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Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits (2016)

Chapter: Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems

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Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
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A

Calculating the Benefits of Rooftop Runoff Capture Systems

This appendix presents the methods used (with examples) to evaluate the beneficial uses of roof runoff harvesting for irrigation of landscaped areas and for toilet flushing. The Source Loading and Management Model, WinSLAMM (Pitt, 1997), was used to calculate the benefits of harvesting stormwater for storage and later beneficial uses. The methods were previously used and described by Pitt et al. (2011, 2014). WinSLAMM is a continuous model that evaluates a long series of rains for an area. WinSLAMM1 is licensed for sale but is available free of charge to academic institutions. An evaluation license is also available to interested readers who wish to examine the model for a limited time. Input files used in this scenario analysis are available in the Academies’ Public Access Records Office.

For this report, WinSLAMM focused on the capture of rooftop runoff and use for turfgrass irrigation and toilet flushing, as described in Box 3-1. Different storage tank volumes were also evaluated. Average monthly (and daily) irrigation requirements were calculated by subtracting average monthly rainfall from 1995 to 1999 (1996-1999 for Lincoln, because of missing data) from average monthly evapotranspiration (ET) values. Then using WinSLAMM and the 5-year precipitation time series, if rainfall was insufficient to meet the irrigation demand, then supplemental irrigation was required. If available, then the supplemental irrigation was supplied by previously stored roof runoff water in storage tanks. Toilet flushing requirements were based on typical national indoor water uses (11 gpcd; see Box 3-1). The following is a summary of the main calculations and data used for these analyses.

WINSLAMM

WinSLAMM evaluates stormwater runoff volumes and pollutant loads under an array of stormwater management practices including rain barrels and water tanks, although the committee did not assess pollutants in this analysis (Pitt, 1987). Using local rain records, the model calculates runoff volumes and pollutant loadings for each rain from individual source areas within various land use categories and sums the results over a given area or land use. Examples of runoff source areas considered by the model include roofs, streets, sidewalks, parking areas, and landscaped areas, which each have different runoff coefficients based on the type of surface, slope, and soil properties (Pitt, 1987). Example land use categories include commercial, industrial, institutional, open space, residential, and freeway/highway. The committee’s scenario modeling exercise mainly focuses on roof runoff for small-scale stormwater harvesting and on land use runoff for larger scale stormwater harvesting.

Any length of rainfall record can be analyzed with WinSLAMM, from a single event to many decades. The rainfall files used in the committee’s calculations were developed from hourly rainfall data obtained from the National Oceanic and Atmospheric Administration (NOAA) rainfall stations as published on EarthInfo CD-ROMs.

DATA REQUIREMENTS AND SOURCES OF INFORMATION

WinSLAMM uses various sets of information in its calculations. The main data required for the analyses in this report included rain data for the six locations examined (from NOAA weather stations), runoff coefficients for the source areas for different land uses, and land development characteristics for the land uses in each area examined.

Rainfall Data

As noted in the report, six areas of the country were examined to represent a range of climatic conditions:

  • Los Angeles, California, having a median rainfall of about 12 inches per year over the long-term record (17 inches average during the 5-year calculation period)

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1 See http://winslamm.com.

Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×
  • Seattle, Washington, having a median rainfall of about 37 inches of rainfall per year (42 inches average during the 5-year calculation period)
  • Lincoln, Nebraska, having a median rainfall of about 26 inches of rainfall per year (28 inches average during the 4-year calculation period)
  • Madison, Wisconsin, having a median rainfall of about 32 inches of rainfall per year (30 inches average during the 5-year calculation period)
  • Birmingham, Alabama, having a median rainfall of about 54 inches of rainfall per year (50 inches average during the 5-year calculation period)
  • Newark, New Jersey, having a median rainfall of about 43 inches of rainfall per year (44 inches average during the 5-year calculation period)

Most of the modeling calculations focused on recent 5 years of rainfall records (1995 through 1999 for all areas, except for Lincoln, where 1996 through 1999 rains were used due to many missing rains in the 1995 record).

The goal was to use a continuous period of actual rains that were similar to the long-term average conditions, because continuous simulations were needed to calculate the inter-event water demands based on the average ET values. The committee based its scenario analysis on 5-year rain periods to reduce data pre-processing demands and because long records are rarely available without data gaps. Moderate rain record lengths reduce these gap problems (although Lincoln was missing 1995) and have been used to reduce large year-to-year variabilities while attempting to match the average monthly ET values. In Table A-1 and Figure A-1, the committee compares the rainfall data from the 4- to 5-year calculation periods with the long-term precipitation record. Some variations are apparent even though the differences are not statistically significant. Some of these differences are discussed in the context of analysis uncertainties in Box 3-2.

The committee judges that the calculation methods and data used for these analyses represent reasonable conditions and present results that are useful for the comparative analysis presented in Chapter 3. However, the data are not intended as definitive predictions or as a basis for design guidance.

TABLE A-1 Comparison of Precipitation Annual Rain Totals and Rain Counts Between the Scenario Analysis Calculation Period and the Long-term Rainfall Record

Los Angeles, CA Seattle, WA Lincoln, NE Madison, WI Birmingham, AL Newark, NJ
Long-term rain record 1948-1999 1965-2012 1973-1999 1948-1999 1948-1999 1948-1999
(1995 gap) (1978-1987 gap)
Scenario analysis calculation 1995-1999 1995-1999 1996-1999 1995-1999 1995-1999 1995-1999
period
Long-term annual median 11.70 36.69 26.45 31.85 53.68 42.51
rain total (in)
Scenario analysis calc. period 15.82 42.10 28.62 31.19 52.40 41.28
median annual rain total (in)
p values (<0.05 indicatesa significant difference)a 0.16 0.078 0.68 0.56 0.78 0.99
Comment of rain depth box and whisker plot comparisons The calculation period has greater rains and a wider variation than the long term conditions The calculation period has greater rains but similar variations as the long term conditions The calculation period has similar rain depths per year and the variations are similar The calculation period has smaller rain depths per year and the variations are similar The calculation period has similar rain depths per year and the variations are similar The calculation period has similar rain depths per year and the variations are similar
Long-term annual median rain counts 29 138 97 109 106 103
Scenario analysis calc. period median annual rain counts 32 140 97 103 97 97
p values (<0.05 indicatesa significant difference)a 0.27 0.62 0.82 0.08 0.20 0.17

aMann-Whitney rank sum p values (not independent data sets because the calculation period was included in the total period). Deemed acceptable as the hypothesis was to compare the full set with the subset. None of the rain depth or rain count comparisons indicated significant differences for the number of data available.

Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×

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FIGURE A-1 Comparisons of the period of record with the scenario analysis period in terms of annual rain depth and number of rainfall events per year.

Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×

image

Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×

Land Development Characteristics

An important element in calculating stormwater beneficial use opportunities using harvested roof runoff for landscaping irrigation is to know the typical areas of the roofs and the landscaped areas that are present in the different land uses and study locations. For larger-scale beneficial-use calculations, the areas of the other source areas in the land uses also need to be known. These areas were obtained from prior summaries conducted to support the U.S. Environmental Protection Agency’s (EPA’s) development of potential future stormwater regulations. These typical land development characteristics throughout the country, described in Pitt (2011a,b,c), are summarized in Table 3-3. Pitt (2011a) contains the citations and sources for the original data sources. More than 100 monitored locations were reviewed using site mapping and aerial photographs, along with concurrent monitoring data.

For irrigation beneficial uses of stormwater, the most suitable source for the collected water is from the building roofs because of its generally better water quality, high unit area runoff yield, and elevation above storage tanks and irrigated land. The landscaped areas represent the amount of area that can be irrigated with the harvested roof runoff water. Therefore, areas having relatively large roofs and small landscaped areas are most likely to have most of the irrigation demand in the area satisfied (but may not reduce the overall stormwater discharges as much as areas having small roofs and large irrigable land). Table A-2 shows the roof and landscaped areas for these six land uses for the Los Angeles area. Commercial areas generally have the smallest ratios of landscaped to roof areas and therefore are more likely to be able to meet irrigation requirements with the abundance of roof runoff. In contrast, it would be much more challenging to replace much of the irrigation water currently supplied by potable water supplies using roof runoff in low-density areas because the amount of roof runoff water is a much smaller portion of the total irrigation requirements. There are some differences in these development characteristics by region, and the rainfall patterns and evapotranspiration requirements vary greatly by area. Table A-3 shows the percentage of landscaped and roof areas and typical housing densities for medium-density, residential land uses (the focus of the committee’s analysis) in each of the six locations of the country examined.

ROOF RUNOFF CALCULATIONS

The following sections describe an example set of calculations used to develop the analyses used in this report. These examples focus on medium-density, residential land use in Los Angeles.

TABLE A-2 Roof and Landscaped Areas for Los Angeles Land Uses

Roof Area (%) Landscaped Area (%) Ratio of Landscaped Area to Roof Area
Commercial 28.1 14.9 0.53
High-density residential 20.7 46.4 2.24
Medium-density residential 18.0 52.5 2.92
Low-density residential 8.0 79.6 9.95
Industrial 20.2 24.3 1.20
Institutional 19.4 41.2 2.12

TABLE A-3 Landscaped and Roof Area, and Number of Households for Medium-Density, Residential Land Use in Six U.S. Locations

Landscaped Areas (%) Roof Areas (%) # Roofs/100 Acres at 1,500 ft2 Each
Los Angeles, CA 52.5 18.0 523
Seattle, WA 63.5 17.1 497
Lincoln, NE 62.8 18.1 526
Madison, WI 63.3 15.0 436
Birmingham, AL 81.3 8.8 256
Newark, NJ 56.2 15.9 462
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×

Runoff Quantity

Table A-4 is a small portion of the WinSLAMM modeled scenario output showing runoff volume contributions for a 100-acre medium-density residential area in Los Angeles. These analyses were repeated for six major land use areas (commercial, high-density residential, medium-density residential, low-density residential, industrial, and institutional) and six U.S. locations. During this 5-year period examined (1995-1999), a total of about 84 inches fell, with rains as large as 3.5 inches (Table A-5). About 47 percent of the rainfall occurred as direct runoff for this area (or a the volumetric runoff coefficient [Rv] of 0.47), higher than for most residential areas, because these analyses assumed directly connected roof drainage, as would be the case for roof runoff harvesting. Most of the runoff volumes in this medium-density residential land use analysis originated from the street and roof areas, with smaller (and about equal amounts) from driveways, sidewalks, and landscaped areas. These relationships vary for different land uses and different geographical areas based on the local development characteristics, soils, and rain patterns.

Based on the 1995-1999 period, 100 acres of medium-density, residential area in Los Angeles produces about 14 million ft3 of runoff, while the roofs in the area contribute about 5.2 million ft3 of that runoff. These can be converted to inches of runoff over the drainage area for the 5-year period, for example:

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For the roof area alone (which comprises 18 percent of the land use, or 18 acres):

image

The total rain depth for the 5 years is 83.67 inches, or 16.73 inches per year. The volumetric runoff coefficient (Rv) is the ratio of the runoff total to the rain total. Therefore, for the whole area, the total flow-weighted annual Rv is:

image

while the Rv for the roof area alone is:

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TABLE A-4 Portion of WinSLAMM Model Output for Southwest, Medium-Density, Residential Areas (100-acre area) Showing Runoff Amounts (ft3) from Different Sources Areas for Each Event and for All Areas Combined (5 years rain series)

Runoff Amounts (ft3)

Month Start Date Rain Total (in.) Land Use Totals Roofs Driveways Sidewalks/Walks Street Area Small Landscaped Area Volumetric Runoff Coeff. (Rv) Total Losses (in.)
1 1/3/1995 0.75 119,655 46,952 13,767 8,850 44,408 5,677 0.44 0.42
1 1/4/1995 3.5 716,277 226,403 83,501 53,679 219,291 133,402 0.56 1.53
1 1/7/1995 1.29 217,432 82,603 27,004 17,360 77,546 12,920 0.46 0.69
1 1/8/1995 0.4 56,379 24,323 6,521 4,192 19,719 1,623 0.39 0.24
1 1/10/1995 2.93 595,083 189,532 68,824 44,244 180,806 111,677 0.56 1.29
1 1/11/1995 0.14 16,023 7,115 1,812 1,165 5,931 0 0.32 0.1
1 1/11/1995 0.4 56,379 24,323 6,521 4,192 19,719 1,623 0.39 0.24
1 1/14/1995 0.12 13,386 5,899 1,499 964 5,024 0 0.31 0.08
1 1/20/1995 0.16 18,776 8,397 2,144 1,378 6,858 0 0.32 0.11
About 150 events between these two dates are not shown on this summary table
4 4/11/1999 1.36 229,828 87,085 28,777 18,499 81,753 13,713 0.47 0.73
6 6/1/1999 0.52 77,811 32,034 8,880 5,709 28,535 2,653 0.41 0.31
6 6/2/1999 0.05 3,334 1,152 476 306 1,401 0 0.18 0.04
6 6/3/1999 0.02 314.4 166 90 58 0 0 0.04 0.02
11 11/8/1999 0.27 34,913 15,520 4,046 2,601 12,344 402 0.36 0.17
11 11/17/1999 0.01 78.6 41 23 15 0 0 0.02 0.01
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×

TABLE A-5 Summary of All Events in 5-Year Rain Series in WinSLAMM Model Output for Southwest, Medium-Density, Residential Areas (100 acre area)

Rain Total (in.)

Runoff Amounts (ft3)

Volumetric Runoff Coeff. (Rv) Total Losses (in.)
Land Use Totals Roofs Driveways Sidewalks/ Walks Street Area Small Landscaped Area
Minimum 0.01 79 41 23 15 0 0 0.02 0.01
Maximum 3.5 716,277 226,403 83,501 53,679 219,291 133,402 0.56 1.53
Average 0.51 85,703 31,728 10,152 6,527 29,112 8,184 0.47 0.75
Total 83.67 13,969,610 5,170,000 1,655,000 1,064,000 4,745,000 1,334,000 n/a 45.18

TABLE A-6 Overall Summary of Runoff Volume Contributions by Source Area and Month for Los Angeles Medium Density Residential Areas

Five-Year Average Flows by Month Rain Total (in.) Land Use Totals Roofs Driveways Sidewalks/ Walks Street Area Small Landscaped Area
Area (% of total land use) n/a 100.00 18.00 7.00 4.50 18.00 52.50
Avg Jan runoff volume (in/mo) 4.89 2.26 4.65 3.85 3.85 4.26 0.41
Avg Feb runoff volume (in/mo) 3.76 1.88 3.63 3.13 3.13 3.38 0.49
Avg March runoff volume (in/mo) 2.48 1.13 2.33 1.88 1.88 2.12 0.22
Avg April runoff volume (in/mo) 0.86 0.35 0.78 0.60 0.60 0.70 0.03
Avg May runoff volume (in/mo) 0.59 0.24 0.54 0.42 0.42 0.49 0.02
Avg June runoff volume (in/mo) 0.25 0.09 0.21 0.15 0.15 0.18 0.00
Avg July runoff volume (in/mo) 0.01 0.00 0.01 0.00 0.00 0.01 0.00
Avg Aug runoff volume (in/mo) 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Avg Sept runoff volume (in/mo) 0.05 0.02 0.05 0.03 0.03 0.04 0.00
Avg Oct runoff volume (in/mo) 0.29 0.13 0.28 0.24 0.24 0.26 0.02
Avg Nov runoff volume (in/mo) 1.30 0.56 1.22 0.95 0.95 1.11 0.05
Avg Dec runoff volume (in/mo) 2.24 1.03 2.14 1.77 1.77 1.97 0.16

All of the event data were sorted by month and then averaged to develop 5-year averaged monthly summaries of runoff volumes (average inches of runoff per month). Table A-6 is an overall summary showing these runoff volume contributions from each of the Los Angeles, medium-density, residential, source areas and the total annual flow conditions, expressed in average watershed-inches per month.

Evapotranspiration and Irrigation Demands

Evapotranspiration (ET) is defined as the rate at which readily available water is removed from the soil and plant surfaces, expressed as the rate of latent heat transfer per unit area or as a depth of water evaporated and transpired from a reference crop (Jensen et al., 1990). In the United States, ET monitoring is primarily focused in agricultural and wild land environments. With educational advancements stressing water conservation in urban areas, there is a new desire to apply ET data as a part of stormwater harvesting options for supplemental irrigation and to fine-tune actual irrigation requirements based on soil moisture and plant needs. Climate-based equations are the most common method used to determine ET. ET potential, ETo, is only relevant for a standard condition that reflects normalized agricultural conditions. The ETo value is therefore adjusted according to the microclimate, soils, plants, and growing season conditions. Most of these adjustment factors were developed for agricultural situations, and their use in highly disturbed urban environments has not been well documented. However, it is becoming more common to directly measure urban area ET as part of stormwater management projects. As an example, Selbig and Balster (2010) directly measured ET in an urban setting in Madison, Wisconsin, as part of a stormwater management project for a variety of soil and plant conditions, including when the plants were mostly covered with snow.

The California Irrigation Management Information System (CIMIS) is a comprehensive example for determining ET rates within a state. Its web services are capable of pro-

Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×

ducing an array of useful information about most locations and regions in California. The stations monitored are not limited to traditional agricultural areas, with some monitoring data also available in urban areas.

The ASCE Standardized Reference Equation (Allen et al., 2005) is an example of an ET equation that has been adopted for reference ETo calculations. Both the ASCE and Food and Agriculture Organization (FAO-56) have approved versions of the equation with only minor differences (standard crop height being the major difference). ASCE reference ETo can be calculated for only two specific crop heights—short (grasses) and tall (alfalfa). The data used in this report were calculated for a short reference crop, most relevant to typical home lawns.

The monthly rainfalls (or soil moisture additions due to the rainfall) for each geographical area, expressed in inches/ month, were compared to the evapotranspiration rate requirements for landscaped area plants to determine the irrigation requirements to meet the plant’s minimum moisture needs. The reference evapotranspiration rates (ETo) were obtained from CIMIS for the southwest near Los Angeles and from the ASCE standardized reference equations for the other locations, as shown on Table A-7. The ETo values are given in inches/day and were therefore converted to inches/month for direct comparison to the monthly rainfall (or soil moisture addition) values. The Los Angeles and Seattle rainfall monitoring locations were represented by two ETo stations that were averaged for these analyses. The other areas only had single ETo stations representing their rainfall monitoring locations. Table A-8 shows the monthly values, while Figure A-2 is a plot comparing the seasonal evapotranspiration values for these six rainfall monitoring locations. The ETo patterns are similar for all locations with the greatest values (maximums of about 5 to 6.5 inches/month) occurring in the summer months, while the minimum winter ETo values are less than 2 inches/month. Seattle has the lowest ETo values for most months (annual total of about 28 inches), while Los Angeles has the highest values for most months (annual total of about 49 inches). Specific details on modeling evapotranspiration are also given by Pitt, et al. (2008).

Tables A-9 through A-14, along with Figure 3-2, show the calculations and resulting plots indicating the average monthly irrigation requirements (based on 1995-1999 rainfall; 1995-1999 for Lincoln) to meet the long-term average monthly ET values. A plant’s actual ET is calculated by multiplying ETo rates by coefficients for each plant type providing a daily moisture estimate for the crop under well-watered conditions. Romero and Dukes (2008) prepared a summary of crop coefficients for the Southwest Florida Water Management District and the Florida Agricultural Experiment Station, which lists turfgrass coefficients for warm and humid areas that ranged from about 0.55 to 0.79 for warm

TABLE A-7 Evapotranspiration Reference Rate (ETo) Stations Used for Beneficial Use Calculations

Rain Gage Location ETo Data Source Station Name Latitude Longitude Elev. (ft)
Los Angeles Airport Weather Service Office, CA CIMIS Average Monthly Rates, 1989-2011 Glendale, CA 34.197 -118.230 1,111
Long Beach, CA 33.799 -118.095 17
Seattle Tacoma Airport, WA ASCE Std. Ref. Eq., 2005-2010 Quilcene, WA 47.82 -122.88 62
Enumclaw, WA 47.2 -121.96 771
Lincoln Airport, NE ASCE Std. Ref. Eq., 2008-2011 Rainwater Basin NE 40.57 -98.17 1,790
Madison Dane Co Airport, WI ASCE Std. Ref. Eq., 2005-2011 Wautoma, WI 43.1 -89.333 857
Birmingham Airport, AL ASCE Std. Ref. Eq., 2003-2011 Talladega, AL 33.44 -86.081 600
Newark International Airport, NJ ASCE Std. Ref. Eq., 2005-2011 New Middlesex County NJ 40.41 -74.494 116

TABLE A-8 Monthly ETo Values for Study Locations (inches/month)

Jan Feb March April May June July Aug Sept Oct Nov Dec Annual total (inches/yr)
Los Angeles, CA 1.86 2.40 3.60 4.80 5.27 5.85 6.36 6.20 4.80 3.57 2.40 1.86 48.96
Seattle, WA 0.78 0.99 1.80 2.85 3.26 4.05 4.81 3.88 2.25 1.71 1.20 0.78 28.33
Lincoln, NE 0.93 1.41 3.00 4.50 5.58 6.30 6.20 5.27 4.50 3.72 2.10 0.93 44.44
Madison, WI 0.31 0.57 1.50 3.60 4.96 5.10 5.58 4.34 3.00 2.17 1.20 0.31 32.64
Birmingham, AL 1.24 2.26 3.30 4.50 4.96 4.80 4.96 4.65 4.20 3.72 2.10 1.55 42.24
Newark, NJ 0.62 0.85 2.70 4.20 5.27 5.10 5.58 4.96 4.20 3.10 2.70 1.24 40.52
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×

season grasses. Aronson et al. (1987) listed coefficients for cool season grasses in the humid Northeast that ranged from about 0.6 to 1.04. Brown et al. (2001) presented a summary for arid areas with turfgrass coefficients ranging from about 0.8 to 0.9. For the calculations in this report, a turfgrass coefficient of 0.8 was used for all conditions.

Tables A-9 through A-14 show the monthly ETo reference values, the 0.8 turf grass coefficient that reduces the reference ETo values to obtain the actual expected evapotranspiration for typical turf grass, along with the average monthly rainfall amounts (based on 1995-1999 precipitation data for five locations and 1996-1999 data for Lincoln). The irrigation requirements shown here are simply the average amounts of water needed monthly in addition to rainfall to meet the ET requirements. Other calculations also considered the moisture added to the soil for each rain instead of the total rainfall, because not all of the rain infiltrates and is available for the plants. These tables show the actual differences between the average ET and rainfall values, and some (especially in the wetter months, or months having low ET requirements) have negative values (the rainfall is greater than the ET requirements). The actual average irrigation requirements per month ignore these negative values, as months with excessive rainfall cannot benefit months requiring irrigation, unless the excess runoff is stored for later beneficial uses (as indicated below in the storage tank modeling descriptions). Figure 3-2 graphically illustrates the average monthly irrigation requirements for the landscaped areas for each of these locations, which were then used in the model to calculate the effects of storage and roof runoff volumes for the different land uses on the resulting domestic water savings.

Table A-15 shows the amount of landscaped area as a percentage of the total land use for different areas in the Los Angeles. The monthly irrigation needs in ft3 of water per acre of land use per month was calculated by unit conversions using the landscaped area percentage of the land use and the irrigation requirements in inches/month. Small rounding effects may be reflected in the summary tables and example calculations because the model and spreadsheet calculations are high precision, while the summaries and example calculations used truncated significant digits. Also shown on Table A-15 are the total runoff amounts from the roofs and for the whole area for these land uses in Los Angeles. Except for the commercial and industrial areas, land use runoff is not sufficient to completely satisfy the irrigation requirements, and roof runoff alone is close to meeting the irrigation needs only for the commercial areas (simply on a total volume comparison, assuming sufficient storage is provided). The effects of storage tanks also need to be considered, as described below. Other geographical areas with differing rain and ET patterns, plus different land development characteristics, result in dif-

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FIGURE A-2 Monthly reference evapotranspiration rates for six study areas.
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×

ferent conclusions. Table A-16 shows the irrigation requirement, expressed in gallons per day per 100 acres of the land use, as used by the model as the water demand for three of the six locations analyzed.

Domestic Water Savings Due to Roof Runoff Harvesting

Two volumes corresponding to typical water storage scenarios (two water barrels per household and one large water storage tank per household) were examined with WinSLAMM corresponding to typical runoff harvesting scenarios. Table A-17 shows the storage volume calculations for the two water storage tank options examined, shown for the Los Angeles example. The model calculates the stormwater runoff volume reductions using continuous simulations for the study period. The water storage tanks are continuously modeled based on additions of roof runoff for each rain and withdrawals to meet monthly average irrigation demand to meet the ET deficits, considering rainfall-induced changes in soil moisture. Overall indoor and outdoor water use behavior was assumed to be the unchanged with the addition of low-cost onsite sources of water. If the tank is full while runoff is still occurring, then the excess runoff is discharged to the drainage system and is not available for beneficial use. If the tank empties due to water withdrawals, then supplemental potable water would be needed to meet additional water demands. Small tanks overflow and are empty more frequently than larger tanks and therefore supply less water for beneficial uses.

The Los Angeles water savings are calculated based on the runoff reductions (with 153,731 ft3 of water storage volume per 100 acres, corresponding to a single 2,200-gallon water tank at each home). The model calculated 11.6 percent stormwater runoff reductions using this size tank for irrigation in this medium-density, residential land use area. The total average annual runoff for the medium-density, residential area was also calculated to be 27,940 ft3 per acre. The average domestic water savings by using harvested roof runoff for this scenario analysis is therefore:

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or 2.42 millions of gallons (Mgal) per year for 100 acres.

Indoor Use of Roof Runoff for Toilet Flushing for Medium Density Residential Areas

Toilet flushing water use is based on a per capita water use of 11 gallons per capita per day. With 12 persons/acre and 100 acres of area, this is therefore

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TABLE A-9 Los Angeles Irrigation Requirements to Meet ET Deficit

Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Annual
LA ETo, in/mo (reference) 1.86 2.405 3.6 4.8 5.27 5.85 6.355 6.2 4.8 3.565 2.4 1.86
Turf grass coefficient 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8
LA ET, in/mo (corrected for turf grass) 1.488 1.921 2.88 3.84 4.216 4.68 5.084 4.96 3.84 2.852 1.92 1.488 39.169
LA avg rainfall (in/mo) 4.89 3.76 2.48 0.86 0.59 0.25 0.01 0.00 0.05 0.29 1.30 2.24 16.734
LA irrigation requirements to match -3.406 -1.837 0.4 2.976 3.622 4.434 5.072 4.96 3.788 2.562 0.616 -0.752
ET (in/mo)
LA irrigation requirements, ignoring excessive rainfall periods (in/mo) 0 0 0.4 2.976 3.622 4.434 5.072 4.96 3.788 2.562 0.616 0 28.43

TABLE A-10 Seattle Irrigation Requirements to Meet ET Deficit

Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Annual
Seattle ETo, in/mo (reference) 0.775 0.989 1.8 2.85 3.255 4.05 4.805 3.875 2.25 1.705 1.2 0.775
Turf grass coefficient 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8
SeaTac ET, in/mo (corrected for turf grass) 0.62 0.791 1.44 2.28 2.604 3.24 3.844 3.1 1.8 1.364 0.96 0.62 22.663
SeaTac avg rainfall (in/mo) 6.20 5.12 4.05 2.63 1.28 1.21 0.78 1.06 1.24 4.00 7.92 6.22 41.694
SeaTac irrigation requirements to match ET (in/mo) -5.576 -4.327 -2.612 -0.348 1.328 2.034 3.064 2.044 0.556 -2.632 -6.964 -5.598
SeaTac irrigation requirements, ignoring excessive rainfall periods (in/mo) 0 0 0 0 1.328 2.034 3.064 2.044 0.556 0 0 0 9.026
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×

For a year and 100 acres, this amounts to 4.82 Mgal/yr. The indoor per capita water use and population density values were assumed to be the same for all of the medium-density, residential areas examined.

Table A-18 summarizes the monthly Los Angeles water uses for the three water demand scenarios examined in the report: conservation irrigation, toilet flushing, and conservation irrigation plus toilet flushing combined. Table A-19 shows the calculated potential water savings from the WinSLAMM model for the 5 years of rainfall data in a Los Angeles, 100-acre, medium-density, residential, study area. Values were obtained for both the roof areas alone and the total area to check the water savings values. The model calculations for water savings were averaged to obtain the annual runoff savings in both ft3 and millions of gallons.

VERIFICATION OF ORIGINAL ANALYSIS

The committee performed several levels of verification on this original analysis of water savings potential to ensure that the results are sound. The committee members performing the analysis vetted the assumptions of the analysis with

TABLE A-11 Lincoln Irrigation Requirements to Meet ET Deficit

Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Annual
Lincoln ETo, in/mo (reference) 0.93 1.4125 3 4.5 5.58 6.3 6.2 5.27 4.5 3.72 2.1 0.93
Turf grass coefficient 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8
Lincoln ET, in/mo (corrected for turf grass) 0.744 1.13 2.4 3.6 4.464 5.04 4.96 4.216 3.6 2.976 1.68 0.744 35.554
Lincoln avg rainfall (in/mo) 0.58 0.55 1.47 3.19 5.29 4.30 2.44 3.89 1.82 1.69 2.15 0.31 27.675
Lincoln irrigation requirements to match ET (in/mo) 0.1665 0.5775 0.935 0.4075 -0.826 0.7425 2.52 0.326 1.78 1.286 -0.47 0.434
Lincoln irrigation requirements, ignoring excessive rainfall periods (in/mo) 0.1665 0.5775 0.935 0.4075 0 0.7425 2.52 0.326 1.78 1.286 0 0.434 9.175

TABLE A-12 Madison Irrigation Requirements to Meet ET Deficit

Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Annual
Madison ETo, in/mo (reference) 0.31 0.565 1.5 3.6 4.96 5.1 5.58 4.34 3 2.17 1.2 0.31
Turf grass coefficient 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8
Madison ET, in/mo (corrected for turf grass) 0.248 0.452 1.2 2.88 3.968 4.08 4.464 3.472 2.4 1.736 0.96 0.248 26.108
Madison avg rainfall (in/mo) 1.49 0.83 1.81 3.46 3.13 5.55 4.07 3.18 1.59 2.60 1.33 0.59 29.62
Madison irrigation requirements to match ET (in/mo) -1.244 -0.378 -0.614 -0.576 0.842 -1.47 0.394 0.288 0.812 -0.86 -0.368 -0.338
Madison irrigation requirements, ignoring excessive rainfall periods (in/mo) 0 0 0 0 0.842 0 0.394 0.288 0.812 0 0 0 2.336

TABLE A-13 Birmingham Irrigation Requirements to Meet ET Deficit

Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Annual
Birmingham ETo, in/mo (reference) 1.24 2.26 3.3 4.5 4.96 4.8 4.96 4.65 4.2 3.72 2.1 1.55
Turf grass coefficient 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8
Birmingham ET, in/mo (corrected for turf grass) 0.992 1.808 2.64 3.6 3.968 3.84 3.968 3.72 3.36 2.976 1.68 1.24 33.792
Birmingham avg rainfall (in/mo) 6.88 4.32 5.96 4.26 3.96 2.66 3.86 3.36 3.12 4.92 3.72 2.82 49.84
Birmingham irrigation requirements to match ET (in/mo) -5.888 -2.512 -3.32 -0.66 0.008 1.18 0.108 0.36 0.24 -1.944 -2.04 -1.58
Birmingham irrigation requirements, ignoring excessive rainfall periods (in/mo) 0 0 0 0 0.008 1.18 0.108 0.36 0.24 0 0 0 1.896
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×

TABLE A-14 Newark Irrigation Requirements to Meet ET Deficit

Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Annual
Newark ETo, in/mo (reference) 0.62 0.8475 2.7 4.2 5.27 5.1 5.58 4.96 4.2 3.1 2.7 1.24
Turf grass coefficient 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8 0.8
Newark ET, in/mo (corrected for turf grass) 0.496 0.678 2.16 3.36 4.216 4.08 4.464 3.968 3.36 2.48 2.16 0.992 32.414
Newark avg rainfall (in/mo) 4.56 3.07 3.71 3.70 3.89 2.94 4.30 2.65 4.65 3.60 3.58 2.86 43.514
Newark irrigation requirements to match ET (in/mo) -4.06 -2.388 -1.554 -0.336 0.328 1.14 0.16 1.32 -1.292 -1.122 -1.424 -1.872
Newark irrigation requirements, ignoring excessive rainfall periods (in/mo) 0 0 0 0 0.328 1.14 0.16 1.32 0 0 0 0 2.948

TABLE A-15 Example Watershed Demand and Available Stormwater by Land Use in Los Angeles

Landscaped Area (% of total land use) ft3 of irrigation water/acre/mo Total Annual Irrigation Demand to Meet ET (ft3/acre) Total Annual Roof Runoff (ft3/acre) Total Annual Land Use Runoff (ft3/acre)
Jan Feb March April May June July Aug Sept Oct Nov Dec
Commercial 14.9 0 0 216 1,610 1,959 2,398 2,743 2,683 2,049 1,386 333 0 15,377 14,014 42,822
High density residential 46.4 0 0 674 5,013 6,101 7,468 8,543 8,354 6,380 4,315 1,038 0 47,885 11,894 30,603
Medium densit residential 52.5 0 0 762 5,672 6,903 8,450 9,666 9,453 7,219 4,883 1,174 0 54,180 10,344 27,939
Low density residential 79.6 0 0 1,156 8,599 10,466 12,812 14,655 14,332 10,945 7,403 1,780 0 82,148 4,596 14,892
Industrial 24.3 0 0 353 2,625 3,195 3,911 4,474 4,375 3,341 2,260 543 0 25,078 10,074 33,534
Institutional 41.2 0 0 598 4,451 5,417 6,631 7,585 7,418 5,665 3,832 921 0 42,519 9,676 30,920

TABLE A-16 Example Irrigation Demand for Land Uses in the Los Angeles, Lincoln, and Newark (gal/day per 100 acres of land use area)

gal/day per 100 Acres of Land Use for Tank Modeling Roof area (%) Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
Los Angeles commercial 28.1 0 0 5,323 39,605 48,202 59,009 67,499 66,009 50,412 34,096 8,198 0
Los Angeles high density residential 20.7 0 0 16,577 123,335 150,107 183,759 210,200 205,558 156,987 106,177 25,529 0
Los Angeles med. density residential 18.0 0 0 18,406 141,504 166,665 210,830 233,386 228,233 180,114 117,890 29,290 0
Los Angeles low density residential 8 0 0 28,439 211,583 257,511 315,242 360,601 352,638 269,313 182,149 43,795 0
Los Angeles industrial 20.2 0 0 8,682 64,591 78,612 96,236 110,083 107,652 82,215 55,606 13,370 0
Los Angeles institutional 19.4 0 0 14,719 109,513 133,285 163,165 186,643 182,521 139,393 94,278 22,668 0
Lincoln commercial 25.0 2,082 7,221 11,692 5,096 0 9,285 31,230 3,420 22,258 15,393 0 5,271
Lincoln high density residential 20.7 6,900 23,933 38,749 16,888 0 30,772 103,504 11,335 73,769 51,017 0 17,468
Lincoln medium density residential 18.1 9,165 34,878 51,465 23,177 0 42,231 138,707 17,944 101,241 70,784 0 23,888
Lincoln medium density residential 18.1 9,339 32,393 52,445 22,857 0 41,648 140,088 15,341 99,842 69,048 0 23,642
Lincoln low density residential 14.9 9,830 34,095 55,201 24,058 0 43,836 147,449 16,147 105,089 72,677 0 24,885
Lincoln industrial 10.2 2,275 7,892 12,777 5,569 0 10,147 34,130 3,738 24,325 16,822 0 5,760
Lincoln institutional 24 6,469 22,438 36,327 15,833 0 28,848 97,035 10,626 69,158 47,828 0 16,377
Newark commercial 28.1 0 0 0 0 4,365 15,171 2,129 17,567 0 0 0 0
Newark high density residential 20.7 0 0 0 0 13,593 47,245 6,631 54,705 0 0 0 0
Newark medium density residential 15.9 0 0 0 0 16,464 57,224 8,031 66,259 0 0 0 0
Newark low density residential 8.0 0 0 0 0 23,320 81,050 11,375 93,847 0 0 0 0
Newark industrial 20.2 0 0 0 0 7,119 24,743 3,473 28,649 0 0 0 0
Newark institutional 19.4 0 0 0 0 12,070 41,950 5,888 48,574 0 0 0 0
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×

the entire committee. Once the analysis was completed, two committee members and one staff person reviewed the spreadsheets containing the graywater analysis and the pre- and post-processing of the stormwater model analysis in detail to check for errors. Assumptions between the two analyses were compared for consistency, and a cell-by-cell assessment was performed to check that the appropriate values and formulas were used. Following this verification, a few minor errors that were detected were discussed with the staff and committee members responsible for the analysis and subsequently corrected.

Additionally, the analysis (including Chapter 3, Appendix A, and associated spreadsheets and input files) was sent to two independent unpaid consultants who were familiar with stormwater modeling to review. They were asked to assess whether the analysis and related assumptions were reasonable and appropriate and to identify any concerns or errors in the analysis. Feedback from the independent consultants was used to strengthen the discussion of uncertainties and the appropriate use of the scenario analysis findings.

TABLE A-17 Site Characteristics and Storage Volumes for the Los Angeles Example

Parameter Calculation
Roof area (ac per 100 ac of medium-density residential land uses, MDR) 18% of 100 acres = 18 acres
Number of homes in 100 acres (1500 ft2 roof)

image

Rain barrel storage (gallons/100 ac)

image

Rain barrel storage (ft3/100 ac)

image

Rain barrel storage (ft3/ft2 roof area)

image

Water tank storage (gallons/100 ac)

image

Water tank storage (ft3/100 ac)

image

Water tank storage (ft3/ft2 roof area)

image

Landscaped area (ac per 100 ac of MDR) 52.5% of 100 acres = 52.5 acres

TABLE A-18 Average Monthly Water Use Patterns for Los Angeles Scenario

Gallons/day/100 ac Medium-Density Residential (MDR) Area Southwest Minimum Irrigation Requirements (gal/day) Southwest Toilet Flushing (gal/day) Southwest Minimum Irrigation Plus Toilet Flushing (gal/day)
Jan 0 13,200 13,200
Feb 0 13,200 13,200
Mar 18,406 13,200 31,606
Apr 141,504 13,200 154,704
May 166,665 13,200 179,865
Jun 210,830 13,200 224,030
Jul 233,386 13,200 246,586
Aug 228,233 13,200 241,433
Sept 180,114 13,200 193,314
Oct 117,890 13,200 131,090
Nov 29,290 13,200 42,490
Dec 0 13,200 13,200
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×

TABLE A-19 WinSLAMM Calculated Water Use Savings for Los Angeles, Medium-Density, Residential Scenario Using One 2,200-gallon Water Storage Tank per Household

Minimum Irrigation Toilet Flushing Minimum Irrigation Plus Toilet Flushing
% volume reduction of roof runoff 31.26 35.48 42.36
Total roof runoff (ft3/5 yrs/100 ac MDR) 5,172,000 5,172,000 5,172,000
Volume of roof runoff used to replace domestic water use (ft3/5 yrs/100 ac MDR)a 1,616,767 1,835,026 2,190,860
% volume reduction of entire MDR area 11.6 13.1 15.68
Total MDR runoff (ft3/5 yrs/100 ac) 13,970,000 13,970,000 13,970,000
Volume of runoff used to replace potable water use (ft3/5 yrs/100 ac)a 1,620,520 1,830,070 2,190,496
Average annual volume of potable water replaced by roof runoff using water tank (ft3 per year/100 ac) 323,729 366,510 438,136
Average annual volume of potable water replaced by roof runoff using water tank (Mgal/yr/100 ac) 2.42 2.74 3.28

aThese values should be the same and were therefore used to verify the calculations.

Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×
Page 187
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×
Page 188
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×
Page 189
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×
Page 190
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×
Page 191
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×
Page 192
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×
Page 193
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×
Page 194
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×
Page 195
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×
Page 196
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×
Page 197
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×
Page 198
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×
Page 199
Suggested Citation:"Appendix A: Calculating the Benefits of Rooftop Runoff Capture Systems." National Academies of Sciences, Engineering, and Medicine. 2016. Using Graywater and Stormwater to Enhance Local Water Supplies: An Assessment of Risks, Costs, and Benefits. Washington, DC: The National Academies Press. doi: 10.17226/21866.
×
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Chronic and episodic water shortages are becoming common in many regions of the United States, and population growth in water-scarce regions further compounds the challenges. Increasingly, alternative water sources such as graywater-untreated wastewater that does not include water from the toilet but generally includes water from bathroom sinks, showers, bathtubs, clothes washers, and laundry sinks- and stormwater-water from rainfall or snow that can be measured downstream in a pipe, culvert, or stream shortly after the precipitation event-are being viewed as resources to supplement scarce water supplies rather than as waste to be discharged as rapidly as possible. Graywater and stormwater can serve a range of non-potable uses, including irrigation, toilet flushing, washing, and cooling, although treatment may be needed. Stormwater may also be used to recharge groundwater, which may ultimately be tapped for potable use. In addition to providing additional sources of local water supply, harvesting stormwater has many potential benefits, including energy savings, pollution prevention, and reducing the impacts of urban development on urban streams. Similarly, the reuse of graywater can enhance water supply reliability and extend the capacity of existing wastewater systems in growing cities.

Despite the benefits of using local alternative water sources to address water demands, many questions remain that have limited the broader application of graywater and stormwater capture and use. In particular, limited information is available on the costs, benefits, and risks of these projects, and beyond the simplest applications many state and local public health agencies have not developed regulatory frameworks for full use of these local water resources.

To address these issues, Using Graywater and Stormwater to Enhance Local Water Supplies analyzes the risks, costs, and benefits on various uses of graywater and stormwater. This report examines technical, economic, regulatory, and social issues associated with graywater and stormwater capture for a range of uses, including non-potable urban uses, irrigation, and groundwater recharge. Using Graywater and Stormwater to Enhance Local Water Supplies considers the quality and suitability of water for reuse, treatment and storage technologies, and human health and environmental risks of water reuse. The findings and recommendations of this report will be valuable for water managers, citizens of states under a current drought, and local and state health and environmental agencies.

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