5 Change in the Southern u.S. Water Demand and Supply over the Next Forty Years

Steven C. McNulty, Ge Sun, Erika C. Cohen, and Jennifer A. Moore Myers

5.1 INTRODUCTION

Water shortages are often considered a problem in the western United States, where water supply is limited compared to the eastern half of the country. However, peri­odic water shortages are also common in the southeastern United States due to high water deJnand and periodic drought. Southeastern U.S. municipalities spend billions of dollars to develop water storage capacity as a buffer against periodic drought. Buffers against water shortage include the development of water reservoirs and well excavation to mine ancient aquifers. It is iluportant to have good estimates of future water supply and demand to prevent wasting money by creating more reservoir capacity than is needed by a community. Conversely, a lack of water reserve capac­ity can lead to the need for water restrictions.

Many factors impact the anl0unt of water that is available and the amount of water that is required by a community. Precipitation is the major determinant of water availability over the long term. In addition to precipitation, air temperature and land cover also impact water availability by modifying how much precipitation is evaporated and transpired back into the atmosphere. Finally, ancient aquifers pro­vide a signi ficant proportion of needed water in some parts of the southern United States such as Texas and Arkansas. The water recharge rates for deep aquifers are very low (i.e., hundred of years), so water is essentially mined from these areas. There are also several factors that control water demand. In addition to residential water use, a great deal of water is also required by industry, irrigated farming, and the energy production sectors. In totat domestic and commercial sectors account for only 5% of the surface water use and 10% of the groundwater use. The other 95% and 90% of the surface and groundwater are used by other sectors of the economy. Thermoelectric power generation uses 500/0 of the surface water~ and crop irrigation and livestock use 67% of the groundwater. Not aU of the water that is used by each sector is lost to the atmosphere; much is quickly returned to the environment to be used again and again. The proportion of returned water varies from 98% from the thermoelectric sector to a 39% return rate from the irrigation and livestock sectors.

43

44 VVetland and \Vater Resource /v\odeling and Assessment

Communit ies need to accurately ass~ss future \vater supply and demand if water limitations arc to be minimized. Ho\vever, estimates of average annual water sup­ply and demand will be of linlitcd lise in \valer planning. Water shortages generally on Iy OCCll r during extreme event years such as \V'hen water supply may be lj m ited by drought or when water demand j" high due to drought and high air temperature. Therefore. this paper examines the sensitivity of the individual factors that influence regional water supply and demand across a range of environmental variability. Some factors such as population are relatively stab1efrom one year to (he next. while other variables such as climate can be markedly different anlong years, Groundwater with­drawal may be relalively stable until the supply is depleted. We will determine how

much each variahle is likely to influence annual water supply stress and the extent to which waler supply stress Illay vary bc{\veen ) 990 and 2045.

5.2 METHODS

Water supply and de.mand are the two components required to assess regional water stress, \Vc wi I J first defi ne the vari3bles needed to caicuJate each water supply stress component and then examine how the variables change from year to year.

5.2.1 CALCULATIONS FOR ESTIMATING WATER SUPPLY

\Ve define water availabil ity as the total potentia) \vater supply available for with­drawal fix each eight-digit hydrologic unit code (HUC) watershed. expressed in the foll()\ving formula (equation 5.1):

\\IS = P - ET + GS + IRF j (5.0

where \VS = water supply in millions of galJons tc}r each watershed per ycar; P = precipitation for each watershed in cm per yeac ET= watershed evapotranspiration for each watershed in crn per year. calculated by an empirical formula as a function of potential evapotranspiration, precipitation. and land cover types; and GS == his­toric groundwater use in millions of gallons for each watershed per year. Detailed methods are found in Sun et al. (2005).

Most of the water rcmoved f()f human use is returned to the environment as return flow (RF). W'e llsed RF estilnates from each of seven water use sectors (WU j )

including domestic. connl1crciaf. irrigation~ thennoelectric. industrial mining, and livestock sectors, which were reported by the USGS (United States Geological Sur­vey 1994). The RF was calculated as the historical return flow rate (RFR)? expressed as a fraction of the an10unt of renloved \vater that was returned to the ecosystem, multiplied by the tot.a) water use (\VU) for each sector, expressed in nlillions of gal­lons per year for each watershed.

5.2.2 GROUNDWATER SUPPLY DATA

The USGS has published estimates of national water use since 1950 (Solley et al. 1998), The groundwater term (CiS) is the 1990 estinlate of groundwater use in

Change in the Southern U.S. Water Demand and Supply 45

rnillions of gallons of water per year for each eight-digit hydrologic unit code (HUe) watershed. Groundwater is defined as the saturated zone below the subsurface (Sol­ley el al. 1993). The 1990 groundwater supply estimate \vas incorporated into the 1990 baseline year, 2020 wet year. and 2024 dry year water supply stress scenarios. The groundwater term was dropped for the 2043 dry year and 2045 wet year sce­narios to examine the implications of a lack of groundwater availability on water

supply stress.

5.2.3 HISTORIC AND PROJECTED CLIMATE DATA

The U.K. Hadley Clitnate Research Center HadC'M2Sul dinlate change scenario was used to project climate between 1990 and 2045. The southern United Slates is expected to beconle generally warmer and weller under the HadCM2Sui scenario. We cOinpared the impact of a future hot and dry year (Figures 5.la and 5.tb) and a

Predpitatic1n Hadley Climate Scenario

Dry Year: 2043

iomm _1500-1609 _1000-1500 _500-1000

~~_,~_ .. ,:,,,,:::::-"_~liles _<500 o 80 160 320 480 6'}O

.~ . ~. ----

AVl'rage Air Temperature HacUL,), Climate Scenario

Dry Year: 2043

Depft$ Celsius

_20-25 _16-20

-=-..,-,._ -=:..::.= __ Miles l2··11" j 087.5 175 ~50 525 700

5.la

5.th

.,.,.. tf3'r'M l>wt em--!

FICURE 5.1 Predicted hot and dry year (e.g., 2043) precipitation (a) and air temperature (b) distribution. and predicted cool and wet year (c.g .. 2045) precipitation (C) and air temperature

(d) distribution.

46 etland and Wate r R ource Mod ling and As

Precipitation Hadley Climate Scenario

\Vet Yt>a r: 2045

__ ' _ , C __ ,' _:\Ii l l~<;

_ 2000·2669 _ 1500-- :W()O

.. JOOO-I:;OO mIt 500 IOOiJ _<5{)()

o ~o J 60 31!) J.80 Mil

Average Ail' Temperature Hadley Climate Scenario

Dry Year: 2045

Degrees Celsiu~ _ 20-25 _ 16-20 _ 12-16

-- '_"o' ._ - '-._!"!iJ~~ _ < 12 O~7 .5 175 350 S25 700

FIGURE 5.1 (Continued)

S.le

I S.ld

future cool and wet year (Figures 5.le and 5.ld) with average (circa 1990) histork cJinlate to assess how changes in air temperature and precipitation will impact water supply stress. The climate data were gridded at 0.50 by 0.51

) (about 50 kIn x 75 km) across the continenta1 U.S. (Kittel et aL 1997). Next~ 1990 climate data were subset and scaled to the 666 corresponding 8~digjt HUe watersheds covering Virginia to Texas (USGS ]994). The same process was repeated for other years used in the water supply stress scenarios. Mean air temperature for 1990 was 24.29°C, while HadC­M2Sul predicts 24.36°C for 2024 and 22.69°C for 2045. Mean precipitation for 1990 was 96.45 cm~ HadCM2Sui predicts mean annual values of 78.07 cm for 2024 and 116.68 cm for 2045.

5.2.4 HISTORIC LAND COVER AND LAND USE DATA

Land cover data were used to drive the water yield model for al I seven water use sectors and each of the 666 8-digit HUC watersheds modeled in this study. The

in the Southern U.S. Water Demand and Supply 47

I 2 Multi-Resolution Land Characterization (M RLC) land coverlland use dataset b ", p:llwww.mrlc.gov) was used to calculate the percentage of each vegetation type ithin each watershed. Land cover was aggregated into five classes including ever­

green forest, deciduous forest, crops, urban areas, and water. In this analysis. land

use was held constant throughout the assessment period.

5.2.5 HISTORIC AND PROJECTED POPULATION DATA

::6 Approximately 100 lnillioD people live in the 13 southern states (U.S. Census 2002). };:,- Population projections at the census block level are available to 2050 (NPA Data '" .,' Services 1999). We aggregated predicted census block-level population data to the i:'j~.' watershed level for each year between 2000 and 2045. Between 1990 and 2045, the ~,'" population of the 13 southern states was predicted to increase by 94% (NPA Data

Services 1999), No new areas of growth within the region were projected. but current urban centers are expected to expand. Rural areas are generally expected to become more densely populated. However. population growth between 1990 and 2045 will not be uniform (Figure 5.2a); percentage change in popu lation between 1990 and 2045 varied frOlll -210/0 to +6020/0 across the region (Figure S.2b).

5.2 .. 6 CALCULATIONS FOR ESTIMATING WATER DEMAND

Water demand is as important as water supply in determining if a community is likely to experience recurrent water shortages. Water demand (WD) represents the sum of all water use (WU) by each of the seven water use sectors within a watershed

(equation 5.2): WD = LWU j i = I - 7 (5.2)

Annual domestic water use (DWU) for each watershed was predicted by correlat­ing USGS historical water use (in millions of gallons per day per watershed) for the dOIuestic water use sector with watershed population (P, in thousand persons) for the

years 1990 and 1995 (equation 5.3): .

DWU :: 0.008706 * P + ) .34597 R2:: 0.51. n :: 666 (5.3)

Similarly, irrigation water use (lWU) for each watershed was derived by correlating USGS historical irrigation water use (in millions of gallons per day per watershed) with the irrigation area (lA~ in thousands of acres) for the years 1990 and 1995

(equation 5.4):

IWU = 1.37l4 * IA + 2.06969 R2 = 0.67, n = 666 (5.4)

Currently, we do not have water use models for the other five sectors (i.e., commer­cial, industrial, livestock, mining, and thermoelectric), therefore historic water use

data were utilized for future periods.

48 Wetland and vVater Resource IVtodeling and Asses

D.J!a :'lluY<t?s

",'PA P')pui.\ l1 •• n Piu!t-'t tJulh

l r~l(~S rwht ·j- h~it HI. t BOUlLdri. , 'i

NJ'A tI11"U~,lt:,,>tl Pr<lwclI1~n.'(

11,r~;G'> I '!th!·Ltigit lIl'e H()lmdll"~

Population Changt' 1990 to 2045

_ ii 2)()

-l- O

Pt.'f nL Changt· in Popul tl n Hadley C lim ate Seen,trio

_ 300'lh-fxr.!'!t,

_ JOO"'; -300'~;

51)'\i,-IOO'!{>

80tx, 50'!/. _ <!l'ii;--U',li>

____ c.c-=-=-c"'--_;:._!v1iles () ~5 170 :qO 510 680. "....,.,,* -_ttl"""'"

5.2a

5.2b

fiGURE 5.2 The ScpatiaJ and temporal change in southern U.S. population between 1990 and 2045 expressed as absolute ch,mge (a) and pen:entage change (b).

5.2.7 CALCULATIONS fOR ESTIMATING THE WATER SUPPLY STRESS INDEX (WASSI)

We have defi ned a water supply stress index (W ASSI) by dividing water supply by water demand (equation 5.5). Cmnparing the WASSI between two points in time results in a WASSI ratio (WASSIR, equation 5.6). The WASSI was used to quantita­tively assess the relative magnitude in water supply and demand at the 8-digj( HUe watershed scale. The WASSIR was used to assess the relative change in the WASSI between the baseJine scenario (SI}) and one of the other scenarios (S() described Jater. Positive WASSIR values indicate increased water stress and negatives values indicate reduced water stress conlpared to historical conditions (scenario 1):

h ngein the Southern U.S. Water Demand and Supply

WD" ~VASS'J = -- -

. • ~ ~VS(

x represents one of six simulation scenarios described below.

49

(5.5)

(5.6)

i scenarios were developed, each examining the impacts of changing population, lirnate, and ground water supply on annual WASSI values. Changes in the water upply portion of the WASSI term were addressed in three ways. First, we chose

t dry years (2024 and 2043) and two wet years (2020 and 2025) to conlpare to historic climate base year of 1990. Second, ground water is a finite resource and

. n the current rate of usage, it is possible that ground water nlay be completely dple t1 in some areas during the next 40 years. We tested the impact of the loss of

"' ground water supply on water supply stress by examining wet and dry ye,lrs with and i( ut ground water inputs into the WASSI model. Finally, population impacts on ater supply stress were examined by comparing wet and dry years in the 2020s and

. with the baseline water supply stress year (Le., 1990) .

. 2.8.1 Scenario 1: Small Population Increase-Wet Year (2020)

i scenario used 2020 population projections that predicts above average precipi­a: ion for the region compared to 1990 values. Groundwater withdrawal was held

at 1990 levels.

5.. 8.2 Scenario 2: Small Population Increase-Dry Year (2024)

hi. scenario used 2024 population projections. 2024 is predicted to have below . . 'erage precipitation compared to 1990 levels, thus decreasing water supply. Ground­

y~ter withdrawal was held constant at 1990 levels.

'5.2.8.3 Scenario 3: Large Population Increase-Wet Year (2045)

,:Tilis scenario used 2045 population projections, and it is predicted to have above i ~rage precipitation compared to 1990 levels. Groundwater withdrawal was held

constant at 1990 levels.

5.2.8.4 Scenario 4: Large Population Increase-Dry Year (2043)

This scenario used 2043 population projections, that is predicted to have below aver­age precipitation compared to 1990 levels. Groundwater withdrawal was held con-

stant at 1990 levels.

50 Wetland and 'vVater Resource Modeling and Assessment

5.2.8.5 Scenario 5: large Population Increase-Wet Year (2045), No Groundwater Supply (GS)

This scenario used 2045 population projections that is predicted to have above aver­age precipitatjon compared to 19<)0 levels. However, groundwater supplies 111ay be exhausted in some areas by 2045. Therefore. we renloved groundwater for the entire region as a water supp]y source to the WASSI model in this scenario.

5.2.8.6 Scenario 6: Large Population Increase-Dry Year (2043), No Groundwater Supply (GS)

This scenario used 2043 popUlation projections that is predicted to have below aver­age precipitation compared to 19<)0 levels. In addition to the increased population and below average year precipitation, the groundwater supply was renlOved from the WASSJ model across the region in this scenario.

5.3 RESULTS AND DISCUSSION

The results section is divided into three parts: (1) climate controls on water supply stress, (2) population and other water use sector controls on water supply stress. and (3) ground water supply controls on water suppJy stress.

5.3.1 CLIMATE CONTROLS ON THE WASSI

Historically. annual precipitation and air tenlperature vary widely across the region: central Texas averages less than 70 em of precipitation per year. while parts of the Gulf coast and southern Appalachians receive almost 200 em. Average annllal air temperature is roughly inversely proportional to latitude within the region. Annual precipitation and air temperature are the most important determinants of water loss by evapotranspiration and thus water yield across the southern Unite-d States (Lu et aL 2003). Therefore, the Appalachians and the Gulf coast had the highest water availability. while the lowest was found in semiarid western Texas.

Irrigation and thernl0e]ectric sectors were the two largest water users, followed by domestic livestock and industrial users. Consequently, the western Texas region. which had a lot of irrigated farmland and Bmited water supplies, had the. highest WASSI for both wet and dry years (Figures 5.3a-d). Other areas with WASSI values indicating stress induded southern Florida. southern Georgia, and Mississippi valley areas with a high percentage of irrigated 1and (relative to the total 1and area). Several isolated watersheds in high-preclpitation regions east of the Mississippi River also showed high water stress. primarily due to thernloelectric water use.

Conlpared to the base1ine conditions of 1990, the WASSI in 2020 (Figure 5.3a) and 2045 (not shown) were projected to decrease due to a moderate increase in air temperature and a large increase in precipitation. The WASSI in 2024 (Figure 5.3b) was projected 10 increase due to a moderate temperature increase and moderate decrease in precipitation compared to 1990 levels. As a result, the average regional WASSIR value (compared to 1990) decreased by 5'?;f.J during the wet year of 2020 (Figure 5.3c), but increased by 22% for the dry year of 2024 (Figure 5.3d) and 66%

Change in the Southern U.S. Water Demand and Supply

N

A

Water Supply Str~s Index Hadh~y Climale Scenario

Wet '1'1.""6[; 2020

----- -Water Supply Stress Index Hadley Climate Scenario

Dry Year: 2024

5.3a

I S.3b

~-=--_-== __ Miles i

I.--____ --=:.......:..:....:.:..;:;._.=....:..::...---=:..:..::....-==~.~ .. -~---..J

51

FIGURE 5.3 Climate change impacts on the southeastern U.S. water supply stress (WASSI) during the wet year of 2020 (a) and the dry year of 2024 (b). Change in the water supply stress ratio (WASSIR) between the 1990 baseline WASSI and the wet year WASSI of 2020. (c) and

the dry year WASSI of 2024 (d).

for the dry year of 2043 (not shown). The WASSIR again decreased for the dry year of 2045 by 4% (not shown).

5.3.2 POPULATION AND OrHER WATER USE SECTOR CONTROLS ON THE WASSI

Water demand by the domestic water use, sector is directly related to population, as, demonstrated in Equation 5.3. Population centers that are projected to expand dramatically over the next 40 years (e.g., Atlanta, Georgia; Dallas, Texas; RaJeigh­Durham~ North Carolina; and northern Virginia) will see up to 200% increases in domestic water use. Therefore, population growth may be responsible for increasing the WASSI by more than 70% in watersheds containing relatively large increases in population, but population change will have little impact «5%) on the regional-scale WASSL

52 'vVct/and and \Nater Resource Modeling and Asse

j'ertt'nt Ch;mgc in Water Supply Stress Index Ratio Hadley Climate Scell.uio

--=- _"-'liles - ~. -_-.2. 85 !J! .~ _ 1_0 __ _

Peru' t Change In \X'ater

flGlJ RE 5.3 (Continued')

I-ladlc~' C1imat(' SCenal"jo \,\f(·t YL';U : l 02l)

j5(j'\'- j LJS'!>,

: <'~::?;;1 I O()",,- 150% .•• ':' 5fJU,,- J(}O'!!. I

_ ()~(· :)O'>i,

_ r,O~J -O':'\!

5.3c

5_3d

The Inean regional WASSI increased from n.ll (Figure 5.4a) to 0.12 (Figure 5.4b), dC$pite a 30% increase in southeastern U.S. population between 2024 and 2043. Pop­ulation changes had little impact on the Wi\SSI ",'hen compared to that of the inter­annual variation in climate and potential loss of groundwater reserves. A doubling of locaJ populations around 111etropolitan areas wiU have a limited impacl on interan~ nual WASSJ variability. Even in heavily popuJated areas. residential and commer­cial water use represent snlaJ1 segments of total waler demand, but cities do affect water quality. As the population increases. costs t()[ water treatolem and acquisition increase: water conservation rnay be important for reasons other than water supply,

Other sectors~ such as hydroe1ectric power generation. use much more water than other sectors but also recycle approximately 98% of the water that is used. In contrast. the irrigated farming sector uses a large share of the total water supply while returning only approximately 68(k of the water back to the 1and; the rest is lost to evaporation.

e in the Southern U. S. Water Demand and Supply

N

Water Supply Strc)i;$ Index. Hadley Climate Scenario

Dry Year. 2024

2.()O~2.1S

1.00-2.00 0.50-1.00 Intfe ' .....

. tr>

I Percent Chan; e in- ',X.-·'a-ter-S-up-p-Iy Stress Index R-at-io--­

Hadley Climate Scenario Dry Year: 2043

I

- ISo%-2()()Qj, lO()%-l~

• ' . 5()%.-1 00% I~ .. OOb-SO% _ -~--O':Il>

53

5.4b

fiGURE 5.4 Population change impacts on the southeastern U.S. water supply stress (WASSI) during a dry year in 2024 (a) and a dry year in 2043 (b). Change in the water supply stress ratio (WASSIR) between 1990 and the two dry years of 2043 (c) and 2024 (d). -

5.3.3 GROUND WATER SUPPLY CONTROLS ON THE WASSI

The loss of the groundwater resource can have severe implications for the WASSI in some areas where groundwater represents a major source of the water supply. By the 2040s, it is Jike1y that areas with limited aquifer reserves and heavy groundwater use will begin to run out of groundwater. In our study, we expected loss of groundwater to have a severe impact on the WASSI during the dry year of 2043 (Figure 5.5a). It was somewhat surprising that even during the projected wet year of 2045~ severe water stress would occur over much of the region without groundwater (Figure 5.5b). The water supply stress index ratio (\VASSIR) increased by 232% between the base­line year of 1990 and the dry, no groundwater year of 2043 (Figure 5.Se). Even for the wet year/no groundwater scenario of 2045, the WASSIR difference between 1990 and the dry years without groundwater (i.e., 2024 and 2043) was 119% (Figure 5.5d).

54 Wetland and Water Resource. Modeling and Assessment

Pc!Ct'nt Change in \Vater Supply Stress Index Ratio

I\:

A~ D..u (>c;.

"E f M~~~l ; lh.JJ:p, (l ,rl ! ~r"A 1)(~p:t.d.uJl'li Pr':~I'(,..tI~HH

Hadley Climate SCl'nario Dry Year: '2043

~ 100%- 150% ll;itlt 5(~\j ··1 OO'-!>'\ l»u _ 0%-50'*, I _ -50'l6-0'lIi

~~~.~ ~C;;~~~;~~:~~~:::~:t.~~U 7~)·~"~s.w::;;~1,_il_es~. ~~~~

Percent Change In 'J atcor upply Slr Hadler Chmate Scenario

Dry Year: 202~4 g~l.al

N

, J\ lD"r-~ \.i~l.fr".ro:"S

1 AO .\l",dd ;11".; ... ~ n .. i i NPA ~·ull!'ulll'n'i<'<~." ..

1SO, - 19 ,.. ~ UlO%- E,O% Sil SO%-lO(J'.-, _ i)\,-50% _ -50%-0%

tnO"e-,d3ho~ SUf:.'!l\

; 1~5(~Srl!ll .. f)j¥1f :w~;li<>'J...t~I·j .. __ .;.-:c_:::,c::,:". '._ Miles : (,5(,;; 1X'~1~' SUPI"" Il<~'>rd. 0 85 170 34() 510 680 .~'rtrlD

fiGURE 5.4 (Continued)

5.4

5Ad

Land use planners should carefully review the inlplication of groundwater loss on local economies and consider converting land area from higher to lower water-con­suming practices (e.g., reduce irrigated acreage) or the use of water transport systems to replace exhausted aquifers. Even the most optimistic estimates of climate change and increased precipitation will not likely alleviate future water stress, should aqui­fers run dry.

5.4 SUMMARY

This paper explored the likely inlpacts of climate, population, and groundwater sup­p1y on interannual water supply stress across the southeastern United States during the next 40 years. We found that predicted climate variability will have the largest impact on the water supply stress. However, the current \VASSI model does not carry water reserves or deficits from one year to the next. There is no drawdown of water reservoir capacity as would occur during a prolonged drought. Simi1arly, there is no

Change in the Southern U.S. Water Demand and Supply

Water Supply Stress Index Hadley Climate Scenafio without Groundwater

DiM... U«=I _

,UT Mud.I,:Zh.lng<1.U I NI'A p •. ,pt.dJtil'fl f"i~l,··d.lC.fI~

Dry Year: 2043 ~~U'

_ 2J)(}- H.:l!) _ I.OO~2.00

_ 050-1.00

.' 0.11-0.50 _ O.06- D.1O _ n.OO ..... Ou5

\ ' <;(;~''lth'·I)j~,' HUCS.)UJld ...... ~~~~=---:"!'!'~ Miles .. . .. ,.. lIJ1PIy......s.. JLM 170 510 980 ~""":'"' .... ~::er:.'l"'l

'aler Supply tr Hadley Climate Scenario without Groundwater

N

i D.u",s.,"lIU"t:"f'!l J~

iAn M<'<khZh;u\j;o<aI.1 : NI'A I'<.frubt- I'rOl«l1on.

Dry Year: 2045

_ 2.00-21.44 _ 1.00-2.00 _ 0.50-1.00

i, .: O.lO-050 _ 0.05·-0.10 _ 0.00-0.05

: i !~j, tiijb< IJipt Hl:~: 1Iow,d. .....

t..'!:<;"~~I«~I!'LR.~~~.~ __ . .9-. =-=I;"(1=--l*)o:::::::;;;;==a511-)L=-:::;MO~~~~~~

55

S.Sa

5.5b

FIGURE 5.S Climate change impacts on the southeastern U.S. water supply stress (WASSl) durjng the dry year 2043 if no groundwater were available (a) and the wet year of 2045 ~jth no available groundwater (b). Change in the water supply stress ratio (WASSIR) between 1990 and the dry year of 2043 if no groundwater were avai.lable (c) and the wet year of 2045 with no available groundwater (d).

reserve water capacity to compensate for water shortfalls during a drought. There­fore, the current WASSI model could overestimate the impact of short-term droughts because water deficits could be offset by water reservoirs.

Watersheds receiving limited precipitation and with a heavy dependence on groundwater will be the most susceptible to chronic and potentially permanent water shortages. Water use managers should expect even more stress in large population centers. Less-populated areas that had little water shortage problems in the past may also face water stress issues under changes in global and regional climate. However. future climate change-induced precipitation patterns remain uncertain, especially in the eastern United States. and thus realistically predicting future water stress remains a challenge.

.56 \Netland dnd Water Resource f\..1odeling and Assessment

Pl'n':en! Changt· ill Water Suppl1" Strt~SS Index Ralil.) Iladley Climate Scenario without Groundwater

Dry Ye,IF: 204J

PerCCTl[ Change in \Vater Supply Stress Index R,)tio Ilddley Climate Seen.Hi!) without Groundwater

Drr Year: 2045

FIGURE 5.5 (Continued)

ACKNOWLEDGMENTS

-l

5.Se

5,5d

Funding t()r this work was provided by the U.S. Department of Agriculture Forest Service Southern Global Change Program in Raleigh, North Carolina. The authors thank Corey Bunch for prograrnming support.

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