Global-scale analysis of river flow alterations due to water withdrawals and reservoirs

20 Pages·2009·2.93 MB·English

Hydrol. EarthSyst. Sci.,13,2413–2432,2009
Hydrology and
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Earth System
©Author(s)2009. Thisworkisdistributedunder
theCreativeCommonsAttribution3.0License. Sciences
Global-scale analysis of river flow alterations due to water
withdrawals and reservoirs
P.Do¨ll,K.Fiedler,andJ.Zhang
InstituteofPhysicalGeography,GoetheUniversityFrankfurt,FrankfurtamMain,Germany
Received: 17June2009–PublishedinHydrol. EarthSyst. Sci.Discuss.: 3July2009
Revised: 24November2009–Accepted: 6December2009–Published: 22December2009
Abstract. Global-scale information on natural river flows flow alterations are the Western and Central USA, Mexico,
and anthropogenic river flow alterations is required to iden- thewesterncoastofSouthAmerica,theMediterraneanrim,
tify areas where aqueous ecosystems are expected to be SouthernAfrica,thesemi-aridandaridcountriesoftheNear
strongly degraded. Such information can support the iden- East and Western Asia, Pakistan and India, Northern China
tification of environmental flow guidelines and a sustain- and the Australian Murray-Darling Basin, as well as some
able water management that balances the water demands Arcticrivers. Duetoalargenumberofuncertaintiesrelated
of humans and ecosystems. This study presents the first e.g. to the estimation of water use and reservoir operation
global assessment of the anthropogenic alteration of river rules,theanalysisisexpectedtoprovideonlyfirstestimates
flowregimes,inparticularofflowvariability,bywaterwith- ofriverflowalterationsthatshouldberefinedinthefuture.
drawalsanddams/reservoirs. Sixecologicallyrelevantflow
indicatorswerequantifiedusinganimprovedversionofthe
global water model WaterGAP. WaterGAP simulated, with
1 Introduction
aspatialresolutionof0.5degree,riverdischargeasaffected
byhumanwaterwithdrawalsanddamsaroundtheyear2000, Freshwater ecosystems, which include rivers, wetlands and
as well as naturalized discharge without this type of human lakes as well as their floodplains, have been deteriorating
interference. Comparedtonaturalizedconditions,long-term faster than other ecosystems. According to the Millennium
average global discharge into oceans and internal sinks has Ecosystem Assessment (2005), populations of freshwater
decreased by 2.7% due to water withdrawals, and by 0.8% species (included in the Living Planet Index) declined, be-
due to dams. Mainly due to irrigation, long-term average tween1970and2000,onaverageby50%,comparedto30%
river discharge and statistical low flow Q90 (monthly river for marine and also for terrestrial species. Approximately
discharge that is exceeded in 9 out of 10 months) have de- 20%oftheworld’s10000describedfreshwaterfishspecies
creased by more than 10% on one sixth and one quarter of havebeenlistedasthreatened,endangered,orextinctinthe
the global land area (excluding Antarctica and Greenland), last few decades. Over one third (37%) of the freshwater-
respectively. Q90 hasincreasedsignificantlyononly5%of dependentmammalspeciesassessedfortheIUCNRedList
the land area, downstream of reservoirs. Due to both water weregloballythreatened,includingmanatees,riverdolphins
withdrawalsandreservoirs,seasonalflowamplitudehasde- and porpoises (Millenium Ecosystem Assessment, 2005).
creasedsignificantlyononesixthofthelandarea,whilein- Besides, about one half of the 200 species of freshwater
terannualvariabilityhasincreasedononequarteroftheland turtles were classified as globally threatened in the IUCN
areamainlyduetoirrigation. Ithasdecreasedononly8%of Red List. Threats to global freshwater biodiversity can be
thelandarea, inareasdownstreamofreservoirswherecon- groupedunderfivecategories: overexploitation,invasionby
sumptivewateruseislow. Theimpactofreservoirsislikely exoticspecies,waterpollution,destructionordegradationof
underestimatedbyourstudyassmallreservoirsarenottaken habitat (e.g. related to changes in fluvial morphology), and
into account. Areas most affected by anthropogenic river alterationofflowregimes(Dudgeonetal.,2006). Whilethe
firsttworelatetothebioticcomponentoffreshwaterecosys-
tems,thelatteraffecttheabioticcomponent.
Correspondenceto: P.Do¨ll
([email protected])
PublishedbyCopernicusPublicationsonbehalfoftheEuropeanGeosciencesUnion.
2414 P.Do¨lletal.: Global-scaleanalysisofriverflowalterations
Monitoringoffreshwaterspeciesisrequiredtocharacter- quency, duration, timing and rate of change. Large differ-
izethedegreetowhichhumanshaveaffectedaquaticecosys- ences between natural and actual, i.e. anthropogenically al-
tems. The knowledge of the status and trend of freshwater tered, regimes are likely to indicate that the biotic compo-
species,however,isstillverypoor,inparticularindevelop- nents of the aquatic ecosystem have been altered too, and
ingcountries, anditisnotlikelytosignificantlyimprovein thatbiodiversityhasbeendecreasedduetohumanimpacts.
thenearfuture(Revengaetal.,2005). Therefore,assessment Bothreservoirsandwaterwithdrawalsresultinincreased
and monitoring of the physical conditions of the freshwater evapotranspirationandthusdecreasedannualriverflowval-
habitat is an option, firstly because it provides a more inte- ues, and they affect the seasonality of river flow. Reser-
grated characterization of ecosystem change, and secondly voirs lead to decreased seasonal flow amplitudes, while the
because physical data may be available at more locations impact of water withdrawals depends on their seasonality.
than species data (Revenga et al., 2005). Humans have sig- For the Krishna River in India, for example, Bouwer et
nificantly influenced most rivers of the world with respect al.(2006)showedthatreservoirconstructionandpertaining
tothephysicalhabitatconditionswaterquality,fluvialmor- irrigationafter1960hadleadtodecreasedannualrunoff,de-
phology,andflowregimes(Dudgeonetal.,2006). Changes creasedmonsoonseasonflowsandsomewhatincreasedpost-
inwaterqualityarepredominantlyduetohumanandanimal monsoonseasonflows. Studiesonboththeimpactofreser-
excretions as well as agricultural and industrial emissions, voirsandwaterwithdrawalsonflowregimesandtheimpact
while fluvial morphology has been modified mainly to im- of altered flow regimes on the biotic ecosystem component
prove navigation and flood protection. River flow regimes mainly concern North American or Australian rivers. For
havebeenalteredbywaterwithdrawalsaswellasbyreser- the Murrumbidgee River in Australia, for example, Kings-
voirconstructionandmanagement. Thesealterationsdonot ford and Thomas (2004) described a river flow reduction to
only affect river ecosystems themselves but also associated aboutonethirdofthenaturalmedianflow,andtheresulting
ecosystemslikeriparianwetlandsandfloodplains. degradation of the major wetland caused by damming and
Many studies have shown that flow regimes play a major subsequent water withdrawals. This led to a 21% reduction
role in determining the biotic composition, structure, func- ofthenumberofwaterbirdspeciesanda90%reductionof
tion and diversity within river ecosystems (Richter et al., thetotalnumberofwaterbirdsbetween1983and2001. For
1996;ArthingtonandPusey,1993). Theimportanceofflow theBrazosRiverbasinintheUSA,withlargeandincreasing
variability for river ecosystems has been well documented waterwithdrawalsand39reservoirs,VoglandLopes(2009)
(e.g. Poff and Ward, 1989; Poff et al., 1997; Richter et al., compared naturalized and anthropogenically impacted river
1996,1997;Puckridgeetal.,1998;ClausenandBiggs,2000; flowregimes. Theyidentifieddecreasesinthefrequencyof
WorldCommissiononDams,2000). Researchersnowgen- high flow events (in spring and winter) and increased sum-
erallyagreeonthe“naturalflowparadigm”, statingthatthe mer low flows. These changes likely caused the observed
fullrangeofnaturalintra-andinterannualvariabilityofhy- increase of habitat generalist fish species, a decrease of na-
drological regimes is critical in sustaining native biodiver- tiveriverinefishesandanoverallhomogenizationofspecies
sityandintegrityofaquaticecosystems(Richteretal.,1997; assemblages. Analyzing the temporal development of 186
Poffetal.,1997). Thus,environmentalflowguidelinesmust intermediate-sizedriversaffectedbydamsinthecontinental
take into account flow variability as expressed by a number USA,Poffetal.(2007)foundthatflowregimeshavebecome
of indicators, not just prescribe minimum flows. The natu- morehomogeneousduetomodificationofecologicallycriti-
ralflowparadigmalsosuggeststhatapproachesfordefining calhighandlowflows.Suchahomogenization,whichfavors
environmental water requirements only as fraction of long- thespreadofcosmopolitan,nonindigenousspecies,wasnot
termaverageflows,liketheSmakhtinetal.(2004)approach, identifiedfor317undammedreferencerivers.
areoverlysimplisticandinappropriateforprotectingecosys- At the global scale, what is known about the drivers of
tems. riverflowregimealteration, i.e. wateruseanddams? Total
A comparison of the natural flow regime of a river with global water withdrawals are estimated to be 4000km3/yr,
the flow regime that is affected by human intervention pro- approximately one tenth of the renewable water resources
vides an indication for the degree of human alteration or (Do¨ll,2009),butratiosexceed0.4inmanyriverbasinswhich
degradation of the freshwater ecosystem. Such a compar- arethencalled“water-stressed”.Thesecoveraboutonequar-
ison requires the identification of appropriate hydrological ter of the global land area outside the ice caps and are the
indicators that are relevant for the well-being of the biotic home of more than 2 billion people (Alcamo et al., 2003a).
componentsofthefreshwaterecosystem(Blacketal.,2005). Consumptive water use (i.e. the fraction of the withdrawn
The Indicators of Hydrologic Alteration (IHA) approach of water that evapotranspirates during use and therefore does
Richteretal.(1996)hasbeenwidelyadoptedbecauseofits notreturntotheriver)leadstoriverdischargereductionand
comprehensive ability to characterize ecologically relevant isthereforetherelevantquantityfordetermininghumanriver
hydrologicalchanges. Inthismethod, twosetsofflowtime flowalterations. Itamountsto1300–1400km3/yr, ofwhich
seriesrepresentingnaturalandalteredconditionsatthesame morethan90%arecausedbyirrigation(Do¨ll,2009). There-
sitearecomparedusing32indicatorsofflowmagnitude,fre- fore, river flow reductions due to human water use are high
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P.Do¨lletal.: Global-scaleanalysisofriverflowalterations 2415
insemi-aridandaridareaswithsignificantirrigation. In Sect. 2, the methods to compute anthropogenically
Avakyan and Iakovleva (1998) estimated that there were altered and naturalized river flows, the selected indicators
around 60000 reservoirs world-wide, but gave no lower of river flow alteration and a simple approach for relating
size limit. They estimated that their total capacity exceeds changes of annual flows to changes of the number of fish
6500km3 and that their water surface equals 400000km2. speciesaredescribed. InSects. 3and4,resultsarepresented
According to ICOLD (1998), there are more than 45000 and discussed. In the last section, we summarize the study
large dams (with a dam height of more than 15m, or of resultsanddrawconclusions.
morethan5mifthereservoirvolumeisabove3millionm3),
but part of these dams are run-of-river dams without sig-
nificant water storage and thus with a small effect on the 2 Methods
flow regime. Chao et al. (2008), mainly based on ICOLD
data, studied the development of total global water storage 2.1 Computationofnaturalandanthropogenically
in reservoirs between 1900 and 2007, taking into account alteredriverflowswithWaterGAP
almost 30000 reservoirs with, after 2000, a storage capac-
ityofapprox. 8300km3. Unfortunately,neitherICOLDnor The global water resources and use model WaterGAP con-
Chaoetal.(2008)includethegeographicalcoordinatesofthe sists and the WaterGAP Global Hydrology Model WGHM
damsandreservoirs. Nilssonetal.(2005)foundthat172out andofanumberofsectoralwaterusemodels(Alcamoetal.,
of 292 large river systems (i.e. 60%) are affected by dams. 2003b). Withaspatialresolutionof0.5◦ by0.5◦ (55kmby
While Europe has almost no unfragmented large river sys- 55km at the equator), it covers all land areas of the globe
tems, there are many unfragmented systems in North and excludingAntarctica. Wateruse,i.e.waterwithdrawalsand
Central America (outside the USA). The investigated 292 consumptivewateruse,isestimatedseparatelyforthesectors
riversystemsaccountfor60%oftheworld’sriverdischarge. irrigation, livestock, households and industry. With a daily
Analyzing around 600 of the largest reservoirs world-wide, timestep,WGHMcomputeswaterstorageandwaterflows,
Vo¨ro¨smarty et al. (1997) found that the mean age of river includingtotalrunoffgeneration, groundwaterrechargeand
waterhaslikelytripledtowelloveronemonth,whichshows riverdischarge,takingintoaccounttheimpactofhumanwa-
the increase of transport time of river water due to reser- teruseonriverdischargeandsurfacewaterstorage(Do¨llet
voirs. Poff et al. (2007) stated that extensive construction al., 2003; Do¨ll and Fiedler, 2008). WGHM is tuned in a
ofdamshasgreatlydampenedseasonalandinterannualriver basin-specific manner against long-term average discharges
discharge variability, with negative impacts on global bio- at1235gaugingstations(HungerandDo¨ll,2008).
diversity in river and riparian ecosystems as biodiversity is For each grid cell of WGHM, a vertical water balance is
generatedandmaintainedbygeographicvariation. computed,andtheresultingrunoffisroutedlaterallywithin
The objective of this study was to analyze the impact the cell through a groundwater store and various types of
of water withdrawals and dams (i.e. reservoirs or regulated surfacewaterstores(lakes,reservoirs,wetlands,andrivers).
lakes)onmonthlyandannualriverflowregimesworld-wide, Theeffectofsurfacewaterstorageonwaterbalanceandflow
consideringecologically-relevanthydrologicindicators. We dynamics is modeled by first routing the runoff generated
wanted to represent the alteration of natural conditions that withinthegridcellthroughaso-called“local”lake/reservoir
hadoccurredbyaroundtheyear2000duetowithdrawalsand storageanda“local”wetlandstoragecompartment. There-
dams only, under climatic conditions that had not yet been sultingdischargevolumeisaddedtothedischargefromthe
appreciablyalteredbyclimatechange(i.e.before1990). We upstream grid cell and routed through a so-called “global”
used the global hydrology and water use model WaterGAP lake and/or reservoir compartment and a “global” wetland
(Alcamo et al., 2003b) which takes into account the impact storage compartment, and finally through the river storage
of reservoirs and water withdrawals on river discharge. For compartment. Ifthereareanumberoflakes(orreservoirsor
thisstudy,weappliedthemostrecentmodelversion2.1g. It wetlands)withinagridcell,theyarelumpedintoone. “Lo-
differsfromthepreviousversion2.1faspresentedinHunger cal” lakes and reservoirs are lumped together into one “lo-
and Do¨ll (2008) with respect to the implementation of the cal” lake, too, while “global” lakes and “global” reservoirs
reservoiralgorithmofHanasakietal.(2006),andofthenew are treated separately within the cell. The water balance of
GRanD reservoir data set (Lehner et al., 2008; Lehner et “global”lakesandreservoirs,whichcancovermorethanone
al., 2009). With this version, the impact of more than 6500 gridcell,iscomputedinthegridcellwheretheoutflowofthe
reservoirsandregulatedlakescouldbeanalyzed. Themodel lakeorreservoirislocated. Thedifferencebetweenprecipi-
wasusedtogeneratetimeseriesofanthropogenicallyaltered tationandpotentialevapotranspirationisaddedtothewater
river discharge, and of naturalized discharge that would oc- balance of lakes, reservoirs and wetlands, thus taking into
curiftherewerenodamsorwaterwithdrawals.Thisallowed accounttheeffectofthesurfacewaterbalanceoncellrunoff.
thequantificationofanthropogenicriverflowalterations. Globallakesandreservoirsaredefinedbasedontheirsize,
exceeding a surface area of 100km2 or a maximum storage
capacityof0.5km3. InformerversionsofWGHMincluding
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2416 P.Do¨lletal.: Global-scaleanalysisofriverflowalterations
WGHM 2.1f (Hunger and Do¨ll, 2008; Do¨ll and Fiedler, 2.1.2 Reductionofriverflowduetohumanwater
2008),reservoirsweremodeledlikenaturallakes,whereout- withdrawals
flow is computed as a nonlinear function of water storage.
Evapotranspiration from lakes (and wetlands) is reduced at Forthecomputationofindicatorsofriverflowalterationdue
lowstoragevalues,andoutflowisstopped(HungerandDo¨ll, to human water withdrawals, domestic, industrial and live-
2008). InWGHM2.1gusedhere,reservoirmanagementis stock water use in 2002 as computed by the respective Wa-
simulated following the approach of Hanasaki et al. (2006) terGAPwaterusemodelswastakenintoaccount. Irrigation
which is explained in Sect. 2.1.3 below. In addition, the waterusewascomputedaccordingtoDo¨llandSiebert(2002)
database of lakes, reservoirs and wetlands that was used in using, as input, 1) version 4.0.1 of the Global Map of Irri-
version2.1f(LehnerandDo¨ll,2004),hasbeenenhancedby gatedAreasGMIA(Siebertetal.,2005),(2)estimatesofac-
inclusionofalargernumberofman-madereservoirs(comp. tuallyirrigatedareapercountryin2002and(3)theclimate
Sect.2.1.3). datatimeseries1961–1990,totakeintoaccounttheeffectof
Important WGHM inputs are time series of monthly val- climate variability on irrigation water use. While domestic,
ues of climate variables as well as information on soil and industrial and livestock water uses are assumed to be con-
land cover. Monthly climate data are downscaled to daily stantwithineachyear,irrigationwaterusevariesfrommonth
data, in the case of precipitation using the number of wet tomonth. InWGHM,theeffectofhumanwaterwithdrawals
dayspermonth. Monthlyclimatedata,exceptprecipitation, issimulatedbysubtractingtotalconsumptivewaterusefrom
areprovidedbytheCRUTS2.1dataset(MitchellandJones, river discharge, or from the water stored in lakes and reser-
2005). Asprecipitationinput,0.5◦ griddedmonthlytimese- voirs,ifthereareanyinthegridcellandthereisnotenough
riesoftheGPCCFullDataProductVersion3(Fuchsetal., water available from the river itself. Consumptive use of a
2008)wereused,togetherwiththenumberofwetdaysfrom cellissuppliedfromthecellitself, orfromtheneighboring
theCRUTS2.1dataset. cellwiththehighestlong-termaverageriverdischargeifnot
enoughwaterisavailableinthecellitself.
2.1.1 Specificationofmodelruns ConsumptivewateruseisparticularlyhighinIndia, Pak-
istan, partsofChinaandtheUSAandintheMediterranean
Five time series (ANT, NAT, RES, USE, ANT LAKE) of
region,mainlyduetothelargeirrigationareasthere(Fig.1a).
griddedmonthlyriverdischargefrom1961–1990werecom-
Global consumptive water use has more than doubled be-
putedbyWHGM,whichwerethenusedtoquantifytheindi- tween 1951 and 2002, reaching about 1300–1400km3/yr
cators of river flow regime alteration described in Sect. 2.2.
around2000(Fig.1b).Irrigationaccountsformorethan90%
In our analysis, ANT conditions refer to the flow regime as
oftheglobalconsumptivewateruse. Indryyears,irrigation
impacted by human water withdrawals as well as by reser-
water requirements are particularly high, which results in a
voirs and regulated lakes. This simulation is the standard
strongeranthropogenicreductionofthealreadynaturallylow
WGHM simulation for which tuning was performed. Dur-
riverdischarge.
ingtuning,observedlong-termaveragedischargeatthebasin
Duetovariousreasons,itisnotalwayspossibleinWHGM
outletwascomparedtomodeledlong-termaveragedischarge
tosubtractthetotaldailyconsumptiveusefromrivers,lakes
duringtheobservationtimeperiods.Modeleddischargetook
or reservoirs, due to a lack of water. One reason is the
into account the time-varying consumptive use during the
likely overestimation of irrigation water use by the Water-
tuningperiod,butitwasassumedthatthereservoirsexisted
GAP irrigation water use model (Do¨ll and Siebert, 2002),
duringthewholetuningperiod.NATreferstothenaturalized
as in dry years, farmers might not have enough water to ir-
regimeascomputedbyarunwiththetunedmodelinwhich
rigate all fields with the optimal amount. Another reason
there are no water withdrawals and in which all reservoirs
may be long-distance water transfers, which are not repre-
areremovedwhileregulatedlakesarenottreatedlikereser-
sented in WGHM. In addition, non-renewable groundwater
voirsbutlikenaturallakes. UnderRESconditions,thereare
iswithdrawninreality,e.g. intheUSA,Libya,Saudi-Arabia
no water withdrawals but reservoirs and regulated lakes ex-
or China (Custodio, 2001; Foster and Loucks, 2006). Cur-
ist. UnderUSEconditions,theimpactofwaterwithdrawals
rently,wecannotmodelgroundwaterwithdrawalsexplicitly
on river discharge is simulated but not the impact of reser-
becauseitisnotknown(globally)whichpartofthewateruse
voirs and lake regulation. To show the effect of the newly
comesfromgroundwaterorsurfacewater. Thus,inWGHM,
implementedreservoiralgorithm,themodelrunANTLAKE
weattempttowithdrawallwaterfromsurfacewatersources.
wasdesignedinwhichallreservoirsweretreatedlikenatural
If on any day there is not enough water available in sur-
lakes,likeinpreviousmodelversions. Inthefollowingtwo
face waters to satisfy the consumptive use, the model will
sections, the methods to simulate the impact of human wa-
take out this consumptive water use later in the year or in
terwithdrawalsandofdams/reservoirsonriverdischargeare
the next year. This approximates withdrawals from renew-
explainedindetail.
able groundwater resources, as, in reality, groundwater can
bewithdrawneveninperiodswithlowriverflows. Thede-
layed satisfaction of water requirement leads to a stronger
Hydrol. EarthSyst. Sci.,13,2413–2432,2009 www.hydrol-earth-syst-sci.net/13/2413/2009/
P.Do¨lletal.: Global-scaleanalysisofriverflowalterations 2417

a)

1500
households
1250 industry
livestock
irrigation
1000
actual use
r
a
e
y 750
³/
m
k
500
250
0
1 4 7 0 3 6 9 2 5 8 1 4 7 0 3 6 9 2
5 5 5 6 6 6 6 7 7 7 8 8 8 9 9 9 9 0
9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 0
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2

b)
Fig.1.Consumptivewaterusein2002,inmm/yr(a),andtimeseries1951–2002ofglobalconsumptivewateruse,usingclimateandirrigated
areasofparticularyear(b),assimulatedbytheWaterGAPwaterusemodels. InFig.1a,thelocationofthefourbasinsdiscussedinSect.4
isshown. InFig.1b,actualusereferstothepartofthecomputedconsumptiveusethatcanactuallybetakenoutofwaterstorageinthe
WaterGAPGlobalHydrologyModelWGHM.
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2418 P.Do¨lletal.: Global-scaleanalysisofriverflowalterations
◦
Fig.2.Reservoirareainpercentof0.5 gridcellarea,andlocationofregulatedlakes.

dischargereductionintheriver(ascomparedtosimulations The new reservoirs and regulated lakes data set includes
wheredelayedsatisfactionisnotallowed),whichismorere- 6553reservoirsand52regulatedlakes(Table1andFig.2).
alistic if groundwater that is connected to surface waters is It was derived by adding additional reservoirs from a pre-
actuallywithdrawn. Also,groundwaterwithdrawalsinacer- liminary(July2008)versionoftheGRanDdatabase(Lehner
tainmonthleadtodelayedresponseofbaseflowtotheriver, et al., 2008; Lehner et al., 2009) to the 886 reservoirs in-
whichisalsosomehowreflectedbythedelayedsatisfaction cludedinWGHM2.1f. ForWHGM2.1f,theGlobalLakes
approach. Nevertheless,actualtemporalvariationsoftheef- and Wetlands Database of Lehner and Do¨ll (2004) had al-
fect of water withdrawals on surface water flows are only ready been augmented by 64 reservoirs. The development
approximatedveryroughly. The“actualuse”lineinFig.1b of the GRanD data set aimed at including, as polygons, all
showsthatthefractionofwaterdemandthatcanbefulfilled reservoirs world-wide with a storage capacity of more than
from renewable water resources has been decreasing in re- 0.1km3. WhileforEuropeandtheUSA,thisgoalwasprob-
centdecades,inlinewiththeincreasingdemand. Thediffer- ably reached, it is believed that the dataset is incomplete
encebetween“actualuse”andtotaldemand,whichreaches particularly in China, India and South America. GRanD
a maximum of about 20% of the demand, is expected to be doesnotdistinguishbetweenregulatedlakesandreservoirs.
causedmainlybyoverestimationofactualwaterwithdrawals Therefore,all“global”reservoirs(withanareaofmorethan
duetodeficit(sub-optimal)irrigation,andbywithdrawalof 100km2 or a maximum storage volume of at least 0.5km3)
non-renewablegroundwater. Whethertheimperfectconsid- were checked to decide whether they are actually regulated
eration of water use leads to an over- or underestimation of lakes. Thisresultedintheidentificationof52“global”regu-
the reduction of river flows due to human water use is not latedlakes,inadditionto1022“global”reservoirs. “Global”
known,bothattheglobalandthegridscales. reservoirsandlakesareassumedtobefedbyriverdischarge
fromtheupstreamcell,whilesmallerreservoirsareassumed
2.1.3 Modificationofriverflowsduetoreservoir to be “local”, i.e. they are only fed by the runoff generated
operation withinthegridcell.
ThemajorityofreservoirsareinNorthAmericaandAsia
Forthisstudy,weneededtodistinguishbetweenman-made
(Fig. 2). The surface area of the reservoirs and regulated
reservoirs and regulated lakes, i.e. natural lakes whose out-
lakesis291000km2 and124000km2,respectively,ascom-
flows are regulated by a dam. This was required because
pared to a total of 254000km2 in version 2.1f. Maxi-
under naturalized conditions (NAT), reservoirs do not exist
mum storage capacity of reservoirs and regulated lakes is
atall,whileregulatedlakesaretreatedasnaturallakes. Un-
5930km3 and 405km3, respectively, vs. 4642km3 before
deranthropogenicallyalteredconditions,reservoirsandreg-
(Table1). Pleasenotethatmanyofthenewreservoirswere
ulatedlakesaremodeledbythesamealgorithm.
formerly included as lakes. The newest dams taken into
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P.Do¨lletal.: Global-scaleanalysisofriverflowalterations 2419
Table 1. Reservoirs and regulated lakes taken into account in this study. Data based on a preliminary version of the GRanD data base,
(Lehneretal.,2008,2009).
number surfacearea[km2] storagecapacitya[km3]
oldb reser- regul. oldb reser- regul. oldb reser- regul.
voirs lakes voirs lakes voirs lakes
Africa 170 678 2 38899 40238 67380 1302.7 1807.3 90.5
Asia 171 1952 9 47914 61607 35939 804.7 877.3 206.5
Europec 150 1097 15 45525 42340 10313 419.0 541.3 53.4
Oceaniad 30 238 0 5303 7899 0 80.0 110.0 0
N.America 269 2302 25 69051 87663 9735 1250.9 1590.7 54.5
S.America 96 288 1 47610 51169 147 785.7 1002.8 0.6
Global 886 6553 52 254301 290916 123513 4642.0 5929.5 405.4
aOnly672reservoirsin“old”versionand6512reservoirsinthecurrentversionofthereservoirsandregulatedlakesdatasetwereusedto
calculatethestoragecapacitybecauseoflackofstoragecapacitydata.Storagecapacityofregulatedlakesincludesall52regulatedlakes.
btakenintoaccountinpreviousWGHMmodelversion2.1f(HungerandDo¨ll,2008).
cEurasiaissubdividedintoEuropeandAsiaalongtheUral;TurkeyisassignedtoAsia.
dincludingAustralia,NewZealand,thePacificislandandPapuaNewGuinea.
account in this study were finished in 2006 but the data set ordowntothenextreservoirortherivermouth. Thisisdif-
certainly does not cover all reservoirs that existed in 2006. ferent from Hanasaki et al. (2006), who took into account
TheThreeGorgesDamontheYangtzeRiverinChinaisin- wateruseinamaximumof101◦gridcellsdownstream,and
cludedbutnotthedamsattheNarmadaRiverinIndia. preferred water withdrawals to consumptive use. With the
The reservoir operation algorithm of Hanasaki et shorter range in the WGHM version, we mostly avoid that
al.(2006)wasimplementedinWGHMfor1074globalreser- thereismorethanonereservoirthatcouldprovidewaterfor
voirsandregulatedlakes,whileflowdynamicsoflocalreser- a certain cell. Overflow occurs if reservoir storage capacity
voirs were modeled like those of natural lakes. One reason wouldbeexceeded.
for the latter is that the required lumping of all local reser- In WGHM, reservoir storage is not allowed to fall below
voirswithinagridcellintoonelocalreservoirpercellneces- 10%ofstoragecapacity,neitherduetoreservoirreleasesnor
sarilyleadstoa“blurring”ofthespecificreservoircharacter- duetoconsumptivewateruse. Reservoirevapotranspiration
istics,suchthatforlocalreservoirs,thereservoiralgorithmis isreducedwithdecreasingreservoirstorage,bymultiplying
notexpectedtosimulatewaterstorageandfluxesbetterthan potentialevaporationwithareductionfactorr,computedas
thelakealgorithm. (cid:18)|S−S |(cid:19)2.814
Hanasakietal.(2006)developedtwodifferentalgorithms, r=1− max (1)
S
max
oneforreservoirswithirrigationastheirmainpurpose,and
anotherforallotherreservoirtypes.Inbothcases,annualre- withS actualreservoirstorage[m3]andS storagecapac-
max
leaseisafunctionofthelong-termaverageannualreservoir ity of reservoir [m3]. With Eq. (1), reservoir evaporation is
inflowandrelativewaterstorageatthebeginningoftheoper- reducedby15%ifreservoirstoragereacheshalfthestorage
ationalyear. Theoperationalyeariscomputedbasedonthe capacity and by approximately 50% if reservoir storage has
seasonalflowdynamicssincenoindependentdataareavail- decreasedto20%ofstoragecapacity.
able. Different from Hanasaki et al. (2006), in WGHM the For900ofthe1074globalreservoirs(andregulatedlakes),
annual release is a function of the long-term average value informationwasavailableonthemainpurposeofthereser-
of reservoirs inflows plus the difference between precipita- voir,eitherirrigation(249)orothers(651).Fortheremaining
tionandevaporationoverthereservoir,asthelong-termav- 174waterbodies,themainpurposewasestimatedbasedon
erageannualoutflowofareservoirdependsnotonlyonthe consumptiveirrigationwateruseinthefivegridcellsdown-
inflows but also on the reservoir water balance, in particu- streamofthereservoir. Ifthisvalueusewaslargerthanthe
lar in case of large reservoirs (and regulated lakes). In the 75% quantile of the irrigation water use downstream of the
case of non-irrigation reservoirs, monthly outflows are as- known non-irrigation reservoirs, the reservoir was assumed
sumed to be constant throughout the operational year. The to be an irrigation reservoir. Six of the 1074 reservoirs had
monthly fluctuation of releases of irrigation reservoirs de- anegativesumofinflowandverticalreservoirwaterbalance
pends on monthly downstream consumptive water use, tak- inWGHMandhadtobetreatedasnaturallakes.
ingintoaccountwateruseinthenextfivedownstreamcells,
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2420 P.Do¨lletal.: Global-scaleanalysisofriverflowalterations
The performance of the reservoir algorithm in WGHM
Oroville
was tested by comparing time series of observed monthly
outflows from reservoirs to modeled values, distinguish- Oahe

ing four cases: reservoirs modeled according to the de- Missi Falls

scribed reservoir algorithm (ANT), reservoirs modeled as Libby
lakes(ANTLAKE),noreservoirsmodeledbutconsumptive Kettle Rapids
water use taken into account (USE), and naturalized condi-
Jenpeg
tions without reservoir and use (NAT). The observed reser-
voiroutflowdatawereobtainedfromHanasakietal.(2006) Grand Rapids

and included 29 reservoirs with more than 10 years of data Glen Canyon

thataremostlylocatedinUSAandCanada. Tenofthereser- Garrison
voirsaremainlyusedforirrigation.Thebestcorrespondence Fort Randall
to observed reservoir outflows is achieved with ANT (i.e. ANT
Fort Peck
withthereservoiralgorithm)for9outof10irrigationreser- ANT LAKE
Flaming Gorge
voirs(Fig.3b)andfor15outof19non-irrigationreservoirs USE

(Fig. 3a). If these reservoirs are modeled like lakes, model Falcon NAT

performanceismostlybetterthanifitisassumedthatthere EB Campbell
is no surface water body at all (USE and NAT). However, Dworshak non - irrigation reservoirs
formanyreservoirsthediscrepanciesbetweenmodeledand
Canyon Ferry
simulatedmonthlyoutflowsremainhigh,duetoerroneously
Buford
modeled reservoir inflows. For simplicity of analysis, wa-

ter use for 2002 and not the mostly lower values during the Big Bend

observation years were taken into account, which is not ex- Akosombo
pectedtohaveasignificantimpactontheanalysis. Theroot
0 1 2 3 4
meansquarederrorsshowninFig. 3arelargerthanthoseof a)
RMSE
Hanasaki et al. (2006), as Hanasaki and colleagues applied

observed and not modeled river discharge as input to their
Yellowtail
reservoirmodel.
Trinity ANT
Theeffectofthereservoiralgorithmonthequalityofcom-

ANT LAKE
putedmonthlyriverdischargeatthe1235tuningstationswas Sirikit
USE
investigated by comparing the modeling efficiencies (also Palisades
NAT
calledNash-Sutcliffecoefficients)foramodelrunusingthe
Navajo
reservoiralgorithm(ME )andamodelrunwherereservoirs
r
Hungry Horse
were modeled as lakes (ME). Monthly time series of ob-
l
served river discharge were provided by the Global Runoff Grand Coulee
DataCentre(http://grdc.bafg.de). MEisdefinedasthemean Bhumibol
squarederrornormalizedbythevarianceoftheobserveddata irrigation reservoirs
Amistad
subtractedfromunity,andrangesfromminusinfinitytoone
(Janssen and Heuberger, 1995). While a ME-value of one American Falls

represents a perfect fit of simulated and observed time se- 0 2 4 6 8
ries,valuesbelowzeroindicatethattheaverageofobserved b) RMSE
dischargewouldbeabetterestimationthanthemodel. ME
represents model success with respect to the mean as well Fig.3. ValidationofWGHMreservoiralgorithmagainstobserved
as to the variance of the observations. Among the 937 sta- reservoir outflow for non-irrigation reservoirs (a) and irrigation
tionswithME >0,themodelingefficienciesdifferedbyless reservoirs(b). OutflowdatafromHanasakietal.(2006). RMSE:
r
than 0.1 for 836 stations, due mostly to the nonexistence of rootmeansquarederror.
largereservoirsupstream. ME was0.1–0.3unitsbetterthan
r
ME at 32 stations and 0.3–0.5 units better at 36 stations.
l
However, the reservoir algorithm caused a ME decrease of 2.2 Indicatorsofriverflowregimealteration
0.1–0.3(0.3–0.5)at27(6)stations.
Wedevelopedsixdifferentindicatorsofriverflowregimeal-
teration that are ecologically relevant and can be computed
by WGHM in a rather reliable manner (Table 2). The In-
dicatorsofHydrologicAlterationsetofRichteretal.(1997)
wasdevelopedtoguidetheoperationofindividualreservoirs.
Hydrol. EarthSyst. Sci.,13,2413–2432,2009 www.hydrol-earth-syst-sci.net/13/2413/2009/
P.Do¨lletal.: Global-scaleanalysisofriverflowalterations 2421
Table2.Sixecologicallyrelevantindicatorsofriverflowalterationsduetohumanwaterwithdrawalsandreservoirs.
indicator question definition ecologicalrelevance
ILTA How are long-term average river differences between long-term average number of fish speciesa,
flowsaffected? annual river discharges under anthro- groundwater-dep. floodplain
pogenically impacted and naturalized vegetation
conditions,inpercentoflong-termaver-
ageannualriverdischargeundernatural-
izedconditions
ILF How are statistical low flows difference between Q90 (monthly river habitat conditions, connectivity
affected? discharge that is exceeded in 9 out of channel/floodplain, wastewater
10months)underanthropogenicallyim- dilutionb
pactedandnaturalizedconditions,inper-
centofQ90undernaturalizedconditions
ISA How is the seasonal amplitude difference in seasonal amplitude (max- habitat availability in particular on
affected? imum minus minimum long-term aver- floodplains
age monthly river discharge) under an-
thropogenicallyimpactedandnaturalized
conditions,in%ofamplitudeundernatu-
ralizedconditions
ISR How is the seasonal regime meanover12monthlyvaluesofabsolute habitat conditions, compatibility
affected? differencesbetweenunderanthropogeni- withlifecycleoforganisms
cally impacted and naturalized condi-
tions in % of discharge long-term aver-
agemonthlyriverdischargesundernatu-
ralizedconditions
ITS What seasonal flow shifts have temporal shift of month with maximum compatibilitywithlifecycleofor-
occurred? river discharge, in months (if negative, ganisms
this month occurs earlier due to anthro-
pogenicimpact)
IIV Howistheinterannualvariabilityof number of months (Jan, Feb, etc.) in habitatconditionsforaquaticorgan-
monthlyflowsaffected? which the coefficient of variation of isms
monthlyflowsincreasesminusthenum-
berofmonthsinwhichitdecreases(−12,
−10,−8,...,+8,+10,12)underanthro-
pogenicallyimpactedconditionsascom-
paredtonaturalizedconditionsc
aXenopoulosetal.(2005)
bGibsonetal.(2005)
cComputedonlyforcellsinwhichthecoefficientofvariationchangesbyatleast10%inanymonth.
In these cases, daily discharge measurements are generally Indicator I is taken from Black et al. (2005; their in-
SR
available. Therefore, most of the 32 indicators proposed dicator 1a), while I is similar to indicator 3a of Black et
TS
by Richter and colleagues require daily discharges and thus al.(2005)butappliedformonthlyinsteadofdailydischarge
cannotbecomputedwellbyaglobalhydrologicalmodelthat values.Blackandcolleaguesalsosuggestedlookingnotonly
is driven by monthly climate data. Therefore, we only con- at the changes of mean values between natural and anthro-
sideredindicatorsthatarebasedonmonthlyandannualriver pogenicconditions,butalsoonthechangesofthecoefficient
discharge estimates. Please note, however, that neverthe- ofvariation. Weadaptedthisideawhenwedevisedindicator
lesstheuncertaintyofthecomputedindicatorsisveryhigh. I .
IV
Whencomparingobservedtosimulated(ANT)valuesofthe
flow regime indicators used to derive the indicators of river 2.3 Estimationofdecreaseoffreshwaterfishrichness
flowalteration(Q aswellasmeanandinterannualvariabil-
90
ityofmonthlyflows),thefitisgoodinsomebasinsandbad
Xenopoulos et al. (2005) derived a regression equation be-
inothers,oftendependingontheappliedglobalprecipitation
tween the number of freshwater species in river basins and
dataset.
the long-term average river discharge (1961–1990) at the
mouth of the basins. They considered data from 237 river
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2422 P.Do¨lletal.: Global-scaleanalysisofriverflowalterations
basinslocatedbetween42◦Nand42◦S.Thenumberoffish Waterwithdrawalsarebyfarthedominantreasonforthe
species mainly relates to endemic fish, with nonindigenous anthropogenic decrease of long-term average annual river
species being assumed to be less than 5%. Long-term av- discharge, the areas of strong decrease (high negative val-
erage discharge was computed with a previous version of ues,Fig. 4d)coincidingwiththeareasofhighconsumptive
WGHM (Xenopoulos et al., 2005). Fish species numbers wateruse(Fig. 2a). AnexceptionishumidSoutheastAsia,
inriverbasinswerefoundtodecreasewithdecreasinglong- where high consumptive irrigation uses do not lead to high
termaverageriverdischargeaccordingto I valuesbecauseriverdischargevaluesarehigh.Globally,
LTA
16%ofthegloballandarea(notconsideringGreenlandand
Antarctica) suffer from an anthropogenic decrease of long-
Lognumberoffishspeciesinbasin=
term average annual river discharge of at least 10% of the
0.4·logmeanannualdischargeatbasinoutlet(m3/s) naturalized value (Table 3). With “16% of the global land”
+0.6242,r2=0.57 (2) areawemeanthat0.5◦gridcellsthatcover16%oftheglobal
landareaffectedbysuchadecrease. Intheseareas, theav-
Xenopolousetal.(2005)usedEq.(2)topredictdecreasesof
eragedischargedecreaseamountsto35%(Table3),andnot
fishspeciesrichnessduetofutureclimatechangeandfuture
onlyriverwaterlevelsbutalsogroundwaterlevelsinthead-
waterwithdrawals. Here,weappliedtheregressionequation
jacentfloodplainsareexpectedtobesignificantlydecreased,
totranslateindicatorI intoadirectindicatorofachange
LTA negatively affecting riparian vegetation. Based on the work
inthebioticcomponentoffreshwaterecosystems. Wecom-
byXenopolousetal.(2005), weexpectthatthedecreaseof
putedhowfishspeciesrichnessundernaturalizedflowcon-
long-termaverageriverdischargehasledtoadecreaseinthe
ditions has decreased due to human water withdrawals and
numberofendemicfishspecies(comp. Sect.3.7).
reservoirs,providingestimatesfortheupstreambasinofeach
0.5◦gridcell.
3.2 Anthropogenic impact on statistical monthly low
3 Results flowQ90(ILF)
3.1 Anthropogenicimpactonlong-termannualaverage
discharge(ILTA) NaturalizedstatisticalmonthlylowflowQ90iszeroinmany
aridgridcells(Fig.5a). Reservoirsandwithdrawalshaveled
Total discharge into oceans and internal sinks is computed to wide-spread decreases of Q (negative I ) but also in-
90 LF
to be 38164km3/yr under anthropogenically altered condi- creasesalongsomerivers(Fig.5b).Theincreasesarecaused
tions(ANT),comparedto39549km3/yrfornaturalizedcon- by reservoirs or the regulation of natural lakes (Fig. 5c), as
ditions (NAT) (climate normal 1961–1990, without Antarc- dams generally have the purpose to make river flow tempo-
tica). Thus, dams and water withdrawals (in 2002) have rally more homogeneous to allow for hydropower produc-
lead to a decrease of global river discharge of 3.5% and a tion, flood protection or water supply. Examples are the
corresponding increase in evapotranspiration. Water with- Nile just downstream of Lake Victoria, which is regulated
drawalsalone(USE)wouldhavecausedadischargedecrease by a dam for hydropower production, but also the north-
of 2.7%, while dams alone (RES) would have led to 0.8% ern Nile where low flows have been increased by five dams
lessdischarge. in Ethiopia as well as by the Aswan Dam. The effects of
Figure 4 shows naturalized long-term annual river dis- a large number of dams are visible in India, Southeastern
charge (Fig. 4a) as well the I indicator (Fig. 4b). I Africa, SpainandintheUSA.Somereservoirsinsemi-arid
LTA LTA
indicatesthatlong-termaverageannualdischarge(1961–90) regionshaveledtoadecreaseofQ (positiveI )because
90 LF
hasdecreasedduetoanthropogenicimpacts,withdecreases theadditionalopenwatersurfacescausehigherevaporation
reachingupto100%ofnaturaldischarge. Themostaffected (Fig. 5c). This has decreased long-term average discharge
areas are the western and central USA, Mexico, the west- so much that temporal homogenization of discharge cannot
ern coast of South America, the Mediterranean rim, South- balance this decrease. The negative impact of water with-
ernAfrica,thesemi-aridandcountriesoftheNearEastand drawals on Q is larger than the impact on long-term av-
90
Western Asia, Pakistan and India, Northern China and the eragedischargeifexpressedin%decreasefromnaturalized
AustralianMurray-DarlingBasin. Bothreservoirs(Fig. 4c) conditions(comp. Figs.5dand4d). Themainreasonforthis
andhumanwateruse(Fig.4d)haveledtoadecreaseofdis- is that Q values are smaller than long-term average dis-
90
charge. According to WGHM, the damming of a few lakes charge values. Decreases have a particular negative impact
(e.g. Lake Baikal in Russia) has caused a small increase of on habitat availability. Globally, Q has decreased by, on
90
discharge compared to the situation without a dam, i.e. if average,57%on26%ofthelandarea,mostlyduetohuman
theyaremodeledlikenaturallakes(Fig.4c). Thisisrelated wateruse.Ithasincreased,byatleast10%,on5%oftheland
tothedifferentwaterlevelvariationsincaseofreservoirsand area,duetoreservoirs,withanaverageincreaseof161%as
naturallakes,whichleadtodifferentevaporationvalues. comparedtonaturalizedconditions(Table3).
Hydrol. EarthSyst. Sci.,13,2413–2432,2009 www.hydrol-earth-syst-sci.net/13/2413/2009/