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Tech Doc River-Friendly Landscaping Emissions Calculator Technical Documentation

Matthew Heberger

Pacific Institute, Oakland, California

http://www.pacinst.org/

Updated September 2013

Table of Contents

1 Introduction ............................................................................................................................. 1

2 Model Inputs ........................................................................................................................... 6

3 Calculations ........................................................................................................................... 13

4 Software ................................................................................................................................ 28

5 References ............................................................................................................................. 30

1 Introduction The River-Friendly Landscaping Benefits Calculator (hereafter, the Calculator) is a web

application designed to help Sacramento County residents and landscape professionals estimate

the benefits of choosing environmentally-friendly landscaping, and thereby reduce water and

chemical usage, green waste production, and greenhouse gas (GHG) emissions. The calculator

can help you estimate the water requirements, labor, and emissions for your garden based on

your choice of plants, irrigation systems, and landscaping practices. The calculator was created

by the Pacific Institute for Sacramento County, California and funded by an EPA Climate

Showcase Communities grant.

In this document, we provide details about the data, assumptions, and methods used to develop

the calculator. The intended audience is (1) developers or others who would like to modify the

project or create a similar application, or (2) users seeking a more detailed understanding of

how we calculate resource use for landscapes.

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1.1 About the Software The software is open-source, released under the MIT free software license1. You are free to

borrow, remix, or re-use any or all of the code on this site. To download or browse the source

code, go to http://code.google.com/p/landscape-calculator/. Additional information about the

web technologies used in this project is included in Section 4 of this document.

1.2 Zip Codes We use the user’s zip code as the basis to look up certain numeric values used in the

calculations, such as the irrigation requirement for landscape plants, or the driving distance for

trucks transporting green waste to a landfill. We also use it to filter certain option lists, such as

the user’s choice of water utility or waste hauler. There are 56 zip codes in Sacramento County,

as shown in Figure 1, covering areas ranging from 2.4 – 166 square miles. Several zip codes

extend into neighboring counties.

Figure 1 Zip codes in Sacramento County.

1 Open Source Initiative OSI - The MIT License, http://www.opensource.org/licenses/mit-license.php

Sacramento County

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1.3 Water Providers We ask the user her water provider in order to better estimate the cost and emissions related to

landscape water use. There are 27 agencies or utilities that sell water to homes and businesses

in Sacramento County (Figure 2 and Table 1). This information is derived from a GIS data file

provided to us by county staff. Calculator users may identify their water provider, which will be

used to look up certain parameters used in the calculations, such as the local water rates (which

affects the cost of watering the landscape) and the energy requirements for treating and

delivering water (which affects the emissions related to water used on landscaping).

Figure 2 Water providers in Sacramento County

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Table 1 Water Providers in Sacramento County

ID Agency Service Area

(square miles)

1 Cal American Water Company 35.0

2 Carmichael Water District 8.5

3 Citrus Heights Water District 12.6

4 City of Folsom Water District 30.0

5 City of Galt Water District 5.4

6 City of Sacramento Water District 98.2

7 Clay Water District 10.0

8 Del Paso Manor Water District 1.0

9 El Dorado Irrigation District 0.3

10 Elk Grove Water Service 4.7

11 Elk Grove Water Service Retail/ SCWA WSA 7.8

12 Fair Oaks Water District 9.8

13 Florin County Water District 2.3

14 Fruitridge Vista Water Company 2.8

15 Galt Irrigation District 52.2

16 Golden State Water Company 12.2

17 Natomas Central MWC 35.8

18 Omochumne-Hartnell/ SCWA Overlap SA 12.1

19 Orangevale Water Company 4.9

20 Rancho Murieta CSD 5.6

21 Rio Linda Elverta Water District 17.8

22 Sacramento County Water Agency 107.0

23 Sacramento International Airport 3.7

24 Sacramento Suburban Water District 36.0

25 San Juan Water District 4.2

26 SMUD Rancho Seco 3.9

27 Tokay Park Water Company 0.1

Total 558.0

1.4 Defining a River-Friendly Landscape The Calculator performs calculations to estimate of the water requirements, labor, annual

expense, and greenhouse gas emissions for the user’s garden, based on the types of plants and

irrigation systems selected. For comparison, we’ve also calculated these quantities for a

hypothetical River-Friendly Landscape (RFL) and a conventional landscape. While there is no

canonical definition of what constitutes “River-Friendly,” our benchmark RFL landscape has the

following characteristics:

The total landscaped area is the same as the user’s landscape.

The landscaped area includes a small lawn (144 square feet) that is watered with

fixed sprinklers.

The lawn is mowed with an electric push mower.

Grass clippings are left to decompose on the lawn after it is mowed, referred to as

grasscycling.

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Plantings (excluding turf) are either low-water use California-native or

Mediterranean shrubs or ground cover.

Plantings are irrigated with high-efficiency drip irrigation.

Twenty-five percent of the plant trimmings are composted on site. The remainder is

put into a green waste bin.

Watering is scheduled using a properly programmed smart irrigation controller that

meets the plants water requirements, i.e., the garden is not overwatered.

Please note that this configuration is subjective and is simply meant to help users understand

how they can save water, time, and waste by incorporating River-Friendly concepts into their

own yards. Additional savings are possible by, for example, replacing all lawn and replacing with

low- water use plants.

We also compare the user’s garden to a hypothetical “conventional” landscape. We assume that

a conventional garden in the Sacramento area has the following characteristics:

• The total landscaped area is the same as the user’s landscape.

• The landscape area typically has a lawn, and other medium- to high-water use

annuals or perennials.

• Fertilizers and pesticides are used.

• Grass clippings and yard trimmings are put in a green bin for curbside pickup.

• Watering is done by sprinklers.

• The lawn is mowed weekly, 9 months per year, with an electric mower.

• A smart controller or “weather-based irrigation controller” is not used.

Our definitions of these prototype landscapes are summarized in Table 2. These characteristics

are used to calculate the resource use of these hypothetical landscapes for comparative

purposes.

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Table 2 Definition of conventional and River-Friendly landscapes.

Conventional River Friendly

Area Total area of user’s landscape Total area of user’s landscape

Plant Types 100% covered by either conventional lawn or high-water use flowers and shrubs (average plant factor = 0.8).

Small lawn (144 sq. ft.) of low water-use grass. Remainder of area covered by low-water use shrubs and/or California natives (plant factor = 0.2).

Irrigation Sprinklers (efficiency = 70%) High-efficiency drip (efficiency = 90%)

Grasscycling No Yes

Composting No 25% of yard waste composted

Mulch 2” of mulch over most planted areas 3” of mulch over most planted areas

Fertilizer Use Applied over entire landscaped area None

Mowing Electric push mower over entire landscape area. Assume weekly mowing for 9 months per year.

Reel mower or None (zero emissions)

Smart Irrigation Controller

None. In use. Watering scheduled to meet plants’ needs, resulting in less water waste.

Pesticides Regular or as-needed use of chemical pesticides.

Either not used, or only non-toxic/organic alternatives.

Note: For additional information on the model assumptions, see Appendix Tables 1-4.

2 Model Inputs The model contains a variety of assumptions about green waste, landscape equipment, water

use, and fertilizer application. The data and information supporting these assumptions can be

found in Appendix Tables 1-4. In addition, we use a simple water-deficit method to estimate the

average annual water demand for landscaped areas, and potential savings from switching to

low-water use plants. Below, we provide more detail on these methods.

2.1 Landscape Water Requirements Agronomists and hydrologists estimate crop water demand, or theoretical irrigation

requirements, using the concept of evapotranspiration. Evapotranspiration, or ET, is a

combination of evaporation of water from the soil and plant surfaces, and transpiration, which

is water lost by the plant through stomata, or openings, in its leaves. Plants open stomata to

respire; during daylight they take in carbon dioxide and emit oxygen. During darkness this

process is reversed, and plant respiration consumes oxygen and releases CO2. As a side effect,

plants also lose water vapor, in a process called “transpiration.” Transpiration losses increase

under hot and dry conditions such that the plant must take up more water through its roots in

order to survive and grow.

Potential evapotranspiration, or PET, is the evapotranspiration that would occur for a given crop

with an ample supply of water. PET is affected by hydro-climatic factors, including air

temperature, wind speed, humidity, solar radiation, and cloud cover. Actual evapotranspiration,

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or ET, will equal PET in wet conditions, where water is abundantly available. Under drier

conditions, ET will be some fraction of PET. In natural landscapes characterized by aridity, the

actual ET is often less than PET, because the water is not available to plants. On an annual basis,

natural evapotranspiration in California is usually less than PET, which will only occur when

water is abundantly available. For irrigated landscapes, analysts often assume that there is

enough soil moisture available to meet the plants’ water needs at all times, or that ET will

approach PET.

2.1.1 Monthly Irrigation Requirement

The irrigation demand, or plant water requirement, is one of the most important parameters in

the model. We estimated monthly plant irrigation water requirement for each zip code in

Sacramento county using available meteorological data and a simple water balance model. The

water balance model has only two inputs: the long-term average monthly PET and precipitation

(P) for each area under consideration.

For each month in an average year, we calculated the net irrigation requirement using the field

water balance method. We followed equation 27.2.32 in the Handbook of Hydrology (Maidment

ed. 1993):

( )

2-1

where:

I is the monthly irrigation requirement, ETcrop is the evapotranspiration for a cropped area, P is

the monthly precipitation, G is the groundwater contribution, and W is the stored water at the

beginning of the month. We ignore the terms G and W and set them to zero, assuming that they

are negligible for household landscapes and the relatively long time scale of one month.

We developed an estimate of annual irrigation use that is appropriate in warm climates, where

irrigation may take place year round:

∑ ( )

2-2

where t represents the month of the year from January to December.

The application of Equation 2-2 is shown in Figure 3 below. The plot shows natural moisture

demand, and is patterned after the “water balance charts” that were shown in the seminal

California Water Atlas (Kahrl ed. 1979). In months where precipitation exceeds

evapotranspiration, the plants’ water needs are fully met without irrigation and the irrigation

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requirement is zero. The plot in Figure 3 was constructed for Sacramento, which is marked by

hot, dry summers where the potential evapotranspiration is high; most of the precipitation

occurs during the winter months. The height of the green bars

indicates the water deficit that needs to be fulfilled by irrigation

water to meet plant water needs.

Figure 3 Monthly water deficit as a proxy for irrigation demand

Using Equation 2-2, we developed an estimate of irrigation demand for each zip code in

California. We performed the analysis using ArcMap, Geographic Information Systems (GIS)

software from ESRI. The important input layers were monthly precipitation and potential

evapotranspiration. We describe the source of these datasets in the next sections.

All outputs were initially reported by zip code. We obtained zip code boundaries from ESRI Data

& Maps, a compendium of digital data distributed by the GIS software vendor ESRI. We created

a new GIS point layer of zip codes, by converting the point at the centroid of each zip code

polygon to a new feature. Many US zip codes represent post office boxes; these were not

included in the analysis. It should also be noted that new zip codes are created every year as the

population grows and moves. The datasets we used were created in 2006.

0

2

4

6

8

10Ja

n

Feb

Mar

Ap

r

May Jun

Jul

Au

g

Sep

Oct

No

v

De

c

Water depth

(inches)

Irrigation demand (I)

Precipitation (P)

PotentialEvapotranspiration (PET)

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Figure 4 Reference evapotranspiration zones in California. Source: http://www.cimis.water.ca.gov/cimis/images/etomap.jpg

2.1.1.1 Evaporation & Evapotranspiration

We used estimates of reference evapotranspiration from a digital dataset published by the

California Department of Water Resources, shown on the map in Figure 4, which is based on

data from the California Irrigation Management System (CIMIS). There are 18 zones within the

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state, each of which represents an area with a similar climate. DWR reports monthly average

reference ET for each zone based on measurements from the network of 120 measurement

stations deployed since 1982 (DWR 2009). The monthly values for reference crop potential

evapotranspiration (ET0) are long-term averages based on these measurements.

We obtained a GIS shapefile of the ET zone boundaries from DWR staff. Sacramento falls

entirely within Reference ET Zone 14, Mid-Central Valley, Southern Sierra Nevada, Tehachapi &

High Desert Mountains. The reference ET for this zone is shown in Figure 5.

Month ET0 (in/month)

Jan 1.55

Feb 2.24

Mar 3.72

Apr 5.10

May 6.82

June 7.80

July 8.68

Aug 7.75

Sept 5.70

Oct 4.03

Nov 2.10

Dec 1.55

Total 57.0 Figure 5 Monthly average reference evapotranspiration (inches/month)

2.1.1.2 Monthly Precipitation

Next, we sought monthly precipitation datasets. We found that the highest spatial accuracy

among readily available data layers was from the PRISM project (Oregon State University 2009).

PRISM stands for “Parameter-elevation Regressions on Independent Slopes Model.” Researchers

created a spatial distribution of point measurements of rainfall for the time period 1997 to

2004. The rainfall values are distributed using the PRISM model, developed by Christopher Daly,

Director of the Spatial Climate Analysis Service, and documented in a series of reports and

journal articles, e.g. Daly 2008. The resolution of the raster datasets is approximately 2 km, i.e.

each pixel covers about 4 km2, or slightly more than 1 square mile. The PRISM precipitation in

central California is shown in Figure 6 below.

0

1

2

3

4

5

6

7

8

9

10

JAN FEB MAR APR MAY JUNE JULY AUG SEPT OCT NOV DEC

ETo

(in/month)

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Figure 6 PRISM average annual precipitation in central California.

We downloaded the monthly average precipitation data layers for January through December,

and converted them from ASCII Grid to ESRI Grid format using the ASCII to Raster conversion

tool in ArcToolbox. The zip code centroids were assigned a set of attributes for monthly and

annual precipitation in GIS. We used the free ArcGIS extension Hawth’s Tools, and its Intersect

Points tool.

2.1.2 Crop Coefficients and Water Use

The values calculated above reflect the irrigation water requirements in an average year for a

reference crop. A reference crop is well-watered grass; specifically, reference ET is defined as

“the rate of evapotranspiration from an extensive surface of 8 to 15 cm (3.1 to 5.9 in) tall, green

grass cover of uniform height, actively growing, completely shading the ground and not short of

water.” (Handbook of Hydrology, page 27.29, quoting Doorenbos and Pruitt, 1977.)

To account for differences in water requirements among different crops, a crop coefficient, kc, is

used, as shown in Equation 2-3.

2-3

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By the definition above, the crop coefficient for well-watered grass is 1.0. There is a large body

of research related to crop coefficients and irrigation requirements for agricultural crops. There

is much less guidance available regarding garden or landscape plants. In the landscaping

community, crop coefficients are also referred to as “plant water factors,” or simply “plant

factors.” We discuss how we assigned plant factors to different plant types in Section 3.1.

2.1.3 Irrigation Efficiency

Irrigation efficiency is the ratio of water beneficially used divided by the water applied. The

efficiency of an irrigation system depends on the system characteristics and management

practices. Well-designed and maintained systems will have a higher efficiency. For instance, if an

irrigation system is optimized and performing at theoretical 100% efficiency, this means that all

water makes its way to the plants root zone, and the exact amount of water required is applied.

In reality, there are a number of ways that water is lost during irrigation, such as percolation,

runoff, and wind. The Handbook of Hydrology (page 27.33) reports field application efficiencies

range from 0.5 to 0.8. These theoretical efficiency estimates assume a professionally-operated

irrigation system. At the household level, some irrigators may apply more or less than the

optimal amount of water. To describe whether an individual is over- or under-watering, analysts

have defined the application ratio as the actual water applied divided by the theoretical

irrigation water requirement.

Recent evidence indicates that householders apply water in many different ratios, with

approximately equal numbers of households under-watering and over-watering. There is also

evidence that some households apply more water than is required for a well-watered grass crop

while other households apply less; the average household, however, household applies the

amount of water needed to fill the needs of a well-watered grass crop (DeOreo et al. 2011).

2.1.4 Limitations

One shortcoming of our analysis is that it is based on a theoretical average year, rather than any

actual year in the climatic record. Actual irrigation needs in a given year may be lower or higher

due to changes in precipitation, temperature, cloud cover, or other climate variables. We

recommend future work to repeat this analysis using actual monthly data from the climate

record, to hindcast actual irrigation demands for the past. This would give a better estimate of

the variability of water demand, and how it responds to dry and wet years. Further, a more

sophisticated analysis might look at how urban outdoor demand will respond to climate change

in the future.

The input datasets are of limited spatial resolution and accuracy. As climate researchers and

meteorologists produce more detailed datasets in the future, this analysis could be expanded

and refined. Inaccuracy also comes from the limitations of our modeling technique. Our

simplified monthly water balance model does not include the complexities of snowfall, runoff,

deep percolation, or month-to-month soil moisture storage. The advantages of this technique

are its ease of use, and that it does not require calibration. A more sophisticated model could

more explicitly account for soil moisture, perhaps relying on GIS soils datasets for input data.

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In this simplified model, we assume that for vegetated areas, all of the precipitation infiltrates

into the soil and that there is no runoff. We also assume that no water percolates deep

underground where it is unavailable for uptake by plant roots. In reality, runoff and percolation

can be significant fluxes of water. Ignoring these components of the hydrologic cycle would

normally be a grave error. However, a well-prepared lawn or garden with good soil tilth will

have a high infiltration capacity, and good ability to store water in the plants’ root zone. In

practice, ignoring the runoff and percolation means that our model may slightly overestimate

the quantity of rainfall that is available to fulfill plant water demand and underestimate actual

irrigation requirements.

3 Calculations In calculating water use and waste generation for a user’s landscape, we have to make a number

of generalizations and assumptions. We sought out the best and most reliable information for

these estimates. However, there are many factors to consider, many of them related to human

decision making. How long should I water my grass? How big of a compost bin can I use? While

there are many potential sources for error, we don’t feel this makes the calculator less useful.

We tried to model landscape resource use with enough detail to provide meaningful

recommendations and ballpark estimates of resource use associated with landscaping.

The total resource use of the landscape are based on the user’s:

Location, based on zip code

Water Utility, selected from 26 options

Waste Hauler, selected for 13 options

Landscape characteristics (see next paragraph)

Landscaping maintenance practices

Most landscapes have several parts, for example a lawn, flowers, and a vegetable garden. We

allow the user to enter information for up to 10 “zones” in their landscape. Each zone

represents an area with plants that have similar needs in terms of water and nutrients. Each

zone has four properties:

Area, in square feet

Plant community, selected from a list of 21 options

Irrigation type, selected from a list of 9 options

Fertilizer application, yes/no

3.1 Water First, we calculate the annual water use for each plant zone. The user can add up to 10 zones.

The zones are numbered j = 0 to 9.

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3-1

where:

Wj = Annual average irrigation water use in gallons per day

I = Annual irrigation demand (inches)

aj = Area of the zone (square feet, ft2)

kj = Plant factor (dimensionless)

f = watering factor (dimensionless)

conv = 0.00170776, factor to convert from (in·ft²/yr) to (gal/day)

ej = irrigation efficiency (dimensionless) for the zone

The irrigation demand, I, was determined as described in Section 2.1.1. The area of the plant

zone is entered by the user and has a default of 600 square feet. The plant factor is based on the

type of plants the user chooses. The plant factors for each land cover type are shown in Table 3.

In choosing plant factors, we followed guidelines from EPA as well as the California Landscape

Contractors Association (CLCA). CLCA developed water budget standards for the state of

California as part of the development of the California Model Water Efficient Landscape

Ordinance (CLCA 2008). These crop coefficients are derived from the 1994 California

Cooperative Extension Service publication Water Use Classification of Landscape Species: A

Guide to the Water Needs of Landscape Plants (Costello and Jones 1994).

The table also shows other characteristics specific to plant communities: typical fertilizer

application rates, and whether it is mulched (yes for shrubs, no for lawns, etc.) Note that if the

user has not selected a plant community type, the default value for the plant factor is k = 0,

representing no irrigation water use.

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Table 3 Plant factors for the 21 plant communities

ID Name Plant

Factor

Fertilizer Application

Rate (lb per 1,000 sq.

ft.)

Mulch?

0 Low Water Use Grass 0.6 2 N 1 Grass - Traditional lawn 0.8 4 N 2 Vegetables and Herbs 0.9 4 Y 3 Fruit Trees 0.9 4 Y 4 Medium water Perennials 0.5 4 Y 5 Flowering Annuals 0.7 4 Y 6 California Natives" 0.2 0 Y 7 Trees - low water 0.2 1 Y 8 Trees - medium water 0.5 2 Y 9 Trees - high water 0.7 4 Y 10 Shrubs - low water 0.2 1 Y 11 Shrubs - medium water 0.5 2 Y 12 Shrubs - high water 0.7 4 Y 13 Ferns 0.9 2 Y 14 Ground cover - low water 0.2 1 Y 15 Ground cover - medium water 0.7 2 Y 16 Ground cover - high water 0.9 4 Y 17 Cacti and Succulents 0.2 1 Y 18 Pond/Water Feature 1.0 0 N 19 Hardscape/No vegetation 0 0 N 20 Mulched/No vegetation 0 0 Y Data Source: Water Use Classification of Landscape Species (University of California Cooperative Extension 2000)

We use a water factor, f, to adjust water use downward if the user is doing certain water-saving

practices. If the user mulches, water use is reduced by 20%. If the user has a smart controller,

watering is reduced by another 20%. Water factor values are shown in the diagram in Figure 7.

Mulch?

No Yes Sm

art

Co

ntro

ller?

No 1 0.8

Yes 0.8 0.64

Figure 7 Water factor values

The irrigation efficiency is based on the user’s choice of irrigation equipment within a given

zone, according to the values in Table 4. Note that the last entry, “None/Rainfall Only” has a

very large value. Dividing by this number makes the applied water essentially equal to zero.

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Table 4 Irrigation efficiencies

ID Irrigation Type Efficiency, e

0 Watering Can 0.8 1 Hose 0.6 2 Soaker Hose 0.7 3 Drip-Standard 0.7 4 Drip- Pressure Compensating 0.9 5 Fixed Spray Sprinklers 0.65 6 Micro Spray Sprinklers 0.7 7 Rotor Sprinklers 0.7 8 None/Rainfall Only 1 ×1032

The user’s average year-round water use, in gallons per day is the sum of all of the active areas,

(Equation 3-11). In equation 2, n is the number of active zones minus 1.

∑

3-2

Next, we calculate the water use for the prototype River-Friendly landscape. This landscape has

two areas: (1) low-water use grass, up to 144 sq. ft., (2) the remainder is low-water use plants (k

= 0.2, e = 0.9). Note that for a small landscape less than 144 sq ft, the grass will cover the entire

area. However, for larger landscapes, the total area of grass will not exceed 144 sq. ft. The

prototype RFL landscape is the same size as the user’s landscape. The total area is the sum of

the areas of the individual zones:

∑

3-3

The area of the prototype RFL landscape in grass will not exceed 144 square feet. For small

landscapes with a total area of less than 144 square feet, the entire area will be grass. We call

the remainder of the landscape “other,” and it consists of low-water use plants. These areas are

calculated as follows (in pseudocode):

if area_total > 0

if area_total <= 144

rfl_area_grass = area_total

rfl_area_other = 0

else

rfl_area_grass = 144

rfl_area_other = area_total – 144

We calculate the weighted average plant factor for the RFL landscape, using the size of each

area as the weighting factor:

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kRFL = (rfl_area_grass · 0.6 + rfl_area_other · 0.2) / A 3-4

We do the same to calculate a weighted-average irrigation efficiency. We assume that the area

in low-water use plants has an irrigation efficiency of 0.9, the highest efficiency available, from

high-efficiency drip. We assume the small lawn area is irrigated with sprinklers, with a typical

efficiency of 0.7.

eRFL = (rfl_area_grass · 0.7 + rfl_area_other · 0.9) / A 3-5

The total water use for the RFL landscape is:

3-6

where fRFL = watering factor of 0.64 from Figure 7, assuming both a smart controller and

mulching.

For the conventional landscape, we also assume an area equal to the user’s landscape, average

plant factor kconv= 0.8, and sprinklers with an irrigation efficiency of 70%, or e = 0.7. We also

assume that that neither deep mulching is applied, nor is a smart controller in place (fconv = 1).

The water use in gallons per day for a conventional landscape is:

3-7

3.2 Labor We estimate the hours of labor required for a conventional and efficient (RFL) landscapes based

on data published by the Garden-Garden project in Santa Monica. The annual hours of labor

associated with different types of garden are reported in “Maintenance Data”2, and the

landscaped area in the document “Construction Cost Sheet3,” and are shown here:

Annual Labor Hours Landscaped Area Labor Factor (calculated)

Conventional 87 hours 1,998 ft² Lconv = 0.193 hr/ft²·yr

Natives 11 hours 1,879 ft² Leff = 0.053 hr/ft²·yr

2 http://www.smgov.net/uploadedImages/Departments/OSE/Categories/Landscape/Labor%281%29.gif?n=1774

3 http://www.smgov.net/uploadedFiles/Departments/OSE/Categories/Landscape/gg_Constr_Costs.pdf

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Estimating the labor requirements for the user’s landscape is a little tricky, since we don't have

labor hours for any of the different plant communities. We use the plant’s water requirement

(the plant factor) as a surrogate for labor. Our thinking is that high-water use plants not only

require more time to water, but may produce more growth, and may require more trimming.

For each plant community, if k ≤ 0.5, then we assign the lower labor factor lj = leff, and if k > 0.5,

we assign higher labor factor lj = lconv. For unvegetated areas such as hardscape or mulch, we

assume that virtually no labor is required, so we assign lj = 0. The total labor required for the

user’s landscape is:

∑

3-8

For the conventional and river-friendly landscapes:

3-9

3-10

3.3 Waste It is hard to accurately calculate the amount of waste produced by different plant types. We

found very little reliable data on the subject. One of the few published studies we found was the

Garden-Garden project (Santa Monica Office of Sustainability and the Environment 2011). Since

we do not have specific numbers for the individual plant community types, we have assumed

that the plant’s water requirements are related to its waste production. We assign high-water

use plants (k > 0.5) to the high-waste category, and low-water use plants (k ≤ 0.5) to the low-

waste category. We estimate waste production for conventional and efficient gardens is:

waste_conv: 0.35 lb/ft²·yr

waste_eff: 0.15 lb/ft²·yr

We assume that land cover types 18, 19, 20 (pond, hardscape, mulch), don't produce waste.

We also account for grasscycling. If the user grasscycles, then the waste production for lawns

will be 15% of conventional. We based our estimate of 85% reduction of waste from lawns

based on input from project partners who note that many landscapers are unable to grasscycle

in wet conditions.

We reduce the user’s waste production if he composts. Limited data are available to quantify

how much garden waste is diverted from the waste stream as a result of composting. This will

depend on a variety of factors, including the size of the compost bin and how frequently it is

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used. Lacking reliable data on any of these factors, we assumed a 25% reduction. In reality,

100% reduction may be possible for enthusiastic composters. Others may only use their

compost bin for kitchen scraps, and will not divert any garden waste.

3.4 Greenhouse Gas Emissions We calculate the greenhouse gas emissions associated with five components related to

landscape maintenance:

1. Water-related emissions. Must urban landscapes in California are irrigated using municipally-supplied water. It takes energy to collect, treat, and deliver water. Thus, by cutting down on water use, you also reduce energy use and this, in turn, reduces GHGs.

2. Lawn Mowing. These emissions are from using either a gas- or electric-powered lawnmower. These emissions are only included if you specified that you have grass. You can cut down on these emissions by reducing the amount of lawn, mowing less often, or switching to a manual, or reel, mower.

3. Waste Hauling. This is based on how much fuel (usually diesel, but sometimes liquified natural gas [LNG]) it takes to transport green waste to where it is either landfilled or picked up by waste-to-energy operators. This quantity depends on the user’s location and on the waste hauler.

4. Fertilizer N2O. Among the active ingredients in most fertilizers is nitrogen, a nutrient that is vital for plant growth. A small amount of the nitrogen in fertilizer can combine with oxygen and enter the atmosphere as nitrogen oxides such as nitrous oxide (N2O), a potent greenhouse gas.

5. Landfill CH4. In Sacramento County, most green waste is used as boiler fuel in waste-to-energy plants or is added to landfills as alternative daily cover. When landfilled green waste breaks down, it releases methane (CH4), a potent greenhouse gas. Modern landfills are equipped with systems that capture up to 85% of the methane that is produced. The captured gas can then be used to generate electricity, in a process called cogeneration.

We present the calculations for each of these below. First, however, we share a few words

about what is and what is not included in our calculation of greenhouse gas emissions.

3.4.1 Calculator Boundary

It is important to be clear and consistent about the analytical boundaries used in a GHG

assessment, i.e., what is and is not included in the analysis. A lifecycle analysis (LCA), for

example, would evaluate the GHG emissions associated with all the stages of a landscape. This

so-called “cradle-to-grave” analysis would include GHG emissions associated with the

manufacturing, use, and eventual disposal of landscape equipment, fertilizers, and even the

vehicle for hauling green waste to a disposal site. Other analyses may focus on a particular part

of the entire lifecycle, such as operations or location. While an LCA approach generally provides

a more complete accounting of the GHG emissions, it can also require considerable time and

financial resources.

20

The Calculator is not based on a full life-cycle assessment. Rather, we analyze the GHG

emissions associated with maintaining landscapes. Specifically, we include emissions associated

with (1) the treatment and delivery of water for irrigation, (2) application of fertilizer, (3) use of

lawn mowers (but not other motorized landscape equipment), (4) green waste transportation

and disposal, and (5) release of methane from landfills, a result of anaerobic decay of green

waste.

Green waste disposal raises a number of unique issues. Plants grow by taking in carbon dioxide

and releasing oxygen. This carbon forms the basis of plant materials, and as this material decays,

it is released back into the atmosphere. In an aerobic environment, this carbon is released as

CO2. This CO2, however, does not contribute to rising atmospheric GHG concentrations. Because

the carbon in plant materials was only recently captured from the atmosphere, release of this

new carbon from the decomposition of plant material has a net climate impact of zero.

However, when green material decays under anaerobic conditions, such as occurs in a landfill, it

releases methane. Because methane is a much more potent GHG than CO2, decomposition

under anaerobic conditions contributes to atmospheric greenhouse gas concentrations. As a

result, the Calculator includes methane emissions associated with green waste disposal in a

landfill.

In some cases, green waste may be used for a beneficial purpose. For example, it may be burned

to produce power or composted to generate fertilizer. Under these circumstances, we no longer

consider the green material to be a “waste” but rather a “product.” Thus, the GHG emissions

associated with its combustion or decomposition of the plant material are attributed to the new

product rather than the disposal of the green material. Similarly, approximately 75% to 85% of

methane from landfills is captured and used to fuel vehicles or generate electricity. As a result,

we assume that only 15% to 25% of the emissions from landfills in the Sacramento region

contribute to atmospheric GHG concentrations.

Furthermore, carbon is stored in plants and soils, in what is termed “sequestration.” Generally,

shrubs and trees contain more carbon than grasses. Large changes to the composition of a

landscape, e.g., from primarily grasses to shrubs and trees, may result in changes in the amount

of carbon stored on the site. However, unless a landscape undergoes a permanent change from

one plant community to another, sequestration is not likely to be permanent. Because of the

uncertainties involved in determining the change in carbon storage when switching from a lawn

to River-Friendly Landscaping, and because the effect is likely to be small, we do not include

carbon stored onsite in plant material and within soil in the Calculator.

3.4.2 Transportation

When a resident puts green waste in a curbside bin, it is picked up by a truck and transported to

a handling facility, such as a landfill, composting facility, or transfer station. The emissions

related to transporting green waste are a function of the distance traveled and the emissions of

the truck. We reason that when residents produce less green waste, trucks make fewer trips,

and emissions are reduced.

21

There are eight locations that serve as destinations for green waste processing for residents of

Sacramento County (Table 5). These are landfills, composting facilities, or other types of

processing stations.

Table 5 Green waste destinations for Sacramento County

ID Address

1 12701 Kiefer Boulevard, Sloughhouse, CA 95683

2 4450 Roseville Road, North Highlands, CA 95660

3 3562 Ramona Avenue, Sacramento, CA 95826-3817

4 8642 Elder Creek Road, Sacramento, CA 95828-1803

5 15500 Willow Creek Road, Plymouth, CA 95669

6 4201 Florin Perkins Road, Sacramento, CA 95826

7 8260 Berry Avenue, Sacramento, CA 95828

8 916 Frewert Road, Lathrop, CA 95330

We determined the average distance to the landfill based on the zip code and the hauler. We

used Google Distance Matrix API4 to get the driving distance from the center of each zip code to

each landfill. This was a useful service, and allowed us to quickly estimate driving distances from

54 zip codes to 8 landfills (a total of 432 possible trips) in less than an hour. Here is an example

of the URL to retrieve driving distances from zip codes in Sacramento County to Valley Organics,

Inc. on Frewert Road in Lathop, California, where Waste Management of Sacramento drops off

green waste:

http://maps.googleapis.com/maps/api/distancematrix/json?origins=94571|95220|956

08|95610|95615|95621|95624|95626|95628|95630|95632|95638|95641|95652|95655|9566

0|95662|95670|95673|95683|95690|95693|95742|95757|95758|95814|95815|95816|95817

|95818|95819|95820|95821|95822|95823|95824|95825|95826|95827|95828|95829|95830|

95831|95832|95833|95834|95835|95836|95837|95838|95841|95842|95843|95864&destina

tions=916+Frewert+Road+Lathrop+CA+95330&sensor=false&units=imperial

The results are a JSON string that look like this:

{

"destination_addresses" : [ "15500 Willow Creek Rd, Plymouth, CA 95669, USA"

],

"origin_addresses" : [

"Rio Vista, CA 94571, USA",

"Acampo, CA 95220, USA",

"Carmichael, CA 95608, USA",

...

"Sacramento, CA 95864, USA"

],

"rows" : [

{

"elements" : [

4 http://code.google.com/apis/maps/documentation/distancematrix/

22

{

"distance" : {

"text" : "62.2 mi",

"value" : 100149

},

"duration" : {

"text" : "1 hour 33 mins",

"value" : 5556

},

"status" : "OK"

}

]

},

These results were easy enough to parse to extract the distance in miles from each zip code to

each landfill.

The result is a table like this one (columns represent the locations in ):

Zip Dist1 Dist2 Dist3 Dist4 Dist5 Dist6 Dist7 Dist8

94571 61.5 56.1 53.7 49.2 62.2 54.5 48 42.6

95220 29.3 37.9 30.1 29.1 30.5 30.7 27.9 28.4

95838 29.2 3.9 17.0 16.4 46.6 17.7 16.5 64.9

…

95842 29.6 6.3 17.4 20.7 47 18.1 20.8 69.5

95843 32.0 6.6 19.8 23.1 49.4 20.6 23.2 71.9

95864 15.0 6.2 5.4 6.8 31.7 4.2 8.3 64.1

We estimated that the round trip is equal to 2.2 times the driving distance from the center of

the zip code area to the landfill. This accounts for making a trip there and back plus some extra

for driving around making pick-ups.

3.4.3 Water use

Emissions related to water supply (associated with embedded energy above).

First, we look up the energy intensity of water for each water supplier. Note that our lookup

table is sparse, because we could not get specific data for most Sacramento-area water

suppliers. Note that we only obtained estimates for energy intensity for 4 out of 26 water

utilities in Sacramento County.

23

Table 6 Energy Intensity for water agencies in Sacramento County

AgencyID Agency Energy Intensity (kWh/af)

5 City of Galt 698

6 City of Sacramento 327

21 Sacramento County Water Agency

605

23 Sacramento Suburban Water District

330

All Others 330

Water-related emissions are:

3-11

Where

k = subscript representing the garden [River Friendly Prototype, User, Conventional]

emb[k] = embedded energy for landscape k

Water[k] =water use for landscape k

kwh_gal = embedded energy (kWh/gal) = Energy Intensity (kWh/af) x 1 af / 325,851 gal

emissions_kwh = Emissions factor for electricity generation in CA = 0.909 lb CO2/kWh

The emissions factor was based on a factor of 0.865 lb CO2/kWh for Sacramento Municipal

Utility District (SMUD, personal communication). We adjusted this factor to takes into account a

grid loss factor of 4.837 % ("Western Grid" loss factor from EPA’s eGRID 2010).

3.4.4 Mowing

Here we estimated the emissions related to mowing grass, from running a lawnmower that

consumes gas or electricity. We only apply this to the two plant communities representing

lawns: low-water use grass and conventional lawn. Table 7 shows emissions factors, in lb CO2

per square foot of lawn per year. We assumed assume that lawns are mowed weekly for 9

months per year (39 times per year). For more details on how we derived these emissions

factors, see the Appendix: Landscape Equipment Use Reduction5.

5 Note that we assume there are no emissions related to using a manual, or reel, mower. This could be

controversial; some analysts have concluded that human power is not free of emissions, because food must be consumed to provide the energy for labor. And, the reasoning goes, our food systems are

24

Table 7 Emission factors for lawnmower types

Mower type Emissions Factor

(lb CO2/ft²·yr)

None 0 Riding mower 0.0132 Gas push mower 0.0175 Electric push mower 0.0154 Manual (reel) mower 0

Note: For data sources see Appendix Tables 1-4.

3.4.5 Fertilizer use

A small amount of the nitrogen in fertilizer can combine with oxygen and enter the atmosphere

as nitrogen oxides such as nitrous oxide (N2O), a potent greenhouse gas. We estimate the

emissions from fertilizer use as 0.00884 lb CO2 per square foot of fertilized landscape per year.

This estimate is based on a calculation in the Greenhouse Gas Emissions Inventory for

Sacramento County by ICF Jones and Stokes (2009). We consider there to be considerable

uncertainty associated with this parameter, as it does not seem to be based on any

experimental observations.

3.4.6 Landfill methane release

After a truck makes a curbside pickup of green waste, where does it go, and what ends up

happening to all those grass clippings and twigs? Tracking down where green waste goes and

determining its ultimate disposition was by far the most difficult part of this project. We made

dozens of phone calls to city administrators, agency staff, and facility managers. Many of the

people we talked to said they don’t know how green waste is handled once it leaves their

facility.

Much green waste is used in landfills as “alternative daily cover” or ADC. Garbage in a landfill is

covered each day with soil to prevent odors and vermin. In recent decades, landfill managers

have begun using composted or raw green waste in lieu of soil. This solves one problem, but

may have inadvertently created another. Organic material in landfills is broken down by

anaerobic bacteria, forming methane gas, which is a potent greenhouse gas. Most modern

landfills in the United States have systems to capture methane. Good systems can capture 70% -

80% of methane that is released in a landfill.

In the Sacramento area, not all green waste is landfilled. Depending on the hauler, it may go to a

facility where it is composted. We consider compost to be a net zero greenhouse gas emitter.

The amount released when the plant matter is fully degraded is equivalent to the amount of

material that was stored in its cells.

particularly large emitters of greenhouse gases. (See for example, “Driving vs. Walking: Cows, Climate Change, and Choice”

5 by Cohen and Heberger, 2008)

25

Here is how we calculate the emissions related to landfilling yard waste. First, we figure out

which facility the hauler goes to. We already know the user’s hauler from earlier calculations.

The actual amount of the emissions will vary, because some facilities do not landfill all waste.

Tables showing the disposition of waste for different haulers and disposal facilities are included

in Appendix B.

The amount of GHG emissions from landfill methane (in lb CO2/year) is calculated as:

meth[k] = waste[k] * emissions_landfill

where emissions_base is the basic rate of emissions from a landfill = 0.0357 lb CO2-eq/lb waste

and percent_landfilled is a function of the disposal facility.

3.5 Cost We calculate the typical costs associated with maintaining the user’s landscape. We do not

include any startup costs, such as purchasing plants. Neither do we calculate a cost for labor.

This is the same as assuming that labor is free (a do-it-yourselfer that does most of his or her

own mowing, weeding), which may not always be the case. We include the following costs:

1. Water

2. Fuel or electricity for mowing

3. Fertilizer

4. Mulch

5. Pesticide

3.5.1 Water

The user’s annual water cost is equivalent to their total water use, multiplied by their average

water rate (in $ per gallon), as shown in Equation 3-11.

[

] [

] [

] [

]

3-12

The user’s water cost is determined based on her water supplier, and whether the user is a

residential or a commercial customer (Table 7). Note that customers who pay a flat rate that

does not depend on consumption have a marginal water rate of zero. This means that saving

water will not result in any cost savings.

26

Table 8 Average marginal water rates by water agency

ID Agency Resi-dential

Com-mercial

Notes

2 Carmichael Water District $0 $0 transitioning to flat rate; Carmichael Water District. Water Rates for Fiscal Year (FY) 2010-2011. http://www.carmichaelwd.org/budget/Water%20Rates%202010-11.pdf

3 Citrus Heights Water District $0.68 Citrus Heights Water District. Water Rates and Miscellaneous Charges and Fees for 2011. http//www.chwd.org/pdfs/CHWD%202011%20Rates%20and%20Charges.pdf

4 City of Folsom Water District $0 $0 metered rates will begin in 2012

6 City of Sacramento $0 $0 flat rate

10 Elk Grove Water Service $1.46 $1.46 Elk Grove Water District. Schedule of Charges, Rates, Fees, and Deposits. Effective July 1, 2009. http://www.egws.org/waterrates.html

11 Fair Oaks Water District $0 $0 flat rate

18 Orangevale Water $0.50 $0.59

20 Rio Linda Elverta Water District

$- $- Rio Linda Elverta Water District. Current Billing Information. Effective January 1, 2011. http://www.rlecwd.com/view/95

23 Sacramento Suburban Water District

$0.80 $0.81

24 San Juan Water District $0.44 $0.63 San Juan Water District. Customer Service: Current Rates. As of January 1, 2011. http://www.sjwd.org/Rates-And-Fees.html

3.5.2 Fuel to run the mower

We look up the average cost to run different kinds of mowers, expressed in dollars per square

foot of lawn per year (Table 9). For more details on how we derived these cost factors, see the

Appendix: Landscape Equipment Use Reduction.

Table 9 Operating cost for lawnmowers

Mower type Operating Cost ($/ft²·yr)

None 0 Riding mower 0.0132 Gas push mower 0.0175 Electric push mower 0.0154 Manual (reel) mower 0

Electricity to run the user’s smart controller, if they have one, is considered negligible (probably

less than a few dollars per year), and is not included in the model.

3.5.3 Fertilizer

We chose to keep the inputs related to fertilizer use simple. For each plant zone (up to 10 per

landscape), As such, these calculations are ballpark approximations.

27

fertilizer expense ($/sq. ft.) = fertilizer_applied / 1000 * cost_per_pound

where Fertilizer_applied (lb per 1,000 sq. ft) is look up function based on plant type (see Table

3), and cost_per_pound = $4.75.

3.5.4 Mulch

If the user indicates that she applies mulch, we add an expense to replace that mulch. We

assume that mulch lasts for three years, and the expense is spread out over each year. (In the

authors experience, certain mulches such as shredded redwood bark, or gorilla hair, barely last

for a year, while wood chips or bark nuggets may last for several years.) In other words, we

calculate the expense of replacing 1/3 of the mulch each year. Not all land cover types require

mulching, for example lawns. Table 3, which lists the 21 plant communities in the calculator,

shows which ones take mulch. We calculate the volume of mulch needed (in cubic yards) to

apply 3" deep (1/4 ft) over the mulchable area as follows:

mulch_volume = 0.25 * area_mulchable / 27

We estimate the cost of mulch as $25 per cubic yard, based on brief internet research, visiting

the websites of local vendors. Many vendors offer several grades of mulch; we selected the

cheapest sort: bulk wood chips.

For the RFL prototype garden, we assume that the entire area is mulched, other than the small

lawn. Our prototype conventional garden is mulched, but not as heavily (2” instead of 3”).

3.5.5 Pesticides

If the users checks one of the options that indicates that he uses pesticides in the garden, a cost

will be added to the annual expense. We estimate the cost of applying pesticides as $0.025 per

square foot per year based on recommended application rates, and average costs. More

information on how we derived this and other values is in the Appendix:

3.6 Qualifying for River-Friendly Recognition Based on user responses, the Calculator will invite users whose landscapes meet certain criteria

will be invited to join the River Friendly Landscaping Recognition Program. The criteria are as

follows:

The landscape’s waste production must be less than 150% that of a River Friendly landscape.

The landscape’s water use must be less than 150% that of a River Friendly landscape. The landscape’s greenhouse gas emissions must be less than 150% that of a River

Friendly landscape. For pesticide use, the user must check either “non-toxic or organic alternatives” or

“None.” The landscape must be at least 50% vegetated.

28

The last criterion was inserted to prevent users from qualifying by entering a large area covered

by hardscape or mulch.

4 Software The River-Friendly Landscaping Calculator is open-source software. We invite efforts to re-use or

modify our code. In this section, we give a few details about the technologies we used to create

the site. The source code can be viewed or downloaded for free at

http://code.google.com/p/landscape-calculator/.

We used the Python-based web framework Django for serving content and for managing user

authentication. Information is stored securely on our server in a PostgreSQL database.

We set up the main calculator so that it is a single page (instead of having the user navigate between different pages to enter information and view results.) The advantage of this approach is that there are no page loads as you are working. There are some bits of information that are contained in the server-side database (for example, when the user clicks “Save” to store his landscape’s information). In this case, information is retrieved via AJAX and loaded to the page by making changes to the html document. This is the way many, many modern web applications work, for example Gmail. We also aimed to do all of the calculations on the client side, i.e. in the browser. This makes for a faster, more interactive user experience. Calculations and control of the page are all done using the javascript language. We made extensive use of jQuery, a javascript framework, and a number of jQuery plugins. If you are thinking of adapting or reusing the site’s code, it would be a good idea to download the latest versions of these scripts, so that you’ll have the latest enhancements and bug fixes. Here is some information on the external libraries I’ve made use of: jQuery version 1.6.4

http://jquery.com/

jQuery UI For creating a number of interactive elements on the page (form autocomplete, tabbed displays, dialog boxes, etc.) http://jqueryui.com/ version 1.8.17 downloaded 6-26-2011 jQuery UI theme a set of CSS files and images that goes with jQuery UI We use a slightly modified version of the theme called “South Street” http://jqueryui.com/themeroller/ jQplot For rendering graphs in the browser

29

http://www.jqplot.com/ Version 1.0.0b2 Downloaded 6-26-2011 Validation for doing form validation (e.g. making sure the user entered information properly) http://docs.jquery.com/Plugins/Validation version 1.8.1 downloaded 6-27-2011 Numeric makes input fields so that the user can only enter numbers (no letters) http://www.texotela.co.uk/code/jquery/numeric/ version 1.3, dated 5/8/11 downloaded 6-27-2011 Duplicate I used this to help create the pictogram on the “How Do I Compare?” tab. http://jqueryminute.com/duplicate-and-clone-elements-multiple-times/ Cookie Used to easily manage cookies using jQuery. http://archive.plugins.jquery.com/project/Cookie Tooltip Shows some additional help text shown in little tooltips that are visible when the user mouses over certain text or links. http://bassistance.de/jquery-plugins/jquery-plugin-tooltip/ JKey Capture keypresses via jQuery. Allows us to use Ctrl + S as a shortcut for save. Minified Javascript Some of the javascript files on the website have been minified to make them smaller and faster

to download. This strips out the line breaks, indentation, and comments from the files, which

makes them hard to read. We used the Online JavaScript/CSS Compression Using YUI

Compressor at http://www.refresh-sf.com/yui/. This tool also “obfuscates” code by replacing

variable names with short strings like a, b, c, etc. You can view the original un-obfuscated source

files at the Google Code project hosting site.

30

Figure 8 Javascript source code (left) and minified version (right).

5 References University of California Cooperative Extension, 2000. A Guide to Estimating Irrigation Water

Needs of Landscape Plantings in California. Sacramento, California: University of California

Cooperative Extension California Department of Water Resources.

http://www.water.ca.gov/wateruseefficiency/docs/wucols00.pdf.

Brouwer, C., K. Prins, and M. Heibloem, 1989. Irrigation Water Management: Irrigation

Scheduling. FAO Training Manual No. 4. http://www.fao.org/docrep/T7202E/T7202E00.htm

California Air Resources Board, California Climate Action Registry, ICLEI - Local Governments for

Sustainability, and the Climate Registry. (2010). Local Government Operations Protocol For

the quantification and reporting of greenhouse gas emissions inventories, Version 1.1. Table

G.11. http://www.theclimateregistry.org/downloads/2010/05/2010-05-06-LGO-1.1.pdf

Cohen, M. and M. Heberger, 2008. “Driving vs. Walking: Cows, Climate Change, and Choice,”

http://www.pacinst.org/topics/integrity_of_science/case_studies/driving_vs_walking.html

DeOreo, William B., Peter W. Mayer, Leslie Martien, Matthew Hayden, Andrew Funk, Michael

Kramer-Duffield, Renee Davis, et al. California Single-Family Water Use Efficiency Study.

Sacramento, California: California Department of Water Resources/U.S. Bureau of

Reclamation CalFed Bay-Delta Program, July 2011.

http://www.aquacraft.com/sites/default/files/pub/DeOreo-%282011%29-California-Single-

Family-Water-Use-Efficiency-Study.pdf.

DWR 2009. “ET Overview.” California Department of Water Resources.

http://www.cimis.water.ca.gov/cimis/infoEtoOverview.jsp

ENERGY STAR Performance Ratings Methodology for Incorporating Source Energy Use.

Retrieved July 21, 2011 from

http://www.energystar.gov/ia/business/evaluate_performance/site_source.pdf

31

EPA. (2005). Emission Facts: Calculating Emissions of Greenhouse Gases: Key Facts and Figures.

Retrieved July 21, 2011 from http://www.epa.gov/otaq/climate/420f05003.htm#average.

Environmental Protection Agency (EPA). eGRID2010 Version 1.0 Year 2007 Summary Tables;

http://www.epa.gov/cleanenergy/documents/egridzips/eGRID2010V1_0_year07_Summary

Tables.pdf, 2011.

Kahrl, William L., ed. The California Water Atlas. First ed. Sacramento, California: Governor’s

Office of Planning and Research and the California Department of Water Resources, 1979.

http://www.davidrumsey.com/luna/servlet/detail/RUMSEY~8~1~203540~3001703:The-

California-Water-Atlas-.

PRISM 2010. Digital datasets downloaded from http://prism.oregonstate.edu/.

Santa Monica Office of Sustainability and the Environment. “Garden-Garden”, July 21, 2011.

http://www.smgov.net/Departments/OSE/Categories/Landscape/Garden-Garden.aspx.

32

6 About the Pacific Institute The Pacific Institute is an independent, non-profit research and policy organization founded in

1987. The Institute has been a leader in work on a wide range of water science and policy issues.

The Pacific Institute works closely with water, wastewater, and stormwater utilities in the U.S.

and abroad to better understand, and adapt to, the hydrologic impacts of climate change. The

Institute’s work reaches large and diverse audiences from water professionals and utility

managers, to scientists, policy makers, and the general public. Its websites draw over 15 million

hits a year and individual reports have been downloaded in excess of 300,000 times. In the past

year alone, the impact of the Institute’s work was acknowledged by the Environmental

Protection Agency’s Award for “Environmental Achievement,” the AWRA “Csallany Award” for

exemplary contributions to water resources, the U.S. Department of the Interior’s “Partners in

Conservation” Award from Secretary Salazar, and a Global Water Intelligence Award for

“Environmental Contribution of the Year.”