. (Peck, S. W., 2003.)  11  Chapter 2  Calculation Methods and Examples  2.1 Calculation objects The total annual stormwater runoff from chosen residential sites before and after applying stormwater management techniques was calculated in this thesis. Total stormwater runoff includes runoff from impervious surfaces like roofs, sidewalks, roads, and parking lots, and pervious surfaces like lawns and parks. Many stormwater management solutions exist, including natural drainage systems and structural stormwater control systems. Natural drainage systems include native landscaping, open space, and wetlands. Structural stormwater controls include constructed wetland systems, bioretention areas, pervious pavement systems, vegetated swales, etc. However, stormwater management practices should strive to utilize the existing natural drainage system and require as little maintenance as possible. Permeable soils, wetlands, floodplains, and undisturbed vegetated areas can be used to reduce runoff, provide infiltration, filter pollutants and sediment, recycle nutrients, and maximize on-site stormwater storage. Further, natural drainage systems typically require little or no maintenance, and will continue to function many years into the future. (North Central Texas Council of Governments, 2006) One way to utilize the natural drainage system is to disconnect areas of impervious surfaces. (Mid-America Regional Council, 2007) In this thesis, the differences of stormwater runoff between residential sites with connected impervious surfaces and those with disconnected impervious surfaces was calculated. Green roofs are another way to reduce stormwater runoff. Therefore, how much of the total stormwater runoff from the chosen residential sites can be reduced when applying green roofs was also calculated. Scenarios for each residential site are shown as follows. The calculation methods for each scenario are described in section 2.3. 13  a. b. c. d.  Sites Sites Sites Sites  with with with with  connected impervious surfaces disconnected roofs disconnected impervious surfaces green roofs and disconnected impervious surfaces  Stormwater runoff is also dependent on how much rainfall occurs on-site. Therefore, total annual stormwater runoff from each chosen residential site during the wettest year, an average moist year and the driest year was calculated.  2.2 Calculation methodology 2.2.1. Methods to compute runoff Stormwater runoff can be created from impervious surfaces, semi-pervious surfaces like green roofs, and pervious surfaces. Impervious surfaces include roofs, roadways, sidewalks and parking lots. In this thesis, two methods were used to compute runoff from impervious surfaces, green roofs and landscaped areas: the Runoff Curve Number (CN) Method and the Evapotranspiration (ET) Method. The Runoff Curve Number (CN) Method is also known as Technical Release 55 (TR-55) by the United States NRCS (Natural Resources Conservation Service). The runoff Curve Number (CN) method (Cronshey, R. G., 1986), which presents simplified procedures for estimating runoff and peak discharges in small watersheds, was used to compute runoff from roofs, streets and landscaped areas. The Evapotranspiration (ET) Method was used to compute runoff from green roofs.  14  a. The Runoff Curve Number (CN) method i.  Runoff equation (Cronshey, R. G., 1986)  Q=  (P—Ia) 2 (P—Ia)+S  [eq. 1]  Where Q = stormwater runoff (in) P = rainfall (in) S = potential maximum retention after runoff begins (in) Ia = initial abstraction (in)  Initial abstraction (Ia) comprises all losses before runoff begins. This includes water retained in surface depressions; water intercepted by vegetation; evaporation; and infiltration. When initial abstraction (Ia) is greater than rainfall (P), stormwater runoff (Q) will be considered zero. la = 0.2S^  [eq. 2]  S is related to the soil and cover conditions of the watershed through  the CN. CN has a range of 0 to 100, and S is related to CN by: 1000 S = ^ 10 CN  [eq. 3]  Where CN = curve numbers  ii.  Curve Number (CN): The major factors that determine CN are the hydrologic soil group, cover type, treatment, hydrologic condition, and antecedent runoff condition.  15  Table 2-1 Runoff curve numbers for urban areas' Curve numbers for  Cover description Cover type and hydrologic condition  hydrologic soil group Average percent impervious areal  A  BCD  Fully developed urban areas (vegetation established) Open space (lawns. parks. golf courses. cemeteries. etc) 3. Poor condition (grass cover < 50%)  68  79  86  89  Fair condition (grass cover 50% to 75%)  49  69  79  84  Good condition (grass cover > 75%)  39  61  74  80  98  98  98  98  Paved; curbs and storm sewers (excluding right-of-way)  98  98  98  98  Paved; open ditches (including right-of-way)  83  89  92  93  Gravel (including right-of-way)  76  85  89  91  Dirt (including right-of-way)  72  82  87  89  Impervious areas: Paved parking lots, roofs, driveways, etc (excluding right-of-way) Streets and roads:  1.  Average runoff condition, and la = 0.2S.  2.  The average percent impervious area shown was used to develop the composite CNs. Other assumptions are as follows: impervious areas are directly connected to the drainage system, impervious areas have a CN of 98; and pervious areas are considered equivalent to open space in good hydrologic condition.  3. CN's shown are equivalent to those of pasture. Composite CN's may be computed for other combinations of open space cover type.  Source from: Cronshey, R. G., 1986  iii.^Hydrologic soil groups Soils are classified into hydrologic soil groups (HSGs) to indicate the minimum rate of infiltration obtained for bare soil after prolonged wetting.  16  Table 2-2: Hydrologic Soil Groups Hydrologic Soil Groups  Soil textures Description  Sand, loamy ^ Group A sand, or sandy loam  Soils have low runoff potential and high infiltration rates even when thoroughly wetted. They consist chiefly of deep, well to excessively drained sand or gravel and have a high rate of water transmission (greater than 0.30 in/hr).  Silt loam or loam  Soils have moderate infiltration rates when thoroughly wetted and consist chiefly of moderately deep to deep, moderately well to well drained soils with moderately fine to moderately coarse textures. These soils have a moderate rate of water transmission (0.15- 0.30 in/hr).  Group C  Sandy clay loam  Soils have low infiltration rates when thoroughly wetted and consist chiefly of soils with a layer that impedes downward movement of water and soils with moderately fine to fine texture. These soils have a low rate of water transmission (0.05-0.15 in/hr).  Group D  Clay loam, silty clay loam, sandy clay, silty clay, or clay  Soils have high runoff potential. They have very low infiltration rates when thoroughly wetted and consist chiefly of clay soils with a high swelling potential, soils with a permanent high water table, soils with a claypan or clay layer at or near the surface, and shallow soils over nearly impervious material. These soils have a very low rate of water transmission (0-0.05 in/hr).  Group B  Source from: Cronshey, R. G., 1986  iv.^Procedure for calculating stormwater runoff Q  Table 2-3: Procedure for calculating stormwater runoff (Q) Description^  Equation  Calculate potential maximum retention S using Step1 Equation 3, determine CN for impervious surface and open space.  S = ^ 10 CN  Step2 Calculate impervious and pervious surface la using Equation 2  la = 0.2S  1000  17  Description^  Equation  Compare Initial abstraction la with rainfall P. Step3 Rainfall P can be attain from local climate stations. When P-Ia<=0, runoff Q = 0 Step4 Calculate impervious and pervious surface runoff Q using Equation 1 Step5  la)  2  Q = (P — (P — la) + S  Calculate annual runoff from impervious and^Annual runoff Q = Q1+ Q2 pervious surfaces by accumulating daily runoff ^+ ^ + Q365  Step6 Calculate annual runoff volume  Annual runoff volume = Annual runoff Q x Areas  b. Evapotranspiration (ET) Method Under normal conditions, rainwater on green roofs is disposed of in three ways: it is retained in the soil and lost to evapotranspiration; it percolates down to the drainage layer and may be retained for future use, or it becomes surface runoff via drain pipes. As a result, how much stormwater can be retained on green roofs is dependent upon how much rainwater can be lost to evapotranspiration on green roofs.  i. Evapotranspiration (ET): Evapotranspiration (ET) is a combination of the water evaporated from the soil surface and transpired through plant material. Plant water use is directly related to Evapotranspiration (ET). This can be determined by multiplying the reference ETo by a crop coefficient (Kc). The crop coefficient adjusts the calculated reference ETo to obtain the crop evapotranspiration ETc. Different crops will have a different crop coefficient and resulting water use. (http://www.farmwest.com )  18  [eq. 4]  ETc = ETo x Kc^ Where ETo = calculated reference ET for vegetation (mm) ETc = crop evapotranspiration or crop water use (mm) Kc = crop coefficient  The crop coefficient (Kc) takes into account the crop type and crop development to adjust the ETo for that specific crop.  ii.^Reference Evapotranspiration Equations for ETo Two equations to compute reference evapotranspiration are the Penman-Monteith equation and the Hargreaves-Samani equation. For the Penman-Monteith equation, air temperature, solar radiation data, relative humidity data and wind speed data are required for the calculation of ETo. However, when solar radiation data, relative humidity data and wind speed data are missing, ETo can be estimated using the Hargreaves-Samani equation. (R. L. Snyder, 2007) An Excel application program PMday.xls, which can be used to calculate daily reference evapotranspiration (ETref) rates using the Penman-Monteith and Hargreaves-Samani equations, is provided on the internet by the Department of Land, Air and Water Resources at the University of California. ETo = 0.0023Ra  M  ean  + 1 7.8X-  r  max  — Tmin  fR 5  a  [eq. 5]  Where ETo = calculated reference ET (mm day - ') Ra = Ra = extraterrestrial radiation (MJ m -2day -1 ) Tmean =mean temperature (°C ) Tmax =maximum temperature (°C ) Tmin =minimum temperature (°C )  19  2.2.2.^Calculation methods for sites with connected impervious surfaces and disconnected impervious surfaces This thesis calculated total annual stormwater runoff by compounding daily runoff value. Daily stormwater runoff was calculated using the Runoff Curve Number (CN) method and the Evapotranspiration (ET) method. a. Sites with connected impervious surfaces (Figure 2-1): In this scenario, assume that runoff, from all impervious surfaces, flows as shallow concentrated, channel, or pipe flow directly to the downstream drainage system. (James E. M., 2004) Stormwater runoff in this scenario was considered as existing stormwater runoff. Figure 2-1: Runoff process from sites with connected impervious surfaces  C  IRain =Pp —  Rooftop  Streets, sidewalk  Open space  and parking lots  Total runoff Q = Q roof + Q street + Q open space  b. Sites with disconnected impervious roofs (Figure 2-2): In this scenario, assume that only runoff from roofs flows onto the pervious portion of the site before entering the site's drainage system. Impervious surfaces like streets, sidewalk and parking lots were still connected. 20  Figure 2-2: Runoff process from sites with disconnected roof surfaces  G  ain =PD  ^  • Rooftop  Popen space =P +Q  • roof  Streets, sidewalk and parking lots  Open space  Total runoff Q = Q  open space + Q street  4  c. Sites with disconnected impervious surfaces (Figure 2-3): In this scenario, assume that runoff from all impervious surfaces flows onto the pervious portion of the site before entering the site's drainage system. Figure 2-3: Runoff process from sites with disconnected roof surfaces  (Rain =Pp -  •  Streets, sidewalk  Rooftop  and parking lots  Popen space = P^Q roof + Q street  Open space  Total runoff Q =Q open space  21  d. Calculation methods for sites with green roof systems and disconnected impervious surfaces (Figure 2-4): In this scenario, assume that runoff from all impervious surfaces flows onto the pervious portion of the site before entering the site's drainage system, and all the roofs are green roof systems. A part of the stormwater was reduced by green roofs, as R roof shown in Figure 2-4. In the calculation, assume that the stormwater runoff reduced by green roofs was equivalent to the water lost to evapotranspiration. Figure 2-4: Runoff process from green roofs  Rain =P Evapotranspiration  \  f  Streets, sidewalk  Green Roofs  Popen space = P^(Q  and parking lots  greenroof  R greenroof  Q street  Note: R greenroof is runoff reduction of green roof  22  2.3 Calculation examples 2.3.1. Data input for calculations:  a. Rainfall P (in): Data of daily rainfall (in) were used in the calculation. Rainfall between January 1 st and 20 th , 2004 in Richmond was used in this example. b. Curve Number (CN): For all sites, assume that all streets, sidewalks, parking lots and roofs are impervious surfaces with a CN of 98, and all landscape areas are in fair condition with a CN of 69. Initial abstraction (la) is calculated as follows: Impervious area: la roof = la street = 0.2S = 0.2(  1000 10)=0.04 in 98  Pervious area: la open space =  ,, 1000  0.2S = u.zk  69  10)=0.90 in  c. Selected site used in the calculation example: Urban Core Zone with high-density apartments. Richmond, BC  high density  Site area  Roof  (m2)  (m2)  50,000  124,127  Street (m2)  Landscape / open  9,328  16,545  space (m 2 )  2.3.2. Calculations for sites with connected impervious surface  A calculation example for runoff rate from sites with connected impervious surfaces is shown in Table 2-4 below. Total runoff rates from selected sites can be calculated by the following formula:  23  Total runoff rate -  Q roof Area roof + Q street Area street Q open space Area open space Total Area  Table2-4: Calculation examples of runoff rates for sites with connected impervious surfaces  : Q , street (in)  dates  P (in)  2004-1-1  0.00  -0.04  -0.04  -0.90  2004-1-2  0.02  -0.02  -0.02  -0.88  2004-1-3  0.00  -0.04  -0.04  -0.90  2004-1-4  0.00  -0.04  -0.04  -0.90  2004-1-5  0.00  -0.04  -0.04  -0.90  2004-1-6  0.83  0.79  0.79  -0.07  0.62  0.62  2004-1-7  0.57  0.53  0.53  -0.32  0.39  0.39  2004-1-8  0.10  0.06  0.06  -0.80  0.01  0.01  2004-1-9  0.41  0.37  0.37  -0.49  0.24  0.24  P la (roof) -  P la^P Ia (open I space) (street)^ -  -  !Q roof (in)  2004-1-10  0.15  0.11  0.11  -0.75  0.04  0.04  2004-1-11  0.06  0.01  0.01  -0.84  0.00  0.00  2004-1-12  0.25  0.21  0.21  -0.65  0.11  0.11  2004-1-13  0.40  0.36  0.36  -0.50  0.23  0.23  2004-1-14  0.44  0.40  0.40  -0.46  0.26  0.26  2004-1-15  0.01  -0.03  -0.03  -0.89  2004-1-16  0.00  -0.04  -0.04  -0.90  2004-1-17  0.65  0.61  0.61  -0.25  0.46  0.46  2004-1-18  0.35  0.31  0.31  -0.54  0.19  0.19  2004-1-19  0.01  -0.03  -0.03  -0.89  2004-1-20  0.00  -0.04  -0.04  -0.90  Summary  (in) (mm)  Q open space (in)  2.55  2.55^0.00  65  65^0  According to the calculation result in the Table 2-4, runoff rate from roofs and streets is 65mm. There is no runoff during this period from the landscape areas.  24  Total runoff rate -  (65nrim)(24,127m 2 )+ (65mm)(9,328m 2 ) _ 43mm 50,000m 2  2.3.3. Calculations for sites with disconnected roofs A calculation example for the runoff rate from the selected site with disconnected roofs and connected streets is shown in Table 2-5 below. The selected site of high-density apartments (Urban Core Zone) in Richmond (BC) is used in this calculation example. Rainfall P open space -  Q  f  Area  roof  +  Area open space  Total runoff rate from selected sites can be calculated by the following formula: Total runoff rate -  Q street Areastreet ± Q open space Area open space Area total  Table 2-5: Calculation examples of runoff rates for sites with disconnected roofs  dates  P (in)  P-la^Q P-la street (roof) (street) I (in)  Q roof (in)  P (open space)  P-la (open space)  Q open space (in)  2004-1-1  0  -0.04  -0.04  0.00  -0.90  2004-1-2  0.02  -0.02  -0.02  0.02  -0.88  2004-1-3  0  -0.04  -0.04  0.00  -0.90  2004-1-4  0  -0.04  -0.04  0.00  -0.90  2004-1-5  0  -0.04  -0.04  0.00  -0.90  2004-1-6  0.83  0.79  0.79  0.62  0.62  1.74  0.84  0.13  2004-1-7  0.57  0.53  0.53  0.39  0.39  1.14  0.24  0.01  2004-1-8  0.1  0.06  0.06  0.01  0.01  0.12  -0.78  2004-1-9  0.41  0.37  0.37  0.24  0.24  0.76  -0.14  2004-1-10  0.15  0.11  0.11  0.04  0.04  0,20  -0.69  2004-1-11  0.06  0.01  0.01  0  0  0.06  -0.84 25  dates  (in)  (roof)  P la (street)  2004-1-12  0.25  0.21  0.21  P^1 P la  -  -  street 1 roof (in)^(in)  P (open space)  1 P-la (open space)  0.11  0.11  0.41  -0.49  0.74  -0.16  0.83  -0.07  2004-1-13  0.4  0.36  0.36  0.23  0.23  2004-1-14  0.44  0.4  0.4  0.26  0.26  2004-1-15  0.01  -0.03  -0.03  0.01  -0.89  2004-1-16  0  -0.04  -0.04  0.00  -0.90  2004-1-17  0.65  0.61  0.61  0.46 0.19  0.46  1.32  0.19  0.63  -0.27  Q open space (in)  0.43^0.04  2004-1-18  0.35  0.31  0.31  2004-1-19  0.01  -0.03  -0.03  0.01  -0.89  2004-1-20  0  -0.04  -0.04  0.00  -0.90  Summary  (in)  2.55  0.18 5  65  (mm)  According to the calculation result in Table 2-5, between January 1  st  and  January 20 th , 2004, 65mm of stormwater runoff was created by the street, while 5mm was created by landscape areas.  Total runoff rate -  (5mm)(16,545m 2 )+ (65mm)(9,328m2) 14mm 50,000m 2  2.3.4. Calculations for sites with disconnected impervious surfaces  A calculation example for runoff rate from the selected site with disconnected roofs and streets is shown in Table 2-6 below. The selected site of high-density apartments in Richmond (BC) is used in this calculation example. Area  Area  roof +  Area  open space =  street =  24,925m 2 +9,328m 2 = 33,455m 2  16,545m 2  26  Rainfall Popen space - Q roof  ream., p + 0 street A Area open space  Arearoof  Total runoff rate from selected sites can be calculated by the following formula:  Total runoff rate -  open space  Area open space  Area total  Table2-6: Calculation examples of runoff rates for sites with disconnected impervious surfaces dates  P^P-la^P-la (in)^(roof) (street)  2004-1-1 2004-1-2 2004-1-3 2004-1-4 2004-1-5 2004-1-6 2004-1-7 2004-1-8 2004-1-9 2004-1-10 2004-1-11 2004-1-12 2004-1-13 2004-1-14 2004-1-15 2004-1-16 2004-1-17 2004-1-18 2004-1-19 2004-1-20  0 0.02 0 0 0 0.83 0.57 0.1 0.41 0.15 0.06 0.25 0.4 0.44 0.01 0 0.65 0.35 0.01  Summary  (in)  0  (mm)  s:tnr e t roof P (open  space)  -0.02  -0.02  -0.04  -0.04  -0.04  -0.04  -0.04  -0.04  0.79 0.53 0.06 0.37 0.11 0.01 0.21 0.36 0.4  0.79 0.53 0.06 0.37 0.11 0.01 0.21 0.36 0.4  -0.03  -0.03  -0.04  -0.04  0.61 0.31  0.61 0.31  -0.03  -0.03  0.00 0.02 0.00 0.00 0.00 2.09 1.36 0.13 0.89 0.23 0.06 0.47 0.87 0.98 0.01 0.00 1.58 0.74 0.01  -0.04  -0.04  0.00  -0.04  -0.04  0.62 0.39 0.01 0.24 0.04 0 0.11 0.23 0.26  0.46 0.19  0.62 0.39 0.01 0.24 0.04 0 0.11 0.23 0.26  0.46 0.19  ^P-la (open Q open space) space (in) -0.90  -0.88 -0.90 -0.90 -0.90  1.19 0.46  0.22 0.03  -0.77 -0.01 -0.67 -0.84 -0.43 -0.03  0.08  0  -0.89 -0.90  0.68  0.08  -0.16 -0.89 -0.90  0.38 10  27  According to the calculation results in Table 2-6, between January 1  st  and  January 20 th , 2004, only 10 mm of stormwater runoff was created from landscape areas.  Total runoff rate -  (10mm)(16,545m2) =3mm 50,000m 2  2.3.5. Calculations for sites with green roof systems  a. Sunset zones: A plant's performance is governed by the total climate: length of the growing season, timing and amount of rainfall, winter lows, summer highs, and humidity. Sunset's climate zones take all these factors into account. The Sunset Zone Maps factor in winter minimum temperatures, summer highs, lengths of growing seasons, humidity, and rainfall patterns to provide an accurate picture of what will grow there. (Sunset Magazine, http://vvww.sunset.comisunset/web/Sponsors/Garden/sunsetmonrovia_r1/ htmlfilesibotwzones.html) b. Plants selected for green roofs: The amount of rainwater that can be transfered into the air will be dependent on the crop coefficient (Kc) of plants used on green roofs. In order to evaluate the effects of plants on runoff reduction, plants with different Kc values will be selected for the calculation of green roof runoff. Plants shown in Table 2-7 are commonly used on green roofs for all Sunset Zones in North America (Snodgrass, 2006).  28  Table 2-7: Plants used for the calculation of stormwater runoff on green roofs botanical and common  sunset  KC  names  zones  category  all  2  0.25 to 0.35  all  2  0.25 to 0.35  18, 19  2  0.25 to 0.35  all  3  0.40 to 0.60  all  3  0.40 to 0.60  all  3  0.40 to 0.60  Varies  3  0.40 to 0.60  all  3  0.40 to 0.60  3  0.40 to 0.60  Buchloe dactyloides  KC  Buffalo Grass Artemisia caucasica Silver Spreader Sedum rubrotinctum Pork & Beans Cynodon species Hybrid Bermuda Grass Cynodon dactylion Common Bermuda Grass Armeria maritima Sea Pink Coreopsis species Portulaca grandiflora Rose Moss Salvia splendens Scarlet Sage Achillea species  all  3  0.40 to 0.60  Festuca elatior  all  4  0.60 to 0.80  all  5  0.80 or greater  Varies  5  0.80 or greater  Tall Fescue Lolium perenne Perennial Rye Grass Viola species  Category 1 - Low Water Use Plants^Kc = 0 to 0.25 Category 2 - Low Water Use Plants^Kc = 0.25 to 0.35 Category 3 - Medium Water Use Plants ^Kc = 0.40 to 0.60 Category 4 - High Water Use Plants ^Kc = 0.60 to 0.80 Category 5 - High Water Use Plants ^Kc = 0.80 or greater Source from: City of Riverside (CA) Planning Department, 1994.  Based on Kc categories, four types of green roof systems were calculated for stormwater runoff retention, to determine which green roof system was most effective. As shown in Table 2-8, Green Roof 1 would use low water use plants with an average Kc of 0.3, Green Roof 2 would 29  use medium water use plants with an average Kc of 0.5, Green Roof 3 would use high water use plants with an average Kc of 0.7, and Green  Roof 4 would use very high water use plants with a Kc of 0.8.  Table 2-8: Kc of green roofs KC category of plants ^Average Kc Extensive  Green Roof 1^2^ 0.3 Green Roof 2^3^ 0.5  Intensive  Green Roof 3^4^  0.7  Green Roof 4^5^ 0.8  c. Calculation for sites with disconnected impervious surfaces and green roof systems A calculation example for runoff rates on green roofs from the selected site of high-density apartments (Urban Core Zone) in Richmond, BC, is shown in Table 2-9 below. In this calculation, all four types of green roof in Table 2-8 were used for comparison. In the following example, Q green roof is calculated as follows: Q  green roof =  Q  roof -  ET  green roof  Because a part of the stormwater will be retained in green roofs' soil, evapotranspiration will still take effect during a dry day. The negative number of Q  green roof  represents how much rainwater stored in the  growing medium will be lost to evapotranspiration.  30  Tablet-9: Calculation examples of runoff rates for sites with green roofs i ET :1::/^:Q^:Q^I Q Green P-la Q Green I Green ' Green ' Green roof PAN ' Roofl 1 Roof2 i Roof3^Roof4 Roof^1 Roof^i Roof^i Roof i^(roof) (in)^ (mm) ; i^(in)^I^(in)^I^(in)^!^(in) 1^(in)^i^2 (in)^i^3 (in)^; 4 (in) 1  ET^  dates  1^P (in)  ET^: ET^1 ET  : Green ; Green i Green  ^:  1^_^:  ;  .  2004-1-1  0.00  0.32  0.00  0.01  0.01  0.01  -0.04  -0.00  -0.01  -0.01  -0.01  2004-1-2  0.02  0.35  0.00  0.01  0.01  0.01  -0.02  -0.00  -0.01  -0.01  -0.01  -0.01  -0.01  -0.01  2004-1-3  0.00  0.26  0.00  0.01  0.01  0.01  -0.04  -0.00  2004-1-4  0.00  0.22  0.00  0.00  0.01  0.01  -0.04  -0.00  -0.00  -0.01  -0.01  2004-1-5  0.00  0.26  0.00  0.01  0.01  0.01  -0.04  -0.00  -0.01  -0.01  -0.01  2004-1-6  0.83  0.20  0.00  0.00  0.01  0.01  0.79  0.62  0.62  0.62  0.62  0.62  2004-1-7  0.57  0.42  0.00  0.01  0.01  0.01  0.53  0.39  0.38  0.38  0.37  0.37 0.00  2004-1-8  0.10  0.37  0.00  0.01  0.01  0.01  0.06  0.01  0.01  0.01  0.00  2004-1-9  0.41  0.39  0.00  0.01  0.01  0.01  0.37  0.24  0.23  0.23  0.23  0.22  2004-1-10  0.15  0.46  0.01  0.01  0.01  0.01  0.11  0.04  0.03  0.03  0.03  0.02  2004-1-11  0.06  0.54  0.01  0.01  0.01  0.02  0.01  0.00  -0.01  -0.01  -0.01  -0.02  2004-1-12  0.25  0.54  0.01  0.01  0.01  0.02  0.21  0.11  0.10  0.10  0.09  0.09 0.22  2004-1-13  0.40  0.46  0.01  0.01  0.01  0.01  0.36  0.23  0.23  0.22  0.22  0.02  0.40  0.26  0.26  0.25  0.25  0.25  2004-1-14  0.44  0.53  0.01  0.01  0.01  2004-1-15  0.01  0.49  0.01  0.01  0.01  0 02  -0.03  -0.01  -0.01  -0.01  -0.02  2004-1-16  0.00  0.58  0.01  0.01  0.02  0.02  -0.04  -0.01  -0.01  -0.02  -0.02  2004-1-17  0.65  0.60  0.01  0.01  0.02  0.02  0.61  0.46  0.45  0.45  0.44  0.44  2004-1-18  0.35  0.32  0.00  0.01  0.01  0.01  0.31  0.19  0.19  0.18  0.18  0.18  2004-1-19  0.01  0.45  0.01  0.01  0.01  0.01  -0.03  -0.01  -0.01  -0.01  -0.01  2004-1-20  0.00  0.57  0.01  0.01  0.02  0.02  -0.04  -0.01  -0.01  -0.02  -0.02  Summary  (in)  0.10  0.18  0.23  0.27  2.45  2.39  2.32  2.29  (mm)  2 54  4.57  5.84  6.86  62  61  59  58  According to the calculation results in Table 2-9, between January 1  st  and January 20 th , 2004, 62 mm of stormwater runoff was created from Green Roof 1, 61mm from Green Roof 2, 59mm from Green Roof 3, and 58mm from Green Roof 4. The annual runoff rates of green roofs was then calculated by summing the daily runoff (+Q) and the daily Evapotranspiration of green roofs (-ET). However, the calculated annual runoff rates are actually the long-term 31  water balance of green roofs. These numbers are calculated assuming the soils on green roofs will never completely dry up. Therefore, the quantity of rainwater the growing medium can store should be determined. A 10-day water balance was calculated and used to estimate the storage capacity required for the growing medium. A 10-day water balance is a sum of Q  green roof  for every ten days.  Table 2-10, below, is an example of a 10-day water balance for all four types of green roofs between March 21  St  and September 6 th , 2004. From  Table 2-10 the longest drought for each green roof system can be determined. In this study, the longest drought was considered as the maximum deficit.  Table 2-10: Calculation examples of 10-day water balance for green roofs  dates  Green Roof 1  Green Roof 2  Green Roof 3  Green Roof 4  - water balance (mm) (10-day)  - water balance (mm) (10-day)  - water balance (mm) (10-day)  - water balance (mm) (10-day)  2004-3-21^to^2004-3-30^23^19^14^12 2004-3-31^to^2004-4-9^-8^-14^-19  -21  2004-4-10^to^2004-4-19^-6^-12^-18  -24  2004-4-20^to^2004-4-29^-9^-16^-23  -22  2004-4-30^to^2004-5-9^-10^-18^-25  -29  2004-5-10^to^2004-5-19^-10^-18^-26  -31  2004-5-20^to^2004-5-29^20^12^5  -3  •  -12  -21  -30  -28  2004-6-9^to^2004-6-18  -2  -11  -20  -23  2004-6-19^to^2004-6-28  -16  -27  -37  -11^E  -20  2004-5-30^to^2004-6-8  ^2004-6-29^to^2004-7-8  E  ^2004-7-9^to^2004-7-18^E  -14  -24  2004-7-19^to^2004-7-28  -15  -25  2004-7-29^to^2004-8-7  -7  E N CNI  -29 -34  E •ct.  0  -43 -36 -38  -34  -40'  -16  -24  -29  -14  -24  -34  -38  2004-8-18^to^2004-8-27^43  38  32  27  2004-8-8^to^2004-8-17^  •  2004-8-28^to^2004-9-6^-9  -15^-21^-23  32  Because the evapotranspiration of plants also represents plants' water use, if the water stored in the soils is less than the water used by dependent plants, supplemental irrigation may be required. Otherwise, the plants on green roofs would wilt or stop growing during that period. As a result, by calculating the maximum deficits of green roofs, we can find out how much water should be retained in soil.  2.3.6. Calculations for sites with green roof systems and disconnected impervious surfaces The total runoff rate from selected sites can be the calculated by summing the total runoff rate (+Q) for sites with disconnected impervious surfaces (Scenario C, Figure 2-3 and Section 2.3.4) and the Evapotranspiration of green roofs  (-ETgreen roof)  (Section 2.3.5).  Total runoff rate = Q  disconnected^  (El-green roof  )(Area r„f )  Area ow  According to the calculation examples in Section 2.3.4 and 2.3.5, the runoff rate from the site with disconnected impervious surfaces was 3mm, and the Evapotranspiration  (ETgreen roof)  was 2.54mm from Green Roof 1,  4.57mm from Green Roof 2, 5.84mm from Green Roof 3, and 6.68mm from Green Roof 4. Thus, for the four different green roof types the runoff rates are: Green Roof 1: Total 10 day runoff rate = 3mm (2.54mm)(24,925m 50,000m 2  2 )  =  1 . .7mm  33  Green Roof 2:  Total 10 day runoff rate = 3mm  (4.57mm)(24,925m 2 )  50,000m 2  =0.7mm  Green Roof 3:  Total 10 day runoff rate = 3mm (5.84mm)(24,925m 50,000m  2  )  =0.1mm  Green Roof 4:  Total 10 day runoff rate = 3mm  (6.68mm)(24,925m 2 )  50,000m 2  = 0.4mm  34  Chapter 3  Selected Sites for Calculation,.  3.1 Introduction of Transect Zone Residential neighborhoods can be classified into four different Transect Zones: Suburban, General Urban, Urban Center and Urban Core. (Duany Plater -Zyberk & Company, 2006)  a) Suburban Zone: consists of low-density single family dwellings. Lots and setbacks in this area are typically large. Sidewalks are scarce and often occur only on major roads.  otimiLL List.  •^•  b) General Urban Zone: comprised primarily of single family units on small, individual lots. It also may include a limited number of duplexes and townhouses. A regular street network defines medium-sized blocks in this zone.  c) Urban Center Zone: primarily higher-density townhouses, apartments and row houses. It also may include a limited number of mixed-use buildings. It has a tight network of streets and blocks, and buildings are set close to the frontage.  d) Urban Core Zone: consists of the highest-density high-rise apartments and mixed-use buildings. It has a tight network of streets. Medium-density apartments may also be found in this area. It may have larger blocks. The buildings are set close to the frontage, and trees are often contained in planters.  Sources: Duany Plater -Zyberk & Company, 2006  36  3.2 Analysis of selected sites Richmond in British Columbia, Toronto in Ontario and San Antonio in Texas are selected for the comparison of runoff reduction, as their climatic conditions are vastly different, providing a fair cross-section of North American climates. a.  Richmond, BC: The annual precipitation rate is higher than the evaporation rate, but comparing monthly evaporation rates with the monthly precipitation rates, the highest evaporation rates coexist with the lowest precipitation in summer, while the lowest evaporation rates occur in conjunction with the highest precipitation in winter.  b. San Antonio, TX: Annual precipitation rate is much lower than the evaporation rate. Comparing the monthly evaporation rates with the monthly precipitation, the highest evaporation rates coexist with the highest precipitation in summer, while the lowest evaporation rates coexist with the lowest precipitation in winter. c. Toronto, ON: The annual precipitation rate is slightly lower than the evaporation rate. Comparing monthly evaporation and precipitation rates, the highest evaporation rates coexist with the highest precipitation in summer, while the lowest evaporation rates coexist with the lowest precipitation in winter. To quantify the influence of stormwater runoff in residential areas, and to see the differences between these three cities, four residential sites with a site area of 5 hectares have been chosen in each city, making 12 sites in all. The four residential tpyes are Low-density single family dwellings, Low- to Medium-density single family dwellings/duplexes, Medium-density townhouses/apartments, and High-density apartments.  37  Figure 3-1: Selected residential sites in Richmond, BC, San Antonio, TX and Toronto, ON  Richmond, BC  San Antonio, TX  Toronto, ON  3uburbar one Low-density single family dwellings:  3eneral urban Zone Low- to Medium-density single family dwellings /duplexes,  Urban Ce'"er -  f- "),P  Medium-density townhouses /apartments  Urban Core Zan ,-  High-density apartments Impervious surfaces: Roof, sidewalk & street Pervious surfaces: Ground level landscape Semi-pervious surfaces: Green roof & parking roof  38  a. Richmond, BC i Suburban Zone: Low-density single family dwellings: (The site is contained in the following 4 streets: Granville Ave, Bridge St, General Currie Rd, and Ash St.) GRANVILLE AVE  Description: This area is composed mainly of single family houses with deep setbacks, and a small number of new-constructed townhouses. The blocks are large, and have large landscaped areas.  Total site area:  Impervious area  Pervious area  50,000  100%  7,655  15%  m2  Rooftops  m2  Impervious paving  6,770  Ground level landscape  35,575  14%  m2  71%  m2  Source: Richmond's GIS Inquiry http://map.city.richmond.bc.ca/website/gis/viewer.htm  Housing type — Single family houses (Suburban) Description: A typical single-family dwelling in this area has a large area, deep setbacks and large landscaped areas.  1,775 m 2  100%  Rooftops  199 m 2  11%  Impervious paving  251 m 2  14%  Ground level landscape  1,325 m 2  75%  Lot area:  Source: Richmond's GIS Inquiry http://map.city.richmon d.bc.ca/website/gis/vie wer.htm  Impervious area  Pervious area  39  ii General Urban Zone: Low- to Medium-density single family dwellings/duplexes: (The site is contained in the following 4 streets: Comstock Rd, Gilbert Rd, Chatterton Rd, and Grandy Rd.) Description: This area is composed mainly of single family housing units. Compared with suburban single family dwellings, landscape areas are smaller, and the buildings are set closer to the frontage.  Total site area:  50,000  100%  m2  Impervious area  Pervious area  Rooftops  16,377  33%  m2  Impervious paving  9,921 m 2  20%  Ground level landscape  23,702  47%  m2  Source: Richmond's GIS Inquiry http://map.citysichmond.bc.ca/website/gis/viewer.htm  Housing type — Single family houses (urban) Description: Compared to the Suburban Zone, lot sizes in the General Urban Zone are smaller. The square footage of a typical single family house in this zone may be larger, but the house has shallower setbacks and relatively less landscaping.  1,058 m 2  100%  Rooftops  342 m 2  32%  Impervious paving  116 m 2  11%  Ground level landscape  600 m 2  57%  Lot area:  Source: Richmond's GIS Inquiry http://nrop.city.richmon d.bc.ca/website/gis/vie wer.htm  Impervious area  Pervious area  40  iii Urban Center Zone: Medium-density townhouses/apartments: (The site is contained in the following 4 streets: Lansdowne Rd, Arcadia Rd, Ackroyd Rd, and Cooney Rd) Description: This area is composed of low-story apartments, and several townhouses. It has medium sized landscaping zones. Parking lots account for greater surface coverage in this zone than in others.  Total site area:  50,000  100%  m2  Impervious area  Pervious area  Rooftops  19,324  39%  m2  Impervious paving  6,075  Ground level landscape  24,601  12%  m2  49%  m2  Source: Richmond's GIS Inquiry http://map.city.richmond.bc.ca/website/gis/viewer.htm  Housing type — low-rise apartments Description: Larger building footprints and impervious parking lots result in fewer landscaped areas.  7,260 m 2  100%  Rooftops  2,889m2  40%  Impervious paving  1,826 m 2  25%  Ground level landscape  2,545 m 2  35%  Lot area: Impervious area  Pervious area Source: Richmond's GIS Inquiry http://map.city.richmond.bc.ca/website/gis/viewer.htm  41  iv Urban Core Zone: High-density apartments: (The site is contained in the following 4 streets: Saba Rd, Cooney Rd, Park Rd, and Buswell St.) Description: Richmond does not have many high-rise apartments. The Urban Core Zone in Richmond is composed mainly of low-rise apartment buildings. It may also include several high-rise apartments and a small number of townhouses and row houses. There are parking lots in this area. Landscaped areas are small.  50,000  Total site area:  100%  m2  Impervious area  Pervious and semi-pervious area  Rooftops  21,925  44%  m2  Impervious paving  9,328 m 2  19%  Ground level landscape  16,545 m2  33%  Green roof  2,202 m 2  4%  Source: Richmond's GIS Inquiry http://map.city.richmond.bc.ca/website/gis/viewer.htm  Housing type — high-rise apartments Description: Buildings are set close to the frontage, and may have green roofs. Landscaped areas on ground level are small.  5,844 m 2  100%  Rooftops  4,025m2  69%  Impervious paving  1,760m2  30%  Ground level landscape  58 m 2  1%  Green roof  487 m 2  8%  Lot area: Impervio us area Source: Richmond's GIS Inquiry http://map.city.richnn ond.bc.ca/website/gi s/viewer.htm  Pervious area  42  b. San Antonio, TX: a) Suburban Zone: Low-density single family dwellings: (The site is contained in the following 4 streets: J St, Amanda, Sewanee St, and Hampton St.) Description: This area is composed of single family houses with deep setbacks. There are large areas of landscaping.  Total site area:  50,000  100%  m2  Impervious area  Rooftops  7,387 m 2  15%  Impervious paving  3,604 m 2  7%  Pervious area  Ground level landscape  39,009 m2  78%  Source:The City of San Antonio's Interactive GIS Website http://maps.sanantonio.gov/  Housing type — Single family houses (Suburban) Description: A typical single family house in this area has large areas, deep setbacks and large landscaped areas.  817 m 2  100%  Rooftops  173 m 2  21%  Impervious paving  45 m 2  6%  Ground level landscape  599 m 2  73%  Lot area: Impervious area  Source:The City of San Antonio's Interactive GIS Website http://maps.sanantonio.gov/  Pervious area  43  b) General Urban Zone: Low- to Medium-density single family dwellings/duplexes: (The site is contained in the following 4 streets: W Craig Place, Breeden St, W French Place, and Ripley Ave.) Description: This area is composed mainly of single family houses. Compared with the Suburban Zone, landscape sizes are smaller, and the buildings are set closer to the frontage.  Total site area:  Impervious area  Pervious area  50,000  100%  16,441  33%  m2  Rooftops  m2  Impervious paving  7458 m 2  15%  Ground level landscape  26,101 m2  52%  Source:The City of San Antonio's Interactive GIS Website http://maps.sanantonio.gov/  Housing type — Single family houses (urban) Description: Compared with the Suburban Zone, Lot sizes in the General Urban Zone are smaller. The size of a typical single family house in this zone may be larger, but has shallower setbacks and relatively smaller landscape size.  Source:The City of San Antonio's Interactive GIS Website http://maps.sa nantonio.gov/  Lot area:  537 m 2  100%  Impervious area  Rooftops  204 m 2  38%  Impervious paving  12 m 2  2%  Pervious area  Ground level landscape  321 m 2  60%  44  c) Urban Center Zone: Medium-density townhouses/apartments: (The site is contained in the following 4 streets: E Melrose Dr, Shook Ave, Annie, and Judson St.) Description: This area is composed of low-story apartments, townhouses and single family dwellings. Parking lots are found in this area.  Total site area:  Impervious area  Pervious area  50,000  100%  16,771  34%  m2  Rooftops  m2  Impervious paving  7,026 m 2  14%  Ground level landscape  26,203 m2  52%  Source:The City of San Antonio's Interactive GIS Website http://maps.sanantonio.gov/  Housing type — low-story apartments Description: Larger buildings and impervious parking lots result in smaller landscape size.  10,616 m 2  100%  Rooftops  5,875 m 2  55%  Impervious paving  1,420 m 2  13%  Ground level landscape  3,321 m 2  32%  Lot area: Impervious area Source:The City of San Antonio's Interactive GIS Website http://maps.sanantonio.g ov/  Pervious area  45  d) Urban Core Zone: High-density apartments: (The site is contained in the following 4 streets: Avenue B, Brooklyn Ave, N Alamo St, and 4th St.) Description: San Antonio's downtown does not have many high-rise apartments, but is composed mainly of mixed-use buildings. Landscaping is scarce in this zone.  Total site area:  Impervious area  Rooftops  100%  19,756  40%  m2  Impervious paving Pervious area  50,000 m2  29,135  58%  m2  1,109  Ground level landscape  2%  m2  Source:The City of San Antonio's Interactive GIS Website http://maps.sanantonio.gov/  Housing type — high-rise apartments Description: Buildings are set close to the frontage, and may be served by large parking lots. No landscape is provided in this area except by the way of few planters.  8611 m 2  100%  Rooftops  5197 m 2  60%  Impervious paving  3414 m 2  40%  Ground level landscape  N/A  N/A  Parcel area: Impervious area  Pervious area Source:The City of San Antonio's Interactive GIS Website http://maps.sanantonio.gov/  46  c. Toronto, ON: a) Suburban Zone: Low-density single family dwellings: (The site is contained in the following 4 streets: Ridout St, Indian Rd, Howard Park Ave, and Indiangrv.) Description: This area is composed of single family houses with deep setbacks. Landscaped areas are large.  50,000 m 2  100%  Rooftops  15,613 rn 2  31%  Impervious paving  1,271 m 2  3%  Ground level landscape  33,116 m 2  66%  Total site area: Impervious area  Pervious area Source: The City of Toronto hftp://map.toronto.ca/imapit/iMaplt.jsp?app= TOMaps  Housing type — Single family houses (Suburban) Description: A typical single family house in this area has large lot sizes, deep setbacks and large landscape size.  Lot area:  661 m 2  100%  Impervious area  Rooftops  123 m 2  19%  Impervious paving  60 m 2  9%  Pervious area  Ground level landscape  478 m 2  72%  47  b) General Urban Zone: Low- to Medium-density single family dwellings/duplexes: (The site is contained in the following 4 streets: Harbord St, Barthurst St, Ulster St, and Manning Ave.) Description: This area is composed mainly of single family houses. Compared to the Suburban Zone, single family dwellings and duplexes occur together, landscaped areas are smaller, and the buildings are set closer to the frontage.  Total site area:  Impervious area  Rooftops  50,000 m2  100%  24,203  48%  m2  Pervious area  Impervious paving  2,560 m 2  6%  Ground level landscape  23,237  46%  m2  Source: The City of Toronto http://map.toronto.ca/imapit/iMaplt.jsp? app=TOMaps  Housing type — Single family houses (urban) Description: Compared with the Suburban Zone, lot areas in the General Urban Zone are smaller. The size of a typical single family house in this zone may be larger, but has shallower setbacks and relatively smaller landscape size.  333 m 2  100%  Rooftops  183 rre  55%  Impervious paving  34 m 2  10%  Ground level landscape  116 m 2  35%  Lot area: Impervious area  Pervious area  48  c) Urban Center Zone: Medium-density townhouses/apartments: (The site is contained in the following 4 streets: Gerrard St. E, Sackville St, Dundas St E, and Parliament St.) Description: This area is composed of medium-story apartments. Large parking lots are provided in this area. There may be relatively large landscaping in this area, such as parks.  Total site area:  Impervious area  Rooftops  100%  9,796  20%  m2  Impervious paving Pervious area  50,000 m2  Ground level landscape  17,795  35%  m2  22,409  45%  m2  Source: The City of Toronto http://map.toronto.ca/imapit/iMaplt.jsp? app=TOMaps  Housing type — medium-story apartments Description: Medium-story apartments may result in smaller building footprints. There are large parking lots.  30,281 m2  100%  Rooftops  6,774 m 2  22%  Impervious paving  9,145 m 2  31%  14,362  47%  Lot area: Source: The City of  Impervious area  Toronto http://map.t oronto.ca/i mapit/iMapl t.jsp?app=T  Pervious area  Ground level landscape  m2  OMaps  49  d) Urban Core Zone: High-density apartments: (The site is contained in the following 4 streets: St. James Ave, Parliament St, Wellesley St. E, and Ontario St.) Description: This area is composed of high-rise apartments. Large parking lots are provided in this area. There may be relatively large landscaped tracts in this area, such as parks.  Total site area:  Impervious area  Pervious and semipervious area  Source: The City of Toronto http://map.toronto.ca/imapit/iMaplt.jsp?app =TOMaps  50,000  100%  10,834  22%  m2  Rooftops  m2 I mpervious paving  20,359  Ground level landscape  6,172  Green roof/parking roof  12,635 m2  40%  m2  13%  m2  25%  Housing type — high-rise apartments Description: Most buildings are skyscrapers. There are large parking lots. Landscape size is small.  16,942 m 2  100%  Rooftops  6,784 m 2  34%  Impervious paving  8,024 m 2  47%  Ground level landscape  3,134 m 2  12%  Green roof/parking roof  2,050 m 2  6%  Parcel area: Source: The City of Toronto http://map.tor onto.ca/imapit /iMaplt.jsp?ap p=TOMaps  Impervious area  Pervious and semipervious area  50  Chapter 4  Calculation Results for Stormwater Runoff Quantity and Quality  ^  4.1 Calculation results — Quantity of stormwater runoff 4.1.1. Stormwater runoff calculation results for Richmond, BC  a. Rainfall investigation (1995 — 2004): Precipitation data for Richmond, BC, are obtained from Environment Canada. (http://www.climate.weatheroffice.ec.gc.ca/Welcome_e.html) Wettest year: 1997 (P = 1611mm) i. Average year: 2004 (P = 1187mm) ii. iii.^Driest year: 2002 (P = 919mm)  Figure 4-1: Precipitation (1995-2004) in Richmond, BC 1800 -- 1600 ^ 1400 1200^1000 ^800^600 400 200  0 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006  Note: Annual rainfall in 2001 is not available for Richmond Source from: Environment Canada (http://www.climate.weatheroffice.ec.gc.caNVelcome_e.html)  b. Selected residential sites for calculations: Four residential sites of varying density have been selected in Richmond, BC. The areas of impervious and pervious surfaces in each of the sites have been calculated as follows (Table 4-1).  52  Table 4-1: Selected residential sites in Richmond, BC Landscape / Open space ( m 2)  Richmond, BC  Site area (m 2 )  Roof (m 2 )  Urban Core Zone High Density  50,000  100%  24.127  48%  9,328  19%  16.545  33%  Urban Center Zone Medium Density  50,000  100%  19,324  39%  6,075  12%  24,601  49%  General Urban Zone Low To Medium Density  50.000  100%  16,377  33%  9,921  20%  23.702  47%  Suburban Zone Low Density  50,000  35.575  71%  Street (m 2 )  -r  7.655  100%  15%  6,770  14%  c. Storm water runoff calculation results for Richmond, BC i.^Runoff from connected impervious surfaces and disconnected impervious surfaces: Assume that all impervious surfaces have a CN of 98 and all landscape areas are in fair condition with a CN of 69. Using the Equation/ in Section 2.2.1 and the daily rainfall data of an average moist year -2004(Environment Canada 2008) in Richmond, BC, the annual runoff rates created from the sites with connected impervious surfaces and disconnected impervious surfaces are shown in Table 4-2 below.  Table 4-2: Runoff rates by cover types in Richmond, BC Street  Open space  Roof  Connected 1 impervious surfaces  701.28  10.35  701.28  I Disconnected I^roof  701.28  Cover type  Annual runoff rates (mm)  Disconnected impervious surfaces  H 170.38 H 278.07  M  L to M  73.25^62.64  21.65  M^L to M 104.59^115.42  35.46  Foot note: 1. H — High density^M — medium density^L to M — Low to medium density^L — Low density 2. Refer to calculation method explained in Section 2.3.2, 2.3.3 and 2.3.4. P22  53  According to the methods explained in Section 2.2.2, the total runoff volume and rates were calculated with the following formulas:  Sites with connected impervious surfaces: Total runoff Q = Q roof + Q street + Q open space  Sites with disconnected roof surfaces: Total runoff Q = Q street + Q open space  Sites with disconnected impervious surfaces: Total runoff Q = Q open space  Sites with green roofs and disconnected impervious surfaces: Total runoff Q = Q open space - ET plant  0  2  Total runoff rate =  + street Area street + Q^Area open space^open space Q roof Area roofQ Total Area  The total runoff rates in Table 4-3 depict the total runoff from all four sites. The calculation of total runoff rates in Table 4-3 is based on the climate data in an average moist year in Richmond, BC (Environment Canada). Table 4-3 showed that without any stormwater management treatments, the 5-hectare Urban Core Zone can generate 473 mm of annual stormwater runoff. Runoff from the Urban Center Zone and 54  General Urban Zones is 15% less than that from the selected Urban Core Zone, about 370mm. The low-density Suburban Zone generates the lowest runoff, 210mm, less than half of that generated by the Urban Core Zone. If the runoff from roofs is directed onto the landscaped areas of the site before entering the site's drainage system, the total annual runoff can be reduced by 47% to 66%, as shown in Table 4-3. If all the runoff from roofs and other ground-level impervious surfaces like streets and parking lots can flow onto the landscape areas of the site before entering the site's drainage system, the total annual runoff can be reduced by over 80%.  able 4-3: Total runoff rates from selected residential sites in Richmond. BC  (Average  year)  Total Runoff Rate Richmond, BC  Site area (ha)  Urban Core Zone High Density  ^With With With disconnected connected disconnected^ imperviousimpervi ous roofs (mm) surfaces (mm) surfaces (mm) i ^.  •  473  100%  187  40%  92  19%  Urban Center Zone Medium Density  5  361  100%  121  34%  51  14%  General Urban Zone Low To Medium Density  5  374  100%  169  45%  55  15%  Suburban Zone Low Density  5  210  100%  110  53%  25  12%  Footnote: Refer to calculation method explained in Section 2.3.2, 2.3.3 and 2.3.4. P22  55  ii.^Runoff from green roofs: As shown in Table 4-4, traditional roofs created 1,027mm of runoff in the wettest year, 701 mm in the average year and 511mm in the driest year. Green Roof 1 with a Kc value of 0.3 could have reduced the rooftop runoff rate to 76% in the wettest year, 64% in the average year, and 53% in the driest year. Green Roof 2 with a Kc value of 0.5 could have reduced the rooftop runoff rate to 60% in the wettest year, 40% in the average year, and 22% in the driest year. Green Roofs 3 and 4 with a Kc value of 0.7 or more could have reduced the rooftop runoff rate by about 60% in the wettest year, over 80% in the average year, and could have achieved zero runoff in the driest year. However, rainfall alone in the driest year would not have been sufficient for the water use required by plants on Green Roofs 3 and 4 (medium and high water use plants).  Table 4-4 Runoff rates from traditional roof and green roofs, Richmond. BC .  Richmond, BC  Wettest Year Avg. Moist Year  traditional roof (mm)  Kc= 0.8  Kc= 0.3  Kc= 0.5  Kc=0.7  Green Roof  Green Roof  Green Roof  Green Roof  3 (mm)  4 (mm)  1 (mm)  2 (mm)  1,027  100%  782  76%  619  60%  456  44%  375  36%  701  100%  448  64%  280  40%  111  16%  27  4%  100%^272  53%  112  22%  -48  0%  -128  0%  Driest Year^511  Footnote: Refer to calculat i on method explained in Section 2.3.5. P.27  Table 4-5 below shows the effects of green roofs on reducing total stormwater runoff. In an average year, 19% to 27% of the total runoff from the sites with connected impervious surfaces can be reduced by Green  Roof 1, 31% to 45% by Green Roof 2, 43% to 63% by Green Roof 3 and 59% to 72% by Green Roof 4. If roofs are disconnected, 35% to 81% of  56  the total runoff can be reduced by Green Roof 1, up to 100% by Green Roofs 2, 3, and 4. If all impervious surfaces were disconnected, zero runoff could be achieved by all four types of green roofs. If the total evapotranspiration volume were more than the total runoff volume from sites with disconnected roofs and impervious surfaces, the total runoff rates when applying green roofs would be negative, which implies that greening only a portion of the roof areas could achieve zero runoff. The calculation of roof-greening percentages was calculated by the following formula:  Sites with disconnected roofs: Greening % = 100 X  (Total runoff rate disconnectedr„f )(Area tota , ) (ETgreen roof )(Area green roof )  Sites with disconnected impervious surfaces: Greening % = 100 X  (Total runoff rate disconnected impervious )(Area total ) (ETgreen roof  )(Area green roof )  As a result, if all impervious surfaces on the sites were disconnected, as shown in Table 4-5, zero runoff could be achieved by greening 52% to 75% of the rooftop areas with Green Roof 1, 31% to 45% with Green Roof 2, 22% to 32% with Green Roof 3, and 20% to 28% with Green Roof 4.  57  Table 4-5: Total runoff rates when apply ng green roofs: selected resident al sites in Richmond. BC in an average year  Richmond, BC Urban Core Zone High Density  with connected impervious surfaces (mm)  with disconnected  351^74%  75^16%  roofs (mm)  6  2  Urban Center Zone  264  Medium Density  General Urban Zone  (.5  Low To Medium Density  Suburban Zone  General Urban Zone  198  Low To Medium Density  23%  81%  71  34%  57%  -16 ^  -28 ^  CPA,  -14 ^  0%  -111 0%  55%  -42 ^  0%  63%  31  ^ 45%"  -112 ^  0%  0%  31%* 8%  69%  45  21%  40%  -98 ^  -83 ^ -40 ^ -193  0%  66%*  Urban Center Zone  133  Medium Density  37%  -107 ^  0%  0 0/0  0 0/0  Low To Medium Density  Suburban Zone  180  -24 ^  0%  57%  20  -177 ^ -138 ^  10%  -65 ^ 28%"  Urban Core Zone  147  High Density  31%  -138 ^  0%  Urban Center Zone  101  28%  -140 ^  0%  Low To Medium Dens tv  153  41%  -52 ^  0%  77%"  ,  106  51%  7  0%  -233 ^  o% 0%  -210 ^  0%  20%*  46%*  General Urban Zone  0%  28%*  57%*  Medium Density  0%  28%"  87%" 119  Low Density  48%  ^ 32%*  22%"  53%"  General Urban Zone  Suburban Zone  0%  40%*  188  High Density  2  -47 ^  39%*  Urban Core Zone  ‘r  236  145  Low Density  ,  86  74%"  Suburban Zone  112 0  78%  92%"  Urban Center Zone  a)  6%  66%"  269  High Density  Medium Density  73%^23  65%*  Urban Core Zone  2  291  171  Low Density  "6  C,I0/0  52%*  w  CsJ  -20 ^ 75%*  T-  4  with disconnected impervious surfaces (Tom)  -166 ^  0%  25%* 3%  -78 ^  0%  24%* Footnote: 1. Calculations of total runoff rates refer to calculation method explained in Section 2.3.6. P.32 2.* The percentage of the total roof areas recommended to be greened to achieve zero runoff.  58  High evaporation rates during the summer months do not correspond with high rainfall, while low evaporation rates during the winter period do not always correspond with low rainfall. As a result, the actual runoff rates for green roofs would be less than those in Table 4-6. Table 4-6 shows the water balance of Green Roof 1 with a Kc value of 0.3. The lowest water level was reached in August. The maximum deficits of water balance for Green Roof 1 were 51 mm in the wettest year, 92mm in the average year, and 98mm in the driest year. During the summer in the driest year, the water level of Green Roof 1 would not be recharged for 110 days. As a result, the soil water storage capacity should be more than 98mm, in order to prevent plants on green roofs from wilting or dying.  Table 4-6: Calculation of water balance for Green Roof 1, Richmond, BC  Dates  wettest year  average year  (mm)  (mm)  driest year (mm) 3  11-May^to^20-May^-14^-10 21-May^to^30-May^17  • l  31-May^to^9-Jun^4 10-Jun^to^19-Jun^2 20-Jun^to^29-Jun^18 30-Jun^to^9-Jul^50  -14  10-Jul^to^19-Jul  •  19  E CN CS)  -3  -12  -12  -2  -9  -16  -5  -11  -5  -14  -14  -15^co o)  20-Jul^to^29-Jul^E  -14  30-Jul^to^8-Aug^17)  -9  -7  -8  -15  -14  -13  19-Aug^to^28-Aug^3^43  -11  E  9-Aug^to^18-Aug  -  29-Aug^to^7-Sep^-8^-9^• 8-Sep^to^17-Sep^33^41  -14  -5 15  Footnote: Refer to calculation method explained in Section 2.3.5. P.27  59  Table 4-7 shows the water balance of Green Roof 2 with a Kc value of 0.5. The maximum deficits of water balance for Green Roof 2 were 107 mm in the wettest year, 167 mm in the average year, and 212 mm in the driest year. The longest drought period for Green Roof 2 is 60 days in the wettest year, 80 days in the average year, and 140 days in the driest year.  Table 4-7: Calculation of water balance for Green Roof 2, Richmond. BC  Dates  wettest year  average year  driest year  (mm)  (mm)  (mm)  11-Apr  to  20-Apr  45  -12^20  21-Apr  to  30-Apr  10  -16  1-May  to  10-May  -1  -18  -14  11-May  to  20-May  -23  -18  -4  21-May  to  30-May  10  12  -10  31-May  to  9-Jun  -4  -21  -20  10-Jun  to  19-Jun  -6  -11  20-Jun 30-Jun  to to  9-Jul  -5  -18 E  E  -27  10  29-Jun  •  -14  42  E E  -20  NU)  -24  -24  <V CT1  -14  s10-Jul  to  19-Jul  -23  20-Jul  to  29-Jul  -23  -25  -23  30-Jul  to  E 8-Aug^  -19  -16  -16  9-Aug  to  18-Aug  -24  -24  -21  19-Aug  to  28-Aug  -3  38  -19  29-Aug  to  7-Sep  -15  -15  8-Sep  to  17-Sep  28  E  ^•  -  11  37^10  Footnote: Refer to calculation method explained in Section 2.3.5. P.27  Table 4-8 shows the water balance of Green Roof 3 with a Kc value of 0.7. The maximum deficits of water balance for Green Roof 3 were 158mm in the wettest year, 242mm in the average year, and 322mm in the driest year. The longest drought period for Green Roof 3 is 60 days in the wettest year, 80 days in the average year, and 140 days in the driest year. 60  Table 4-8: Calculation of water balance for Green Roof 3, Richmond, BC  Dates  wettest year  average year  driest year  (mm)  (mm)  (mm)  39^-18^15  11-Apr  to  20-Apr  21-Apr  to  30-Apr  1-May  to  10-May  -7^-25  -20  11-May  to  20-May  -32^-26  -11  21-May  to  30-May  3^5  31-May  to  9-Jun  -12  -30  10-Jun  to  19-Jun  -14  -20  20-Jun  to  29-Jun  30-Jun  to  9-Jul  10-Jul  to  19-Jul  20-Jul  to  29-Jul  30-Jul  to  8-Aug  4^-23^•  3 33^E -32 -32  E  C  -11  -17i -29 -26  -37  E E  -29  (N1 (NI Cr)  -24 -22  -34  -34  -34  -32  -28  -24  -24  -34  -34  -29  9-Aug  to  18-Aug^co  19-Aug  to  28-Aug  -10^32  -27 1  29-Aug  to  7-Sep  -21^-21  -17  8-Sep  to  17-Sep  U)  23^33^4  Footnote: Refer to calculation method explained in Section 2.3.5. P.27  Table 4-9 shows the water balance of Green Roof 4 with a Kc value of 0.8. The maximum deficits of water balance for Green Roof 4 were 182mm in the wettest year, 279mm in the average year, and 377mm in the driest year. The longest drought period for Green Roof 4 is 60 days in the wettest year, 80 days in average year, and 140 days in the driest year.  61  ^  Table 4-9: Calculation of water balance for Green Roof 4, Richmond. BC Dates  wettest year  average moist  driest year  (mm)  year (mm)  (mm) 13  11-Apr  to  20-Apr  37  -21  21-Apr  to  30-Apr  -9  -26^•  1-May  to  10-May  -0  -29  -23  11-May  to  20-May  -38  -30  -15  21-May  to  30-May  -14  1  -20  31-May  to  9-Jun  -1  -34  -33  10-Jun  to  19-Jun  -19  -24  -31  20-Jun  to  29-Jun  -3  -43  -29  30-Jun  to  9-Jul  29  E  E  rn  r-  -14  -34^ti  -26  -39  -39  co  10-Jul  to  19-Jul  -34  20-Jul  to  29-Jul  -37  -39  -36  30-Jul  to  8-Aug^E  -33  -28  -27  9-Aug  to  18-Aug^CN  -40  -38  -34  19-Aug  to  28-Aug  -13  29  -30  29-Aug  to  7-Sep  -25  -24  8-Sep  to  17-Sep  19  19  E  00  (  ♦  -20 2  Footnote: Refer to calculation method explained in Section 2.3.5. P.27  4.1.2. San Antonio, TX  a. Rainfall investigation (1997 — 2006): Precipitation data for San Antonio, TX, are obtained from TexasET Network. (http://texaset.tamu.edu/etinfo.php) Wettest year: 2002 (P = 1094mm) i. Average year: 1997 (P = 818mm) ii. iii.^Driest year: 2004 (P = 423.4mm)  62  Figure 4-2: Precipitation (1997-2006) in San Antonio, TX 1800 ^ 1600 ^ 1400 ^ 1200 1000 800 600 400 200 0 1997 1998 1999 2000 2001 2002 00 200 2005 2006  Note: Annual rainfall in 1999, 2005, 2006 are not available for San Antonio, TX Source from: TexasET Network. (http://texaset.tamu.edu/etinfo.php)  b. Selected residential sites for calculations: Four residential sites of varying density have been selected in San Antonio, TX. The areas of impervious and pervious surfaces in each of the sites have been calculated as follows (Table 4-10). Table 4-10: Selected residential sites in San Antonio. TX San Antonio, TX  Site area (m 2 )  Urban Core Zone High Density  50,000^100%^19,756^40%  Urban Center Zone Medium Density  Roof (m 2 )  Street (m 2 )  Landscape / Open space ( m2)  29,135^58%  1,109^2%  50000^100°/0  16771^34%^7,026^14%  26,203^52%  General Urban Zone Low To Medium Density  50,000^100%  16,441^33%  7,458^15%  26,101^52%  Suburban Zone Low Density  50,000^100%  7 387^15%  3,604^7%  39.009^78%  C. Stormwater runoff calculation results for San Antonio, TX i.^Runoff from connected impervious surfaces and disconnected impervious surfaces: 63  Assume that all impervious surfaces have a CN of 98 and all landscape areas are in fair condition with a CN of 69. Using the Equation1 in Section 2.2.1 and the daily rainfall data of an average moist year -1997(TexasET Network 2008) in San Antonio, TX, the annual runoff rates created from the sites with connected impervious surfaces and disconnected impervious surfaces are shown in Table 4-11 below.  Table 4-11: Runoff rates by cover types in San Antonio, TX Cover type  Annual runoff rates (mm)  Street  Open space  Roof  Connected impervious surfaces  563.89  27.14  563.89  Disconnected roof  563.89  Disconnected impervious surfaces  -  H^M  LtoM  101.43^99.91^44.25 H^M  LtoM  144.73^146.02^54.20  Foot note: 1. H — High density^M — medium density^L to M — Low to medium density^L— Low density 2. Refer to calculation method explained in Section 2.3.2, 2.3.3 and 2.3.4, P22. 3. The landscape area in the high density selected site was too small (2%) to disconnect impervious surfaces.  The total runoff rates in the Table 4-12 are the total runoff from all residential sites. The calculation of total runoff rates in Table 4-12 is based on the climate data in an average moist year in San Antonio, TX (TexasET Network). According to the calculation results, without any stormwater management treatments, the 5-hectare Urban Core Zone can generate 552 mm of annual stormwater runoff. Runoff from the Urban Center Zone and General Urban Zone is about 50% less than that from the selected Urban Core Zone, about 283mm. The low-density Suburban Zone 64  generates minimum runoff, which is only 25% of that from the Urban Core Zone. If the runoff from roofs is diverted onto the landscaped areas of the site before entering the site's drainage system, the total annual runoff can be reduced by 12% to 53%. If all runoff from roofs and other ground-level impervious surfaces like streets and parking lots can flow onto the landscaped areas of the site before entering the site's drainage system, the total annual runoff can be reduced by over 70%.  Table 4-12: Total runoff rates from selected residential sites in San Antonio, TX (Average year)  San Antonio, TX  Total Runoff Rate Site^ With^With With area disconnected area^connected^ disconnected (ha) impervious ^impervious^ roofs (mm) surfaces (mm) surfaces^  Urban Core Zone High Density  5  552^100%  483^88%^415^75%  5  283^100%  132^47%^76^27%  General Urban Zone Low To Medium Density  5  284^100%  136^48% j^76^27%  Suburban Zone Low Density  5  145^100%  Urban Center Zone Medium Density  I  75^52%  42^29%  Footnote: Refer to calculation method explained in Section 2.3.2, 2.3.3 and 2.3.4. P22  iii.^Runoff from green roofs: Table 4-13 below shows that the traditional roofs can create 857mm of runoff in the wettest year, 564 mm in the average year and 239mm in the driest year. Green Roof 1 with a Kc value of 0.3 could reduce the rooftop runoff rate to 65% in the wettest year and 46% in the average year. Green 65  Roof 2 with a Kc value of 0.5 could reduce rooftop runoff rate to 41% in the wettest year and 10% in the average year. Green Roofs 3 and 4 with a Kc value of 0.7 or more could reduce rooftop runoff rate by more than 80% in the wettest year. However, rainfall alone in the average year did not fulfill the water needs of the plants for Green Roofs 3 and 4. Moreover, due to the high moisture deficit in the driest year, plants for all four green roofs would not survive without supplemental irrigation.  Table 4-13: Runoff rates from traditional roof and green roofs. San Antonio. TX San Antonio, TX  Traditional  roof (mm)  Kc= 0.3  Kc= 0.5^Kc=0.7  Kc= 0.8  Green Roof  Green Roof^i Green Roof  Green Roof  (mm)^2 (mm)^3 (mm)  4 (mm)  Wettest Year  857^100%  553^65%  350^41%^148^17%  46^5 %  Average Year  564^100%  261^46%  59^10% I^-143^0%  -244^0°/0  Driest Year  239^100%  -107^0%  -337^0%^-567^0%  -683^0%  Footnote: Refer to calculation method explained in Section 2.3.5. P.27  Table 4-14 below shows the effects of green roofs on reducing the total stormwater runoff. In an average year, 22% to 36% of the total runoff created from the sites with connected impervious surfaces can be reduced by Green Roof 1, 36% to 60% by Green Roof 2 and 40% to 67% by Green Roofs 3 and 4. If roofs are disconnected, 60% to 100% of the total runoff can be reduced by Green Roof 1, up to 100% by Green Roofs 2, 3, and 4. If all impervious surfaces were disconnected, zero runoff can be achieved by greening 42% to 75% of the rooftop areas with Green Roof 1, 25% to 45% with Green Roof 2, 18% to 32% with Green Roof 3, and 16% to 28% with Green Roof 4.  66  Table 4-14: Total runoff rates when applying green roofs- selected residential sites in San Antonio, TX (average year) San Antonio, TX Urban Core Zone High Density  Urban Center Zone Medium Density  General Urban Zone Low To Medium Dens  Suburban Zone Low Density  Urban Core Zone High Density  Urban Center Zone Medium Density  General Urban Zone Low To Medium Density Suburban Zone Low Density  Urban Core Zone High Density  Urban Center Zone  2  Medium Density  a)^General Urban Zone a)^  Low To A/Tedium Density  Suburban Zone Low Density  Urban Core Zone High Density  Urban Center Zone Medium Density  General Urban Zone Low To Medium Density  Suburban Zone Low D  with connected impervious surfaces (mm)  with disconnected roofs (mm)  with disconnected impervious surfaces (mm)  432^78%  181  64%  30  11%  -26 ^ 75%*  0%  184  65%  36  23%  -58 ^ 42%*  0%  100  69%  30  21%  -20 ^ 56%*  0%  353  64%  113  40%  -37 ^ 78%"  0°/0  -30 ^ 80%"  0%  -124 ^ 25%*  ()°/.  0%  -50 ^ 34%"  0%  -93  0°/0  45%*  118  41%  71  49%  329  60%  93  33%  -105 ^ 56%*  0%  -161 ^ 32%*  ()°/.  98  35%  -96 ^ 59%*  0%  -190 ^ 18%*  0%  62  43%  -29 ^ 72%*  0%  -79 ^ 24%"  0%  329  60%  93  33%  -139 ^ 49%*  0%  -195 ^ 28%*  0%  98  35%  -130 ^ 51%"  0%  -224 ^ 16%*  0%  62  43%  -44 ^ 63%"  0%  -94 ^ 21%*  0%  Footnote: 1. Refer to calculation method explained in Section 2.3.6. P.32 2." The percentage of the total roof areas recommended to be greened to achieve zero runoff.  67  Compared with Richmond, BC, the annual rainfall in San Antonio is much lower. According to the results in Table 4-13 and 4-14, green roofs with high water-use plants could achieve zero rooftop runoff in the average year. However, even low water-use plants on green roofs would require irrigation in order to survive during the driest year. The Table 4-15 shows the water balance of Green Roof 1 with a Kc value of 0.3. The maximum deficits of water balance for Green Roof 1 were 43 mm in the wettest year, 24 mm in the average year, and 161 mm in the driest year. The longest drought period for Green Roof 1 is 40 days in the wettest year, 20 days in the average year, and 160 days in the driest year.  Table 4-15: Calculation of water balance for Green Roof 1. San Antonio, TX Dates  wettest year  average year  driest year  (mm)  (mm)  (mm) 50  27-Jun  to  6-Jul  313  28  7-Jul  to  16-Jul  -1  -16  -15  17-Jul  to  26-Jul  4  7  -15  27-Jul  to  5-Aug  ♦^-13  -5  -14  8-Aug  to  17-Aug  4  -12  18-Aug  to  27-Aug  -15  -14  E  -15 CN  E E  -10  A  -14  28-Aug  to  6-Sep  -6  7-Sep  to  16-Sep  103  4  E  -10  17-Sep  to  26-Sep  36  6  c;  -12  27-Sep  to  6-Oct  -11  0  -10  7-Oct  to  16-Oct  44  36  -8  17-Oct  to  26-Oct  100  -7  -9  27-Oct  to  5-Nov  37  -8  -8  6-Nov  to  15-Nov  -8  17  -7  16-Nov  to  25-Nov  -8  -4  -5  E  68  Dates  wettest year  average year  driest year  (mm)  (mm)  (mm)  26-Nov  to  5-Dec  -o  -2  6-Dec  to  15-Dec  23  -5  Footnote: Refer to calculation method explained in Section 2.3.5. P.27  Table 4-16 shows the water balance of Green Roof 2 with a Kc value of 0.5. The maximum deficits of water balance for Green Roof 2 were 89 m in the wettest year, 105mm in the average year and 286mm in the driest year. The longest drought period for Green Roof 2 is 60 days in the wettest year, 90 days in the average year, and 180 days in the driest year.  Table 4-16: Calculation of water balance for Green Roof 2. San Antonio. TX Dates  wettest year  average moist^driest year  (mm)  year (mm)^(mm)  27-Jun^to^6-Jul  310  7-Jul^to^16-Jul  -7  17-Jul^to^26-Jul 27-Jul^to^5-Aug  E  E cr) co  43  22  •  •  -27  -26  -3  -3  -25  -21  -13  -24  -17  E  -7  -21  18-Aug^to^27-Aug  -25  Lc)  -24  -24  28-Aug^to^6-Sep  -15  -19  -24  7-Sep^to^16-Sep  97  -5  -17  17-Sep^to^26-Sep  28  -1  8-Aug^to^17-Aug  E  -20  27-Sep^to^6-Oct  -18  -7  E E  7-Oct^to^16-Oct  40  31  CO  -17 -13  \  17-Oct^to^26-Oct  98  -12  -14  27-Oct^to^5-Nov  34  -13  -13  6-Nov^to^15-Nov  -14  14  -12  16-Nov^to^25-Nov  -14  -7  -8  26-Nov^to^5-Dec  -3  -6  -6  6-Dec^to^15-Dec  21  -9  -7  16-Dec^to^25-Dec  -7  -3  21-Dec^to^30-Dec  -3  -8  Footnote: Refer to calculation method explained in Section 2.3.5. P.27  69  Table 4-17 shows the water balance of Green Roof 3 with a Kc value of 0.7. The maximum deficits of water balance for Green Roof 3 were 138mm in the wettest year, 186mm in the average year, and 404mm in the driest year. The longest drought period for Green Roof 3 is 60 days in the wettest year, 90 days in the average year, and 180 days in the driest year.  Table4-17: Calculation of water balance for Green Roof 3. San Antonio. TX Dates 27-Jun  to  6-Jul  7-Jul  to  16-Jul  17-Jul  to  26-Jul  27-Jul  to  8-Aug  to  wettest year  average year  driest year  (mm)  (mm)  ( mm) 35  306^6  -38  -14  A  -36 !  -11  -14  -36  5-Aug^E  -30  -22  -34  17-Aug^Co Co 27-Aug  -25  -17  -30  -34  -33  -28  -35 -24  E  -36  E  18-Aug  to  28-Aug  to  6-Sep  -24  7-Sep  to  16-Sep  92  -14  17-Sep  to  26-Sep  21  -8  -25  co  -13  -27  E E  -23  27-Sep  to  6-Oct  7-Oct  to  16-Oct  35^26  -18  17-Oct  to  26-Oct  96^-17  -20  27-Oct  to  5-Nov  32^-18  -18  6-Nov  to  15-Nov  -19^12  -17  16-Nov  to  25-Nov  -19^-10  -12  26-Nov  to  5-Dec  -6^-9  -9  6-Dec  to  15-Dec  18^-12  -10  16-Dec  to  25-Dec  -10  21-Dec  to  30-Dec  -5  •  -6 -15  Footnote: Refer to calculation method explained in Section 2.3.5. P.27  Table 4-18 shows the water balance of Green Roof 4 with a Kc value of 0.8. The maximum deficits of water balance for Green Roof 4 were 70  162mm in the wettest year, 235mm in the average year, and 463mm in the driest year. The longest drought period for Green Roof 4 is 60 days in the wettest year, 90 days in the average year, and 180 days in the driest year.  Table 4-18: Calculation of water balance for Green Roof 4. San Antonio, TX Dates  wettest year  average year  driest year  (mm)  (mm)  ( mm)  27-Jun^to^6-Jul  304 l  81  31  7-Jul^to^16-Jul  -17  -43  -41  -14  -18  -41  7-Jul^to^5-Aug  E E  -34  -28  -39  8-Aug^to^17-Aug  CO  -28  -21  -35  -39  -38  -32  -40 -28  7-Jul^to^26-Jul  E  E ir) co  18-Aug^to^27-Aug  -41  28-Aug^to^6-Sep  -28  7-Sep^to^16-Sep  90  -18  17-Sep^to^26-Sep  17  -12  27-Sep^to^6-Oct  -28  CV  -24  E  E co CO  -31 -26  7-Oct^to^16-Oct  33  30  17-Oct^to^26-Oct  95  -21  -23  27-Oct^to^5-Nov  30  -20  -21  6-Nov^to^15-Nov  -22  9  -19  16-Nov^to^25-Nov  -22  -10  -13  26-Nov^to^5-Dec  -7  -10  -10  6-Dec^to^15-Dec  17  -15  -11  16-Dec^to^25-Dec  -12  -8  21-Dec^to^30-Dec  -5  -18  -21  Footnote: Refer to calculation method explained in Section 2.3.5. P.27  4.1.3. Toronto, ON  a. Rainfall investigation (1997 — 2006): Precipitation data for Toronto, ON, are obtained from Environment Canada. (http://www.climate.weatheroffice.ec.gc.ca/Welcome_e.html) 71  Wettest year: 2003 (P = 896mm) i. Average year: 2004 (P = 755mm) ii. iii.^Driest year: 1997 (P= 629mm)  Figure 4-3: Precipitation (1997-2006) in Toronto, ON 1800 1600 1400 1200 1000 800 600 400 200  0 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006  Source from: Environment Canada. (http://www.climate.weatheroffice.ec.gc.ca/Welcome_e.html)  b. Selected residential sites for calculations: Four residential sites of varying density have been selected in Toronto, ON. The areas of impervious and pervious surfaces in each of the sites have been calculated as follows (Table 4-19):  Table 4-19: Selected residential sites in Toronto. ON Toronto, ON  Site area (m 2 )  Roof (m 2 )  Street (m 2 ) -•.•-•--•__  Landscape / Open space ( m2) -• ••,_-  _-_-_-_-•--,  Urban Core Zone High Density  50.000^100%  10,834^22%  20.359^40%  18.807^38%  Urban Center Zone Medium Density  50,000^100%  9,796^20%  17,795^35%  22,409^45%  General Urban Zone Low To Medium Density  50,000^100%  24,203^48%  2.560^6%  23,237^46%  Suburban Zone Low Density  50,000^100%  15.613^31%  1.271^3%  33.116^66%  4  72  c. Stormwater runoff calculation results for Toronto, ON i.^Runoff from connected impervious surfaces and disconnected impervious surfaces: Assume that all impervious surfaces have a CN of 98 and all landscape areas are in fair condition with a CN of 69. Using the Equationl in Section 2.2.1 and the daily rainfall data of an average moist year -2004(Environment Canada 2008) in Toronto, ON, the annual runoff rates created from the sites with connected impervious surfaces and disconnected impervious surfaces are shown in Table 4-20 below.  Table 4-20: Runoff rates by cover types in Toronto, ON Cover type  Annual  Connected impervious surfaces Disconnected  runoff rates^roof (mm)  Disconnected impervious surfaces  Street  Open space  Roof  392.92  0.79  392.92  392.92  L to M 9.11^6.01^24.41^6.78 H^M^L 1c M^L ,  57.57^32.96^29.21^7.59  Foot note: 1. H — High density^M — medium density^L to M — Low to medium density^L — Low density 2. Refer to calculation method explained in Section 2.3.2, 2.3.3 and 2.3.4. P22  The total runoff rates in Table 4-2' are the total runoff from all residential sites. The calculation of total runoff rates in Table 4-21 is based on the climate data in an average year in Toronto, ON (Environment Canada). According to the calculation results, without any stormwater management treatments the 5-hectare Urban Core Zone can generate  73  245 mm of annual stormwater runoff. Runoff from the Urban Center Zone and General Urban Zone is slightly less than that from the selected Urban Core Zone, 217mm and 211mm, respectively. The low-density Suburban Zone generates minimum runoff, about half that of the Urban Core Zone. If the runoff from roofs flows onto the landscaped areas of the site before entering the site's drainage system, the total annual runoff can be reduced from 33% to as much as 89%. If all the runoff from roofs and other ground level impervious surfaces like streets and parking lots can flow onto the landscaped areas of the site before entering the site's drainage system, the total annual runoff can be reduced by over 90%.  Table 4-21: Total runoff rates from selected residential sites in Toronto. ON (Average  year) Total Runoff Rate Toronto, ON  Site area (ha)  Urban Core Zone High Density  5  245 100%  163 67%  22^9%  Urban Center Zone Medium Density  5  217 100%  143 66%  15  General Urban Zone Low To Medium Density  5  211 100%  31^15%  Suburban Zone Low Density  5  133 100%  With connected impervious surfaces (mm)  With disconnected roofs (mm)  With disconnected impervious surfaces (mm)  7%  14^6%  5^4%  Footnote: Refer to calculation method explained in Section 2.3.2, 2.3.3 and 2.3.4. P22  ii.^Runoff from green roofs: Table 4-22 below shows that the traditional roofs can create 527mm of runoff in the wettest year, 393mm in the average year and 302mm in the 74  driest year. Green Roof 1 with a Kc value of 0.3 can reduce rooftop runoff rate to 52% in the wettest year, 37% in the average year, and 16% in the driest year. Green Roof 2 with a Kc value of 0.5 can reduce rooftop runoff rate to 20% in the wettest year. However, due to the high moisture deficit, rainfall alone could not offset the water use of plants for Green Roofs 2, 3 and 4 even in the average year, much less in the driest year.  Table 4-22: Runoff rates from traditional roof and green roofs, Toronto, ON Toronto, ON  Traditional roof (mm)  Kc= 0.3  Kc= 0.5  Kc=0.7  Kc= 0.8  Green Roof  Green Roof  Green Roof  Green Roof  3 (mm)  4 (mm)  1 (mm)  Wettest Year  527^100%  2 (mm) r275^52%^107^20%  Average Year  393^100%  144^37%^-22^0%  -188^0%^-271^0%  i 302^100%  48^16% ^-122^0%  -291^0%^-376^0%  -7—  Driest Year  -61^0%^-144^0%  Footnote: Refer to calculation method explained in Section 2.3.5. P.27  Table 4-23 below shows the effects of green roofs on reducing the total stormwater runoff. In an average year, 22% to 58% of the total runoff created from the sites with connected impervious surfaces can be reduced by Green Roof 1, 35% to 92% by Green Roofs 2, 3 and 4. If roofs are disconnected, 60% to 100% of the total runoff can be reduced by Green Roof 1, up to 100% by Green Roofs 2, 3, and 4. If all impervious surfaces were disconnected, zero runoff could be achieved by greening 6% to 41% of the rooftop areas with Green Roof 1, 4% to 24% with Green Roof 2, 3% to 17% with Green Roof 3, and 2% to 15% with Green Roof 4.  75  Table 4-23: Total runoff rates when applying green roofs- selected residential sites in Toronto, ON (average year)  Toronto, ON  with connected^with impervious^disconnected ^surfaces (mm)^roofs (mm)  Urban Core Zone Higti,Density  6  4  2  cu o  Urban Center Zone Medium Density  General Urban Zone Low To Medium Density  Suburban Zone Low Density  Urban Core Zone High Density  N  "a 2  Urban Center Zone  co  General Urban Zone  Medium Density  Low To Medium Dens  Suburban Zone Low Density  Urban Core Zone High Density  v.) 0  Urban Center Zone  2  Medium Density  a.;  General Urban Zone Low To Medium Density  Suburban Zone Low Density^I  Urban Core Zone High Density  Urban Center Zone 0  12  Medium Density  a;  General Urban Zone Low To Medium Dens  Suburban Zone Low Density  with disconnected impervious surfaces (mm) -32  131 °A  191  78%^109  45%  ^ 41 %*  168  78%^94  43%  ^ 31%*  90  43%  0%  ^ 12%"  0%  ^ 6%* ^ 24%*  0%  -66 ^  0%  -34  -90 ^  -107  26%* 55  42%  -64 ^  0%  0%  -73  18%*  -68 160  65%^I^73  30%  140  65%  62  28%  0%  18%* 20  10%  -170 ^  00/0  15%*  -116 11  8%  0 (Y0  11%*  -187 70/o *  -125 4%* -  160  65%  37  140  65%^29  20  10%  11  8%  160  65%  -250 ^ 11%*  -167 i^8%*  0%  104  15%^F ^ 17%" 13%  0%  0%  -99 ^  0%  -267 ^  C)  13%*  0%  5%* ^0%  -176 ^  0%  122 ^  0%  I^3%* -  19  8%  15%*  -115 140  65%  13  20  10%  -291 ^  11  8%  0 0/0  6% 12%*  1 0%* -  193  7%*  0%  -308 ^  0%  4%* 0%  -202 ^ 2%*  0%  Footnote: 1. Refer to calculation method explained in Section 2.3.6. P.32 2." The percentage of the total roof areas recommended to be greened to achieve zero runoff.  76  Table 4-24 shows the water balance of Green Roof 1 with a Kc value of 0.3. The maximum deficits of water balance for Green Roof 1 were 26mm in the wettest year, 17mm in the average year, and 81mm in the driest year. The longest drought period for Green Roof 1 was 30 days in the wettest year, 30 days in the average year, and 80 days in the driest year.  Table 4-24: Calculation of water balance for Green Roof 1, Toronto. ON Dates  wettest year  average year^driest year  (mm)  (mm)^j  (MM)  1  10-May  to  19-May  18  -14  20-May  to  29-May  16  26  30-May  to  8-Jun  29  -9  -12  9-Jun  to  18-Jun  -2  15  -4  19-Jun  to  28-Jun  -15  -9  E  -7  29-Jun  to  8-Jul  -9  20  cc  -7  9-Jul  to  18-Jul  5  7  -15  19-Jul  to  28-Jul  -  1  0  -11  29-Jul  to  7-Aug  -5  -2  8-Aug  to  17-Aug  11  18-Aug  to  27-Aug  El  E  •  -11  •  15  -6  10  -9  12  ti  -12  Footnote: Refer to calculation method explained in Section 2.3.5. P.27  Table 4-25 shows the water balance of Green Roof 2 with a Kc value of 0.5. The maximum deficits of water balance for Green Roof 2 were 84 mm in the wettest year, 50mm in the average year and 158mm in the driest year. The longest drought period for Green Roof 2 was 60 days in the wettest year, 50 days in the average year, and 90 days in the driest year. 77  Table 4-25: Calculation of water balance for Green Roof 2, Toronto. ON  Dates  wettest year  average moist  driest year  (mm)  year (mm)  (mm)  7  30-Apr  to  9-May  13  6  10-May  to  19-May  11  -23  20-May  to  29-May  9  19  -18  30-May  to  8-Jun  22  -17  -21  9-Jun  to  18-Jun  -11  6  -13  19-Jun  to  28-Jun  -26  -18  co  -17  29-Jun  to  8-Jul  E  -20  11  r  -17  9-Jul  to  18-Jul  co  -4  -1  -27  19-Jul  to  28-Jul  -11  -8  -20  29-Jul  to  7-Aug  -13  -10  -25  8-Aug  to  17-Aug  2  -14  1  1 8 -A u g  to  27-Aug  -21  -17  5  E  E  •  •  E  -6  Footnote: Refer to calculation method explained in Section 2.3.5. P.27  Table 4-26 shows the water balance of Green Roof 3 with a Kc value of 0.7. The maximum deficits of water balance for Green Roof 3 were 212 mm in the wettest year, 90mm in the average year and 327mm in the driest year. The longest drought period for Green Roof 3 was 100 days in the wettest year, 50 days in the average year, and 160 days in the driest year.  Table 4-26: Calculation of water balance for Green Roof 3, Toronto. ON  Dates  wettest year  average year  driest year  (mm)  (mm)  (mm)  30-Apr  to  9-May  7  -1  2  10-May  to  19-May  5  -32  -12  20-May  to  29-May  1  12  -26  30-May  to  8-Jun  14  -26  -30 78  Dates  wettest year  average year  (mm)  (  driest year mm  mm)  9-Jun  to  18-Jun  -19  -3  -23  19-Jun  to  28-Jun  -37  -27  -28  29-Jun  to  8-Jul  -30  1  -26  9-Jul  to  18-Jul  -13  -10  -38  19-Jul  to  28-Jul  -16  -29  -20  E  -19  -35  8-Aug  to  7-Aug^(NI c7i 17-Aug  18-Aug  to  27-Aug  -30  -24  28-Aug  to  6-Sep  -25  1  -21  7-Sep  to  16-Sep  -10  -8  -9  17-Sep  to  26-Sep  55  -21  -14  27-Sep  to  6-Oct^-12  -17  -13  7-Oct  to  16 Oct^-2  -5  -14  29-Jul  to  -  -21  E E O  -7  •  O  -22  E  E  r— co  -7 -2  Footnote: Refer to calculation method explained in Section 2.3.5. P.27  Table 4-27 shows the water balance of Green Roof 4 with a Kc value of 0.8. The maximum deficits of water balance for Green Roof 4 were 257mm in the wettest year, 259mm in the average year and 441mm in the driest year. The longest drought period for Green Roof 4 was 100 days in the wettest year, 140 days in the average year, and 210 days in the driest year.  79  Table 4-27: Calculation of water balance for Green Roof 4, Toronto, ON Dates  wettest year  average year  driest year  (mm)  (mm)  (mm)  11-Mar  to  20-Mar  -6  -7  12  21-Mar  to  30-Mar  -8  -10  -1  31-Mar  to  9-Apr  18  -0  -16  10-Apr  to  19-Apr  -23  -7  -10  20-Apr  to  29-Apr  -18  -14  -22  30-Apr  to  9-May  4  -12  -3  10-May  to  19-May  -3  -29  -15  20-May  to  29-May  4  8  -29  30-May  to  8-Jun  11  -29  -33  9-Jun  to  18-Jun  -23  -31  -31  19-Jun  to  28-Jun  -43  -31  •  -31  E E  29-Jun  to  9-Jul  to  8-Jul  E 18-Jul^E  -34  -1  -31  -17  -14  -44  -20  -33  -23  -39  -25  -13  -30  -6  1"--  19-Jul  to  28-Jul^C■J  -25  29-Jul  to  7-Aug  -26  8-Aug  to  17-Aug  -10  18-Aug  to  27-Aug  -35  28-Aug  to  6-Sep  -28  -2  -25  7-Sep  to  16-Sep  -14  -10  -12  17-Sep  to  26-Sep  27  -25  -17  27-Sep  to  6-Oct  11  -20  -15  7-Oct  to  16-Oct  -5  -8  17-Oct  to  26-Oct  -0  -8  E E rn L.r) CV  •  -17 5  Footnote: Refer to calculation method explained in Section 2.3.5. P.27  4.2 Calculation results — Quality of stormwater runoff The quality of stormwater runoff is dependent on the runoff volume and the concentration of contaminants in stormwater runoff. In order to improve the quality 80  of stormwater runoff, both the concentration of contaminants in stormwater runoff and the total runoff volume should be considered. Studies found that green roofs can reduce both the concentration of contaminants and runoff volume (Van Metre, 2003).  4.2.1. Reduction in Concentration of Contaminants Figures 4-4 and 4-5 show the event mean concentration by land use for pollutant types (North Carolina Division of Water Quality, 2007). There is no linear relationship between the coverage of impervious surfaces and the mean concentration for most of the contaminants. The concentrations of many contaminants remain at relatively constant low rates. For example, the concentrations of TKN (Total Kjeldahl Nitrogen), NO2+NO3, organic nitrogen, total nitrogen, total phosphorus, and dissolved phosphorus from high-density residential areas with 72% impervious surface coverage are slightly increased, when compared with those from urban open areas with 4% impervious surface coverage (North Carolina Division of Water Quality, 2007). The concentrations that increase the most in conjunction with the increase of impervious surfaces are TSS (total suspended solids), COD (chemical oxygen demand), and BOD (biochemical oxygen demand). Figure 4-5 shows that the concentration of heavy metals like Zn (zinc), Pb (lead), and Cu (copper), will be influenced greatly by impervious surface coverage. The concentration of Zn from high-density residential areas can be up to six times that of urban open areas. Therefore, reducing impervious surface coverage will reduce concentrations of contaminants like TDS, COD, TSS, BOD, Zn, Cu and Pb, which will in turn reduce contaminant mass loading. Based on calculations of selected sites in Richmond (BC), San Antonio 81  (TX) and Toronto (ON), rooftops can occupy as much as 48% of the total residential coverage (Table 4-1). One way to reduce impervious surface coverage is to apply green roofs. A study in Austin, Texas, showed that metal roofing is a source of cadmium and zinc, and asphalt shingles are a source of lead and possibly mercury (Van Metre, 2003). Eliminating metal and asphalt shingle roofs and replacing them with green roofs could therefore reduce the total lead and mercury counts in stormwater runoff. Green roofs can also remove lead from stormwater runoff through binding and uptake in the growing substrate (Banting, 2005).  TSS^Total Suspended Solids:^TSS in the water refers to the amount of filterable material in the water. TDS^Total Dissolved Solids:^The total dissolved solids load of the water includes sodium, magnesium, calcium, iron, chloride, sulfate, nitrate and many others. BOD^Biochemical Oxygen Demand COD^Chemical Oxygen Demand TKN^Total Kjeldahl N NO2+NO3^Nitrate Nitrogen NH3-N^Ammonia Nitrogen Organic N^Organic Nitrogen Total N^Total Nitrogen Total P^Total Phosphorus Dissol. P^Dissolved Phosphorus Cd^Cadmium Cr^Chromium Cu^Copper Pb^Plumbum Ni^Nickel Zn^Zinc  Source: The North Carolina Division of Water Quality, 2007.  82  ^  •  Figure 4-4: Recommended event mean concentrations by land use for pollutant types (Source: The North Carolina Division of Water Quality, 2007.) 70  2 6) E 2 cn o E H a^0 0 -,-:” E E ^ 0 0  2^ ii,^ E w^ O H  -en E in  60  ^  50 E  40  0  cn • -en E ^  20 10  Eco -0 wH -  U  22 CD r j:i• -J  EE=-CO,-  EE  Ol  60 a E z cza  ^  -  co z  0  O  E  E  30  E ^  2 -6) E  Zni^-  gh„H-t E E  ^  E  0 co  E E or‹) z E O E z z -am ?rg  rnp z- E a_ E z .-Qz a_ . -+ -  ^  z  E  E Z oz-ci_ z •E - o_ •  YO °Hom  ^  Urban open  Low-density residential  Medium-density residential  ■ TSS (mg/L)  20  22.1  30.5  ■ TDS (mg/L)  52  52  High-density residential  47.7  52  ^52  OBOD (mg/L)  4.4  5  7.5^13.3  COD (mg/L)  30.7  33.4  43.5^ 63.1  ■ TKN (mg/L)  0.7  0.8  1.1^  1.7  ■ NO2+NO3 (mg/L) ■ Organic N (mg/L)  0.4  0.4  0.6^  0.8  0.5 1.1  0.6  0.7  1.1  1.2  1.7  2.7  ■ Total P (mg/L)  0.2  0.2  0.1^  0.1  0.2 0.1  0.3  ■ Dissol. P (mg/L)  0 Total N (mg/L)  0.2  Figure 4-5: Recommended event mean concentrations by land use for heavy metals (Source: The North Carolina Division of Water Quality, 2007.) C)  160  a C  140 120  -  100 C)  80  C  60  J  40 20 0  en a  -  - ,  r o^_O 0 0-  °  Mae  Urban open  n_ -2c^ 2 2 ---,^,...,, itb m. ,,,, ,...., 2 ..--..^N^ --• -,_,^.- ,.i 2 --I sen -=.1 ,_ : ^2 ---1 R --d, ' ::-: , ^:i - , ._ c, ..,^o) 01 "."' 1 CD^E) 2 0 -_, a) .. n ----^ r! .- ---^ -- ,-..^-, --a. ......^,_ ,_ U ^._ z . a - z^-3, 0 -. 5 0 a .^3 c 5  .2_  •  Eh=  Low-density residential^  ii  Medium-density^ High-density residential residential 0.7  0Cd (pg/L)  0.5  0.5^  0.6^  Cr (pg/L)  2.9  3.1^  3.8^  4.9  ■ Cu (pg/L)  5.7  6.5^  9.7^  17.3  ■ Pb (pg/L)  3.2  3.8^  6.1^  12  • Ni (pg/L)  4.7  4.8^  5^  5.4  ■ Zn (pg/L)  25.4  31.2^ 59.4^ 145.9  83  4.2.2. Reduction in Runoff Volume As the concentrations of many contaminants are not greatly influenced by impervious surface coverage, improvement in the quality of stormwater runoff may also be achieved by reducing the total runoff volume. Figures 4-6 through 4-9 show the calculated stormwater reduction rates via different stormwater management solutions. In Richmond (BC), regardless of zoning type, the most effective way to reduce stormwater runoff volume would be to disconnect impervious surfaces via vegetative matter. This intervention could improve runoff quality by as much as 88% (Figure 4-9). Replacement of traditional roofs with green roofs could also improve runoff quality by 27% to 72% (Figure 4-7). Moreover, the high annual rainfall in Richmond allowed for the use of high-water-demand plants in green roofs. Higher water-use plants could result in a higher stormwater runoff reduction rate, and therefore lead to improved quality of stormwater runoff. In San Antonito (TX), improving stormwater runoff quality by disconnecting impervious surfaces was efficient for the Urban Center, General Urban and Suburban Zones. Disconnection could improve stormwater runoff quality by over 70% (Figure 4-9). However, due to the lack of pervious landscape areas, disconnecting impervious areas would not be efficient for the Urban Core Zone. Disconnection could only improve stormwater runoff quality by 12% to 25% (Figure 4-6). Applying green roofs, however, could improve runoff quality by up to 67% (Figure 4-7). Because of the lack of rainfall during the summer months, high water-use plants would be at risk. Supplemental irrigation would be required for high water-use plants to survive the summer.  84  In Toronto (ON), disconnecting impervious surfaces could improve the runoff quality by over 90% (Figures 4-6 to 4-9). Applying green roofs could also improve runoff quality, but the effects would be variable. In the Urban Core and Urban Center Zones, rooftop coverage only occupied a small portion of the total impervious areas. As a result, green roofs could only improve stormwater runoff quality by no more than 35% (Figures 4-6 and 4-7). However, in the General Urban and Suburban Zones, rooftops were the major component in the total impervious area. Therefore, applying green roofs could improve stormwater runoff quality by up to 90% (Figures 4-8 and 4-9). Compared with Richmond and San Antonio, however, Toronto has the lowest annual rainfall. High water-use plants would be at risk of wilting, and supplemental irrigation would be required for these plants to survive the summer.  85  Figure 4-6: Stormwater runoff from the selected high-density Urban Core Zone in the average year 120% 100% 80% 60% 40% 20% 0%  Richmond  San Antonio  Toronto  100%  100%  100%  ^ disconnected roof^40% 19% ■disconnected roof+street 74% ^ green roof1  88%  67%  75%  9%  78%  78%  El green roof2  57%  64%  65%  ■green roof3  40%  60%  65%  IS green roof4  31%  60%  65%  • connected^  Figure 4-7: Stormwater runoff from the selected medium-density Urban Center Zone in the average year 120% ^ 100%  -  80% I  -  60% I  -  40% 20% 0%  Richmond  San Antonio  Toronto  ■ connected  100%  100%  100%  El disconnected roof  34%  47%  66%  Q disconnected roof+street  14%  27%  ^ green roof1  73%  64%  7% 78%  El green roof2  55%  40%  65%  ■green roof3  37%  33%  65%  28%  33%  65%  Ed green roof4  86  Figure 4-8: Stormwater runoff from the selected low- to medium-density General Urban Zone in the average year 120% 100% 80% 60% 40% 20% 0%  Richmond  San Antonio  Toronto  ■ connected  100%  100%  100%  ^ disconnected roof  45%  48%  15%  Edisconnected roof+street  15%  27%  6%  0 green roof1  78%  65%  43%  green roof2  63%  41%  10%  II green roof3  48%  35%  10%  41%  35%  10%  green roof4  Figure 4-9: Stormwater runoff from the selected low-density Suburban Zone in the average year 120%  100% 80% 60% 40% 20% -  0% ■ ^ ■ ^ • ■  connected disconnected roof disconnected roof+street green roof1 green roof2 green roof3 Ea green roof4  tir  Richmond  San Antonio  Toronto  100% 53% 12% 81% 69% 57% 51%  100% 52% 29% 69% 49% 43% 43%  100% 11% 4% 42% 8% 8% 8%  87  •  4.3 Summary for Green Roofs 1, 2, 3 and 4 As followed are the summaries of the calculation results for Green  Roofs 1, 2, 3 and 4 on stormwater runoff. a. Green Roof 1 (low water use plants — Kc value 0.3): Figure 4-10 shows that in Richmond, BC, Green Roof 1 would reduce rooftop runoff by 36% in the average year, 24% in the wettest year and 47% in the driest year. Applied in San Antonio, TX, Green Roof 1 would reduce rooftop runoff by 54% in the average year, 35% in the wettest year and 100% in the driest year. In Toronto, ON, Green Roof 1 could reduce rooftop runoff by 63% in the average year, 48% in the wettest year and 84% in the driest year. Figure 4-11 shows that in the driest year, plants on Green Roof 1 would need 98mm of supplemental water to survive days with no rain in summer in Richmond, BC, 161 mm in San Antonio, TX, and 81mm in Toronto, ON.  Figure 4-10: Annual rooftop runoff reduction Green Roof 1  C 0  E  450 400  80% 70%  0C  60% 50%  2 0  40%  O 0  500  100% 90%  o  -  Figure 4 - 11: Maximum deficits - Green Roof 1  N 350 -C) 300  _2 250 200 E 150  30% 20%  rz 100 2 50  10%  161 ^ 92 98 8t_ 51^43 24 ^26 17  0  0% Richmond^San Antonio^Toronto  ■ Wettest year ■Average moist year ^ Driest year  Richmond^San Antonio^Toronto  r■ Wettest year ■Average moist year ^ Driest  b. Green Roof 2 (low to medium water use plants — Kc value 0.5): Figure 4-12 shows that in Richmond, BC, Green Roof 2 would reduce rooftop  88  runoff by 60% in the average year, 40% in the wettest year and 78% in the driest year. Applied in San Antonio, TX, Green Roof 2 would reduce rooftop runoff by 90% in the average year, 59% in the wettest year and 100% in the driest year. In Toronto, ON, Green Roof 2 would reduce rooftop runoff by 80% in the wettest year, and achieve zero runoff in the average and the driest years. Figure 4-13 shows that in the driest year, plants of Green Roof 2 would need 212mm of supplemental water to survive days without rain in summer in Richmond, BC, 286 mm in San Antonio, TX and 158mm in Toronto, ON.  Figure 4-12: Annual rooftop runoff reduction Green Roof 2  Figure 4 - 13: Maximum deficits - Green Roof 2  100%  500  90%  450 E 400  80%  0  ,7; 350  70% 0  2 0_  0  0  -  60%  300  50% 40%  -8 250  286  g 200  30%  .  E 150  20%  100  10%  50 0  0% Richmond^San Antonio^Toronto  [• Wettest year ■ Average moist year ^ Driest year  Richmond^San Antonio^Toronto Wettest year  • Average moist year ^ Driest year  c. Green Roof 3 (medium water use plants — Kc value 0.7): Figure 4-14 shows that in Richmond, BC, Green Roof 3 would reduce rooftop runoff by 84% in the average year, 56% in the wettest year and achieve zero runoff in the driest year. Applied in San Antonio, Green Roof 3 could reduce rooftop runoff by 83% in the wettest year, and achieve zero runoff in the average year and driest years. In Toronto, ON, Green Roof 3 would reduce rooftop runoff by 80% in the wettest year, and achieve zero runoff  89  in the average and driest year. Figure 4-15 shows that in the driest year, plants on Green roof 3 would need 322mm of supplemental water to survive dry days without rain during summer in Richmond, BC, 404mm in San Antonio, TX, and 327mm in Toronto, ON.  Figure 4-14: Annual rooftop runoff reduction Green Roof 3  ▪ 0 •  -  100%  500  90%  450  ^  80% 70%  E 400  ^  30%  322"j; 350 ^ •5 300 4,242 1_ -8 250 200 15 . E 150  20%  '0^100  10%  50  60%  550% 2 40% 0  o cc  Figure 4 - 15: Maximum deficits - Green Roof 3  404  E  0  0% Richmond^San Antonio^Toronto ^ Wettest year ■Average moist year ^ Driest year  Richmond^San Antonio  ^  Toronto  ■ Wettest year ■ Average moist year ^ Driest year]  d. Green Roof 4 (high water use plants — Kc value >0.8): Figure 4-16 shows that in Richmond, BC, Green Roof 4 would reduce rooftop runoff by 96% in the average year, 64% in the wettest year and achieve zero runoff in the driest year. If applied in San Antonio, TX, Green Roof 4 would reduce rooftop runoff by 95% in the wettest year, and achieve zero runoff in the average and driest years. In Toronto, ON, Green Roof 4 would achieve zero runoff even in the wettest year. Figure 4-17 shows that in the driest year, plants of Green Roof 4 would need 377mm of supplemental water to survive dry days during the summer in Richmond, BC, 463mm in San Antonio, TX, and 441 mm in Toronto, ON.  90  Figure 4-16: Annual rooftop runoff reduction Green Roof 4  0  — S 2  100%  500  90%  450  80%  E 400  70%  350  0  463 377 27  300  60% 50%  -8 250  40%  200  30%  E 150  20%  co^100  10%  50  0  0  Figure 4 - 17: Maximum deficits - Green Roof 4  ^23 _18  -  —  16  0  0% Richmond^San Antonio^Toronto • IAtest year  ■ Average moist year 1:1Driest year  Richmond^San Antonio^Toronto • Wettest year  ■ Average moist year  ^  Driest year  The effects of all four types of green roofs on runoff reduction were significant, as showed in Figures 4-10, 4-12, 4-14 and 4-16. Therefore it is important to evaluate green roofs with the maximum deficits.  4.4 Conclusions for maximum deficits 4.4.1 Relationship between maximum deficits and soil type The maximum deficit of water balance is a short-term water balance for green roofs during the summer. It shows how much water should be retained in the soil for plants to survive the summer. Higher maximum deficits require a higher water-holding capacity on green roofs. There are several ways to increase the water-holding capacity of green roofs. The soil depth can be increased or soil materials with higher water-holding capacity qualities can be used. Additional drainage layers below the growing medium can be utilized as well. However, increasing the soil depth or using extra drainage layers would increase the weight of green roofs. This increase of green roof weight could increase the cost of the green roof installation due to the additional structural considerations put into play. If 91  a green roof is part of the initial design of a building, the additional loading can be accommodated easily and for a relatively minor cost. However, if a building is retrofitted with a green roof, the design will be limited by the carrying capacity of the existing roof and structural members, unless the owner is prepared to upgrade the building, often a significant investment. (Banting D., 2005) An efficient and economical green roof should be designed to be lightweight and require minimum maintenance, but at the same time be able to reduce runoff efficiently. As a result, a reasonable maximum deficit should be considered when designing green roofs.  4.4.2 Maximum deficits and substrate design for green roofs a. Properties of soil: The ideal substrate for green roofs must be highly efficient at absorbing and retaining water while the same time having free-draining properties. (Dunnett, N. 2004.) Different soil textures have different values of Field Capacity and Available Water Storage Capacity.  Figure 4-18: Saturation, Field Capacity, and Wilting Point.  Saturation^Field capacity^Wilting  ^  Dried  No drained^Unavailable^No water ^ water Gravitational  92  i Field Capacity: the amount of water held in the soil after excess water has drained away. Field capacity of the soil increases with finer soil textures. ii Wilting Point: a water content level that identifies when plants are no longer able to extract water from the soil. iii Plant Available Water: the amount of water in the soil that can be extracted by the plant. Plant available water is calculated as follows: (Field capacity - Wilting point) x soil depth = Plant available water Therefore, the plant available water is in fact much lower proportionately than soil depth. The Soil texture of Silt Loam with 30% sand and 25% clay is one of the most appropriate growing materials for green roofs as calculated using the Water Balance Model (http://model.waterbalance.ca ). The properties of Silt Loam as followed: Field capacity: 310 mm/m Wilting point: 150 mm/m Plant available water: 310mm/m -150mm/m=160mm/m b. Maximum deficits and soil depth: The maximum deficits represent the amount of water needed for plants during dry summer days. Therefore, the plant available water should meet this requirement, in order for plants to survive drought, in summer. Using the soil texture of Silt Loam described above, for instance, 100mm of plant available water will require as much as 625mm of soil depth of Silt Loam, while a 100mm soil depth of Silt Loam contains only 16mm Plant available water. The calculations are as follows:  To achieve 100mm of plant available water: Soil depth = (1000mm)(100mm)(160mm/m) -1 = 625mm 93  With a soil depth of 100mm: Plant available water= (160mm/m)(100mm/1000mm)= 16mm  In order to minimize the soil depth but provide enough plant available water, extra drainage layers will usually be used for green roofs with high water-use plants or in dry areas. The water capacity of drainage layers can be very variable. In Germany, ZinCo provides drainage layer with capacity from 20mm to 180mm. Although drainage layers can provide greater capacity, they can be quite heavy. As a result, the maximum deficits will be an important index for designing green roofs. For an appropriate and economical green roof, especially for extensive green roofs with a soil depth between 50mm to 150mm, the maximum deficits should not be too high. A soil depth of 150mm Silt Loam has 24mm Plant available water. Assuming the maximum capacity of drainage layers for extensive green roof is 75mm (ZinCo), the maximum water-holding capacity for extensive green roofs is approximately 100mm. If the assumptive plant-available water on extensive green roofs is 100mm, the designed maximum deficit for an extensive green roof is therefore recommended within 100mm, in order to prevent vegetation from wilting during the summer drought.  4.5 Calculated Runoff vs. Real Runoff 4.5.1. Calculated Evapotranspiration (ET) vs. real ET To some extent, the runoff reduction capacity of green roofs is dependent on the evapotranspiration potential of plants, as plants with higher 94  evapotranspiration rates can transfer more rainwater from soils into the air. The evapotranspiration potential of plants in the calculations in Chapter 4, was calculated by the Evapotranspiration (ET) Method with crop coefficient (Kc) as described in Chapter 2. The calculated ET can be considered the standard crop evapotranspiration. However, the real ET would change under different conditions. When the plant available water in soil is low, the real ET would drop below the stand crop evapotranspiration. (Allen, R. G., 1998) This would happen during the summer, when high ET rates coexist with low rainfall. Temperature can also influence evapotranspiration. During cold periods in many regions like Richmond and Toronto, freezing temperatures preclude plants from remaining green and actively growing. These periods could be considered as non-growing periods. Evapotranspiration from inactive plants during non-growing periods will drop as well. (Allen, R. G., 1998) As a result, when calculating real ET using the Evapotranspiration (ET) Method when the plant available water in soil is low or during cold periods, a lower crop coefficient (Kc) should be applied.  4.5.2. Impact of roof pitch  Studies have shown that, in most cases, increasing roof slope does not necessarily increase runoff volume. Schade (2000) reported nearly constant water retention rates for roof slopes ranging from 2% up to 58%. Liesecke (1999) generalized that annual retention rates of 55 to 65% on an 8.7% sloped roof are comparable to a 2% slope. Recently, however, a study at Michigan State University found that roof pitch does influence the quantity of  95  runoff. Researchers measured runoff from roof platforms over a 14-month period, and found that platforms pitched to 6.5% (3.7°) containing 40mm of medium retained 65.9% of the total rainfall, while 70.7% of total runoff was retained by platforms at a 2% (1°) pitch with 40mm of medium. (VanWoert, N.D 2005) Therefore, if the objective of a green roof is to maximize rainfall retention, then factors of slope should be addressed.  4.5.3. Impacts of soil materials  Soil materials can influence the performance of plants on green roofs. One term related to plant medium structure is "porosity". Porosity is a measure of the pore space in a given medium. Pore space is related to the shape, size, and arrangement of media particles. Aeration porosity and water-holding capacity are two critical physical attributes of container media. Generally, smaller pores remain filled with water while larger pores empty and fill with water and air, alternately. Therefore, media with high water-holding capacity would usually have low air-holding capacity, and vice versa. (Dunnett, N. 2004) (Figure 4-19) A study at University of Sheffield by Professor James Hitchmough has found that in low-mass mineral substrates like LECA (light expanded clay granules) which high aeration but low moisture retention, plants would grow well, but suffer badly during a drought. On the other hand, in high-mass mineral substrates like crushed brick or building rubble, which are poorly aerated, but have higher moisture retention, plants would grow relatively poorly, but survive better under drought. (Hitchmough, J. 2006)  96  Figure 4-19: (a) Crushed building rubble; (b) LECA -- Light expanded clay granules) ; (c) Performance of plants in summer Source: Hitchmough, J. 2006  (a)  (b)  --^4 Note the absence Orseedtings LECA trays!  c)  97  As a result, considering the maintenance of green roofs, high-mass mineral substrates like brick or building rubble, which are poorly aerated but have higher moisture retention, would be appropriate for places where rainfall is insufficient in summer. However, the beneficial effects of green roofs on runoff would then be reduced.  98  Chapter 5  Conclusions for Calculation  JSUlt  ••  5.1 Effects of precipitation and impervious surfaces Precipitation and impervious surfaces can directly influence the amount of stormwater runoff. As shown in Figures 5-1, 5-2 and 5-3, there is a linear relationship between precipitation and stormwater runoff: higher precipitation results in higher stormwater runoff. It is also noticeable that the Urban Core Zone has the steepest curves. As a result, the increase of impervious surfaces also accelerates the runoff.  Figure 5-1: Stormwater runoff vs. precipitation — ^Figure 5-2: Stormwater runoff vs. precipitation Richmond, BC^ — San Antonio, TX 800 E 700  900 8_00_  -  E 600 0 500 400 7,, 300  g  200 < 100 0  -----  800^1000^1200^1400^1600^1800 Annual precipitation (mm)  Suburban Zone^--Urban Center Zone General Urban Zone Urban Core Zone^I  ^  E 7 °° — 600 S 500 2 400 300 E 200 < 100 0  ^ ^ ^ ^ ^  300^500^700^900^1100 Annual precipitation (mm)  -4-Suburban Zone^-4- Urban Center Zone General Urban Zone — Urban Core Zone I  Figure 5-3: Stormwater runoff vs. precipitation — Toronto, ON  350 300 -E- 250 200  2 150 2 100  <  50 ^ 0 ^ 600^700^800^900^1000  Annual precipitation (mm) -4-Suburban Zone ^-4- General Urban Zone] Urban Center Zone — Urban Core Zone  100  5.2 Conclusions for Green Roofs 1, 2, 3 and 4 a. Green Roof 1: Considering its runoff reduction and maximum deficits, Green Roof 1 could be efficient in Richmond, BC, San Antonio, TX and Toronto, ON. Especially for Richmond and Toronto, little maintenance would be required for Green Roof 1, since its maximum deficits were less than 100mm even in the driest years (Figures 4-10 and 4-11). Because Toronto experiences less rainfall than Richmond, Green Roof 1 had the highest runoff reduction in Toronto. For San Antonio, as its maximum deficit is 161 mm in the driest year, plants on Green Roof 1 may be at risk of wilting (Figure 4-11). b. Green Roof 2: The higher water use plants on Green Roof 2 resulted in higher runoff reduction, compared with Green Roof 1. For San Antonio and Toronto, Green Roof 2 could achieve zero rooftop runoff (Figure 4-12). On the other hand, rainwater alone would be insufficient for the water demands of plants. As the maximum deficit was 158mm in Toronto, plants on Green Roof 2 may be at risk of wilting (Figure 4-13). Moreover, in the driest year the maximum deficits in Richmond and San Antonio were too high (>200mm) for the substrates were hard to accommodate (Figure 4-13). Therefore, extra irrigation systems would be required for Green Roof 2 in Richmond and San Antonio. c. Green Roofs 3 and 4: For all three locations, even though Green Roofs 3 or 4 could achieve zero rooftop runoff, rainwater alone would be insufficient for the water demands of plants in the driest year. Combining this with the extreme maximum deficits, in excess of 400mm, extra irrigation systems would be necessary for Green Roofs 3 and 4 (Figures 4-15 and 4-17). 101  5.3 Conclusions for Richmond, BC; San Antonio, TX; and Toronto, ON. Assuming that the most efficient green roofs are designed for minimum maintenance, rainwater alone should be able to accommodate plants water needs and the water-holding capacity of substrates should be able to accommodate the maximum deficits in the driest year. a. Richmond, BC: Green Roof 1 would be the most economical green roof in Richmond, as its maximum deficit was within 100mm and would be easily accommodated by a thin substrate (Figure 4-11). Though the annual rainfall in Richmond was high enough even for the highest water use plants of Green Roof 4, the maximum deficits for Green Roofs 2, 3 and 4 were still too high in the driest year (Figure 4-13, 4-15 and 4-17). This is because rainfall occurred unequally throughout the year, as most rain events take place in winter rather than in summer. Therefore, Green  Roofs 2, 3 and 4 would require irrigation systems to complement natural rainfall quantities. However, there are other design solutions that make sense. If a few high water-use plants from Green Roofs 2, 3 or 4 were interspersed with the more resilient plants of Green Roof 1, Green roof 1 could to some extent increase its runoff reduction rate but still maintain minimum maintenance requirements. b. San Antonio, TX: According to the precipitation data for San Antonio, TX, the annual rainfall (1997-2006) in San Antonio varied from 423mm in the driest year to 1,094mm in the wettest year. Due to the great difference of rainfall between the driest and wettest years, the maximum deficits in the driest year were more than three times those in the wettest years (Figures 4-11, 4-13, 4-15 and 4-17). For Green roof 2, 3 and 4, their maximum 102  deficits in the driest year were so high that the plants would not survive without supplemental irrigation systems. Even for Green Roof 1, the maximum deficit in the driest year was high: 161mm (Figure 4-11). As a result, the maximum deficits in the driest year in this calculation can be considered as an exception. When considering the maximum deficits in the average and wettest year, both Green Roofs 1 and 2 would be appropriate since their maximum deficits were below 100mm and could be easily accommodated by a thin substrate (Figures 4-11 and 4-13).  Green Roofs 3 and 4 would again require irrigation systems. c. Toronto, ON: Considering runoff reduction, Green Roofs 2, 3 and 4 can achieve zero runoff (Figures 4-13, 4-15 and 4-17). However, rainwater in Toronto would be insufficient to provide for plant water needs. As a result,  Green Roof 1 would be the most efficient green roof for Toronto, as its maximum deficit is within 100mm and would be easily accommodated by a thin substrate (Figure 4-11). In order to maximize the runoff reduction of green roofs, a mix of Green Roofs 1 and 2 would increase the runoff reduction rate but still maintain minimum maintenance requirements. And  Green Roofs 3 and 4 are inappropriate for Toronto.  In conclusion, Green Roof 1 could be most economical green roof for Richmond, BC; San Antonio, TX; and Toronto, ON. Green Roof 2 could be also appropriate for San Antonio and Toronto, and could achieve greater runoff reduction, but may need additional attention in summer. Green Roofs 3 and 4 would be inappropriate for San Antonio and Toronto, as the rainwater alone would be insufficient for the water use by plants. In Richmond, as rainwater was sufficient, there are potentials for Green Roofs 2, 3 and 4 in  103  order to further reduce runoff rates. Because most rainfall in Richmond would take place in winter rather than in summer, irrigation systems would be required for these three systems, and extra water storage systems would be needed to store rainwater for future use, especially during the summer drought.  104  PART B:  TOOLS, STRATEGIES, SOLUTIONS FOR DESIGNERS  Chapter 6  Best Case Scenario for the Rezoning Site in Richmond, BC  6.1 Objectives The Part A of this thesis has quantified the effects of buildings, pathways, green space, climatic conditions, and green roofs on urban stormwater runoff. It has found that the area of green space and the design of landscape and green roofs were the key factors that influence the total stormwater runoff. To reduce urban stormwater runoff, impervious surfaces can be disconnected, and green roofs can be applied. The purpose of Part B is to show how to disconnect impervious surfaces through landscape design and how to associate green roofs with ground level landscape to minimize the total stormwater runoff. A site in Richmond was used for design analysis. Three scenarios for the proposed development plan are made. Using the calculation results from Chapter 4, the pre-development runoff rates for each scenario are calculated. Then a comparison of the stormwater runoff reduction for each scenario is made to discover the best-case scenario.  6.2 Analysis of the selected rezoning site in Richmond 6.2.1. Location map and site context The selected rezoning site, which is owned by Onni Development (Imperial Landing) Corp, includes two (2) two-story commercial buildings between No. 1 Road and Easthope Avenue, and three (3) three-story multiple-family residential buildings containing sixty-nine (69) dwelling units between Easthope Avenue and Bay view Street. The location map is shown in Figure 6-1. As the focus of this thesis is runoff from residential areas, the area identified as "B", with three (3) three-story multiple-family residential buildings, has been selected for analysis.  106  Figure 6-1: Location map and site context  MONCTON ST  II  C5 111111111111111111711M,  ztal  _BAY VIEW ST B  Impsigionding in Sfiggion, Ricend, BC  Proposed Rezoning  Source: City of Richmond, Planning and development Department.  6.2.2. Concept development plan The proposed development plan for area "B" is shown in Figure 6-2. The proposed development plan for area "B" currently provides for three (3) three-story multiple-family residential buildings with 69 dwelling units: Building C, D and E. It will also provide a 26 space public parking lot at the south end of English Avenue; an expanded Easthope Avenue public plaza; a Ewen Avenue cul-de-sac; public green space adjacent to the public dyke walkway; and several public accesses from Bayview Street to the public dyke walkway. (City of Richmond, 2007)  107  Figure 6-2: Concept development plan for area "B"  ZI  z  BAYVIEW ST /Expanded asthope Ave public plaza  tE  public green space  Source: City of Richmond, Planning and development Department.  To calculate the runoff from area "B", specific site areas of impervious surfaces like parking lots and pathways, and pervious surfaces, i.e. the public green space area were measured. As the report of the development plan did not provide landscape design, an assumed landscape design for area "B" was created as shown in Figure 6-3, which was used to calculate stormwater runoff. The areas of impervious and pervious surfaces are calculated as follows (Table 6-1). In reference to the Transect Zones in Richmond in Chapter 3, this site, with low-story apartments and townhouses, can be considered Urban Center Zone.  108  Figure 6-3: Development plan for area "B"  Figure 6-4: Perspective rendering of the development plan for area "B"  Table 6-1: The areas of impervious and pervious surfaces for the redevelopment plan  Total site area^  10,630 m 2^100%  Impervious area^i Buildings^3,503 m 2  33%  Parking lots  1,170 m 2  11%  Pathways  1,140 m 2  11%  Ground level landscape/  4,817 m 2  45%  Pervious area  green space  109  6.2.3. Best case scenario To determine the best case scenario, three models were generated for the rezoning site to compare their stormwater runoff retention potential. Scenario 1: Assume all impervious surfaces are connected. As shown in Figure 6-5, runoff from rooftops, green space, pathways and parking lots are directly connecting with the site's drainage systems. As shown in Table 6-2 below, a total runoff of 388mm would be created from the rezoning area, with 39% (1,620 m 3 ) from streets, 1°/0 (50 m 3 ) from open space and 60% (2,457 m 3 ) from rooftops.  Figure 6-5: Model of site with connected impervious surfaces  from roof  Runoff from pathways and parking lots  Runoff from green space  Urban sewage system  110  Table 6-2: Calculated runoff rates and runoff volume from sites with connected impervious surfaces — rezoning area (average moist year 2004)  Cover type  Street  Open space  Roof  Total  Annual runoff rates (mm)  701.28  10.35  701.28  388  1,620  50  2.457  39%  1%  60%  Annual runoff volume (m' )  4,126  Footnote: Refer to calculation method explained in Section 2.3.2 p23-24  Scenario 2: Based on findings in Chapter 5, Green Roof 1 (Section 2.3.5., Chapter 2) is the most economical green roof type in Richmond. Assume that Green Roof 1 with low water use plants is applied and all the impervious surfaces are connected. As shown in Figure 6-6, part of the rainwater would be retained on the green roof and then lost to evapotranspiration through the plants, but the overflow will drain directly into the urban sewage system. Other surface runoff from green space, pathways and parking lots is still directly connected with the urban sewage system. As shown in Table 6-3, the runoff rate created from rooftops could be reduced significantly when applying green roof systems. The rooftop runoff rate could be reduced from the initial 701.28mm (Table 6-2) to 448.41mm by Green Roof 1, 279.84mm by Green Roof 2, 111.26mm by Green Roof 3, and 26.97mm by Green Roof 4. The total runoff rate could be reduced by 21% when applying Green Roof 1, 36% by Green Roof 2, 50% by Green Roof 3 and 57% by Green Roof 4.  111  Figure 6-6: Model of site with connected impervious surfaces with green roofs  Evapotranspiration A A A A A A A A A  ^Runoff from ^reen roof  Runoff from pathways and parking lots  Runoff from green space  Urban sewage system  Table 6-3: Calculated runoff rates and runoff volume from sites with Green Roofs 1, 2, 3, and 4 and connected impervious surfaces — rezoning area (average moist year 2004)  Annual runoff Green  rates (mm)  Roof 1  Annual runoff volume (m 3 )  Green Roof 2  Annual runoff rates (mm)  Street  Open space  Roof  Total  701 28  10.35  44841  305  1,620  50  1571  Reduction vs. 388mm (connected)  21% 3.241  50%  701 28  10 35  279 84  249  36% Annual runoff volume (m 3 )  1,620  50^980  61%^2%^37%  2,650  112  Cover type  Annual runoff Green^rates (mm) Roof 3^1 Annual runoff volume (m 3 ) Annual runoff Green^rates (mm) Roof 4^I Annual runoff volume (m 3 )  Street  Open space  Roof  Total  701.28  10.35  111.26  194  Reduction vs. 388mm (connected)  50% 1,620  ^50^390  79%  2%^19%  701.28  10.35  2,060  166  26.97  57% 1,620  50^94  92%  3%^5%  1.764  Footnote: Refer to calculation method explained in Section 2.3.5 p27-32  For extensive green roofs built on sloping roofs, baffles or anti-erosion netting would be required to prevent the soil from sliding off. Figure 6-7 shows the typical build-up for sloping extensive green roofs by ZinCo inc.  Figure 6 7: Typical build up for sloping extensive green roofs -  -  1.Vegetation 2. Jute anti-erosion net JEG 3. Sod 4. Floratec FS 75 Drainage Layer Moisture mat Waterproofing 1.N. ith integral root barrier  Source: ZinCo Canada Inc. (www.zinco.ca )  Scenario 3: Assume that Green Roof 1 with low water use plants is applied and all the impervious surfaces are disconnected. As shown in Figure 6-8, part of the rainwater would be retained on the green roofs and 113  subsequently lost to evapotranspiration through the plants, and the overflow would drain onto adjacent pervious surfaces. For other impervious surfaces like pathways and parking lots, runoff from those areas would also first flow onto adjacent pervious surfaces, like an infiltration swale. As a result, only overflow from the pervious areas would become final runoff. Most runoff would infiltrate the soil. Table 6-4 below shows that the total runoff rate could be reduced by 55% from the initial 388mm to 174mm by disconnecting rooftops, or by 89% (to 43mm) by disconnecting all impervious surfaces. As the total runoff volume created from the site with disconnected impervious surfaces was 455m 3 , much less than the total evapotranspiration volume when greening all the rooftop areas, applying Green Roofs 1, 2, 3, and 4 to just a portion of the rooftops could all achieve zero runoff on the site.(Table 6-4) Table 6-4: Total evapotranspiration (ET) volume - Green Roofs 1, 2, 3, and 4 (average moist year 2004) Green Roof 1^ Green Roof 2 ^ ^ Annual ET rates^Annual ET volume Annual ET rates Annual ET volume ^ ^ ^ (mm) (mm) (m 3 ) (m3) ^ 253^886 421^1,476 ^ Green Roof 3 Green Roof 4 Annual ET rates (mm) 590  Annual ET volume  Annual ET rates  Annual ET volume  (m' )  (mm)  (m' )  2,067  674  2,362  Footnote: Refer to calculation method explained in Sections 2.2.1 p18 - 19  As shown in Table 6-5, greening 51 % of the total rooftop areas with Green Roof 1 can achieve zero runoff. The same goal could be achieved by greening 31% of the total rooftop areas with Green Roof 2, 22% with Green Roof 3, or 19% with Green Roof 4.  114  Table 6-5: Calculated runoff rates and runoff volume from sites with Green Roofs 1, 2, 3 and 4. and disconnected impervious surfaces — rezoning area (average moist year 2004) Cover types Annual runoff rates (mm)  Street  Open space  701.28  66.61  174  1.620  233  1,853  129.79  43  455  455  Roof  Total  With disconnected roof Annual runoff volume (m' ) With disconnected impervious surfaces With Green Roof 1 and disconnected impervious surfaces With Green Roof 2 and disconnected impervious surfaces  Annual runoff rates (mm) Annual runoff volume (m' ) Annual runoff rates (mm) Annual runoff volume (m' ) Annual runoff rates (mm) Annual runoff volume (m' )  With Green Roof 3 and disconnected impervious surfaces  Annual runoff rates (mm)  With Green Roof 4 and disconnected impervious surfaces  Annual runoff rates (mm)  Annual runoff volume (m' )  Annual runoff volume (m' )  Zero runoff (by greening 51% of the rooftop areas)  Zero runoff (by greening 31% of the rooftop areas)  Zero runoff (by greening 22% of the rooftop areas)  Zero runoff (by greening 19% of the rooftop areas)  Footnote: Refer to calculation method explained in Sections 2.3.3 and 2.3.5 p24-32  115  Figure 6-8: Model of site with disconnected impervious surfaces with green roofs  Rain ss s  Runoff from green roof  Evapotranspiration A A •••  Absorbed by green s ace  Overflow into sewage system  A^ed  Runoff from pathways and parking lots  swale sys  Urban sewage system  Infiltration swale system  Therefore, the best case scenario requires the disconnection of all impervious surfaces and the creation of extensive green roofs. To maximize the effects of disconnecting impervious surfaces, infiltration swale system may be used, as shown in Figure 6-8. In terms of rooftop runoff, the best case scenario requires a greening of at least 50% of the rooftop areas with extensive green roofs (Green Roof 1) and 100% disconnectivity of rooftops. As shown in Figure 6-9, overflow from the green roofs should drain onto the adjacent green areas.  116  Figure 6-9: Direction of runoff — green roofs  m► Direction of rooftop runoff  e ^F  Green space to disconnect roolitop runoff  Figures 6-10 and 6-11 show the direction of runoff from pathways, parking lots and the cul-de-sac. Runoff from pathways should flow into the nearest green space, as shown in Figure 6-10, Infiltration swales are required to disconnect the parking lots and the cul-de-sac, as traditional parking lots and cul-de-sacs are usually enclosed by curbs, which keep runoff from flowing into green areas. Figure 6-11 shows the infiltration swale layout for parking lots and the cul-de-sac.  Figure 6-10: Direction of runoff — pathways  =No- Direction of surface runoff Pathways  11 7  Figure 6-11: Direction of runoff —parking lots and cul-de-sacs Parking lots^  Cul-de-sac  1111111Mbre., ^11141._ 111141/41C1b. Direction of surface runoff  Infiltration swale  1111 Disconnected impervious surfaces  Using permeable paving for the parking stalls can also reduce stormwater runoff volumes and improve the runoff quality, since permeable paving allows rainwater to percolate into the ground before sheeting off.  Figure 6-12: Permeable paving for parking stalls Parking lots  Example of permeable paving for parking stalls  si Permeable paving Direction of runoff  118  6.3 Summary Using the CN method as explained in Section 2.2.2, and assuming a CN of 98 for the impervious surfaces and an average CN of 69 for the ground-level landscape, 388mm of the total stormwater runoff would be created from the rezoning site with all impervious surfaces connected (Table 6-2). Disconnecting impervious surfaces with pervious surfaces such landscaped areas or infiltration swales and applying green roof systems could eliminate the total stormwater runoff. a. Disconnect impervious surfaces: i.  Disconnect roofs: If runoff created from rooftops would flow onto the adjacent pervious portions of the site before entering the site's drainage system, the total runoff volume would be reduced from 4,162m 3 to 1,853m 3 (Tables 6-2 and 6-4). The total runoff rate would be reduced 55%, from 388mm to 174mm (Tables 6-2 and 6-4).  ii.  Disconnect all impervious surfaces: If runoff created from rooftops, streets, sidewalks and parking lots would flow onto the adjacent pervious portion of the site before entering the site's drainage system, as shown as Figures 6-9, 6-10 and 6-11, the total runoff volume would be reduced from 4,126m 3 to 455m 3 (Tables 6-2 and 6-4). The total runoff rate could be reduced 89%, from 388mm to 43mm (Tables 6-2 and 6-4).  b. Apply green roof systems: Utilizing the Crop coefficient method explained in Section 2.3.5, the runoff rate created from rooftops could be reduced by 252.87mm (Green Roof 1), by 421.44mm (Green Roof 2), by 590.02mm (Green Roof 3), and by 674.31mm (Green Roof 4) (Table 6-3).  119  For the selected rezoning site, the best scenario would suggest disconnecting all impervious surfaces and simultaneously applying green roofs. The calculations for the rezoning site shows that simultaneously disconnecting all impervious surfaces and greening all rooftop areas with any type of green roof system would achieve zero runoff from the site. As Green Roof 1 would be the most economical green roof in Richmond (Section 5.3), the best case scenario for the rezoning site would be greening 50% of the total rooftop area and disconnected all impervious surfaces.  120  PART C:  CONCLUSIONS AND DISCUSSION  Chapter 7  Conclusion and Discussion  7.1 Conclusion This thesis provides a different and effective methodology for quantifying the effects of green roofs on stormwater runoff, using local climate data and the water use properties of vegetation. Table 7-1 shows that green roofs growing with plants of higher Kc values can achieve higher stormwater runoff reduction rates, but will be less economically efficient, as they will require irrigation systems and result in higher maintenance costs especially in the dry summer months. The water needed by plants in summer is equivalent to the maximum deficits. Table 7-1: Collective summaries Richmond, BC Stormwater runoff reduction  Maximum deficits  Maintenance requirement  Green^0.3 Roof 1  24% to 47%  51 to 98mm  Low  Green^0.5 Roof 2  40% to 78%  107 to 212mm  Medium  56% to 100%  158 to 322mm  Medium  64% to 100%  182 to 377mm  High  Stormwater runoff reduction  Maximum deficits  Maintenance requirement  35% to 100%  24 to 161mm  Low to medium  Kc  Appropriateness  Irrigation requirement  ti  Green^0.7 Roof 3 Green^>0.8 Roof 4 San Antonio, TX Kc  Appropriateness  Irrigation requirement  Green^0.3 Roof 1 Green^0.5 Roof 2  w  59% to 100%  89 to 286mm  Medium to high  Green^0.7 Roof 3  v  83% to 100%  138 to 404mm  High  Green^>0.8 Roof 4  v  95% to 100%  162 to 463mm  High  122  Toronto, ON Kc Appropriateness Irrigation^Stormwater^Maximum Maintenance requirement runoff reduction^deficits^requirement Green^0.3^ Roof 1^  48% to 84%^17 to^Low 81mm  Green^0.5^ Roof 2^  80% to 100%^50 to^Medium 158mm  Green^0.7^ Roof 3^  100%^90 to^Medium  Green >0.8^ Roof 4^  100%^257 to^High 441mm  327mm  This methodology uses local climate data and crop coefficient numbers, based on the water use properties of vegetation, to calculate the potential effects of green roofs on reducing stormwater runoff, as opposed to other methodologies that calculate runoff coefficients based on percolation rates of the growing media. The Curve Number method used to calculate stormwater runoff is based on local rainfall rates, and the size or percentage of study area impervious surfaces; while the Crop coefficient method used to calculate the water absorbed by vegetations is determined by the water-use properties of plants and local climatic conditions, such as evapotranspiration rate, temperature, solar radiation, wind speed, and relative humidity. Therefore, this methodology can be a good estimating tool especially in the early stages of a design process; it can be applied to any city, and it should be applied by both urban planners and designers when considering the use of green roofs as a mitigation tool for stormwater runoff.  123  7.2 Discussion 7.2.1 Implications for the practice of city planning for site design  Using this methodology, the effects on stormwater runoff when applying green roofs can be pre-calculated, including both runoff volumes and runoff reduction rates. For developers, detailed runoff volumes and rates before and after applying green roofs can show how sustainable their projects will be. Moreover, stormwater runoff volume reduced by green roofs may also result in monetary savings from a decreased need of sewer infrastructure. Accompanied with other benefits of green roofs, such as energy savings, roof life extension, increased property values, aesthetic improvements, the method developed in this study will help to encourage developers to build green roofs on their new developments. For designers such as architects, landscape architects, and urban planners, this methodology can be easily applied in most places, as the necessary climatic data is available. Architects and landscape architects can use this methodology to evaluate the costs and benefits of their designs and in sustainability. One of the goals for governments would be to maintain sustainable living/working environments. Quantifying the effects of green roofs can help local governments to make policies and strategies to encourage green roof construction to achieve the goal of sustainability.  7.2.2 Gaps and future research opportunities  This methodology used daily rainfall to calculate the stormwater runoff, which assumed that the total daily rainfall fell in 24 hours. However, in the real world, the daily rainfall might occur in less than a minute. As a result, the calculations might detect zero runoff while in reality, the runoff might be substantial, if short-lived. Therefore, future research is required to ascertain the differences between the 124  calculated runoff and the actual runoff. One way to find out the differences is to apply actual rainfall and evapotranspiration rates from the monitored green roofs for calculation, and then compare the calculated runoff with the measured runoff. There might be a relatively constant ratio between the calculated runoff and the actual runoff, which could vary by geographic location. Evapotranspiration rates and crop coefficients of plants used for green roofs are also prerequisites for this methodology. Although the evapotranspiration rates can be calculated using other climate data, measured evapotranspiration rates will make the calculated runoff more accurate. Furthermore, crops are not normally grown on rooftops; thus the crop coefficients of plants grown on rooftops may be different from those grown on the ground. As the crop coefficients for many plants used for green roofs are still unknown, future research is needed to measure their crop coefficients, so that the runoff reduction rates of green roofs growing with specific plants can be identified.  7.2.3 Shortcomings of the research  1. This methodology is applicable only when local climate data and Kc values of plants are available. Finer data resolution is needed to better predict the benefits of different green roofs. 2. Because the effects of the intensity of a single rainfall event were not considered in this methodology, the calculated runoff volume from traditional roofs would be lower than the real runoff volume using the Curve Number method. Hour-by-hour precipitation data can be used to analyze the intensity. 3. Research has shown that compacted urban soils could also influence infiltration (Pitt, 2002). Therefore, the CN selected for pervious surfaces would be determined not only on soil type, but also infiltration rates. In this research, the calculation of stormwater runoff from pervious surfaces used an average CN of 69  125  for the soil texture (silt loam or loam) with a moderate rate of water transmission (0.15 - 0.30 in/hr) (Cronshey, 1986). However, urban soil in reality might be highly compacted, with a very low rate of water transmission (0 — 0.05 in/hr) (Pitt, 2002). A lower CN might therefore be more appropriate for the pervious surfaces in an urban environment. 4. The reference evapotranspiration rates used in the Crop Coefficient method must be either available or calculable, and the Kc values of plants must be accurate. For the calculation of plant water usage, the crop coefficients were assumed to be constant. In reality, however, plants' crop coefficients would vary over the growing period, relative to air and soil temperature; average crop coefficients of green roofs would also be determined on the coverage of plants on green roofs. 5. The runoff rate from sites with disconnected impervious surfaces was calculated using the CN method, while the runoff reduction of green roofs was calculated by the Crop Coefficient method. The runoff from sites with both disconnected impervious surfaces and green roofs was simply calculated by subtracting the evapotranspiration volume from green roofs from the total runoff volume. However, the runoff reduction may overlap, as runoff from smaller rainfall events could be reduced by 100% by either disconnecting the roof areas or applying green roof systems. Therefore, the calculated runoff volume will be usually lower than actual runoff volume; and the calculated runoff reduction volume by plants will be usually higher than the real reduction volume. In other words, the net effects of green roofs will potentially be lower than calculations predict, but the amount of difference is as yet unknown.  126  References Allen, R. G., Pereira, L. S., Raes, D. and Smith, M.1998. "Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements." Rome:Food and Agriculture Organization of the United Nations Banting D., Doshi, H., Li, J., Missios, P., Au, A., Currie, B. A. and Verrati, M. 2005. "Report on the Environmental Benefits and Costs of Green Roof Technology for the City of Toronto." Toronto: Ryerson University. Bass, B. and Baskaran, B. 2003. "Evaluating Rooftop and Vertical Gardens as an Adaptation Strategy for Urban Areas." Ottawa: National Research Council of Canada. Boscoe, A. 2003. "An Assessment of the Potential of Green Roofs to Act as a Mitigation Tool for Increased Urban Densities." Manchester: University of Manchester. City Of Riverside (CA) Planning Department, 1994. "Water Efficient Landscaping And Irrigation Ordinance Summary And Design Manual, 2nd Edition" Riverside: Planning Department City of San Antonio Planning and Community Development Department, 1999, "Downtown Neighborhood Plan, 1999", Texas: San Antonio. Cronshey, R.G., Roberts, R.T., and Miller, N., 1986. "Urban Hydrology for Small Watersheds (TR-55 Revised)". Washington, D.C. Duany Plater -Zyberk & Company, 2006, "Miami 21: Transect Theory", Florida: City of Miami Planning Department. <http://www.miami21.org/clientuploads/IntroTransectTheory.pdf >  Dunnett, N. and Kingsbury, N. 2004. "Planting Green Roofs and Living Walls." Portland: Timber Press. Gelbspan, R. Aug. 30, 2005. "Katrina's real name". The Boston Globe, Aug. 30, 2005. <http://www.boston.com/news/weather/articles/2005/08/30/katrinas_real_name?mo de=PF>  127  Hitchmough, J. 2006. "Life on green roofs; the above and below ground environment". Presentation in Green Roof Conference 2006 in the University of Sheffield James, E. M., Bradley M. C., Ernest, P. H. and Larry, B., 2004. "New Jersey Stormwater Best Management Practices Manual". Trenton: New Jersey Department of Environmental Protection Johnston, C., McCreary, K. and Nelms, C. 2004. "Vancouver Public Library green roof monitoring project." In Greening Rooftops for Sustainable Communities 2004 conference proceedings, CD-Rom. Green Roofs for Healthy Cities. Liesecke, H.J. 1999. Extensive begri.inung bei 5° dachneigung. Stadt Gain 48:337-346. Liu, K. 2004. "Sustainable building envelope — garden roof system performance." Ottawa: National Research Council of Canada. Liu, K. 2006. "Thermal Performance of Green Roofs." <http://www.greenroofs.com/research_links.htm > Mid-America Regional Council and American Public Works Association, 2007. "Manual of Best Management Practices For Stormwater Quality." Kansas City: Mid-America Regional Council <http://www.marc.org/Environment/Water/bmp_manual.htm >  Moran, A.C., 2004, "A North Carolina Field Study to Evaluate Greenroof Runoff Quanity, Runoff Quality, and Plant Growth." Raleigh: North Carolina State University. North Central Texas council of Governments, 2006. "iSWM TM Design Manual for Site Development." Arlington: North Central Texas Council of Governments. <http://iswm.nctcog.org/Documents/index.asp >  Peck, S. W., Callaghan, C., Kuhn, M. E. and Bass, B. 1999. "Greenbacks From Green Roofs: Forging A New Industry In Canada." Ontario: Canada Mortgage and Housing Corporation.  128  Peck, S. W. and Kuhn, M. 2003. "Design Guidelines for Green Roofs." Ontario: Canada Mortgage and Housing Corporation and the Ontario Association of Architects. Pitt, R., Chen, S.E., and Clark., S. 2002, "Compacted Urban Soils Effects on Infiltration and Bioretention Stormwater Control Designs". The 9th International Conference on Urban Drainage. IAHR, IWA, EWRI, and ASCE. Portland: Oregon, September 8-13. Snyder, R. L., and Eching, S., 2007, "Penman-Monteith daily (24-hour) Reference Evapotranspiration Equations for Estimating ETo, ETr and HS ETo with Daily Data." Sacramento: Regents of the University of California Schade, C. 2000. Wasserriickhaltung and AbfluRbeiwerte bei dOnnschichtigen extensivbegrunungen. Stadt GrOn 49:95-100. Scholz-Barth, K. and Tanner, S. 2004. "Green Roofs: Federal Energy Management (FEMP) Federal Technology Alert." Washington: US Department of Energy. Snodgrass, E. C. and Snodgrass, L. L., 2006, "Green Roof Plants — A Resource and Planting Guide." Portland: Timber press Stephens, K. A. and Reid, D.2002. "Stormwater Planning: A Guidebook For British Columbia." Government of British Columbia: Ministry of Environment Government of British Columbia <http://www.env.gov.bc.ca/epd/epdpa/mpp/stormwater/stormwater.html > The City of Richmond Planning and Development Department Policy Planning Section, 2005, "City of Richmond State of the Environment: 2005 Update Report", British Columbia: Richmond. The North Carolina Division of Water Quality, 2007. "North Carolina Division of Water Quality- Stormwater Best Management Practices Manual". Raleigh: The Department of Environment and Natural Resources VanWoert, N.D. Rowe, D.B., Andresen, J.A., Rugh, C.L., Fernandez, R.T. and Xiao, L. 2005. "Green Roof Stormwater Retention: Effects of Roof Surface, Slope, and Media Depth", J. Environ. Qual. 34: 1036-1044  129  Van Metre, P.C. and Mahler, B.J. 2003. "The contribution of particles washed from rooftops to contaminant loading to urban streams." Chemosphere, Vol. 52, No. 10: September, 2003Chemosphere, Vol. 52, No. 10: 1727 - 1741.  130  

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