Runoff Prediction in Ungauged Basins: Synthesis across Processes, Places and Scales

492 Pages·2013·33.18 MB·English

by  Günter Blöschl

Runoff Prediction in Ungauged Basins
Synthesis across Processes,Places and Scales
Predictingwaterrunoffinthemostlyungaugedwatercatchment Gu¨nter Blo¨schl is Professor of Hydrology, Director of the
areas of the world is vital to practical applications such as the CentreforWaterResourceSystems,andHeadoftheInstituteof
designofdrainageinfrastructureandfloodingdefences,forrun- HydraulicEngineeringandWaterResourcesManagementatthe
off forecasting and for catchment management tasks such as ViennaUniversity ofTechnology.Hehaspublishedextensively
waterallocationandclimateimpactanalysis. onsubjectsrelatedtohydrologyandwaterresourcesandserved
This important new book synthesises decades of rigorous as an editor and associate editor for ten of the best scientific
analytical research from around the world, forming a holistic journals in the field. Professor Blöschl has been elected Fellow
approach to catchment hydrology, and providing a one-stop oftheAmericanGeophysicalUnionandtheGermanAcademyof
resourceforhydrologistsinbothdevelopedanddevelopingcoun- Science and Engineering, has chaired the International Associ-
tries. It brings together results from individual location-based ationofHydrologicalSciences(IAHS)PredictionsinUngauged
studieswithcomparativeanalysisalonggradientsofclimateand Basins (PUB) initiative, and has been elected President of the
landscapefeatures.Topicsincludedataforrunoffregionalisation EuropeanGeosciencesUnion.Recentlyhehasbeenawardedthe
and the prediction of runoff hydrographs, flow duration curves, prestigious Advanced Grant of the European Research Council
flowpathsandresidencetimes,annualandseasonalrunoff,and (ERC).
floods.
Murugesu Sivapalan isProfessorofCivilandEnvironmen-
Illustratedwithmanycasestudies,andincludingafinalchap-
tal Engineering, and of Geography and Geographic Information
ter on recommendations for researchers and practitioners, this
ScienceattheUniversityofIllinois.Hewasfoundingchairofthe
book is written by expert international authors involved in the
International Association of Hydrological Sciences (IAHS) Pre-
prestigious International Association of Hydrological Sciences
dictions inUngauged Basins (PUB) initiative. He has published
(IAHS) Predictions in Ungauged Basins (PUB) initiative. It is a
extensivelyoncatchmenthydrologyinseveralinternationaljour-
keyresourceforacademicresearchersinthefieldsofhydrology,
nals and is Executive Editor of the European Geosciences
hydrogeology, ecology, geography, soil science, and environ-
Union’sHydrologyandEarthSystemSciencesjournal.Professor
mental and civil engineering, and professionals working with
SivapalanhasalsoreceivedtheEuropeanGeophysicalSociety’s
waterrunoffinungaugedwaterbasins.
John Dalton Medal, the International Hydrology Prize of the
IAHS, and the Hydrological Sciences Award and the Robert
E. Horton Medal of the American Geophysical Union. He was
also the recipient of the Centenary Medal of the Australian
Government and an Honorary Doctorate of the Delft University
ofTechnology.
ThorstenWagenerisProfessorofWaterandEnvironmental
SecurityintheDepartmentofCivilEngineeringattheUniversity
ofBristol.HeisaVicePresidentoftheInternationalAssociation
of Hydrological Sciences, editor of the journal Hydrology and
Earth System Sciences, and associate editor of several other
journals.DrWagenerhasbeenawardedDAAD(DeutscherAka-
demischerAustauschdienst)fellowships,anIEMSSEarlyCareer
ExcellencePrize,BestPaperAwardsoftheJournalofEnviron-
mentalModelingandSoftware,aUSEPAEarlyCareerAward,
theWalterHuberCivilEngineeringResearchPrizeoftheAmeri-
can Society of Civil Engineers, an Alexander von Humboldt
Foundation Fellowship, and an Education and Public Service
AwardoftheUniversitiesCouncilforWaterResources.
Alberto Viglione is a Research Hydrologist at the Vienna
UniversityofTechnology.During2004–7heconducteddoctoral
researchon‘Non-supervisedstatisticalmethodsfortheprediction
of hydrological variables in ungauged sites’ at the Hydraulic
Department of the Politecnico of Turin. He has authored or
co-authored numerous papers in hydrology, particularly on
floods,from bothstatistical andprocess-based perspectives,and
onhydrologicalcharacterisationofriverbasins.DrViglionehas
developedsoftwareforregionalfrequencyanalysisandrainfall–
runoff modelling under the R environment, which is available
online.Healsoactsasareviewerforseveralprestigiousjournals,
andhasbeeninvolvedinanumberofresearchprojectsrelatedto
hydrology and flood frequency analysis in Italy, Austria and
severalotherEuropeancountries.
Hubert Savenije is Professor of Hydrology andHead of the
Water Resources Section at the Delft University of Technology
andalsoservesasEditor-in-ChiefofHydrologyandEarthSystem
SciencesandPhysicsandChemistryoftheEarth.HeisPresident-
Elect of the International Association of Hydrological Sciences
(IAHS) as well as Chair of the IAHS Predictions in Ungauged
Basins(PUB)initiative.ProfessorSavenijehaspublishedwidely
in several leading international journals and was Vice Rector at
UNESCO-IHE, Institute for Water Education. He is Past-
PresidentofHydrologicalSciencesoftheEuropeanGeosciences
Union (EGU), and Past-President of the International Commis-
sion on Water Resources Systems of the IAHS. He has been
awarded, among other things, the Henry Darcy Medal of the
EGUandtheEGUBatchAward.
Runoff Prediction
in Ungauged
Basins
Synthesis across
Processes, Places
and Scales
edited by
GÜNTER BLÖSCHL
TechnischeUniversitätWien,Austria
MURUGESU SIVAPALAN
UniversityofIllinois,Urbana-Champaign,USA
THORSTEN WAGENER
UniversityofBristol,UK
ALBERTO VIGLIONE
TechnischeUniversitätWien,Austria
HUBERT SAVENIJE
TechnischeUniversiteitDelft,theNetherlands
cambridge university press
Cambridge,NewYork,Melbourne,Madrid,CapeTown,
Singapore,SãoPaulo,Delhi,MexicoCity
CambridgeUniversityPress
TheEdinburghBuilding,CambridgeCB28RU,UK
PublishedintheUnitedStatesofAmericabyCambridgeUniversityPress,NewYork
www.cambridge.org
Informationonthistitle:www.cambridge.org/9781107028180
©CambridgeUniversityPress2013
Thispublicationisincopyright.Subjecttostatutoryexception
andtotheprovisionsofrelevantcollectivelicensingagreements,
noreproductionofanypartmaytakeplacewithout
thewrittenpermissionofCambridgeUniversityPress.
Firstpublished2013
PrintedandboundintheUnitedKingdombytheMPGBooksGroup
AcataloguerecordforthispublicationisavailablefromtheBritishLibrary
LibraryofCongressCataloguinginPublicationData
Runoffpredictioninungaugedbasins:synthesisacrossprocesses,placesandscales/editedbyGünterBlöschl,Technische
UniversitätWien,Austria,MurugesuSivapalan,UniversityofIllinois,Urbana-Champaign,USA,ThorstenWagener,Universityof
Bristol,UK,AlbertoViglione,TechnischeUniversitätWien,Austria,HubertSavenije,TechnischeUniversiteitDelft,TheNetherlands.
pages cm
ISBN978-1-107-02818-0(Hardback)
1. Runoff. 2. Rainandrainfall. 3. Runoff–Mathematicalmodels. 4. Rainandrainfall–Mathematicalmodels. 5. Hydrology.
I. Blöschl,Günter,1961–editorofcompilation.
GB980.R872013
551.4808–dc23 2012036513
ISBN978-1-107-02818-0Hardback
CambridgeUniversityPresshasnoresponsibilityforthepersistenceor
accuracyofURLsforexternalorthird-partyinternetwebsitesreferredto
inthispublication,anddoesnotguaranteethatanycontentonsuch
websitesis,orwillremain,accurateorappropriate.
Contents
List of contributors page ix 3 Adata acquisition framework for runoff
Forewordby Thomas Dunne xv prediction in ungaugedbasins 29
Preface xix 3.1 Whydoweneeddata? 29
Abstract xxii 3.2 Ahierarchyofdataacquisition 30
3.2.1 Assessmentbasedonglobaldatasets 31
1 Introduction 1 3.2.2 Assessmentbasedonnational
1.1 Whyweneedrunoffpredictions 1 hydrologicalnetworkandnationalsurveys 31
1.2 Runoffpredictionsinungaugedbasins 3.2.3 Assessmentbasedonlocalfieldvisits
aredifficult 3 includingreadingthelandscape 32
1.3 Fragmentationinhydrology 4 3.2.4 Assessmentbasedondedicated
1.4 ThePredictioninUngaugedBasinsinitiative:a measurements 34
responsetothechallengeoffragmentation 5 3.3 Runoffdata 34
1.5 Whatthisbookaimstoachieve:synthesisacross 3.3.1 WhatrunoffdataareneededforPUB? 34
processes,placesandscales 6 3.3.2 Whatrunoffdataarethere? 35
1.5.1 Synthesisacrossprocesses 7 3.3.3 HowvaluablearerunoffdataforPUB? 36
1.5.2 Synthesisacrossplaces 8 3.4 Meteorologicaldataandwaterbalance
1.5.3 Synthesisacrossscales 8 components 36
1.6 Howtoreadthebookandwhattogetoutofit 9 3.4.1 Whatmeteorologicaldataandwater
balancecomponentsareneededfor
2 Asynthesis framework for runoff PUB? 36
prediction inungauged basins 11 3.4.2 Precipitation 36
2.1 Catchmentsarecomplexsystems 11 3.4.3 Snowcoverdata 39
2.1.1 Co-evolutionofcatchment 3.4.4 Potentialevaporation 39
characteristics 11 3.4.5 Remotelysenseddataforcalculating
2.1.2 Signatures:amanifestationof actualevaporation 40
co-evolution 13 3.4.6 Remotesensingofsoilmoistureand
2.2 ComparativehydrologyandtheDarwinian basinstorage 40
approach 15 3.5 Catchmentcharacterisation 41
2.2.1 Generalisationthroughcomparative 3.5.1 Topography 41
hydrology 15 3.5.2 Landcoverandlanduse 41
2.2.2 Hydrologicalsimilarity 18 3.5.3 Soilsandgeology 42
2.2.3 Catchmentgrouping:exploitingthe 3.6 Dataonanthropogeniceffects 43
similarityconceptforPUB 20 3.7 Illustrativeexamplesofhierarchicaldata
2.3 Fromcomparativehydrologytopredictionsin acquisition 44
ungaugedbasins 22 3.7.1 Understandingprocesscontrolsonrunoff
2.3.1 Statisticalmethodsofpredictionsin (TenderfootCreek,Montana,USA) 44
ungaugedbasins 22 3.7.2 Runoffpredictionsusingrainfall–runoff
2.3.2 Process-basedmethodsofpredictions models(ChickenCreek,Germany) 47
inungaugedbasins 23 3.7.3 Forensicanalysisofmagnitudeand
2.4 Assessmentofpredictionsinungaugedbasins 23 causesofaflood(SelškaSora,Slovenia) 49
2.4.1 Comparativeassessmentasameansof 3.8 Summaryofkeypoints 51
synthesis 23
2.4.2 Performancemeasures 25 4 Process realism: flow paths and storage 53
2.4.3 Level1andLevel2assessments 26 4.1 Predictions:rightfortherightreasons 53
2.5 Summaryofkeypoints 26 4.2 Processcontrolsonflowpathsandstorage 55
vi Contents
4.3 Inferenceofflowpathsandstoragefrom 6.3.4 Runoffestimationfromshortrecords 121
responsecharacteristics 57 6.4 Process-basedmethodsofpredictingseasonal
4.3.1 Inferencefromrunoff 57 runoffinungaugedbasins 123
4.3.2 Inferencefromtracers 59 6.4.1 Deriveddistributionmethods 123
4.4 Estimatingflowpathsandstorageinungauged 6.4.2 Continuousmodels 124
basins 64 6.5 Comparativeassessment 126
4.4.1 Distributedprocess-basedmodels 64 6.5.1 Level1assessment 127
4.4.2 Indexmethods 64 6.5.2 Level2assessment 129
4.4.3 Methodsbasedonproxydata 65 6.6 Summaryofkeypoints 134
4.5 Informingpredictionsofrunoffinungauged
basins 66 7 Prediction of flow duration curves in
4.5.1 Process-based(rainfall–runoff)methods 67 ungauged basins 135
4.5.2 Statisticalmethods 67 7.1 Forhowlongdowehavewater? 135
4.5.3 Roleoffieldvisits,readingthelandscape, 7.2 Flowdurationcurves:processesandsimilarity 137
photosandotherproxydata 68 7.2.1 Processes 138
4.5.4 Regionalinterpretationandsimilarity 68 7.2.2 Similaritymeasures 141
4.6 Summaryofkeypoints 69 7.2.3 Catchmentgrouping 145
7.3 Statisticalmethodsofpredictingflowduration
5 Prediction ofannual runoff in ungauged curvesinungaugedbasins 147
basins 70 7.3.1 Regressionmethods 148
5.1 Howmuchwaterdowehave? 70 7.3.2 Indexflowmethods 148
5.2 Annualrunoff:processesandsimilarity 71 7.3.3 Geostatisticalmethods 151
5.2.1 Processes 72 7.3.4 Estimationfromshortrecords 152
5.2.2 Similaritymeasures 78 7.4 Process-basedmethodsofpredictingflow
5.2.3 Catchmentgrouping 79 durationcurvesinungaugedbasins 153
5.3 Statisticalmethodsofpredictingannualrunoff 7.4.1 Deriveddistributionmethods 153
inungaugedbasins 83 7.4.2 Continuousmodels 154
5.3.1 Regressionmethods 83 7.5 Comparativeassessment 156
5.3.2 Indexmethods 84 7.5.1 Level1assessment 156
5.3.3 Geostatisticsandproximitymethods 88 7.5.2 Level2assessment 158
5.3.4 Estimationfromshortrecords 88 7.6 Summaryofkeypoints 162
5.4 Process-basedmethodsofpredictingannual
runoffinungaugedbasins 89 8 Prediction of low flows inungauged basins 163
5.4.1 Deriveddistributionmethods 89 8.1 Howdrywillitbe? 163
5.4.2 Continuousmodels 90 8.2 Lowflows:processesandsimilarity 164
5.4.3 Proxydataonannualrunoffprocesses 91 8.2.1 Processes 164
5.5 Comparativeassessment 92 8.2.2 Similaritymeasures 167
5.5.1 Level1assessment 92 8.2.3 Catchmentgrouping 170
5.5.2 Level2assessment 96 8.3 Statisticalmethodsofpredictinglowflowsin
5.6 Summaryofkeypoints 100 ungaugedbasins 172
8.3.1 Regressionmethods 172
6 Prediction ofseasonal runoff inungauged 8.3.2 Indexlowflowmethods 175
basins 102 8.3.3 Geostatisticalmethods 176
6.1 Whendowehavewater? 102 8.3.4 Estimationfromshortrecords 178
6.2 Seasonalrunoff:processesandsimilarity 104 8.4 Process-basedmethodsofpredictinglow
6.2.1 Processes 104 flowsinungaugedbasins 179
6.2.2 Similaritymeasures 111 8.4.1 Deriveddistributionmethods 179
6.2.3 Catchmentgrouping 114 8.4.2 Continuousmodels 180
6.3 Statisticalmethodsofpredictingseasonal 8.4.3 Proxydataonlowflowprocesses 180
runoffinungaugedbasins 118 8.5 Comparativeassessment 181
6.3.1 Regressionmethods 118 8.5.1 Level1assessment 182
6.3.2 Indexmethods 118 8.5.2 Level2assessment 184
6.3.3 Geostatisticalandproximitymethods 119 8.6 Summaryofkeypoints 188
Contents vii
9 Prediction of floods in ungauged basins 189 11 PUB inpractice: casestudies 270
9.1 Howhighwillthefloodbe? 189 11.1 PredictionsinUngaugedBasinsinasocietal
9.2 Floods:processesandsimilarity 190 context 270
9.2.1 Processes 191 11.2 Hydrologicalinsightsfromlong-termrunoff
9.2.2 Similaritymeasures 196 patternsacrossKrishnaBasin,India 272
9.2.3 Catchmentgrouping 200 11.3 Predictingmeanannualrunoffacross
9.3 Statisticalmethodsofpredictingfloodsin HuangshuiBasin,China 277
ungaugedbasins 203 11.4 Anindexapproachtomappingannual
9.3.1 Regressionmethods 203 runoffinaSiberiancatchment,Russia 280
9.3.2 Indexfloodmethods 205 11.5 Predictingspatialpatternsofinter-annual
9.3.3 Geostatisticalmethods 208 runoffvariabilityintheCanadianPrairies 283
9.3.4 Estimationfromshortrecords 209 11.6 Seasonalflowpredictionwithuncertainty
9.4 Process-basedmethodsofpredictingfloods inSouthAfricaandLesotho 289
inungaugedbasins 211 11.7 Settingenvironmentalflowtargetsin
9.4.1 Deriveddistributionmethods 212 north-eastUSA 293
9.4.2 Continuousmodels 215 11.8 Continuoussimulationoflowflowsfor
9.4.3 Proxydataonfloodprocesses 217 hydropowerdevelopmentinOntario,Canada 297
9.5 Comparativeassessment 219 11.9 Estimatingflowdurationcurvesfor
9.5.1 Level1assessment 220 hydropowerdevelopmentincentralItaly 300
9.5.2 Level2assessment 222 11.10 ImplementingtheEUflooddirectivein
9.6 Summaryofkeypoints 225 Austria 305
11.11 RevisionofAustralianRainfallandRunoff
10 Prediction of runoff hydrographsin forimprovedfloodpredictions 309
ungauged basins 227 11.12 Understandingflowpathsforhydrograph
10.1 Whatarethedynamicsofrunoff? 227 predictioninanAndeancatchment,Chile 313
10.2 Runoffdynamics:processesandsimilarity 228 11.13 Frequencyofrunoffoccurrenceinephemeral
10.2.1 Processes 229 catchmentsinFrance 317
10.2.2 Similaritymeasures 233 11.14 Overcomingdatalimitationsforhydrograph
10.2.3 Catchmentgrouping 236 prediction,LuangwaBasin,Zambia 321
10.3 Statisticalmethodsofpredictingrunoff 11.15 Remotelysensedlakelevelstoassistrunoff
hydrographsinungaugedbasins 238 modellinginGhana 328
10.3.1 Regressionmethods 238 11.16 Modelenhancementsforurbanrunoff
10.3.2 Indexmethods 238 predictionsinthesouth-westUSA 332
10.3.3 Geostatisticalmethods 239 11.17 RunoffpredictionstohelpmeetMillennium
10.4 Process-basedmethodsofpredictingrunoff DevelopmentGoalsinZimbabwe 337
hydrographsinungaugedbasins 240 11.18 RunoffpredictionsinsupportoftheNational
10.4.1 Structureofrainfall–runoffmodels WaterAudit,Australia 345
forungaugedbasins 241 11.19 DistributedrunoffpredictionsintheMekong
10.4.2 Parametersofrainfall–runoff Riverbasin 349
modelsinungaugedbasins: 11.20 ImplementingtheEUWaterFramework
overview 246 DirectiveinSweden 353
10.4.3 A-prioriestimationofmodel 11.21 Summaryofkeypoints 360
parameters 247
10.4.4 Transferofcalibratedmodel 12 Outcomes ofsynthesis 361
parametersfromgauged 12.1 Learningfromsynthesis 361
catchments 251 12.2 Synthesisacrossprocesses,placesandscales 363
10.4.5 Constrainingmodelparameters 12.2.1 Synthesisacrossprocesses 363
bydynamicproxydataand 12.2.2 Synthesisacrossplaces 367
runoff 256 12.2.3 Synthesisacrossscales 369
10.5 Comparativeassessment 262 12.2.4 Inter-comparisonofmethods 371
10.5.1 Level1assessment 263 12.3 SynthesisofNewtonianandDarwinian
10.5.2 Level2assessment 266 frameworks 374
10.6 Summaryofkeypoints 268 12.3.1 Evidenceforco-evolution 374
viii Contents
12.3.2 Comparativehydrologyandthe 13.2.1 Viewingcatchmentsascomplex
Newtonian–Darwiniansynthesis 376 systems 385
12.3.3 Anewunifieduncertaintyframework 13.2.2 Comparativehydrologytodetect
forPUB 379 co-evolutionpatterns 385
12.4 Synthesisandthesciencecommunity 381 13.2.3 Newtonian–Darwiniansynthesis 385
12.4.1 Accumulationofknowledgeinthe 13.2.4 Theglobeisourlaboratory 385
hydrologicalsciences 381 13.3 Organisingthehydrologycommunityto
12.4.2 Roleofthecommunity 382 advancescienceandpredictions 385
13.3.1 Capacitybuilding 385
13 Recommendations 384 13.3.2 Collaborativeendeavour 386
13.1 Advancingrunoffpredictionsinungauged 13.3.3 Knowledgeaccumulation 386
basins 384 13.3.4 Hydrology,aglobalscience 386
13.1.1 Understandingasthekeytobetter 13.4 Bestpracticerecommendationsfor
predictions 384 predictingrunoffinungaugedbasins 386
13.1.2 Exploitingrunoffsignaturesand
linkingthem 384 Appendix: Summary ofstudiesused inthe
13.1.3 Addressinguncertaintyfromaprocess comparative assessments 388
perspective 384 References 415
13.1.4 Dataavailabilityandpredictions 385 Index 463
13.2 Advancinghydrologicalscienceglobally
viaPUB 385