Estimation of Climate Impact on WaterAvailability and ExtnemeEvents for Snow-Freeand Snow-Affected Catchmentsof the Murray-Dartng Basin* S Yu Schreideq PhD MSc, BSc, Resealch Fellow Al fakeman**, PhD BSc,Professor Centre for Resource and Environmental Studies, AI$U PH Whefton, PhD BSc, Senior Research Scientist A B Pittock, PhD, BSc, Chief Scientist, Leader of Climate Impact Group Division of Atmospheric Research,CSIRO
SIIMIv/IARY Thc pssihteimpacts of clinute clungeon umterauitlability arearulysed for eastenBasins of theMuray-Darling DiainageDioision AvtOOD in Victoria.This rcgion uns stuilieil becau*of its imryrtance to umtersippty fm Austntkn rural inilustry,sperially inigation saryIy.It includa the Goulburn,Ooens and Kieua Basinsand thc Victnian part of tlu UpperMuttay Basin.
TIu conceptualrainfutl-runoff moilel IHACRESuas selectdas tlu strutfloat.prfilPf ryL.lt hasbeen suc' cessfultyutnratea'ana oaiiatd for the snow-freeGoulburn anil Ouns Basin#zoand for tlu snowaffected Xictn Easinand Mitta-Mittn utihnent in the UpperMunay Basint. In thelaftn use, an mrydtiul snowmcltl accumulntionmodel, baxd on a modifieditegret4ay appoadt, uns appliedin miler to owert snou melt ucess and snw accumulationlosses into Lquioalattrainplti, which wasised as an input to ttu IHACRESmoilel. Seasonalchange smurios for the regionalclimate,relcaxlba tly O-toisionof AtnnrephnlcResut& CSIRC,fol the years2ff,id and 2070ioere usdto transformdaity historiul ctimatedata. These anil othq limitationsof tlu approachare discussed. Estimates of streamftw clungesfor tlu climatescmariu unre obtainedfor all Basins underconsideratbn.
Climate impactswne considnedfrcm two pmpectioes:impacts on the annualand monthly dischargein the Basins,and impcts on theprobabitity of extranena*s suchas floods and droughts.As the scauria.Pr@id: q olsesToete unsidercd:'mwt ilry' rangeof possiiteclanga to Uothtaipiranre and pecipitatan, two ryy wt' clhnntii clunges Win ntes (2030and 2070. lJnilq stiNatd assumptions, a"i'*wi for'nost 1unrc .strumflout wasantsiderably reduced foi ttft itry' (pssimistid scauriosin bothsnryfrcj and mow affi regions. ooIume-vnsrduced by 287o- 38% 2030anil 53%- 64Vo 2070,Thcdcoux was slightlyaccentu- Annual 'mostfor fa ateilin the snow-fru utchmhtts. The wet' (optimistic)scau/ros ptooidtt^diffaettt for snow-free llrycts' andsnm; affecteit'catchtnants:thex changesare negligtblysmatl GSVo to +4Voat 20B;Aand |Vo +6Voat 2070for thesnow-free ann, butlaryn (7Vo- 77%inmtxit2OSO anit72Vo - 2!Voat 2070) fot mow+ffectd Basins.
In estittutingthe impact of ctinute clungeon tlu gobabilityof atrme @ents,thc sndusion ftom our assumV in tiu pnbabiltilrsol sUputitA lewtsin the arcabutt 50*70%at 2030and tionsis tlutlnctu*s food'[ng'mai future iniOn at 2070for futh Wes of utchmentsfor tle wet' us xauia Tlnx probabilitia are slightly higha for snw affectd regbns. bothtypes Theyobability offlaod nentsamputed forthe'nnst dry' scauriw rapitllyilenuses at thex ilatesfor of utctmenti. i6r tte snow 1 INTRODUCTION climatechanges, induced by inoeasing greenhousegas con- centrationsin the Earth's ahosphere, is a temperaturein- 1.1 Rationaleand background crease(the global waruring effect) and lesscertain dnnges in precipitation-Future dimate drangesmay bring an asso- Analysis of possibledimate impacts on surface water re- ciatedsignificant variation in water zupply with subsequent sourc€sin the MDDD in relation to dimate forcing is e,x- efiectson demand for water and other related rcsotuc€s. tremely important for water planning and was the main Reductionof water availability can lead to an incase in prob obFctive of the work reported here.The naturc of poosible water use conflicts, causing serious socioeconomic lesrs.Increases in water availability, on the other hand, may opportunities. im- * PaperW l9402ftstsu6mitted to IEAust onl0h/96.PaPet createnew econouric IGrowledgeof the ac&pted on25/71/96- pactsof possibledimate changeson water rcsourc€suray F Also Adiunct Professor,University of !{rbsternAustralia lia tne taking of objective and inforned decisionsabout VoI.2,No.7,7997 AustralianJwnal ol Wata Rrrourczr l "Estimation of climate impact on water availability and extremeevents for snow -frce..." -Schreider lakeman,Wheilon g pittock loss module which harrsforrns measurcd rainfall to excess or effective rainfall; and a linear module defined as a recur- sive relation at time step k (daily here) for modelled streamflow y*, calcrrlatedas a linear combination of its an- tecedentvalues and excessfainfall u*. c€rtainfy about the frequency of low rainfall events under climate change, it is probable that the intensity of laqge The non-linear loss module allows one to take into account rainfalls will increase with future global warminge. An the effect of antecedent weather conditions on the clrrrent analysis of potential changes in streamflow requires a spe-. status of catchment storag€ using a wetness index s*.Here cial effort in some MDDD basins. They are sensitive to mi- the exces rainfall u* is calculated from the measured pre- nor changes in their climatic forcing and show a high level cipitation r* (rainfall or rainfall equivalent of prccipitation) of flow variability. and temperatuie f* using the following recursive relations: Reviews of recent publications devoted to the analysis of sk=rklc + (1 -71 t,(t)) sr_, possible climate change impacb on streamflow can be found in Gleickrrrl Doogd, Fukushima et al.ro and kavesley'e. ur= rrGr + sr/2 (1) Most work related to the possible effecb of global warming on snow-affected regions is devoted to glacierised basins. r*(t)= qexpQlf-trfl The main cons€quenceof warming in these basins, where a huge ice pack has accumulated over thousands of years, is The constant c is calculated so that the volume of excess a dramatic increase in the melting of glaciers. This paper is rainfallis equal to the total streamflow for the period over relevant to theestimation of climaticimpace forBasins with which the model is calibrated. The parameters z" and/are a seasonal snowpack, and where only critical data inpub to be optimised. Catdrment storage or wetness index s* is also a very important "the on precipitation, temperature, elevation and stream dis- characteristic for interpretation of charge are available. snow melt/accumulation prlcesses. It reflecb the infiltra- tion capacity in the area: the higher it is, the lower is the The problem of which meteorological factors most affect infilhation level. ice and snowmelt proceses in different geographical rcgions The linear module and under different climate conditions was discussed in of IHACRES is defined as follows: Aizen and Aizenr. They concluded that the major dimatic - factor for continental regions, where the share of the solar ax=4tvrt azar-z+bnur+ b, ur-, radiation is more than 907oof the total heat balance, is shortwave radiation, whereas for regions with sbong oce- It implies that excessrainfall is considered to havel through two parallel storagesinterprcted anic influence, it is temperature. This conclusion accords as a quick and slow flow (In with our choice of a degreeday approach for the snow melt/ component of river discharge some caseswhere slow accumulation modelling in the present work, because the flow is negligible one storage may suffice). The calibration procedure for study region has primarily oceanic climate. the linear module is based on the Simple Re. trhriable fined Instrumental technique described in Jakeman at al. [13]. The rainfall-runoff model has 6 parameters to be estimated during the calibration procedure t,, f, a, a, bn and Duwith c determined directly by equating the volume of effective rainfall with dischaqge over the calibration pe- riod. Snow melt/accumulationprc,cesseswere taken into account for the snow-affected area of the Kiewa and Mitta-Mitta catchments.A spatially dishibuted snow melt/accumula- tion module based on the modified degree-day approach 12 The model was used to convert measured rainfall to equivalent pre- cipitation, which was used as an input to the IHACRES model.Adetailed description of this module The conceptual rainfall-runoff model IHACRES (Identifi- was presented in Schreider et al.z. caHon of Hydrographs And Components from Rainfall, EvaporaHon and Streamflow data) was developed at the The model's rcliability is illushated by the CenEe for Reourre and Environmental Studies at the Aus- accuracy of the results obtained under historic conditions for the Goulburn, balian National University and the Institute of Hydrology, Ovens, Kiewa and Mitta-Mitta catchments. The absolute UK. It is described in lakeman et al.r3 and Jakeman and relative errors for a long-term validation (10 to 30 years Hornbergerr{. Worldwide applications of rainfall- de. pending on the basin) on independent sfteamflow modelling with IHACRES in catchmenb of dif- daily stream dis- charge data were 1Vo for the Upper Goulbum, ferent size, and under various climatic conditions, can be 8Zo for the lpwer Goulbum, SVofor the Ovens, 7Vo for the Kiewa and found, for instance,in Jakemanet al.r5J6,Post et al.r and Ye 72Vofor the Mitta-Mitta catchmenls6'z'2. et al.t$. The results of calibration and validation of the IHACRES model in the essentially snow-free Goulburn and Daily time series of climate data Ovens Basins can be found in Schreider et al.6e, while were generated by bans- forming historical series using Schreider et al.z describe the resultspf ib application to the average Zochanges based on climate scenarios developed in the Dvision snow-affected Kiewa and Mitta-Mitta catchmenb. of Ahospheric Research CSIROT'2'for two dates in the future: at 2030 and 2070.The IHACRES model was used The IHACRES rainfall-runoff model is a dynamic lumped to calculate the ctranges parameter in streamflow for these scenarios. Daily sfreamflow was model consisting of two modules: a non-linear 'most ,most estimated for wet' and dry, scenariosfor 2030 Austmlian loumalof lhter Rwurces Vol.2,No.l,1997 -, '€stimation of climate impact on water availability and extremeevents for snow-free ..." -khrcider, lakeran' Whctton& Pittock and 2070 respectively.Climate impacts were generatd for tion classeslocated closest to the polar zones(or located mean monthly and annual discharge in the region under highestin mountains)are expected to be partially replaced consideration. by neighbouringvegetation classb that aretypical of more temp€rateclimatic zones.. 1.3 Assumptions This general conclusionis supported by Busby' who ana- lysedpossibleclimatic impactson Australian vegetation There is substantial uncertainty in the magnihrde, timing cover and found that the elevationof heelines in the Al- 'lhsmania and spatial disEibution of climate change. One approach, pine regionsof Victoria and is expectedto increase. used here, is to use scenarios based on dranges to long term A methodologyfor estimating possibleclimate dranges in s€asonal mean values of climate descriptors to transform Australia's terrestrialecosystems is developedin Williams present climatic time series, here being daily precipitation et al.x. It is basedon the analysisof correlationsbetween and temperature. Following this approach, two exheme prcsentvegetation areal distribution and climatic factorsat cases of possible future mean dimatic characteristics were thesesites and subsequentexhapolation of thee relation- considercd: an optimistic scenario, reflecting a minimum ships for fuhrre climatic changes.The shategy forurulated reduction ox, possibly, an increase in river disdrarye (the taking into accountmany factors in- 'most 'most is very sophisticated, wet' scenario) and a pessimistic or dry' sce' cluding conservationimplications and land use changes, nario, where discharge is reduced maximally. The frequency and has not yet beenimPlemented. of rain days and variability of temperature and PreciPila- tion are presumed to remain the same as at preent. This As well as climatic factors,human-induced factors, such as assumption is very strong and altemative approadres are deforescationand natural hazardslike bushfires,also have discusied in Fowler and Hennessy'and Whetton et alP. the potentialto severelyaffect vegebation cover and response in the areaconsidered. Future land use changesin the rural Limitations of this approach are described by Bates et al3. areaswhere the analysiswas implemented can be neglected The direct transformation of historical dimate recotds, us- becausethe area modelled is located mostly in the upper ing Global Climate Model (GCM) outputs, according to alpine areasof all four Basins.Kirkpatrickrz emphasises the changes in mean values, in order to estimate possible di- rctaUvay small loss in the vegetationof Australia's alpine mate impacts may be considered improper due partly to regions,compared with other flora communities. the coarse resolution of GCM spatial grids and the simpli- fied GCM representation of land surface'atmosphereocean In sumnrary from the above brief analysisof possible al- interactions. Theuse of stochastic urodels representing daily terationsin vegetationunder climatechange or induced by weather variations at the site of the hydrological model human activitile, two points can be made. Firstly, boreal flora tends to be replacedby temperatetyP€s. In the catch- ments considered,this meansincreases in the elevation of the alpine tree'line and the line betweenalpine ashesand snow gurls. While the total forestedarea of the catdrments considlred should thereforeincrease in the long term, the variables simulated is realistic, at least in terms of historical periods over which climate impacts are estimated in this climate. The use of Limited Area Models (LAM's) with paper arc too short (about70 years) for foresq to gro_wover higher than GCM spatial resolution, when a LAM:: gng bisiderable areas.Secondly, deforestation due to logging area is comparable with the areas of catdtmenb (0(1@) km'z) is also unlikely in theseareas because most Parts of this considered-for mnoff modelling, is another possible adiunc- region are govemmentallyprotected l-eservesf while the ef- tive solution to this problemm2l. feds of any-bushfiresare likely to beeither spatially rcstricted or short tenn in nature.Thus the assumption,that overall In addition to assumptions about mean seasonal changes vegetationresPonse will remain similar to that over recent hit-toty for the periods when the possibleclimatic impacb on sbeamflow were analysed,s€ems to be quite plausible. Another unknown which will needfurther attention in the However, the vegetation cover and/or its evapotranspiration resPonse may change with future changes in dimatic pattems of temperature, precipitation, net radiation, and fertilisation and stomatal resisiance ef- fects related to increases in carbon dioxide. that no one se€rrs to have been able to discern this effect fiom water balanceanalysis in catchmentsover the last 50 The impacts of dimate on vegetation structure worldwide was corsidered in Monserud et al'z. Climate scenariosbased on four GCM's were applied to the entire globe subdivided into gridcells with resolution 0.5 x 0'5 degree. A modified version of Budyko's vegetation model was applied in-order to calculate thi ratio of annual Pan evaPoration to the an- vation and model error. nual precipitation for every gridcell. The methodolory ap plied-by Monserud et al.z implies that this ratio is a mairr UNDER CONSIDERATION iactor determining boundaries between vegetation zones. 2 TI{E REGION They conclude thatloreal and temperate vegetation zones Kiewa and Murray Basin of ar" to undergo the maximum changes. In par- The Goulburn, Ovens, Upper it"di.t"a Division locatedin the tiarLr, all boreal zones ar€ predicted to shrink. The vegeta- the Murray-Darling Drainage are VoL2, No.l,7997 Austnlianlounul ol WaterResourca "Estimation of climate impact on water availability and extremeevents for snow-free..." -Schreido, lakanan, lNhetton& Pittock \ I --\- I _ I I I ) I I t, \ ) \ \ ) \.1 ,- 1/ 'v; \ [.-aT] ueo rmuat esartg. fiijJ (thdends o, Mt) 0 20 &kn 405231. Nmb€r o{ slrcam 96ugingslatim Figure 1 River nefwork and dischargestations for the catchmentsunder consideration in the Goulburn, Ovens and Kiewa Basinsand for the Mitta-Mitta catchmentof the Upp"t Murray Basin easternpart of the state of Victoria, Ausbalia, and are im- under consideration and relevant referencescan be found portant contributorsto its water supply (Fig. 1). The im- in Schreider et al,Enz. pacts of climate on water availability in this region are of interest for planning purpos€s;the water resourcesof the Goulburn Basinalone prcvide approximatd 407oof total 3 THE CLIMATE SCENARIOS AND GENERAIION irrigation water usein ViCoria. The thee largestwater res- OF THE CLIMATIC TIME SERIES ervoirs of Mctoria, the Dartmouth, Eildon and Hume Lakes with a total capacityover 2000,000ML, are locatedin this Climate scenarios for the Australian region were described area-Analysis of possible impacts was perforured on five in CIG6 and Whettona. They are based on the scenarios of Foups of catchments: future global warming given by Wigley and Rapet'r and local changesin temperature and precipitation derived from 1. C-atchmmtsupsEeam of Iake Eildon in the Goulburn 5 slab ocean GCM's. Their partiorlar realisation for the Vic- Basin: the Big (station 405227in Fig. 1), Upper torian alpine region was prcsented in Schreider et al.x. These Goulburn (405279),famieson (405219) and Delarite scenarios,developed for the Southern coastal region ofAus- (405274) Rivers; halia 0ess then 200 km from the coast), provide a warming 2. C-atchmenbdownstream of Lake Eildon: the Rubicrcn in the year 2030 in the range 05. - 2.OC and in 2070 in the (N5241\, Adreron (4052Cf),Murrindindi (405205)and range 1.0'- 5.0'C. The rainfall change scenarigsfor the Vic- Yea(40,5217) Rivers and King Parrot Creek (405231); torian alpine region are 0 - +2OTofor the summer half-year 3. Catchmentsof the Ovens Basin:the Upper Ovens (November-April) and -7OVo- +70% for the winter half-year (403205), (40323il, Buckland Buffalo (403222), (MayOctober) in 2030. 1n2070 this change is 0 - +40Voand Dandongadale(403218) and King (n3227) Rivers; -20 - +20Vorespectively. In order to characterise a range of 4. The catchmentof the Kiewa River at MongansBridge uncertainty foi future climate changes, two scenarios were (402203); and selected for climate at these two points in time: 'most wet' 5. Thecatchmentofthe Mitta-Mitta RiveratHinnomuniie (minimum warming with maximum increase of precipih- (,m1203). tion) and'most dq/ (maximum warming with maximum 'most decrease of precipitation). The wefl and 'most dr;/ The totat areaof the catchmentsmodelled is around &750 scenarios, selected as an interval within which streamflow km2and the total meanamual dischargemodelled exceeds response could vary in the fuhrre, are summarised in Table 4,000,000Mlper year.A detaileddecription of the Basins I. Austrclian lounalol llhto Rcsrlurce Vo|.2,No.7,1997 '€stimation of climate impact on water availability and extr€meevents for snow-fiee ..." -Schttido,laketnan, WhettonI Pi[ock Table I Climate sc€nariosfor the Victorian alpine region Scenario Waming (" C) Changes Changes in precipiation in precipitation (summer) (winter) 'mostdry'2030 2 0Vo -1OVo 'mostwet'2030 1.5 +20Vo +l0Vo 'most dry'2070 J 0Vo -20Vo 'most wet'2070 J +40Vo +20Vo For all catchments considered the scenarios were applid The small difference in the annual precipitation changes by changing all observed daily temperatures by the scenario between different clusters of snow-fiee and snow-affected increment and by changing precipitation by the scenario catdrments is related to the fact that the part of precipita- percentage on all days with prccipitation. This means (for tion occurring in the winter pedod is not exactly the same 'most wef scenarios) that the frequency distribution of tem- for all groups of catchments. The coruiderable increase cal- perature is not altered, while that of precipitation is moved culated in annual flow for the'most wet'scenarios in snow- toward an increase in the fiequency of heavy precipitation affected areas, compared with almost no change in events in accordance with the trend found on GCM simula- streamflow for snow-free catchments, should be empha- tione4. It should be noted that this method leaves the his- sised. torically experienced year-to-year variability unaltered, but rathersuperimpose this ona trend in the longer term means Figurc 2 shows how the,Syear running mean values for due to dimatic change. annual discharge are affected by the different climate sce- narios forall groupsof catchmenb selectd and all scenarios in Tables II and III. These results ate for the catchments of 4 CLIMATE IMPACTS ON ANNUAL AND the lower part of the Goulburn Basin (snow-free) and for 'most 'most MONTHLY FLOW the snow-affected Kiewa Basin The we( and d4/ sheamflow scenarios for 2030 (dashed lines) and for Changes in mean annual streamflow after application of 2070 (dotdashed lines) might be considercd as upper and the scenarios, listed in Table I, are summarised in Table II lower endpoints for possible annual streamflow fluctuations for snow-free and in Thble III for snow-affected catchments. for future climate changes. Table II Climate impact on annual precipitation and streamflow for selected scenarios in the snow-free region The Goulburn Basin(upper part) Period 2030prccip 2030flow 2070precip 2M0 flow 'most dry' scenario -7Vo -38Vo -13Vo -64Vo 'most wefl scenario +13Vo -37o +27Vo 0% l The Goulburn Basin (lower part) Period 2030prccip 2030flow 2070precip 2070flow 'most dr5/ scenario - 6Vo -34Vo -137o -62Vo 'most wef scenario +74Vo +4Vo +27Vo +6Vo The OvensBasin Period 2030prccip 2030flow 2070precip 2070flow 'most dry' scenario -7% -37Vo -73Vo -63Vo 'most wef scenario +13Vo -2Vo +27Vo +2Vo Table III Climate impact on annual precipitation and sheamflow for selected scenarios in the snow-affected catc.hments The Mitta-Mitta catdrment Period 2030precip 2030flow 2070precip 2070flow 'most dry' sc€nario - 6Vo '32Vo -L2Vo -59Vo 'most wef scenario +7AVo +7Vo +28Vo +72Vo The Kiewa catchment Period 2030prccip 2O?0flow 2070precip 2470flow 'most drl/ scenario - 7Vo -28Vo -13Vo -53Vo 'most wefl scenario +1,3Vo +7lVo +27Vo +2'I7o Austnlian lournalof WaterRrrourca Vo|.2,No.7,7997 "Estimation of climate impact on water availability and exbeme evenb for snow-trce ..." -Schreiden Jakamn, WhettonI Pittxk a) The catchmgnts downstream ol 1000 - Historicalsimulalion a) The catchmentsdownstream of L€keEildon --- 2030scenarios 100 --- 2070scenarios 800 J s 60 a o 3 o 600 o E * (g 20 o o E 400 o o o -20 .J) o 200 o) (u -60 o 04 1955 1960 1965 1970 1975 1980 1985 -100 b) Tho Kiewacatchment 123456789101112 r000 f b)The Kiewa catchment = 800 100 o o o ' 600 o * ou E = d e 400 (UE 20 d q E c 200 o c -20 o o) 0 (u 1965 1970 1975 1980 1985 -ou Year -100 Figure 2 Climateimpact on annualsbeamflow for the four 1 2 'Most 3 4 5 6 7 I I 10 11 12 scenarioslistd in TablesII andIII. wefl and Month 'most dry' limits might be consideredas upp€r and lower endpoints of possible annual streamflowfluctuations for future dimate change Figure3 Climateimpact (in percent)on meanmonthly dis- (a) in (a) the snow-freecatchments of the Goulburn chargefor the snow-freecatchments of the Basin downstreamof Lake Eildon and (b) the GoulburnBasin downstream of lake Eildon and (b) snow-affectedKiewa Basin the snow-affectedKiewa catchment Thedimate impactonmean monthly flowin thelowerpart of the GoulburnBasin for eadr month of the year (Fig.3a) 5 CLIMATE IMPACTS ON EXTREMEEVENTS: was comparedwith the impact on monthly flow in the FLOODS AND DROUGHTS snow-affectedKiewa Basin (Fig. 3b). The 'most wet' sce- 'flood' narios lead to negligible changeduripg late winter-early The term is defined here directly in terms of critical surnmer (August-fanuary)in snow-freeregions and to in- values of streamflow.The more cprnmondefinition of this creasesin mean monthly flow during late summer-early term asa maximumannual (biannual, decennial, etc...) dis- winter (February-fuly).These increases at2070 range from chargeis less convenientfor the purposesof the analysis apprcximately 10VoinJuly up to 457ofor May. Increasesin presentedbelow becausethe daily streamflow recordsare monthly flow were observedfor anery month of the year relatively short for the rivers in the region considered. for the snow-affectedKiewa catchment.They arc higher Analysisof flood frequencychange under different dimatic during late zummer-earlywinter (about 20Voat 2030and scenarioswas implementedfor the snow-freecatchmmt of 50%at 2070 for mean April flow) and lower during late the Upper Ovens River at Bright (gauging station 403205) winter-early surnmer(on averageabout a 157oincrease in and the snow-affectedcatchment of KiewaRiver at Mongans 'flood' flow at 2030and 257oat2070). For the'most dry'scenarios Bridge (402203)(see Figure 1). For the Overs River a a very substantialreduction in streamflowis found in each eventisdefined as a streamflowevent with dischargehigher case;about 35Vorn 2030and 60Voin2070 for snow-freear- than 50 m3/s (cumecs).This thresholdwas chosenarbitrar- eas,and about 25Voin 2030 and 50Voin 2070for snow-af- ily and correspondsto eventsocctrrring approximately once fected regions,on average. every two monthson average.As the absolutevalue of dis- chargeis larger in the Kiewa than in the Upper OvensRivei 'floods'in Figure4 illushates the dimate impact on meanmonthly a larger theshold was chosenfor definition of 'floods' flow at 2070 for the snow-fiee Ovens and snow-affected the Kiewa Basin.There, are defined as streamflow Mitta-Mitta catchmentsfor the 'most dq/ and 'most wef eventswith dischargegreater than 65cumecs (the probabil- scenarios.Under our assumptions,the annual dishibution ity of suchevenb at present,0.024,is almostthe sameas the of monthly dischargeforboth typesof'regions does not shift prcbability of streamflowevents with dischaqgegreater than considerablyfor all climate changesscenarios considered. 50 cumecsfor the Uppet Ovens). August remains the month with maximum dischargefor the Ovens catchmentwhile Septemberand Octoberrcmain TableIV demonstrateshow the frequencyof dischargefor so for the Kiewa catchment. August, Septemberand October(months with the maxi- Australion lourtul of llthter Rrrrurcel VoI.2,No.l,1997 "Estimation of climate impact on water availability and exkeme events for snow-free ..." -Schrcider, lakcman,Wlutton & Pittock 41 The catchmentsof the OvensBasin The Mitta-MittaRiver 200 J presentflow o o scenario o 150 F B o 100 c c o E 50 c (U o 0 23456789101112 0123456789101112 200 100 J o o 80 o 150 F = o 60 100 -c 40 o E 50 (uc 20 o 0 01 234567 89101112 01 234 56789101112 Month Month Figure 4 For the 'most dry' and 'most wef scenariosat2070, climate impact on the annu.ll distribution of mean monthly dischaqgefor the snow-freecatchmenb of the Ovens River Qeftcolumn) and the snow-affected Mitta-Mitta catchment(right column) mum mean value of streamflow discharyefor the maiority 5 DISCUSSIONAND CONCLUSIONS of the rivers under study) varies with time (for the present, 2030and 2070)for these two catdrmenb. Most striking is The investigationof dimate impacb on stneamflowcovered that the wet scenarios,while providing little increasein av- four Basins(&750 km'z) in easternMctoria with a bal dis- erageannual flow, give a large increasein flood frequency chargeof over 4,000,000ML The conceptualrainfall-runoff 'most The probability of flood eventsfor the dr5/ sc€narios model IHACRESwas usedas a tool to calculatethe stream sharply reducesfor thesetwo dates in the future, for both dischargefor hypotheticalfuture dimate conditions at 2030 types of catchments. and2070.Themodel, successfully calibrated and validated on independentdata sets for thesefour Basinsunder present The catchmentwetness index of the IHACRESmodel, s' is dimatic conditions in Schreideretal.a4e, provides a good 'drought' used here to define and to calculatechanges in performancein snow-freeareas (the Goulburn and Ovens drought frequency.The definition of this index is grvm by Basirs) as well as in snow-affectedareas (the Kiewa Basin the recursiverelationship (1) in Section1.2. The probabili- and the Mith-Mitta catchmentin the UpperMurray Basin). ties of s*events with magnitude less than 0.05(a threshold In the latter areat a snowmelt/acanmulation module based 'droughf) 0.05is arbitrarily chosenas a defi5ritionof for the on a modified degee-day apprcachwas applied. The reli- Ovensand Kiewa catchmenb for the two future datesand ability of the model suggestsit can be used for estimation for both types of scenariosare presentedin Table V. Soil of possible climatic impacts on annual and monthly wetnessindex frequencieswere calculatedfor the 3 months strreamflowas well ason the frequenciesof exbemeevents with minimum dischargeJanuary February and March. such as floods and droughts.However, there are several Austmlian loumal of lNater Rcsourca Vo|.2,N0.7,1997 "Estimabion of climate imPact on water availability and extremeevents for snow-free..." -Schreider, laketnan,Whctton I Pittock Thble IV Possible climatic impacts on flood evenb between August and October for the snow-frce Ovens catchment and the snow-affectedKiewa catchment Date and scenario Ovens catchment (snow-free) Kiewa catchment (snow-affected) frequency change frequency change present 0.022 - 0.024 2030 0.004 -82V0 0.004 -83Vo 'most d4/ 2030 0.031 +47Vo 0.039 +62Vo 'most wet' 2070 0.000 -7wvo 0.001 -96% 'most dr5/ 2070 0.0,m +81.Vo 0.053 +t2'!Vo 'most wet' TableV Possibleclimatic impactson droughts betweenJanuary and March for the snow-free t Ovens catchment and the snow-affected Kiewa catchment Date and scenario Ovens catdrment (snow-free) Kiewa catdrment (snow-affected) frequency drange frequency change present 0.76 0.1,44 2030 0.226 +36Vo 0.796 +36% 'mostdr;/ 2030 0.774 +57o 0.145 +|Vo 'mostweY 2070 0.314 +89Vo 0.269 +87Vo 'mostdry' 2070 0.186 +727o 0.151 +72Vo 'mostwefl assumptionsinvolved for this estimationand they arespeci- free and snow-affected catchments. The runoff change cal- fied in Section1.3. culated is small for snow-free areas (-3Vo- +47oat 2030 and OVo- +67o at 2070\, whereas it is higher for snow-affected Scenariosdeveloped for the Australian region with respect Basins:an TlVoincrease for the Kiewa catchment and aTVo 0ochanges in seasonalclimate were employed for estimat- increase for the Mitta-Mitta at 2030; the increases are 21Vo ing possible climate impactson water availability in these and.12Vorespectively for these catchmenb at 2070. As the 'most Basins.Two exheme caseswerc cpnsidered:a dr/ values for snow-free catchments are very close to the pre- scenarioyielding a minimum amount of river runoff and a 'nost dictive error in the model, the current sbreamflow discharge wet' scenarioyielding a maximum amount.These regime could be considered similar to the conditions pro- 'most two casesmight define the lower and upper limits respec- vided by the wefl scenarios. In this case evaporation tively for total discharyeof the rivers in the region coruid- resulting from increased warming approximately cancels ered given our present understandingof the range of un- the maximum possible increase in rainfall. cartainties in estimation future regional climate under the enhancedgreenhouse effect. Even if the climatechange sce. Analysisof climate impactsonmean monthly flow insnow- nariosare subFct to substantialrevision in future,the present affected regions shows that the higher increase in mean rcsults at leastillushate the sensitivity of runoff to changes annual streamflow under the'most wet'scenarios c;tn not in prccipitation and temperature.Under our assumptions, be explained by the rcdistribution 'most of the monthly discharge the reduction in annual dischargefor the dry' sce. by snow melt excessesor snow formation losses. A possi- narioo reaches8Vo -38Voat 2030and 53%- (AVoat 2070;the ble explanation is a different rate of change of evaporation amount of availablewater is reducedmore in snow-fiee losse with possible increase of precipitation for 'the wef than in snow-affectedregiens, although the differencebe sc€narioo. As a considerable increase in precipitation is the 'most 'most tween these two types of catchmentsis small. The main characteristic of the wef scenarios Chble I), a wet' scenariosprovide slightly different impactsfor snow- more significant effect is that the relative losses decrease Australianlounul of l&ter Rc*urces VoL2, No.L,7997 "Estimation of climate impact on water availability and extreme events for snow-free ..1' -Schreider,Jakeman, Whetton & pittock faster with increasesin precipitation in the snow-affected than in snow-free regioni. The result can be illusfrated em- 100 pirically, using long-term streamflow observations for both types of catchments.Figure 5 illustrates the disbibution of annual proportional losses,calculated (1 - as annual run_ 80 OO 860 o o a o o o .340 20 TheOvens River at Bright For climatic impacts on the frequencies of extreme events 0 (flood and drought), the generil conclusion is that flood 200 400 600 800 1000 12oO1400 1600 probabilities are slightly higher for snow-affected catch- 'most 100 menb in the case of the wet, scenarios than thev are for the snow-free catchments. Howeve4, their future growth can be summarised as about S}x.lTVoat 2030 and 16t207o at2070 torboth tlpes of catchmenb. The probabilityof flood 80 'most events under the dr;/ scenarios sharply reduces for snow-free, as well as for snow-affected, catihments. 860 o Drought frequency, as defined by a soil wetness indo<, in- v, ^o 'most (to creased 35% for the dq/ scenario at 2030 and g9% for U' the'most dy' scenarioat2070 forsnow-freeareas and, simi- -9 40 larly,3SVo and.87Vofor the snow-affected Kiewa River. The similarity of results received for snow-fiee and snow-af- TheKiewa River fected regions naturally corresponds to the fact that, even 20 in the alpine areas, the snow pr,cesses are negligibly small during thesummerperiod.These results for flood frequency are similar to thoseobtained by Whetton et al.s but are more 200 400 600 800 1oo0 12oo pessimistic regarding droughts. The effect of a l2Voincrease 14001600 Meanannual precipitation (1000 ML) Figure 5 Proportionalannual lossesfor the snow-freeOv- ens catchments(above) and the snow-affected Kiewa catdrment(below). The regressionlines of proportional losseson annual precipitationare indicated Two important limitations of thd model,s applicability to the estimation of possible climate impact in ihe snow-af- wherea majnr part of the surfaceis coveredby snow.How- fected areas must be mentioned herc. Firstly, the methodol- eve4,this assumptionseerns rcasonable for the catchmenb ogy assumes that the parameters of the IHACRES model, in the region coruideredbecause only llVo to 20%of their as well as those of the snow melt/acctrmulation module, arcasare coveredby snow in winter. remain constant under different climatic conditions. These parameters in turn are a function of the catdrment land- The models,selected for eachof the catchments,were used scape attributes and vegetation cover (see Section 13). The for estimatingfuture climate impactsunder the assump Hon that ltle vggeq-tioneffects on sheam dischargein ttie areaconsidered will remain similar to today. Considerable changesin land use or deforestationin this areain future Tay prcvide more dramatic changesto dischargein these Basins,although suchchanges are unlikely in the areacon- sidered(see Section 1.3). Another limitation of the resulbis relatedto the high level of uncertainty in the estimatedcli_ matic patterns,mirrored in the large-setectea differences in sbeamflowvalues associated with the scenarios. The second limitation is related to the assumption that fluc- Australianlourwlof WataRrsource' Vo|.2,No.l,7997 "Estimation of climate impact on water availability and extremeevents for snow-free..." -Schreider,laketnan,Whetton & Pittock scenarios.The advent of improved GCM's, eg. ones which Dooge JCI. Hydrologic Models and Clmate Change.Journal more explicitly model ocean circulation and ENSO, may of Geophysical Research, 199297(DI:2677 -zffi . also lead to significant future revisions to climate change scenarios. (Updated scenarios were published when the FowlerAM and Hennessy K|. Potentiaitmpa'ctof Global Warm- ing on the Frequency and Mqgnitude of Heavy Precipitation. this paper was under review: CIGt. A pre' manuscript of Natural Hazards, 1995;11 :28$303. liminary analysis showed that updated scenarios reduced 'most 'most the level of uncertainty between wef and d4/ Fukushima Y Watanabe O and Higuchi K. Estimation of scenarios.) This highlights the need for flexible climate SheamJlow Change by Global Warming in a Glacier{overed runoff modelling systems.which can be used to rapidly ex- High Mountain Area of the Nepal Himalaya. Iru Bergman H, amine implications of different scenarios. Lang H, Frcy W, Issler D and Salam B, eds. Snow, Hydrology and Forestsin HighAlpineArcas. IAHS Publ. no 205,191 :181- 188. 7 ACKNOWLEDGMENTS 11. Gleick PH. Methods for Evaluating the RegionalHydrologic Impacts of Global Climatic Changes.Joumal of Hydrology, This work is part of the project "Potential Impact of Cli- 1986'f8:97-176. mate Change on Runoff and Water Availability for lrriga- tion" sponsored by the Rural Industries Research and De' 12. Gleick PH. Clinute Change, Hydrology, and V6ter Resources. (31 -3M. velopment Corporation. We thank climate modellers at Reviews of Geophysics, 7989:27 :38 CSIRO Dvision ofAturospheric Researchfor providing the 13. lakemanAJ, Littlewood IG and Whitehead PG.Computation basis for the climate change scenarios used, and the De. of the lnstantaneous Unit Hydrograph and Identifiable Com- partment of Environment, Sport and Territories for its sup ponent Flows with Application to Two Small Upland Catch- port of the core Climate C-hangeResearch Program in CSIRO menb. lournal of Hyd rology 7990:777 :275-3N. and the Bureau of Meteorology. fakernan AJ and Hornberger GM. How Much Complexity is The snow melt/accumula6on module used for the daily Warranted in a Rainfall-Runoff Model? l4Ater Resources Re. (8) -2649. snow runoff modelling in the snow-affected areas was based searrdr, 19329 :2637 on the approach of Dr. R.Galloway who developed it for 15. JakemanAJ,ChmT-H, Post DA, HornbeqgerGM, Littlewood modelling monthly melt/accumulation in the Australian IG and Whitehead PG. Assessing Uncertainties in Hydrologi- Alpine Region cal Responseto Climate at LaqgeScale. In: WB Wlkinson, Ed. Macroscale Modelling of the Hydrosphere, Wallingfond, UI( We are grateful to Dr David Hansen, Mr Jason Evans and IAHS Publ No. 274, 7993:3747. Dr Roger jones for their valuable corunents on the manu- script. The critical comments of three anonfmous review- JakemanAJ,HombergerGM, ChenT-H and SwankWL Simu- ers were much appreciated. lating the Effectsof ClimaticVariability on CatchmentRunoff. Water ResourcesResearch, 1996, (submitted). 17. Kirkpatrick J.AContinent Transformed:Human Impact on the 8 REFERENCES Natural rrbgetation of Aushalia. Melbourne: Oxford Univer- sity Prcss,794:133. 1. Aizen VB andAizen EM. GlacierRunoff Estimation and Simu- lationof Sheamflowin the PeripheralTerritoryof CentralAsia. 18. KuhnM. Methods ofAssessing theEffecb of ClimaticChanges Snowand GlacierHydrology. Prcceedings of the Kathmandu on Snow and Glacier Hydrology Snow and Glacier Hydrclogy. Symposium,November 1992 IAHS Publ no 218,793,pp.167- Proceedings of the lGthmandu Symposium, November 1992 779. IAHS Publ No 218,1993:73*7M. BatesBC, Charles SP and FlemingPM. $imulationof Daily Oi- lcavesley GH. Modelling the Effecb of Clirute Change on maticSeriesfor theAssessmentofClimate Changelmpacb on Water Resources- a Review Climatic Change, 794'28:759- WaterResources. Engineerhg Hydrology.Kuo CY.Ed. Amer 7n. SocCiv Eng,NY, 793, pp.67-72. McGregorfL and Walsh K NestedSimulations of Perpetual BatesBC, CharlesSR SumnerNR and Fleming PM. Climate JanuaryClimate Over the AustralianRegion. Journal of Geo- Changeand ib HydrologicalImplications for SouthAushalia. physicalResearch, 19398(D72):23 28&?3,?90. Transactionsof the Royal Societyof Southern Australia, 194;118(1):3$43. McGregorfLandWalsh K. ClimateChangeSimulationof Tas- manianPrecipitation Using Multiple Neting. Journalof Geo. BusbyJR PotentialImpacts of ClimateChange on Aushalia's physicalResearch, 19599220,88 - 20,905. Flora and Fauna.Greenhouse: Planning for Climate Change. PearmanGI. Ed.EJ.Brill, New York,1988, pp.W-398. MonserudRA, lbhebakovaNM and kemans R Global Veg- etationChange Prcdicted by theModified BudykoModel. Cli- CharlesSR Fleming PM and BatesBC. Prcblems of Simulation matic Change,1993'P5:59 33. of Daily Precipitationand Other Inptrt TimeSeries for Hydro- logicalClimate Change Models. Proceedings of Hydrology & OglesbyRJ. Sensitivityof Glaciation to Initial SnowCove4, CQ, WaterResources Symposium. IEAust Nat Conf PublNo.93l SnowAlbedo,and OceanicRoughness in theNCAR CCN4. Cli- 74,79P.3,pp.469477. mate Dynamics, 799O ;4:279 -235. CIG.Climate Change Scenarios for theAustralianRegiorg192 PostDA, fakeman Af, Littlewood IG, WhiteheadPG and Climate lmpact Group CSIRQ Dvision of AtmosphericRe. JayasuriyaMDA. Modelling Land Cover lnduced Variations searclu in Hydrologic Response:Piccaninny Creel Victoria.Ecologi- cal Modelling,l96;85:.lV -182. CIG.Climate Change Scenarios for theAustralianRegioru 1996. Climate ImpactGroup, CSIRO,Division of AbnosphericRe. SchreiderSYu, fakemanAJ and PiftockAB. Modelling rainfall- search. runofffrom largecatchment to basinscale: the Goulburn Val- Australian lourtul of l/hter Rtwurces Vol.2,No.l.1997 "Egtlmation of climate impact on water availability and extreme events for snow-free ...,, -Schrcider,lakeman, Whettotl & Pittock '"ley, Victoria. Hydrclogical Processes,Ig6;I0l8fl3376. 1993'25:289-377. .. Schreider SYu,Jakeman Af and Pittock AB and Whetton pH. Estimation of PossibleOirnate Change Impacts on WaterAvail- Williams JE,Norton TW and Nix HA. Climate Change and the Values ability, Exheme Flow Evenb and SoilMoisture in theGoulblrrn Maintenance of Consewation in lbrfestridt Ecosvstems. and Ovens Basins, Victoria. Climatic Change, 1996F4:51&546. A Report to the Department of Environment, Sport and Terri- tories, October 194, Canberra , pp:702. '. Schreider SYu, Whetton PH, Jakeman AJ, Pittock AB and Li f. Runoff Modelling for Snow-Affected Catchments in the Aus- 31. Wigley TML and Raper SCB. Implications for Climate and Sea Level of Revised IPCC Emissions Scenarios. Nature, tralian Alpine Region, Eastern Victoria. fournal of Hydrology, 1997,(in press).Also in CRES $rbrking Paper,ANU, Canberra, 192;357:29T300. 7996/5,26pp. Ye W, fakernan AJ and Barnes C. A Parametrically Efficient Model for Prediction SEeamflow ,. Whetton PH. New Climate Change Scenarios.Oimate Change of in an Australian Bench- Newsletter, May 1993f, (2):7{. mark Catchment with Complex Storage Dynamics. Environ- ment International, 19521(5) 539-W. WhettonPH, FowlerAM,HaylockMRand Pitto€kAB.Impli- Ye W, Bates B, Viney NR, Sivapalan M and AJ. Per- cationsof Jakeman Climate Changedue to the EnhancedGreenhouse formance of conceptual rainfall-runoff models in low-yielding Effect on Floodsand DrrougheinAustralia. Oirnatic Change, ephemeral catchments.Water ResourcesResearch, 199793:151 166. S YTJSCHREIDER SergeiSchreider obtained his M.Sc.degree in mathematicsfrom the Moscow StateUniversity in 1982and PhD degreein resourcemanagement and envircnment3lscience from the Aus- halian National University in 1997.He is ResearchFellow at the Centre for Resourceand EnvironnrentalStudies, the Australian National University. His mapr rcsearchinterests are modellingof geophysicalsystems, statistical analysis and forecastingof quasistochasticalproc- essesand clirnatechange impact studies.For the last five yearshe has worked in the areaof the surfacerunoff modelling and flood forecasting.His researchwas reported in a range of irurnal publicationsand scientificrcports.He haS held visiting positiors at the NationalGeo' physical ResearchInstihrte (Hyderabad,India) and the International Centre of Earth, Envi- ronmentaland Marine Scienceand Technology(ICEM) of the United NationsIndusbial De. velopment OrganisationCfrieste, Italy). A J IAKEMAN Tonyfakemanobtained his B.Scdegree in pure and applied mathematicsfrom the University of New South l,ifrlesin 1973,and, his Ph.D.in applied numericalanalysis from The Australian National University in7976. He is currently hofessor of EnvironmentalSystems at the Cen- he for Resourceand EnvironmentalStudies and Adiunct Professorat the University of West- ern Australia. He hasheld visiting positionsat CambridgeUniversity, Universily of lancas- ter Stanford.Universityand the Instituteof Hydrology(UK). He is alsoEditor-in4hief of the Elsevieriouinal, EnvirronmentalModelling and Softwareand Presidentof the Modelling and Simulation Sociefyof Australia, Inc. P H WHETTON Dr Whefton is a SeniorResearch Scientist in the C[mate Impact Group of the CSIRODvision of Atmospheric Research.Since pining the Group in 1989,Dr Whetton's researchhas been primarily in the areaof developingregional scenarios of dimate drange due to the enhance' ment of the greenhouseeffect. He has also worked on a rangeof collaborativeprcj€cts in the field of dimate changeimpact ass€ssment,induding studie prior to the ctrrrent one in the hydrological field. Dr Whefton's climate change rcsearchhas been published in a range of purnal articles as well as in various researchreports to StateGoverments. He was also the main contributor and editor of the Climate Impact Grouy's statementson Australian region dimate changereleased in November 19912and November 195. Prior to pining CSIRO,Dr Whettonwas with the Departmentof Geographyand EnvironmentalScience at MonashUni- versity where tre investigatedhistorical patterns of floods and droughbsaround the world associatdwith the El Nino - SouthernOscillation. He maintainsan activeintercst in climatic variability and palaeoclimaticresearch. Dr Whettonobtained his Ph.D. in 1987in the Meteor- ology Departmentat. Melboume Univercity stralian lourtul of Water Rc*urca Vol.2,No.7,7997 "Estimation of climate impact on water availability and extremeevents for snow-free ..." -Schreider,lakeman, lNhetton & Pittack A B PTTTOCK Dr. A. Barrie Pittock obtained a Ph. D. at the University of Melbourne in 1963. He spent 196$ 64 on a Fulbright Fellowship at the National Center for Atmospherie Re*arch in Colorado ard pined the Australian Commonwealth Scientific and Industrial ResearchOrganisation (CSIRO)in 1965. During 7977-79he was a visiting scientist dt the L^aboraloryfor Tree'Ring Researchin Arizona. Atlhe CSIRO Division of Atmospheric Research(DAR) he has worked on stratospheric ozone, solar-weather relationships, surface climate change, the climatic ef- fecb of nuclear wa1 and the greenhouse effect. He has been a major contributor to several international reports including the 199O 19Fl2and 1995 Intergovernmental Panel on Climate Change Scientific and Impacts Assessmenb. Dr. Pittock has served on various national and internltional committees,and is the author of some 180 scientific papers and reports, and author/editor of severalbooks. Currently he leads the Climate Impact Group in CSIRO DAR, which is working to unravel the potential impacb of the enhanced greenhouse effect at the local and regional level. The group acts as an interface between global/regional climate modellers and those who may be af- fected by climate and related changes. The Group has had research contracts with State gov- ernments and with the Asian Development Bank, and since 1990has been involved in more than forty collaborative researchpropcb on regional climate scenario development and cdimate change impact studies. Australian lourtul ol V,laterRenurces Vol.2,No.7,7997