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Modelling of flood hazard extent in data sparse areas: a case study of the Oti River basin, West Africa

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ContentslistsavailableatScienceDirect

Journal

of

Hydrology:

Regional

Studies

j ou rn a l h o m e pa g e :w w w . e l s e v i e r . c o m / l o c a t e / e j r h

Modelling

of

flood

hazard

extent

in

data

sparse

areas:

a

case

study

of

the

Oti

River

basin,

West

Africa

Kossi

Komi

a,∗

,

Jeffrey

Neal

b

,

Mark

A.

Trigg

c

,

Bernd

Diekkrüger

d

aWestAfricanScienceServiceonClimateChangeandAdaptedLandUse(WASCAL),UniversityofAbomey-Calavi,RepublicofBenin bSchoolofGeographicalSciences,UniversityofBristol,Bristol,UnitedKingdom(UK)

cSchoolofCivilEngineering,UniversityofLeeds,Leeds,LS29JT,UnitedKingdom(UK) dDepartmentofGeography,UniversityofBonn,MeckenheimerAllee166,53115Bonn,Germany

a

r

t

i

c

l

e

i

n

f

o

Articlehistory:

Received22December2015

Receivedinrevisedform24February2017 Accepted6March2017

Keywords:

HydrologicalModelling FloodInundationModelling LISFLOOD

LISFLOOD-FP

a

b

s

t

r

a

c

t

Studyregion:TerrainandhydrologicaldataarescarceinmanyAfricancountries.Thecoarse spatialresolutionoffreelyavailableShuttleRadarTopographicMissionelevationdataand theabsenceofflowgaugesonflood-pronereaches,suchastheOtiRiverstudiedhere,make floodinundationmodellingchallenginginWestAfrica.

Studyfocus:Afloodmodellingapproachisdevelopedheretosimulatefloodextentindata scarceregions.Themethodologyisbasedonacalibrated,distributedhydrologicalmodel forthewholebasintosimulatetheinputdischargesforahydraulicmodelwhichisusedto predictthefloodextentfora140kmreachoftheOtiRiver.

Newhydrologicalinsightfortheregion:Goodhydrologicalmodelcalibration(Nash Sut-cliffecoefficient:0.87)andvalidation(NashSutcliffecoefficient:0.94)resultsdemonstrate thatevenwithcoarsescale(5km)inputdata,itispossibletosimulatethedischargealong thisregion’srivers,andimportantlywithadistributedmodel,derivemodelflowsatany ungaugedlocationwithinbasin.Withalackofsurveyedchannelbathymetry,modelling thefloodwasonlypossiblewithaparametrizedsub-gridhydraulicmodel.Floodmodelfit resultsrelativetotheobserved2007floodextentandextensivesensitivitytestingshows thatthisfit(64%)islikelytobeasgoodasispossibleforthisregion,giventhecoarseness oftheterraindigitalelevationmodel.

©2017TheAuthor(s).PublishedbyElsevierB.V.Thisisanopenaccessarticleunderthe CCBY-NC-NDlicense(http://creativecommons.org/licenses/by-nc-nd/4.0/).

Contents

1. Introduction...123

2. Studyareaanddatasets...123

3. Methodology...124

3.1. Descriptionofthehydrologicalmodel...124

3.2. Calibrationandvalidationofthehydrologicalmodel...125

3.3. Descriptionofthefloodinundationmodel...125

3.4. ApplicationoftheLISFLOOD-FPmodel...125

3.4.1. Modelsetup...125

3.4.2. Sensitivitytests. ... 126

∗ Correspondingauthorat:WASCAL,UniversityofAbomey-Calavi,RepublicofBenin. E-mailaddress:kossik81@yahoo.fr(K.Komi).

http://dx.doi.org/10.1016/j.ejrh.2017.03.001

2214-5818/©2017TheAuthor(s).PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBY-NC-NDlicense(http://creativecommons.org/ licenses/by-nc-nd/4.0/).

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3.4.3. Simulationofthe2007floodevent...126

4. Resultsanddiscussions...126

4.1. Hydrologicalmodelling ... 127

4.2. Hydraulicmodeling ... 127

4.2.1. Sensitivityanalysisresults...127

4.2.2. EffectsofDEMresolutiononthesimulationresults. ... 128

4.2.3. Simulationofthe2007floodevent...129

4.3. Limitations...130 5. Conclusion...130 ConflictofInterest...131 Acknowledgments...131 References ... 131 1. Introduction

Duringthelasttwodecades,manydamagingfloodshaveoccurredinWestAfrica(DiBaldassarreetal.,2010).InSeptember 2007,intenserainfallcausedtheworstfloodsthisregionhadfacedformanydecades.Theworstaffectedcountrieswere Ghana,BurkinaFasoandTogowith56,46and23personskilledrespectively(Tschakertetal.,2010).Inordertoimprovethe provisionoffloodhazardinformationinthestudyareaandacrossWestAfricagenerally,werequirebothhydrologicaland hydraulicmodelstofirstsimulatethepeakflowsorhighwaterlevelandthensimulateinundationofthispeaktoidentify flood-proneareas.Unfortunately,thelackofappropriatedataavailability(typeandresolution)intheregionpreventsthe applicationofstandardengineeringfloodmodels.Recently,theresearchcommunityhavebeguntotacklethischallenge. Forinstance,whenmodellingfloodinundationatthereachscaleindatascarceenvironments,oneofthedifficultiesisthe coarseresolutionofthefreelyavailableDigitalElevationModel(DEM)comparedtothenarrowwidthoftheriverchannel.To tacklethisissue,onesolutiondevelopedbyNealetal.(2012)istodevelopasub-gridchannelhydraulicmodel.Incorporated intheLISFLOOD-FPmodel,thisapproachprovidesameansofrepresentinganyriverchannelwhosewidthisnarrowerthan thespatialresolutionofthetopographydataonlowresolutionterraindatawhererivergeometrysurveydataareabsent. ThismodelwassuccessfullyvalidatedfortheNigerRiverinMali(Nealetal.,2012).Otherstudiesaimingatsimulatingflood inundationandpropagationinadatasparseregionshavealsobeencarriedout.Yanetal.(2014)usedesignfloodsderived fromAfricanenvelopecurvesandaphysicalmodelchaintosimulatefloodextentwiththeLISFLOOD-FPmodelonthe BlueNile.TheresultsofYanetal.(2014)highlightthedifficultiesinmodellingfloodinundationextentindatascarceareas, particularlyingeneratingrealisticfloodflows.Moreover,Sanyaletal.(2013)usethesameraster-basedhydrodynamicmodel (LISFLOOD-FP)tosimulatefloodinundationinalargeungaugedriveroftheDamodarRiverinIndia.Theauthorshighlighted thedifficultiesinperforminghydrodynamicmodellingindevelopingcountriesbecauseofthelackofdatabutshowedthat evenafew‘well-designed’fieldsurveyscanprovideadditionalinformationtothefreeDEMsinordertoimproveflood routing.Although,themajorityofthesepreviousstudiesrevealedtheobstaclesinmodellingfloodindevelopingcountries, theydodemonstratetheusefulnessofthefreelyavailableDEMinaccuratelysimulatingflooddynamicindatascarceareas. Giventheabsenceofrivergeometryobservationsandtheneedtousegloballyavailabledigitalelevationdata,themain objectiveofthisstudyistoinvestigatetheabilityofthemethodsdevelopedfordatascarceareastosimulatetheflood extentfortheOtiRiver.Thiscasestudywillfurtherevaluatethesensitivityofinundationpredictionstosomekeyinput variablesthathavenotpreviouslybeenexaminedinenoughdetailontheOtiRiverorelsewhereinAfrica.Specifically,(i) howsensitivearethemodelresultstotheManning’sfrictioncoefficientofthechannel?(ii)Howsensitivearethemodel resultstoriverchannelgeometryparameters?And(iii)doeschangingfloodplainDEMresolutionhaveasubstantialeffect onwatersurfaceelevationandfloodplaininundationsimulation?

2. Studyareaanddatasets

ThisstudyfocusesontheOtiRiverbasinwhichisasub-basinoftheVoltaRiverbasinofWestAfrica.Inthepresent work,weconsiderapproximately140kmoftheOtiRiverstartingfromtheMandourigaugingstation(Fig.1)andending justdownstreamofMangogaugingstation.Bothgaugesarecurrentlyabandoned.

Theaveragewidthoftheriverinthestudyreachis60mandthemodeldomainisbetweenlatitudes10.20and10.84 degreesNorthandlongitudes0.02and1.15degreesEast.Thestudyareaisaruralcatchmentwhichismainlycharacterized byagriculturallandusewithfloodplainelevationsfrom103mto559moverthemodeldomain(Fig.2a).Themeanwater levelatMangogaugestationisabout5m(Moniodetal.,1977).

Inadditiontotheseverefloodof2007,thestudyareahasexperiencedsubstantialeventsintheyears2010,2008,1999 and1998.Furtherbackintime,majorfloodsalsooccurredintheOtiRiverbasinonOctober6,1957(10mofwaterlevelat Mangogaugestation)andSeptember21,1962with10.64mofwaterlevelatMango(Moniodetal.,1977).

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Fig.1. Locationofthestudyareashowingthemodeldomain,mainsettlementsalongtheOtiRiverinTogoandhistoricalflowgauges.

Fig. 2.(a) DEM of the study site from SRTM and (b) observed flood extent of the 2007 floods from NASA MODIS data (http://www.floodobservatory.colorado.edu)inred.

Theextentofthe2007floodwascapturedbyNASA’s1MODIS(moderateresolutionimagingspectroradiometer)satellite

andpublishedbytheDartmouthFloodObservatory(Fig.2b).However,observeddischargedataforthestudysiteareonly availablefromtheyears1959to1987atMandourigaugestationandfrom1953to1989atMangogaugestation,withmany datagaps.

3. Methodology

Toperformfloodinundationmodellingforthestudyarea,twomajorstepswerefollowed.First,calibrationandvalidation ofadistributedhydrologicalmodel(LISFLOOD)wereundertaken,usingremotesensingdataandobserveddischargedata fromdownstreamofourTogolesestudysite.Oncecomplete,themodelprovidedflowdataforthe2007eventatourstudy site.Second,theLISFLOOD-FPhydraulicmodel(nottobeconfusedwiththehydrologicalmodel)wasappliedtotheselected channelreachoftheOtiRiverusingthehistoricalfloodextentin2007forcalibration.

3.1. Descriptionofthehydrologicalmodel

TheLISFLOODhydrologicalmodel(versionMarch15,2010)wasusedtosimulateinputhydrographsfortheflood inun-dationmodelling.LISFLOODisaraster-baseddistributedhydrologicalmodelwhichwasdevelopedbytheJointResearch CenteroftheEuropeanCommission(VanDerKnijffandDeRoo,2008).LISFLOODhydrologicalmodelisimplementedinthe PCRastermodellinglanguagewrappedinaPythonbasedinterface.Themaincomponentsofthishydrologicalmodelare brieflydescribedasfollows:(i)asub-modelforthesimulationofthewaterbalance,(ii)sub-modelsforthesimulationof groundwaterandsubsurfaceflow,(iii)asub-modelfortheroutingofsurfacerunoffand(iv)asub-modelfortheroutingof channelflow.Themodelismainlybasedonfivecalibrationparametersnamely:theupperzonetimeconstant,lowerzone

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Table1

Remotesensingdatausedinthehydrologicalmodelling.

Remotesensingdata Spatialresolution Source

TropicalRainfallMeasuringMission-daily rainfall

0.250×0.250 http://iridl.ldeo.columbia.edu

ClimateResearchUnit-dailytemperature (NationalCenterforAtmosphericResearch Staff,2014)

0.50

×0.50 https://climatedataguide.ucar.edu/climate-data/cru-ts321

HarmonizedWorldSoilDatabase-soildata - http://www.iiasa.ac.at/Research/LUC/luc07 ShuttleRadarTopographicMission–elevation

data

≈90m http://srtm.csi.cgiar SatelliteApplicationFacility-LeafAreaIndex 3km http://Landsaf.meteo.pt Landcovermap 222m×222m http://131.220.109.2/geonetwork

timeconstant,groundwaterpercolationvalue,powerpreferentialflowandXinanjiangparameterb(VanDerKnijffandDe Roo,2008).

3.2. Calibrationandvalidationofthehydrologicalmodel

Therainfall-runoffmodelwasappliedat5kmspatialresolutionusingtheremotedsensingdatathatareshowninTable1. Inorder toreducevolumeerrorsduringthesimulation,correctionfactorswereestimatedand appliedtothedaily griddedrainfalldata.Duetothelackofsufficientclimatologicaldata,thereferenceevapotranspirationwascomputedusing theHargreavesandSamaniequation(HargreavesandSamani,1985).Furthermore,therainfall,meantemperature,leafarea index,referenceevapotranspiration,potentialevaporationfromabaresoilandpotentialevaporationfromopenwaterwere interpolatedto5kmspatialresolutionusing‘gstat’applications(PebesmaandWesseling,1998).Finally,themodelwas manually(trialanderrormethod)calibratedforthreeyears(2001,2002and2003)andvalidatedforthreeyears(2005,2006 and2007)forSabarigauge(catchmentarea:58,670km2),downstreamofthestudyareaintheOtiRiverbasin(Fig.1).The

performanceofthehydrologicalmodelwasassessedusingRootMeanSquareError(RMSE)andNashSutcliffecoefficient NSE(NashandSutcliffe,1970).FurtherdetailsregardingthesetupandcalibrationoftheLISFLOODhydrologicalmodelcan befoundinVanDerKnijffandDeRoo(2008).

3.3. Descriptionofthefloodinundationmodel

Inthisstudy,LISFLOOD-FPversion6.0.4(Batesetal.,2013)wasusedtomodelthefloodplainextentoftheOtiRiver. LISFLOOD-FPisarasterbasedhydraulicmodeldevelopedattheUniversityofBristol.Thehydraulicmodelsolvesnumerically thelocalinertia(Nealetal.,2012),diffusive(Triggetal.,2009)orkinematic(BatesandDeRoo,2000)approximationstothe one-dimensionalSaint-Venantequationsinordertosimulatethepropagationofthefloodwavethroughtheriverchannel. Inthismodel,theriverchannelisrepresentedusingthelocalinertiaapproximationimplementedatsub-gridscale(Neal etal.,2012).Therequireddataofchannelwidthsweremanuallymeasuredat2kmintervalsfromGooglemapsalongthe channelcentreline.Duetothelackofdetailedriverbathymetry,thecross-sectionoftheriverchannelwasmodelledusing arectangularchannelapproximation.

TheperformanceofLISFLOOD-FPtopredictfloodinundationextenthasbeenwidelytestedusingobservedfloodextent mapsfromsatellite(DiBaldassarreetal.,2009).Inaddition,themodelhasgivengoodresultsinfloodinundationmodelling notonlyinEurope(Batesetal.,2010)butalsoinWestAfrica(Nealetal.,2012),SouthernAfrica(Schumannetal.,2013)and NorthAfrica(Yanetal.,2014)andtheAmazon(Wilsonetal.,2007,Baughetal.,2013).

3.4. ApplicationoftheLISFLOOD-FPmodel 3.4.1. Modelsetup.

Acoupled1D-2DLISFLOOD-FPmodelwassetupfora140kmreachoftheOtiRiverusingthesub-gridsolverasdescribed byNealetal.(2012).Thesub-gridmodel waschosenfor thisstudybecauseofitsabilitytobeappliedindatascarce environment.Theapplicationofthesub-gridsolverofLISFLOOD-FPrequiresthespecificationofthecenterlinesoftheriver, floodplaintopography,riverwidths,riverbankelevation,inflowhydrographsanddownstreamboundaryconditionsalong withmodelfrictionandchanneldepthparameters.Thecenterlineswerederivedfromthedigitalelevationmodelusingthe flowaccumulationfunctioninArcMapsoftware.Apartfromtheinflowhydrographsandthemodelfrictionparameters,all theinputdatawerecreatedinArcMapsoftwareandprojectedinaCartesiancoordinatesystem(UTMzone31N).These rasterdatasetswereexportedastextfiles(asciraster)tobereadbyLISFLOOD-FP.

Inaddition,aDEM(≈30mhorizontalresolution)ofthestudyareawasobtainedfromtheSRTM(shuttleradartopographic mission)dataset.Noelevationcorrectionforvegetationerrorswasmadebecausethefloodplainandtheriverbanksofthe OtiRiveraresituatedinasemi-aridregionwithasparsesavannavegetation.Therefore,errorsintheSRTMelevationvalues duetovegetationcoverarenotexpectedtobesignificantinthisarea(Baughetal.,2013).Startingfromtheoriginal30m resolution,fiveotherrastergrids(60m,120m,240m,480mand960m)werecreatedbyaggregatingmeanvaluesinorder

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totesttheaccuracyofthemodelatthedifferentresolutionsandassessthesensitivityofthemodeloutputstofloodplain DEMresolution.

Theriverwidthsweremeasuredfromsatelliteimagery(Googleearth)acquiredinFebruary2015.Inthisperiod,itiseasy toidentifythechannelwidthbecausetheriveriswithinitsbanks.Moreover,theriverbankelevationwasestimatedfrom theDEMbyextractingtheelevationofthefloodplaincellsthatareadjacenttotheriverandsmoothingthesealong-river overadistanceof1kmusingamovingwindowfilter.Afreeboundaryconditionthatspecifiedthatthevalleyslopeand watersurfaceslopewereequivalentattheboundarywasappliedtothedownstreamendofthemodeltoallowwaterto leavethemodeldomain.

Sincethestudysiteischaracterizedbyalackofrecentobservedhydrologicaldata,theLISFLOODrainfall-runoffmodel(as describedinSection3.2)wasusedtosimulateinputdischargedata.Thehydrographofthereachoutletwasthenusedasthe inputattheupstreamendofthemodeltoensurealllateralinflowsoverthereachwereaccountedforinthehydrodynamic modelling.However,itisimportanttonotethatalternativemethods,namelyremotesensingtechniques,havebeenproposed toestimatedailydischargeatungaugedsitesofcatchments(e.g.Bjerklieetal.,2005;Birkinshawetal.,2014;Sichangietal., 2016).Thesatellitealtimetrytypicallyprovidesstagedataforriversmorethan100mwide(Birkinshawetal.,2014),making difficulttheapplicationofthesetechniquesforriverslessthan100mwide,suchastheOtiRiver.

Finally,thesub-gridchannelsolverofLISFLOOD-FPhasfourparametersnamely;theManning’sfrictioncoefficient sepa-ratelyforchannelandfloodplain,andalsotheexponent(p),andcoefficient(r)ofthehydraulicgeometry.Manning’sfriction coefficientisaparameterthatcharacterizesflowresistanceforboththeriverchannelandthefloodplain.Manning’s fric-tioncoefficientcanbedistributedinspacebutthemodelistypicallysetupwithonecomponentforthefloodplain(nfp)

andanothercomponentfortheriverchannel(nc)whereonlylimiteddatafortheriverareavailable.AccordingtoChow

(1959),Manning’sfrictioncoefficientforchannelvariesfrom0.03(clean)to0.1(veryweedy/rockyreaches)andManning’s frictioncoefficientforfloodplainfrom0.03(pastureshortgrass)to0.120(heavystandsoftimberandafewfallentrees).The hydraulicgeometrycoefficientaffectstheareaandhydraulicradiusofthechannelbankfullcross-section(Nealetal.,2012) andcanbeestimatedfromhydraulicgeometryrelationshipsproposedbyLeopoldandMaddock(1953)andrearrangedby Nealetal.(2012)toobtainthefollowingexpressionshowninEq.(1):

d=rwp (1)

Wheredandwarethereachaverageddepthandthereachaveragedwidthrespectively,whilstrandparethehydraulic geometryparameters.Duetothelackofdatainthestudyarea,theinitialvaluesofthefourparameters(p,r,nfpandnc)where

obtainedfromChow(1959)andLeopoldandMaddock(1953).

3.4.2. Sensitivitytests.

Threesetsofsensitivitytestswereundertakenwiththefinishedhydraulicmodel,sensitivityto;(i)channelfriction, (ii)channelgeometry,(iii)floodplainDEMresolution.Firstly,theaimofthechannelfrictionsimulationswastotestthe sensitivityofthemodelresultstodifferentvaluesofManning’sfrictioncoefficientofthechannel(nc)rangingfrom0.02to

0.05in0.001increments.Foreachsensitivitytest,thevaluesoftheotherparameterswereheldconstant.Otherapplication ofLISFLOOD-FP(e.g.Horritt,2006;DiBaldassarreetal.,2009)haveshownthatthemodelsensitivitytothefloodplain frictionparameterisoftennegligibleoratleastmuchlowerthanthesensitivitytochannelfriction.Therefore,itwillnotbe consideredinthisstudy.Secondly,thesensitivityofthefloodinundationextenttotheriverchannelgeometrywastested byrunningthemodelfordifferentvaluesofthecoefficientofthehydraulicgeometry(r)rangingfrom0.035to0.175,in 0.005incrementsThisisineffectalinearscalingofthechanneldepth,withreachaverageddepthincreasingwithr.Foreach simulation,thevaluesoftheotherparametersweresetconstant.Finally,totestfloodplainDEMresolution,themodelwas runusingthesixdifferentresolutionsofthefloodplainDEMoutlinedabove.

3.4.3. Simulationofthe2007floodevent

Weusedthehydraulicmodeltosimulatetheextentofthe2007floodeventforaperiodbetween1stMay2007and30 November2007.ThesimulatedinundationextentwascomparedwiththeMODIS(Fig.2b)satelliteobservation,produced onSeptember21,2007,usingasimpleindexoffitmeasureF(BatesandDeRoo,2000).TheFmeasureallowsquantitative comparisonofthesimulatedextenttothesatelliteobservation.Theperformancemeasure(F)isgivenbyEq.2:

F (%)=AABB×100 (2)

whereAistheobservedinundatedarea,andBtheinundatedareapredictedbythemodel.InordertocalculateF,an inundationboundaryvectorwasfirstcreatedfromtheobservedsatelliteimage,astheoriginalMODISrasteranalysiswas notobtainable.Theboundaryvectorwasconvertedtoabinarywetanddryraster,resampledtothesameresolutionasthe modelsimulationoutput.Thesamewetanddryclassificationwasappliedtothesimulationresults.Inordertocalibratethe model,weconsideronlytheManning’sfrictioncoefficientforchannelandthehydraulicgeometrycoefficientwhichwere sampledintherangeoftheintervalsgiveninSection3.4.2ofthispaper.

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Fig.3.ComparisonbetweensimulatedandobservedhydrographsatSabariforthecalibration(a)andvalidation(b). 4. Resultsanddiscussions

Inthissectionwebrieflypresenttheresultsofthehydrologicalmodelling,butwefocusindetailontheresultsofthe hydraulicmodelling.

4.1. Hydrologicalmodelling

Thecalibrationofthehydrologicalmodelusingdatafrom2001to2003resultedinNSEandRMSEvaluesof0.87and 237m3/swhilethemodelvalidationusingdatafrom2005to2007producedbetterperformancemeasures(NSE=0.94

andRMSE=179m3/s).TheRMSEis9%ofthemeanflooddischargeforthecalibrationperiodand0.7%forthevalidation

period.Generally,thegoodness-of-fitmeasuresforcalibrationarebetterthanforvalidation(e.g.BormannandDiekkrüger, 2003;Ibrahimetal.,2015;Masafuetal.,2016)sincethecalibrationprocessseekstominimisedifferencesbetweenthe observedandsimulatedtimeseries.Inthisparticularcase,thegoodness-of-fitmeasuresareactuallybetterforvalidation thancalibration.Thiswouldsuggestthatvariabilityfromthenorminthecalibrationdatasetisgreaterthaninthevalidation dataset.Moreover,Fig.3showsthecomparisonbetweenthesimulatedandobservedhydrographs.Theseplotsrevealsthat exceptfortheyear2001,allthepeakflowsarewellsimulatedbythehydrologicalmodel.Thishighperformanceofthe LISFLOODhydrologicalmodelhelpedtogeneratedischargedataforthefloodinundationmodelling.

Finally,thebestcalibrationparametersoftheLISFLOODhydrologicalmodelaretabulatedinTable2,withthelowerand upperboundssuggestedbyVanDerKnijffandDeRoo(2008).Itisworthnothingthatforallthecalibrationparameters,the bestvaluesliewithintherangesspecifiedinTable2.

Inordertoevaluatethecontributionoflateralflowsalongthestudiedriverreach,Fig.4showsthecomparisonbetween thesimulatedhydrographsattheinlet(Mandouriwithanareaof29,100km2)andoutletofthestudiedreach(Fig.1).Itcan

benotedthatthepeakdischargeattheoutletofthestudiedreachisabout31%higherthanthepeakflowattheinlet.This increaseofdischargefromtheupstreamboundarytothedownstreamendsuggestssomecontributionsoflateralinflow, whichhasbeentakenintoaccountinthehydraulicmodelling.

4.2. Hydraulicmodeling 4.2.1. Sensitivityanalysisresults.

TheinitialparametersofthemodelwereobtainedfromLeopoldandMaddock(1953)andChow(1959)andareshown inTable3.Fig.5showstheperformanceoftheLISFLOOD-FPat960mDEMresolutionwithdifferentManning’sfriction coefficientsforthechannel(Fig.5a)andwithdifferentvaluesofthehydraulicgeometrycoefficientr(Fig.5b).Onecannote Table2

Optimalvaluesofthecalibrationparameters.ThelowerandupperboundsoftheparametersweretakenfromVanDerKnijffandDeRoo(2008).

Parameter Optimalvalues Lowerbound Upperbound

Upperzonetimeconstant 10 1 50

Lowerzonetimeconstant 1300 50 5000

Groundwaterpercolationvalue 0.1 0 1.5

Xinanjiangparameterb 0.3 0.1 1

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thattheperformanceofthesub-gridmodelpeakedatncof0.042butdecreasewithfurtherincreaseinthevalueofnc.The

modelperformancewaslesssensitivetoManning’snwhentheoptimalnwasexceeded.Thisbehavioriscommonlyseen whenlargefloodeventsareassessedusingspatialperformancemeasuresbecausethefloodextenttendstoincreaseonly graduallywithincreasedwaterdepthoncemostofthefloodplainvalleyisinundated.Themaximumperformancemeasure forrwasobtainedat0.04.Fromtheseresults,itisclearthatboththefrictioncoefficientforthechannelandthehydraulic geometrycoefficientinfluencetheinundationextentinthiscasestudy.However,thesensitivityofthemodelresultstothe hydraulicgeometrycoefficientwasrelativelylowcomparedtofrictioncoefficientforchannel.

4.2.2. EffectsofDEMresolutiononthesimulationresults.

WaterelevationalongtheriverfromthesimulationsresultsforthedifferentaggregatedDEMresolutionsareshownin Fig.6.ThesimulatedwatersurfaceelevationsarealmostthesameforthedifferentaggregatedDEMresolutionswithaslight differenceatabout80kmofthereachwherethewatersurfaceelevationsfrom480mand960mDEMresolutionareover 1mlowerthanthewatersurfaceelevationsfor30m,60m,120mand240mDEMresolutions.Generally,bychangingthe resolutionofthefloodplainDEM,otherinputstothemodelnamelychannelwidthandbankelevationmustbeaggregated astheresolutioncoarsens.Thiscanlocallyaffectthechannelslopeandsimulatedwatersurfaceelevationsalongwith thedifferingtopographies(e.g.DuttaandNakayama,2008).However,theresultsofthepresentstudyshowthattheDEM resolutiondoesn’treallyaffectthewatersurfaceelevationsimulationsinmostlocations,meaningthatthechangesinextent withresolutionareessentiallyduetothedetailoftheDEMratherthananymorecomplexhydraulicinteractionbetweenthe DEMandriverchannel.ThevariationofthemodelperformanceinsimulatingthefloodplainextentwhentheDEMresolution coarsensispresentedinTable4.Thistableshowsthattheperformanceofthemodelactuallydecreaseswithresolutionand therecouldbeanumberofreasonsforthis.ItmightbethatthelocalscalenoiseintheSRTMdataisreducingtheaccuracyof theinundationsimulationatfinerresolutione.g.somesmoothingoftheDEMbyaggregatingtolowerresolutionmightbe beneficialforthefloodextentsimulationinthiscase.Anotherfactoristhevalidationdataresolution.Themodelperforms

Fig.4. Simulatedhydrographsofthe2007floodatinletandoutletofthestudiedreach(seeFig.1forthemodeldomain).

Table3

Initialvaluesofthehydraulicmodel(LISFLOOD-FP)parameters.

Parameters nc nfp p r

Initialvalues 0.03 0.04 0.74 0.36

Fig.5.Performanceofthesub-gridmodelofLISFLOOD-FPwith(a)differentManning’sfrictioncoefficientforchannelandwith(b)differenthydraulic geometrycoefficient.

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Fig.6.Riverbedlongitudinalprofile(blacklinebased30mDEMminusriverdepth)andwatersurfaceelevationssimulatedbyLISFLOOD-FPfordifferent aggregatedDEMresolutions.

Table4

Performanceofthesub-gridmodelofLISFLOOD-FPfordifferentDEMresolutions.

DEMresolutions(m) 30 60 120 240 480 960

Indexoffit(%) 52 53 56 59 60 59

Fig.7. Resultsofthecalibrationofthesub-gridmodelofLISFLOOD-FPshowingmeasuresoffitasafunctionofthehydraulicgeometrycoefficientandthe Manning’sfrictioncoefficientforchannel.

worsewhenyougotoahigherresolutionthanthatofthemodelvalidationdataandthismightbeexpectedgiventhatthe validationdatacannotrepresentthefinerscaledetailintheinundationmodel.

4.2.3. Simulationofthe2007floodevent

TheoptimumhydraulicmodelparametersaregiveninTable5whileFig.7showstheresultsofthecalibrationforthe hydraulicmodelat480mDEMresolutionascontourplotsofmeasureoffitovertheparameterrange.Thebestfitofthe sub-gridmodelofLISFLOOD-FPischaracterizedbyaManning’scoefficientforchannel(nc)ofaround0.045m1/3S−1and0.05

Table5

Models’parametersusedforthefloodinundationmodeling.

Parameters nc nfp p r

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Fig.8.Comparisonofsimulatedfloodextentwith(a)satelliteobservationbeforecalibration(b)andaftercalibrationfortheseverefloodofSeptember 2007.

forthecoefficientofthehydraulicgeometry(r).However,byanalyzingFig.7,onecanobservethatdifferentcombinations ofoptimumparametervaluesmayfitthecalibrationdataequally.Thisequifinalityinfloodinundationmodellinghasbeen alreadyillustratedinthescientificliterature(e.g.Batesetal.,2005;DiBaldassarre,2012).

Itisinterestingtonotethataperformancemeasureof60%wasachievedforthesimulatedfloodextentpriortothe calibration(Fig.8a)comparedto64%afterthecalibration(Fig.8b).

ThevaluesofFfoundforthisstudyarerelativelylowcomparedtopreviousstudieswhereeitherhighresolution topogra-phywasavailableorthefloodplainwasmanykilometerswide(e.g.BatesandDeRoo,2000;HorrittandBates,2001;Wilson etal.,2007)butrelativelyhighcomparedtotheresultsfromotherdatasparseareassuchasAmarnathetal.(2015)who found38%forFandsimilartotheresultsofSayamaetal.(2012)whofound61%forF.However,themodelsimulationcanbe consideredasanacceptableresultbecausethemajorityofthefloodedareasalongthemainreachwasidentifiedasshown visuallyinFig.8bandotherstudieshaveobtainedsimilarfitswhenSRTMdatahasbeenused.Thedisagreementsbetween theobservedandsimulatedfloodextentsoccurwherethecentrelinesderivedfromtheDEMbyflowaccumulationdonot correspondwithobservedriverchannellocations.Moreover,someofthefloodingoccurredontributariesthatwehavenot includedinthemodel.

4.3. Limitations

Inthispaper,amethodologytosimulatefloodextentonungaugedriversispresented.Thismethodologylinks rainfall-runoffmodellingandhydraulicmodellingtodelineatefloodextent.Adistributedhydrologicalmodelwasinitiallyused togeneratethefloodhydrographsofinterest.Thisapproachisusefultotransferhydrologicalinformationfromgauged catchmentstoungaugedsitesandsimulatefloodextentsinfloodprone-areaswhichsufferfromlackofhydrological infor-mation.However,itisimportanttonotethatduetothelackofsufficientdatatovalidatethehydraulicmodel,aswellasthe simulationcharacteristics,itisdifficulttoeliminateacertaindegreeofuncertainty.Thisuncertaintywasnotestimatedin thepresentstudybecauseitiscomputationallyexpensiveparticularlyforcombinedhydrologicandhydraulicsimulations. Nevertheless,thesensitivityanalysesperformedinthisworkcanbeusefultounderstandboththesimulationuncertainty andthebehaviorofthemodelwithdifferentparametervaluesandDEMresolutions(e.g.Sayamaetal.,2012).

5. Conclusion

Themainobjectiveofthis studyis toexploreamethodologyforsimulatingfloodextentindatascarceareasusing ahydrologicalmodel(LISFLOOD)andfloodinundationmodel(LISFLOOD-FP).Theapplicationofthehydrologicalmodel showsitsgoodperformanceinpredictingpeakflowsintheregionoftheOtiRiverbasin(RMSErepresentslessthan10% ofthemeanpeakflows).ThesimulatedhydrographoftheseverefloodofSeptember2007isveryclosetotheobservation with0.7%errorforthepeakflow,andwasusedtoprovideinputhydrographforthehydraulicmodel.GiventheDEMdata availableandthesimilarfitsobtainedbyotherstudieswhereSTRMdatahavebeenused,theindexoffitof64%obtained

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inthisstudyisconsideredacceptable.Theresultsofthisstudyshowalsothatincontrasttothesimulatedwatersurface elevations,themodelledfloodextentismoresensitivetothegridresolution.Inaddition,thesub-gridmodelofLISFLOOD-FP showedmoresensitivitytotheManning’sfrictioncoefficientforthechannelthantothehydraulicgeometrycoefficient.

Thepossibilitytoidentifyandpredictfloodproneareasonungaugedriversisthemajoradvantageoftheproposed methodology.ItisthefirsttimethatafloodinundationmodellinghasbeenundertakenfortheOtiRiverbasinandthe outcomesofthisstudycancontributetowardsanefficientfloodriskmanagementdecisionsforthisarea.Forinstance, floodinundationmapscanhelpinmitigatingflooddamagesandestablishingearlyfloodwarningsystems.Moreover,the calibratedmodels(hydrologicalandhydraulic)couldbeusedtoassessthefutureimpactsofclimateandlandusechanges onfloodriskintheOtiRiverbasin.

ConflictofInterest

Theauthorsdeclarenoconflictofinterest. Acknowledgments

ThisworkhasbeenfundedbytheGermanFederalMinistryofEducationandResearch(BMBF)throughtheWestAfrican ScienceServiceCentreonClimateChangeandAdaptedLandUse(WASCAL).WewouldliketothankAdDeRoo,PeterBurek, BernardBisselink,BrendenJongmanandErinCouglanfortheircontributioninthecalibrationofthehydrologicalmodel. References

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