RMRS-GTR-295 

Vulnerability of U.S. Water Supply to Shortage: A Technical Document Supporting the 

Forest Service 2010 RPA Assessment

Appendices

Online: http://www.fs.fed.us/rm/pubs/rmrs_gtr295.html
Appendix A: Detailed Methods for Projecting Water Use

Future consumptive water use (C) was projected by estimating future withdrawal (W), 

multiplying that withdrawal by a consumptive use rate (γ), and then adding the change in 

consumptive use attributable to future changes not captured by extrapolating past trends in 

withdrawals (ΔC): 

CW C = ⋅ +Δ γ (A1)

Withdrawal is computed as the product of a water demand unit (also called a water use driver) (U) 

and an estimate of withdrawal per demand unit (Φ). For example, a water use driver could be a 

person for domestic use or an irrigated acre for agricultural use; corresponding withdrawal rates 

would be withdrawal per person and withdrawal per acre, respectively. 

Estimates of withdrawal rates (Φ) are developed by extrapolation of past trends. Past trends 

in the rates of water withdrawal (Φ) in most cases have been nonlinear, with the rate of change 

gradually diminishing. Extrapolation of past trends in Φ was accomplished by applying an annual 

growth rate (g) based on data from recent years and a corresponding decay in that growth rate (d). 

The decay rate was chosen to attenuate the trend, leading gradually toward a hypothesized 

equilibrium level. Given a five-year time step for projecting withdrawals, the extrapolation procedure 

for a given year (Y) and Water Resource Region (WRR) is as follows: 

( ) ( )

5

, ,5 1 1 Y LDY

WRR Y WRR Y DIV DIV g d −

Φ =Φ + + − (A2)

where LDY is the last year for which withdrawal data were available (typically 2005), and DIV is a 

major division of the United States, either the eastern or western portion. g and d typically were 

computed for major divisions rather than for each WRR because past trends for individual WRRs, as 

estimated using withdrawal data from the USGS circulars, were somewhat erratic. The annual growth 

factor (g) was computed from all or part of the record from 1985 to 2005. 

Estimates of water withdrawal and consumptive use are computed for all ASRs, but the 

factors used to produce those estimates (e.g., Φ or γ) are typically estimated at a larger spatial scale 

because the data for Assessment Sub-regions (ASRs) are sometimes erratic—perhaps because of 

annual weather fluctuations or errors in estimation—so that they do not appear to support 

estimation at the smaller scale. Factors Φ and γ are estimated by WRR and applied to ASRs within the 

WRR. Similarly, g and d are estimated for eastern (specified as WRRs 1-9) and western (WRRs 10-18) 

divisions of the United States and typically applied to all ASRs within the division. 

Domestic and public withdrawals and, to some extent, industrial and commercial withdrawals 

are distributed spatially with population, allowing use of census tract data for carefully apportioning 

county data to ASRs. Withdrawals in the thermoelectric, agricultural irrigation, and livestock and 

aquaculture sectors, however, are not distributed spatially with population, thus requiring a different 

procedure for allocating county-level withdrawal estimates to ASRs. Lacking data on the actual 

locations of thermoelectric plants, irrigated fields, or livestock and aquaculture operations, county 

data were apportioned to ASRs by assignment of whole counties to ASRs based on which ASR 

contained a greater amount of the county. 

Domestic and Public (DP) Water Use

Consumptive water use (C) in the DP sector (CDP) in gallon-days (gallons per day for a year) in 

future year Y was computed by ASR as: 

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 1
, , , ,1990 95 ,

DP DP DP DP C C ASR Y ASR Y WRR Y WRR = ⋅Φ ⋅ +Δ ρ γ − ASR Y (A3)

where ρ ASR Y, is population (as computed in equation 5.5), DP ΦWRR is withdrawal in gallons per capita 

per day for DP uses in the WRR to which the ASR belongs, DP

WRR γ is a consumptive use proportion of 

withdrawal for DP uses in the corresponding WRR based on an average of the proportions for 1990 

and 1995 (the last two years for which the USGS provided estimates), and ΔCDP is the change in 

consumptive use attributable to climate change. 

ΦDP for future years was computed by extrapolation of past trends as follows (see equation 

A2, which is identical to equation 5.3): 

( ) ( )

5

, ,5 1 1 DP DP Y LDY

WRR Y WRR Y DIV DIV g d −

Φ =Φ + + − (A4)

where LDY is 2005 and g and d are as listed in Table 5.8. ΦDP for past years, providing the basis for 

computation of g, was computed as: 

,

,

,

DP

DP WRR Y

WRR Y

WRR Y

W

ρ

Φ = (A5)

where WDP is withdrawal for DP uses. 

The change in consumptive use attributable to climate change was computed as: 

2 ,' , ,

, ,, ,

DP DP P DP ETp DP CO Δ =Δ +Δ +Δ CCC C ASR Y ASR Y ASR Y ASR Y (A6)

where the three terms are as specified in equations 5.15, 5.17, and 5.18. 

Industrial and Commercial (IC) Water Use

Consumptive use in the IC sector (CIC) in gallon-days for future year Y was computed by ASR 

as: 

, , , ,1990 95 , / 365 IC IC IC IC C I ASR Y ASR Y WRR Y WRR CASR Y γ = ⋅Φ ⋅ +Δ − (A7)

where I is total annual personal income in 2006 dollars, ΦIC is withdrawal in gallons per day for IC 

uses per $1000 of annual personal income in the corresponding WRR, IC

WRR γ is a consumptive use 

proportion of withdrawal for IC uses in the corresponding WRR based on an average of the 

proportions for 1990 and 1995, and ΔCIC is the change in consumptive use attributable to meeting the 

renewable fuel standard goals (from equation 5.7). 

Future personal income by ASR was estimated using county-level population data to spatially 

distribute nationwide estimates of future income. Future county-level estimates of I were computed 

from national estimates of future I for the three scenarios, while accounting for projected changes in 

relative population among counties, as follows: 

,2005

, ,,

, ,2005

j

j Y j Y US Y

jY j

j

I

I I

P I

ρ

ρ = ⋅ ρ  ⋅   

 (A8)

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 2
where j indicates a county and Iρ is income per person. These estimates, as well as county-level I for 

2000 and 2005 from BEA, were then allocated to ASRs using the 2000 census tract-based allocation 

of county population to ASRs as follows: 

ASR Y, j Y ASR j , , ,2000

j

I Iz = ⋅     (A9)

where zASR,j,2000 is the proportion of a county’s population in the ASR in year 2000. 

ΦIC was computed for future years by extrapolation of past trends following the procedure of 

equation A2 where LDY is 2005 and g and d are as listed in Table 5.8. ΦIC for past years was 

computed as: 

,

,

,

IC

IC WRR Y

WRR Y

WRR Y

W

I

Φ = (A10) 

where WIC is withdrawal for IC uses. 

Thermoelectric Fresh (TF) Water Use

Computation of future water use at fresh water thermoelectric plants (CTF) must acknowledge 

that electric energy consumed in one ASR may be produced in another ASR, and that electric energy 

is produced at not only fresh water thermoelectric plants but also at salt water thermoelectric, 

hydroelectric, solar, wind, and other types of plants. In light of these facts, the basic approach adopted 

here can be characterized as requiring the following four steps: 

(1) estimate total energy produced in the United States, 

(2) allocate the national electricity production to the ASRs, 

(3) determine the proportion of that energy that is produced at fresh water thermoelectric 

plants in the ASR, and 

(4) apply an estimate of withdrawal per unit of electricity produced to the estimate of energy 

produced. 

Step 1 was accomplished by multiplying population by Energy Information Administration 

(EIA) estimates of future electric energy consumed per person in the United States, under that 

assumption that production equals consumption at the national scale. Step 2 was based on the 

location of past production capability, on the assumption that future thermoelectric production 

capacity would be located proportional to recent past capacity. Step 3 was accomplished by first 

subtracting non-thermoelectric electricity production from total production and then apportioning 

thermoelectric production among fresh and salt water plants assuming that the recent ratio of fresh 

water thermoelectric production to total thermoelectric production remains constant into the future 

(i.e., that growth in production occurs at fresh and salt water plants in proportion to recent past 

allocation between the two types of thermal plants). Information from the EIA was used to estimate 

future non-thermoelectric energy production. Step 4, regarding water use at thermoelectric plants, 

was accomplished using USGS water use data. Because USGS thermoelectric energy production data 

did not distinguish between these two kinds of thermoelectric plants, we assumed that electricity 

produced per gallon of water withdrawn at salt water plants is identical to production per gallon at 

fresh water plants.

Water withdrawal and consumptive use at fresh water thermoelectric plants was estimated at 

the WRR level because ASRs were considered to be too small for modeling future electricity 

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 3
production (as production is not so spatially connected to demand that future changes in demand are 

all met by changes in production within the same ASR). The water use in an ASR was then estimated 

as a proportion of the WRR water use based on the proportion of the withdrawal of the WRR that 

occurred in the ASR in 1995, the last year for which we have accurate water basin data from the 

USGS. 

In more detail (and ordering the procedural steps differently for the purpose of presentation), 

consumptive water use at fresh water thermoelectric plants (CTF) for future year Y in gallon-days is 

computed by WRR as: 

, ( ) , , ,1990 95 , / 365 TF TF TF TF TF C E WRR Y WRR Y WRR Y WRR CASR Y γ = ⋅Φ ⋅ +Δ − (A11) 

where ETF is electric energy produced as fresh water thermoelectric plants (measured in kilowatt 

hours, kWh), TF ΦWRR is withdrawal per kWh at fresh water thermoelectric plants in the corresponding 

WRR based on an average of the 1990 and 1995 proportions, ,

TF

WRR Y γ is a consumptive use proportion 

of withdrawal for IC uses in the corresponding WRR based on an average of the proportions for 1990 

and 1995, and ΔCTF is the change in consumptive use attributable to climate change (see equation 

5.22). 

TF EWRR of equation A11 (thus, for future years) was estimated as a proportion of total thermal 

production T EWRR based on USGS data for 2005 on the breakdown between salt and fresh water 

production: 

,2005

, ,

,2005

TF

TF T WRR

WRR Y WRR Y T

WRR

E

E E

E = ⋅ (A12) 

T EWRR was estimated by subtracting non-thermoelectric energy from total electric energy 

production as follows: 

, ,,,

T HA E EEE WRR Y WRR Y WRR Y WRR Y =−− (A13) 

where EWRR is total electricity production, H EWRR is hydroelectric energy production, and A EWRR is 

other (alternative source) electricity production.1 EWRR of equation A13 was estimated from 

population and energy production per capita as: 

E E WRR Y WRR Y WRR Y , ,,

ρ = ⋅ ρ (A14) 

where ρ is population and Eρ is electric energy production per capita, which was assumed to remain 

constant at the year 2005 level taken from Kenny and others (2009). The assumption of a constant 

level of per-capita electricity use was based on the EIA projections, which show little change in percapita use through year 2035 (EIA 2010: Tables 8 and 20). H EWRR of equation A13 was estimated for 

years 2010 to 2035 by apportioning the EIA U.S. total hydroelectric energy projections (EIA 2010: 

Table 16) to ASRs based on the 1995 apportionment (the USGS circular did not report hydroelectric 

energy production after 1995) as follows: 

 

1 We took electric energy production and water use data from the USGS, rather than going directly to the EIA 

from which the USGS obtained much of its data, because the USGS data include some small plants not included 

in the EIA data and because we could not account for differences between the two databases that could not be 

explained by the inclusion of small plants. 

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 4
,1995

, ,

,1995

H

H H ASR

WRR Y US Y H

US

E

E E

E = ⋅ (A15) 

For years beyond 2035, H EWRR was assumed to remain at the 2035 level.2 A EWRR of equation A13 

was estimated for years 2010 to 2035 by apportioning the EIA U.S. total for electricity projection 

from wind, solar, geothermal, municipal waste, wood and other biomass sources ( A EUS ) (EIA 2010: 

Table 16) to ASRs based on the 1995 apportionment of total thermal generation, as follows: 

,1995

, ,

,1995

T

A A ASR

WRR Y US Y T

US

E

E E

E = (A14) 

For years beyond 2035, A EWRR was computed by extrapolation of past trends using equation A2 

with LDY equal to 2035 based on the projected growth from 2015 to 2035.3 

TF ΦWRR of equation A11 was computed by extrapolation of past trends as in equation A2 with 

LDY equal to 2005. To allow this extrapolation, TF ΦWRR for past years (1985-2005)4 was computed as: 

,

,

,

TF

TF WRR Y

WRR Y TF

WRR Y

W

E

Φ = (A17) 

where WTF is fresh water withdrawal from the USGS circulars and ETF was computed as a portion of ET

based on USGS withdrawal data as follows:5 

,

, ,

,

TF

TF T WRR Y

WRR Y WRR Y T

WRR Y

W

E E

W = ⋅ (A18) 

Finally, as previously mentioned, the WRR values are apportioned to their respective ASRs as 

follows: 

,1995

, ,

,1995

TF

TF TF ASR

ASR Y WRR Y TF

WRR

W

C C

W = ⋅ (A19) 

 

2 These estimates ignore the possibility of developing hydrokinetic energy (wave, tidal, ocean current, and river 

kinetic energy). Current projections of hydrokinetic energy production would be very uncertain. Much of the 

potential for hydrokinetic energy is located in Alaska and thus is outside of our study area (Bedard and others 

2009). Assuming, as did Bedard and others, that 15% of the available kinetic energy can be developed and 

assuming a 90% efficiency rate, we estimate that the potential is about 84,000 GWh, or about 2% of projected 

electricity consumption in 2030. Apparently, including this source of electricity in our estimates would have 

only a small impact on water use. 

3 There is thought to be tremendous potential for developing offshore wind energy. Musial (2008) estimated 

that potential to be 3948 TWh per year, which is about equal to the total current electricity use of the United 

States. Much of this potential is in Alaska, and there are other issues of transmission from the coasts, but the 

potential in the lower 48 states remains large. Very little of this potential—only 0.34% of projected total wind 

energy generation in 2035—is included in the EIA projections incorporated here. 4 Excepting year 2000 when the USGS did not provide estimates of electricity production for its corresponding 

estimates of thermoelectric withdrawal. Linear interpolation was used to fill in this missing year based on the 

values for 1995 and 2005. 

5 WTF includes both self-supplied withdrawals and deliveries from public supplies. 

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 5
Irrigation (IR)

Consumptive water use in the IR sector (CIR) for future year Y in gallon-days was computed by 

ASR as: 

,

, , , , ,1990 95

IR

IR IR IR ASR Y

ASR Y ASR Y gross ASR Y WRR

C

C A γ α β −

    Δ

= Φ⋅ +    

   

(A20) 

where A is irrigated acres, IR Φgross is irrigation withdrawal in feet of depth, IR

WRR γ is a consumptive use 

proportion of withdrawal for IR uses in the corresponding WRR based on an average of the 

proportions for 1990 and 1995, ΔCIR is the change in consumptive use attributable to climate change 

(from equation 5.11), β is 30.5 (the number of centimeters per foot), and α is 893 (for converting 

from acre-feet to gallon-days). AASR of equation A21 is computed by allocating acres within the WRR 

as follows: 

,1995

, , ,

,1995

ASR RFS

ASR Y WRR Y ASR Y

WRR

A

AA A

A

=⋅ + (A21) 

where AWRR,Y for future years is computed by extrapolation of past trends using equation A2 where 

LDY is 2005 (for 2010, the mean of 2000 and 2005 was used as the base year), and RFS AASR is the 

increase in acres attributable to meeting the renewable fuel standard goals (see equation 5.8). AWRR,Y 

for past years was taken from USGS water use circulars. The year 1995 was used for the 

apportionment to ASRs because it is the last year the USGS provided estimates by basin.6 

,

IR Φgross ASR , withdrawal for IR uses per irrigated acre in equation 5.10, was computed for future 

years by extrapolation of past trends at the WRR level using equation A2 where LDY is 2005 and g

and d are as listed in Table 5.8, as follows: 

,, , ,

IR IR Φ =Φ gross ASR Y gross WRR Y (A22) 

,

IR Φgross WRR for past years was computed as: 

,

, ,

,

IR

IR WRR Y

gross WRR Y

WRR Y

W

A

Φ = (A23) 

where WIR is withdrawal for IR uses. 7

Livestock (LS) and Aquaculture (AQ) Water Use

The USGS’ estimates of livestock (farm animals and feedlots) water use go back to 1960. 

Aquaculture was added to the livestock category in 1985. Beginning in 1990, the fast-growing 

 

6 The USGS acreage from the 2005 circular could have been used by allocating county acreage data to ASRs. The 

loss of accuracy in that allocation was considered a greater problem than using the earlier (1995) data. 7 The USGS estimates of irrigated acreage account for double cropping by counting a double-cropped acre twice 

(the same approach is used for triple cropping). By using the extrapolation approach described here, we are 

assuming that the proportion of acres that are double cropped in a given WRR will not change in the future, 

which may be unrealistic if temperature increases with climate change make double cropping more prevalent 

in some ASRs. 

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 6
aquaculture category was reported separately from livestock. We report results for only the 1990 to 

2005 period. 

Two facts complicate the projection of livestock and aquaculture withdrawals. First, these 

categories consist of water use by several different animal species and kinds of aquaculture 

operations, and site-specific data on numbers of animals or acres of fish farms are not easily obtained. 

Without accounting for numbers of livestock animal units by species (on the range and then in 

feedlots and other confined areas) and acres of fish farm, there is no obvious summary unit of 

production. Second, livestock products are often not consumed where they are produced, so future 

changes in ASR livestock withdrawals will not be proportional to changes in basin population. 

For projecting future water withdrawals, the first fact (lack of data on demand units) was 

accommodated by basing future withdrawals not on numbers of animals or acres of fish ponds but 

rather on human population, as humans are the consumers of livestock products. The second fact 

(spatial mismatch between production and consumption) was accommodated by computing total 

livestock withdrawal for the WRR and then apportioning that total to individual ASRs based on the 

location of past 2005 withdrawals at the county level, under the assumption that the future annual 

rate of growth in withdrawal will be the same in all counties. 

The approach followed to project future livestock withdrawals, then, was to estimate 

withdrawals for the United States as a whole and then apportion those withdrawals to counties (and 

then to ASRs) based on county withdrawals for years 1985-2000. Water use for livestock (CLS) for 

future year Y is computed by ASR as: 

, , , ,2005 ,1995

LS LS LS LS CASR Y WRR Y WRR Y ASR WRR = ⋅Φ ⋅ ⋅ ρ τγ (A24) 

where ,

LS CASR Y is consumptive use for livestock purposes in year Y, ,LS ΦWRR Y is withdrawal per person in 

the WRR to which the ASR belongs, ,

LS

ASR Y τ is the proportion of the withdrawal of the WRR in 2005 that 

occurred in the ASR, and ,1995

LS

WRR γ is the consumptive use proportion of the WRR in 1995. τ was 

computed from county withdrawal data for 2005, which each county assigned to the area-dominant 

ASR of the county. ΦLS was computed for future years by extrapolation of past trends following the 

procedure of equation A2 with LDY = 2005 and g and d as listed in Table 5.8, with the base for 

computing 2010 withdrawal a weighted average of the 2000 and 2005 withdrawals, with weights of 

0.25 and 0.75, respectively. ΦLS for past years was computed as: 

,

,

,

LS

LS WRR Y

WRR Y

WRR Y

W

ρ

Φ = (A25) 

where WLS is withdrawal for livestock purposes. 

For aquaculture, equations A24 and A25 also apply, replacing LS with AQ. 

 

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 7
Appendix B: Monthly Breakdown of Annual PublicSupplied Water Deliveries

Comprehensive water use data that would be used to estimate water demand, such as the 

water use data provided by the USGS circulars, typically have been compiled at the annual time step. 

However, levels of some water uses, such as irrigation, vary temporarily during the year. The monthly 

variation in annual public supply deliveries was needed to help estimate the effect of future climate 

change on domestic and public water use. 

Lacking a centralized database of monthly water use, we contacted individual cities (or water 

companies serving cities, which are considered “cities” herein for the sake of brevity) across the 

United States and requested monthly water delivery data for recent years (we accepted monthly 

withdrawal data if delivery data were not available). We attempted to obtain data from at least one 

city in each of the 204 four-digit basins in the contiguous 48 states (the four-digit basins are a 

standard hydrologic division supported by the USGS). Cities of at least 10,000 persons were favored, 

but in less populated regions, we contacted cities with at least 2500 people. Nearly all of the monthly 

water delivery data are for one or more years during the period 2000 to 2006, but a few are for years 

during the 1990s. The process of obtaining municipal data in many cases required repeated efforts to 

gain the assistance of city officials familiar with their water delivery data. In all, we obtained data on 

10,433 months of water use from 238 cities, for an average of 44 months of data per city. 

City data were averaged for ASRs and WRRs. The procedure we used for summarizing the city 

data is as follows: 

(1) Remove any city without at least one estimate for each month (this step resulted in loss of 

two cities). 

(2) For each remaining city, use all available data to compute monthly proportions by first 

computing average delivery for each month and then computing proportions from the 

monthly averages. 

(3) Remove a city if the monthly proportions appear to be in error (this step resulted in loss of 

four cities). 

(4) Compute simple average proportions for all remaining cities within a given ASR or WRR. 

(5) Use cluster analysis with the ASR averages to define a small set of clusters of monthly 

proportions (cluster analyses were performed using the K-means cluster analysis routine of 

SPSS, which allows the user to specify the number of clusters desired). We limited the number 

of clusters by restricting cluster size to five or more ASRs. 

After removing six cities from the database for reasons explained above, 232 useable cities 

remained, representing 91 ASRs. 

Table B1 lists the monthly percentages by ASR and the number of four-digit basins and cities 

representing each of the ASRs. The average and median numbers of cities per ASR are 2.5 and 2. 

Table B2 lists the monthly percentages for four clusters of ASRs, and Figure B1 shows the 

locations of the clusters. Cluster 3 contains 45 ASRs, represented by 106 cities, located largely in the 

eastern half of the country. Cluster 2 contains 16 ASRs, represented by 41 cities, covering roughly the 

northern two-thirds of the West, except the West Coast. Cluster 1 contains 25 ASRs, represented by 

72 cities, located in the Great Plains, Southwest, and along the West Coast. Finally, cluster 4 contains 5 

basins, represented by 13 cities, 2 in the upper Great Basin, 1 in northern California, and 2 in the 

headwaters of the Missouri Basin. 

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 8
The monthly percentages of the clusters of Table B2 are plotted in Figure B2. The eastern 

cluster (number 3) shows the least temporal variation. The next most evenly distributed cluster (1) 

represents a mixture of climates. Here, the weather is either generally drier than in the East, 

requiring more landscape irrigation whenever the temperatures warrant it (the Great Plains and 

Southwest) or rainfall is less evenly distributed over the year then the East (as along the upper West 

Coast). The two clusters showing the highest temporal variation are located in the more northern dry 

parts of the West, one (cluster 2) with a maximum use in July and the other smaller group (cluster 4) 

with a maximum use in August. 

Table B3 lists the monthly percentages of annual water use for the 18 WRRs and the number 

of four-digit basins and cities representing each of the WRRs. The WRRs are made up of from 3 (WRR 

9) to 26 (WRR 10) four-digit basins. The overall difference in monthly distribution between the 

eastern and western portions of the country is seen by comparing Figures B3 and B4. 

References 

Bedard, Roger J.; Previsic, Mirko; Polagye, Brian L. 2009. Marine energy: how much development 

potential is there? Hydro Review 28(4). 

EIA. 2010. Annual energy outlook 2010. DOE/EIA-0383(2010). Washington, DC: Energy Information 

Administration, U.S. Department of Energy. 

Kenny, Joan F.; Barber, Nancy L.; Hutson, Susan S.; Linsey, Kristin S.; Lovelace, John K.; Maupin, Molly 

A. 2009. Estimated use of water in the United States in 2005. Circular 1344. Reston, VA: U.S. 

Geological Survey. 

Musial, W. 2008. Status of wave and tidal power technologies for the United States. Technical Report 

NREL/TP-500-43240: National Renewable Energy Lab. 

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 9
Figure B1. Location of four clusters of ASRs for Table B2. 

Figure B2. Monthly distribution of annual municipal water delivery for four clusters of 

ASRs (see Table B2). 

4 clusters of ASRs

2

4

6

8

10

12

14

16

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Percent

C1

C2

C3

C4

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 10
Figure B3. Monthly distribution of annual municipal water delivery for eastern WRRs (see Table B3). 

Figure B4. Monthly distribution of annual municipal water delivery for western WRRs (see Table B3). 

 

East (WRRs 1-9)

2

4

6

8

10

12

14

16

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Percent

1

2

3

4

5

6

7

8

9

West (WRRs 10-18)

2

4

6

8

10

12

14

16

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Percent

10

11

12

13

14

15

16

17

18

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 11
Table B1. Monthly distribution of annual municipal water delivery for ASRs. 

ASR No. of 

basins 

No. 

of 

cities 

Percent 

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 

101 4 4 8.7 7.8 8.3 8.0 8.2 8.5 8.9 9.4 8.2 8.2 7.8 8.0

102 2 2 7.2 6.9 7.2 7.5 8.0 9.7 10.5 10.8 9.7 8.1 7.3 7.2

103 1 1 7.5 7.6 7.5 7.6 7.7 9.4 9.9 10.6 9.9 7.8 7.4 7.3

104 1 1 7.8 7.1 7.4 7.3 8.5 9.2 10.5 10.2 8.9 8.2 7.4 7.5

105 1 1 8.0 7.2 8.1 7.9 8.4 8.7 10.1 10.4 8.4 8.0 7.4 7.4

106 0 0 

201 1 1 8.5 8.4 8.9 8.0 8.3 8.5 8.3 9.0 7.9 8.1 8.0 8.1

202 0 0 

203 1 1 9.9 8.1 7.9 7.6 7.7 7.9 9.4 8.2 8.1 9.1 8.1 8.0

204 1 1 8.1 8.8 7.6 8.3 8.0 8.4 9.0 8.9 9.1 8.1 7.7 8.0

205 2 5 7.9 7.2 7.9 7.8 9.0 9.0 9.0 9.7 8.4 8.3 7.9 7.8

206 1 1 8.4 8.0 8.3 8.2 8.6 8.6 8.8 8.9 8.4 8.2 7.4 8.1

207 1 1 7.6 6.8 8.5 6.6 6.6 8.8 7.9 9.4 10.9 8.4 8.8 9.7

301 3 3 7.9 7.1 7.9 7.8 8.5 8.7 9.2 9.6 9.1 8.7 7.7 7.8

302 2 2 7.6 6.8 7.8 8.2 9.4 9.4 9.6 9.5 8.6 8.5 7.5 7.1

303 2 3 6.7 6.0 6.3 7.8 9.5 9.8 10.4 9.8 9.7 8.6 8.2 7.0

304 3 3 7.4 7.7 8.4 8.8 9.5 9.2 8.4 8.5 8.7 7.7 7.9 7.8

305 1 1 7.7 7.8 8.3 9.0 9.2 8.5 8.5 8.5 7.9 8.4 8.3 7.9

306 2 3 7.6 7.0 8.1 8.8 9.0 9.6 9.0 8.6 8.3 8.6 7.9 7.6

307 2 3 7.5 7.6 6.7 7.8 8.3 9.6 8.7 8.8 9.8 9.0 9.0 7.3

308 1 1 7.5 6.7 7.3 7.8 8.5 10.0 10.3 9.6 8.5 8.3 7.6 7.9

309 2 2 7.7 6.9 6.4 7.3 7.5 10.4 9.6 9.7 9.7 8.4 8.6 7.9

401 2 3 7.9 7.5 8.0 7.9 7.8 8.6 10.0 9.8 8.8 8.3 7.5 7.9

402 1 2 7.8 7.1 7.8 7.6 8.2 9.1 11.1 8.9 8.4 8.3 7.5 8.1

404 2 3 7.2 7.2 7.6 7.1 7.9 8.1 9.5 11.1 9.8 8.9 8.3 7.4

405 2 2 8.1 7.4 8.1 7.9 8.4 8.9 10.2 9.7 8.5 7.8 7.4 7.7

406 2 2 7.2 6.8 7.0 7.2 7.7 9.3 9.9 10.3 10.9 8.6 7.6 7.5

407 1 1 8.3 7.7 8.2 7.8 8.2 9.8 9.6 9.7 8.2 7.6 7.2 7.8

408 2 3 8.3 7.1 7.9 8.0 7.5 9.9 9.6 9.0 8.5 8.6 7.6 8.1

501 0 0 

502 3 4 8.3 7.9 8.3 8.0 8.3 8.7 9.1 9.3 8.3 8.1 7.8 8.1

503 3 3 7.9 7.2 7.9 7.8 8.5 9.6 9.3 9.8 8.5 8.1 7.4 7.8

504 1 1 8.3 8.2 8.5 8.6 8.5 8.3 8.1 8.0 8.9 8.5 8.4 7.8

505 3 4 7.7 7.0 7.9 7.6 8.5 9.3 9.4 10.0 8.4 8.2 8.2 7.9

506 1 1 7.8 7.4 8.9 8.3 8.6 9.2 9.2 9.4 8.4 8.4 6.8 7.6

507 1 1 7.7 7.6 7.6 7.9 8.3 9.3 10.1 9.0 8.6 8.4 7.7 7.9

601 2 2 7.8 7.7 7.3 7.8 8.2 8.8 9.3 9.0 8.9 8.6 8.2 8.2

602 2 2 7.7 7.6 7.6 7.7 8.6 9.0 9.2 9.4 8.8 8.6 7.8 8.0

701 3 3 6.4 6.4 6.5 6.5 8.3 8.9 11.7 13.1 10.5 7.7 7.1 6.9

702 3 4 7.1 6.6 7.1 7.7 7.9 9.7 10.9 10.6 9.6 8.3 7.1 7.2

703 3 4 7.3 6.9 7.4 7.6 8.4 10.3 10.5 9.7 8.7 8.3 7.4 7.5

704 3 6 7.7 6.6 7.6 7.0 8.2 9.4 10.6 10.1 9.8 8.0 7.2 7.8

705 0 0 

801 2 2 7.5 7.0 7.2 7.4 8.6 10.1 9.8 10.1 9.4 8.5 6.9 7.4

802 3 3 7.4 7.4 7.0 7.1 7.9 8.8 8.9 10.0 10.1 9.3 8.6 7.6

803 2 3 7.1 6.6 7.7 8.3 8.8 10.8 9.3 8.4 8.9 8.8 7.7 7.7

901 3 3 7.4 7.0 7.3 7.2 7.9 9.1 10.2 11.0 9.8 8.3 7.3 7.4

1001 1 1 5.5 5.0 5.7 6.9 9.2 9.5 17.1 15.1 9.3 6.0 5.4 5.4

1002 2 3 4.6 4.6 4.4 4.5 6.1 8.7 14.4 15.0 15.9 11.2 5.8 4.8

1003 0 0 

1004 4 4 5.7 4.3 4.8 5.1 7.3 10.7 13.8 15.0 14.2 8.5 6.0 4.6

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 12
1005 4 5 6.0 5.1 5.2 6.2 7.4 9.9 15.5 16.5 10.7 6.7 5.6 5.3

1006 1 1 6.5 5.9 6.6 7.0 8.4 9.7 13.6 12.5 9.1 7.6 6.4 6.6

1007 2 4 5.4 5.0 5.5 6.0 9.0 12.3 15.1 13.7 10.7 6.9 5.1 5.3

1008 4 7 5.4 5.2 5.5 6.1 9.5 11.5 14.8 12.9 9.8 7.9 6.0 5.5

1009 2 2 6.9 6.3 6.7 7.3 8.2 10.7 11.9 11.2 9.6 8.2 6.4 6.6

1010 3 3 6.0 5.8 6.3 7.3 8.8 11.7 12.0 11.3 9.7 8.3 6.6 6.2

1011 3 5 6.7 6.3 6.4 8.0 8.6 10.3 10.8 11.3 9.5 8.8 6.6 6.6

1101 1 1 7.2 6.6 7.3 7.5 8.4 8.9 10.4 11.0 9.6 8.8 7.2 7.1

1102 1 1 4.3 3.7 4.2 6.6 9.6 13.8 14.2 13.5 11.7 8.7 5.3 4.4

1103 3 3 5.6 5.2 6.0 8.8 8.8 10.9 10.7 12.1 10.7 9.2 6.4 5.5

1104 2 2 7.2 6.5 7.2 7.7 8.7 9.3 10.9 10.3 9.5 8.4 7.1 7.2

1105 3 4 6.2 5.4 6.4 7.6 9.8 11.1 12.8 11.6 9.2 7.5 6.4 6.1

1106 2 3 7.4 6.3 6.8 7.6 9.0 11.6 11.5 11.2 7.9 8.0 6.8 6.0

1107 1 1 7.0 5.7 6.4 7.0 8.5 10.2 12.1 12.0 8.9 8.7 7.2 6.5

1201 1 2 7.6 6.3 7.0 7.8 8.7 9.8 10.5 11.2 9.3 8.3 6.9 6.7

1202 2 7 7.2 6.0 6.8 7.4 8.8 9.6 11.0 10.9 9.0 9.1 7.8 6.6

1203 3 6 6.6 6.3 6.5 7.7 8.7 10.4 11.3 11.0 9.5 8.3 6.9 6.7

1204 1 3 6.1 5.5 7.0 8.0 9.0 9.9 11.8 11.8 9.5 8.5 6.2 6.6

1205 2 6 7.4 6.8 7.5 7.7 8.5 9.0 10.0 10.3 8.9 8.6 7.7 7.6

1302 3 3 5.7 5.7 6.3 5.9 9.5 12.4 12.6 11.0 11.1 7.9 6.3 5.6

1303 2 4 7.0 6.4 6.3 8.5 8.8 10.4 10.4 8.6 9.1 8.1 9.5 7.0

1304 0 0 

1305 1 1 6.8 6.6 7.6 7.8 9.4 9.7 11.1 10.6 8.7 8.3 7.0 6.5

1401 3 4 5.4 5.3 5.9 7.0 10.2 14.1 14.6 12.2 8.3 5.9 5.4 5.6

1402 3 3 4.0 4.3 4.7 7.4 11.7 13.8 13.7 13.2 9.5 7.9 5.3 4.5

1403 2 2 4.7 4.3 5.2 7.2 9.6 12.0 14.2 12.2 11.2 8.5 5.7 5.1

1501 1 1 6.1 6.1 6.0 8.1 10.5 13.3 10.2 8.2 11.5 7.7 6.3 6.0

1502 2 2 6.3 5.9 6.7 7.2 9.4 10.4 11.3 11.1 9.9 8.3 7.0 6.5

1503 5 5 5.7 5.0 5.5 6.7 9.8 12.2 12.5 10.6 10.0 8.6 7.0 6.5

1601 2 2 4.9 4.3 4.7 3.4 4.3 10.6 13.3 17.7 15.5 10.0 5.8 5.5

1602 1 1 4.4 3.4 3.9 5.0 8.3 13.7 18.2 14.2 13.7 7.4 4.1 3.7

1603 2 2 4.2 4.7 4.8 5.1 9.9 12.1 13.1 13.5 12.3 8.6 6.0 5.4

1604 1 1 4.1 3.7 4.2 5.4 8.2 12.3 14.5 14.2 13.8 10.3 5.5 3.9

1701 1 1 4.7 4.7 4.9 6.2 9.4 11.9 15.9 15.7 10.7 6.3 4.7 4.9

1702 3 3 4.6 4.5 6.0 7.2 8.8 11.4 14.4 14.2 11.1 7.9 5.2 4.7

1703 2 2 5.7 5.2 6.1 6.3 8.9 11.5 14.4 13.0 9.7 8.0 5.7 5.5

1704 1 1 3.8 3.9 4.8 5.3 9.3 11.7 18.0 17.0 12.3 6.0 3.9 3.9

1705 3 3 6.9 6.5 7.2 7.4 7.9 9.1 11.4 12.1 9.8 7.8 7.1 6.8

1706 1 1 7.5 7.3 7.4 7.4 7.2 8.0 8.8 12.4 11.1 9.5 6.8 6.8

1707 0 0 

1801 1 1 5.2 4.9 6.4 6.4 8.6 11.8 12.2 12.7 11.3 9.0 5.9 5.5

1802 2 3 3.3 3.4 3.8 5.4 7.6 11.0 13.4 14.6 12.9 10.3 7.7 6.6

1803 2 3 4.3 4.3 5.2 6.5 9.5 11.6 13.1 13.1 11.1 9.5 6.7 5.2

1804 1 1 6.2 6.3 6.0 7.3 7.6 10.2 10.5 11.0 10.6 9.9 7.3 7.1

1805 1 2 6.0 5.8 6.1 6.7 7.4 9.2 11.4 10.3 10.4 10.2 8.6 7.9

1806 2 3 5.5 4.6 5.0 6.0 9.6 10.5 12.8 12.1 11.8 8.0 6.9 7.2

1807 1 1 4.4 4.2 4.9 6.8 11.0 11.5 13.9 13.1 11.2 8.4 5.3 5.3

Sum 181 232 

 

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 13
Table B2. Monthly distribution of annual municipal water delivery for clusters of ASRs. 

Cluster No. 

of 

ASRs 

No. 

of 

cities 

Percent 

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 

1 25 72 6.4 5.9 6.5 7.3 8.8 10.5 11.6 11.2 9.9 8.4 6.9 6.5

2 16 41 4.8 4.5 5.2 6.4 9.5 12.0 15.0 14.0 10.8 7.6 5.3 5.0

3 45 106 7.8 7.3 7.7 7.8 8.3 9.2 9.5 9.6 9.0 8.4 7.7 7.7

4 5 13 4.5 4.1 4.4 4.8 6.7 10.6 13.9 15.3 14.5 10.0 6.2 5.1

Sum 91 232 

Table B3. Monthly distribution of annual municipal water delivery for WRRs. 

WRR No. of 

basin

s 

No. of 

cities 

Percent 

Jan Feb Mar Ap

r 

May Jun Jul Aug Sep Oct Nov Dec 

1 9 9 8.0 7.4 7.9 7.7 8.2 9.0 9.7 10.0 8.8 8.1 7.6 7.6

2 7 10 8.3 7.8 8.2 7.8 8.2 8.6 8.8 9.1 8.7 8.3 8.0 8.2

3 18 21 7.5 7.1 7.5 8.1 8.8 9.4 9.2 9.2 9.0 8.5 8.1 7.6

4 12 16 7.8 7.2 7.8 7.6 7.9 9.0 9.9 9.9 9.1 8.4 7.6 7.8

5 12 14 7.9 7.4 8.1 7.9 8.4 9.1 9.2 9.5 8.5 8.2 7.7 7.9

6 4 4 7.7 7.7 7.5 7.8 8.4 8.9 9.3 9.2 8.8 8.6 8.0 8.1

7 12 17 7.1 6.6 7.2 7.2 8.2 9.6 10.9 10.9 9.7 8.1 7.2 7.4

8 7 8 7.3 7.0 7.3 7.5 8.4 9.7 9.3 9.6 9.5 8.9 7.8 7.6

9 3 3 7.4 7.0 7.3 7.2 7.9 9.1 10.2 11.0 9.8 8.3 7.3 7.4

10 26 35 5.8 5.3 5.6 6.3 8.2 10.7 13.8 13.6 11.0 8.1 6.0 5.6

11 13 15 6.4 5.6 6.4 7.7 9.1 10.8 11.7 11.6 9.6 8.4 6.6 6.1

12 9 24 6.9 6.2 6.9 7.7 8.7 9.8 10.9 10.9 9.2 8.6 7.2 6.9

13 6 8 6.3 6.1 6.5 7.1 9.2 11.3 11.6 10.1 10.0 8.0 7.5 6.2

14 8 9 4.7 4.7 5.3 7.2 10.6 13.4 14.2 12.6 9.5 7.3 5.4 5.0

15 8 8 5.9 5.4 5.9 7.0 9.8 11.9 11.9 10.4 10.2 8.4 6.9 6.4

16 6 6 4.4 4.2 4.5 4.6 7.5 11.9 14.3 15.2 13.8 9.2 5.5 4.9

17 11 11 5.6 5.4 6.3 6.8 8.5 10.5 13.6 13.6 10.6 7.7 5.8 5.5

18 10 14 4.8 4.6 5.1 6.3 8.8 10.9 12.7 12.6 11.5 9.3 7.0 6.4

Sum 181 232 

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 14
Appendix C: Projected Precipitation and Potential

Evapotranspiration

In the following maps of precipitation the scale is truncated at +10 cm and -10 cm. 

(A) (B)

(C) (D)

Figure C1. Change from current conditions in mean precipitation (cm/yr) with the A1B-CGCM future for: 

(A) 2020; (B) 2040; (C) 2060; (D) 2080. 

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 15
(A) (B)

(C) (D)

Figure C2. Change from current conditions in mean precipitation (cm/yr) with the A2-CGCM future for: 

(A) 2020; (B) 2040; (C) 2060; (D) 2080. 

(A) (B) 

(C) (D) 

Figure C3. Change from current conditions in mean precipitation (cm/yr) with the B2-CGCM future for: 

(A) 2020; (B) 2040; (C) 2060; (D) 2080. 

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 16
(A) (B) 

(C) (D) 

Figure C4. Change from current conditions in mean precipitation (cm/yr) with the A1B-CSIRO future for: 

(A) 2020; (B) 2040; (C) 2060; (D) 2080. 

(A) (B) 

(C) (D) 

Figure C5. Change from current conditions in mean precipitation (cm/yr) with the A2-CSIRO future for: 

(A) 2020; (B) 2040; (C) 2060; (D) 2080. 

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(A) (B) 

(C) (D) 

Figure C6. Change from current conditions in mean precipitation (cm/yr) with the B2-CSIRO future for: 

(A) 2020; (B) 2040; (C) 2060; (D) 2080. 

(A) (B) 

(C) (D) 

Figure C7. Change from current conditions in mean precipitation (cm/yr) with the A1B-MIROC future 

for: (A) 2020; (B) 2040; (C) 2060; (D) 2080. 

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 18
(A) (B) 

(C) (D) 

Figure C8. Change from current conditions in mean precipitation (cm/yr) with the A2-MIROC future for: 

(A) 2020; (B) 2040; (C) 2060; (D) 2080. 

(A) (B) 

(C) (D) 

Figure C9. Change from current conditions in mean precipitation (cm/yr) with the B2-HADN future for: 

(A) 2020; (B) 2040; (C) 2060; (D) 2080. 

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 19
In the following maps of potential evapotranspiration the scale is truncated at +1 mm and -1 mm. 

(A) (B)

(C) (D) 

Figure C10. Change from current conditions in mean potential evapotranspiration (mm/day) with the 

A1B-CGCM future for: (A) 2020; (B) 2040; (C) 2060; (D) 2080. 

(A) (B)

(C) (D) 

Figure C11. Change from current conditions in mean potential evapotranspiration (mm/day) with the 

A2-CGCM future for: (A) 2020; (B) 2040; (C) 2060; (D) 2080. 

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 20
(A) (B)

(C) (D) 

Figure C12. Change from current conditions in mean potential evapotranspiration (mm/day) with the 

B2-CGCM future for: (A) 2020; (B) 2040; (C) 2060; (D) 2080. 

(A) (B)

(C) (D) 

Figure C13. Change from current conditions in mean potential evapotranspiration (mm/day) with the 

A1B-CSIRO future for: (A) 2020; (B) 2040; (C) 2060; (D) 2080. 

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(A) (B)

(C) (D) 

Figure C14. Change from current conditions in mean potential evapotranspiration (mm/day) with the 

A2-CSIRO future for: (A) 2020; (B) 2040; (C) 2060; (D) 2080. 

(A) (B)

(C) (D) 

Figure C15. Change from current conditions in mean potential evapotranspiration (mm/day) with the 

B2-CSIRO future for: (A) 2020; (B) 2040; (C) 2060; (D) 2080. 

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 22
(A) (B)

(C) (D) 

Figure C16. Change from current conditions in mean potential evapotranspiration (mm/day) with the 

A1B-MIROC future for: (A) 2020; (B) 2040; (C) 2060; (D) 2080. 

(A) (B)

(C) (D) 

Figure C17. Change from current conditions in mean potential evapotranspiration (mm/day) with the 

A2-MIROC future for: (A) 2020; (B) 2040; (C) 2060; (D) 2080. 

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 23
(A) (B)

(C) (D) 

Figure C18. Change from current conditions in mean potential evapotranspiration (mm/day) with the 

B2-HADN future for: (A) 2020; (B) 2040; (C) 2060; (D) 2080. 

RMRS-GTR-295: Vulnerability of U.S. water supply to shortage: a technical document supporting the Forest Service 2010 RPA: Appendices 24