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Spatialtargetingofnaturalfloodriskmanagementwithinlargerivercatchments:AnestedapproachofSCIMAP-FloodandCRUM3 SimM.Reaney&CallumPearson,DepartmentofGeography,DurhamUniversity.sim.reaney@durham.ac.ukTomanagefloodriskwithinalargerivercatchment,suchastheRiverEden(2300km2),thereisaneedtoconsiderthespatialtargetingattwoscales:1,thewholeofthelargescalecatchmentand2,thelocalsub-basin.Withlargecatchments,therearemultiplepointsofimpactandhenceanactiontoreducefloodriskinonelocationmayincreasetheriskinanotherduetochangesinthetimingsub-catchmentfloodpeaksandassociatedsynchronisation.Therangeofrainfallpatternsandstormtrackswillgivedifferentfloodtimingdynamicsineachevent.Therefore,thereisaneedtoconsiderhowthesevariablesinteracttogiveintegratedspatialtargetingmapsforNFMwhichhasthegreatestchanceofreducingfloodriskoverarangeofpossiblefutureevents.Oncethekeylocationshavebeenidentified,thedetailsoftheeffectivenessofprocessedmitigationactionsonfloodmagnitudescanbecalculatedthroughtheapplicationofdetailedhydrologicalandhydraulicmodels.ThisreportthereforeproposesatwostageapproachtomanagingfloodriskwithintheRiverEdencatchment:

1. Theuseofspatiallydetailed,catchmentwide,riskbasedmapping,accountingforrainfallpatterns,sub-catchmentsynchronisationandmultiplepointsofimpact,toidentifykeysub-catchments

2. Theapplicationofdetailedphysicallybasedmodels,withinanuncertaintyframework,withintheseidentifiedlocationstodesignandtesttheproposedNFMscheme.

LandscapeScaleSpatialTargetingforNFM:SCIMAP-FloodThesuitabilityofasitefortheimplementationofnaturalfloodriskmitigationmeasuresisdeterminedby1,thetraveltimeofthefloodwaterstothepointofimpact,2,thespatialpatternoftherainfalldepthpattern,3,theeffectivenessofthelandcoveringeneratingrapidfloodflows(overland,drainsandnearsurfaceflows)and4,thestrengththeofthehydrologicalconnectivityfromthelandscapetotheriverchannels.ThisreportpresentstheinitialversionofthenewSCIMAP-FloodtoolforspatialtargetingofNFMmeasuresatthelandscapescale.ThisapproachisbasedontheSCIMAPfinesedimentriskmappingtool(Reaneyetal.2011)butexpandedtocapturefloodissues.TheSCIMAP-Floodtoolassignsriskweightstoeachofthefloodhazarddrivingfactorsandthencombinesthesetogiveapointscaleassessmentofthepotentialvalueofslowingflowsatthatlocationfordecreasingfloodpeaksatthepointofimpact.Thisassessmentisbasedonthecriticalsourceareaconceptwherebythereneedstobebothagenerationoffloodriskandanactivehydrologicalconnectiontotheriverchannel(Heathwaiteetal.2005).Thesourceriskisdeterminedasafunctionoftraveltimes,rapidrunoffgenerationpotentialandtherainfallpatternandthehydrologicalconnectivityisdeterminedbytheNetworkIndex(Laneetal.2004).ExampleresultsofSCIMAP-Floodareshowninthefigurebelow.

SCIMAP-FloodfortheRiverEdencatchmentforthesinglepointofimpactinCarlisle

DetailofthefieldscalenatureofSCIMAP-FloodfortheRiverRoecatchment

Actionclustersidentifiesareaswheretherearemultiplefloodsources.Shownforallpointsofimpact

SimReaneyandCallumPearson,DurhamUniversity

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Sub-CatchmentScaleSpatialTargetingforNFM:CRUM3Havingdeterminedthekeysub-catchmentsfromSCIMAP-Flood,thenextpartoftheanalysisusestheCRUM3hydrologicalmodeltoinvestigatetheperformanceofmitigationactions.CRUM3isafullyspatiallydistributed,processbasedhydrologicalmodelrunningatthelandscapescale(Laneetal.,2009).CRUM3consistsoffourkeyelements:weather,1Dverticalhydrologicalprocesses,2Dlandscapeprocessesandroutingandtheriverchannelnetwork.ThemodelwasusedwithintheGLUEpredictiveuncertaintyestimationframework(Beven&Binley1992).TheresultsforsoilcompactionmanagementthroughaerationandtheimplementationofwoodydebrisdamsarepresentedfortheRiverRoecatchment,althoughothersscenarioswereconsidered.Theassessmentofmitigationactionperformancewasassessedbythechangeinthepeakdischargeforeachofthebehaviouralmodelparametersets,hencecapturingsomeofthepredictiveuncertainty.Theresultsforthelandcovertargetedsoilaerationscenariosandfortheimplementationoflargewoodydebrisdamsondifferentstreamordersareshownbelow.

Thepeakdischargepercentagechangeusingthelandcovertargetedsoilaerationscenarios.‘H’referstoheavycompactionlevels,‘M’ismediumand‘L’islight.‘Ara’isarablelandcoverand‘ImpG’isimprovedgrassland.

LargeWoodyDebris(LWD)damscenariosforpeakflowreductionfortheStrahler(Str)numberedstreamcombinationsusingthe-40%maximumdischargereductionfromWenzeletal.(2014).

Thegreatertheamountofcatchmentareaassignedtosoilaerationapplicationthegreaterthereductioninpeakdischarge.Thoughunrealisticasthesolemitigationactionduetotherequiredareatobeaeratedandtheunlikelinessthattheentirecatchmentwillbecompacted,theuseofsoilaerationhasasignificantimpactonthepeakdischargeintheRiverRoecatchment.Theresultsforsimulatinglargewoodydebrisdamsareshownforthemaximumreportedreductioninpeakdischargeof40%,althoughotherlowerlevelswerealsomodelled.TheimplementationoflargewoodydebrisdamsinbothStrahleroneandStrahlertwochannelreachesresultsinanincreaseinmeanandmedianpeakdischarge.Thisincreaseispotentiallyduetotheflowrestrictionprolongingthemaximumdischargemovingdownstreamandthecumulativeeffectatthepointofimpactisaprolonged,butrestricted,maximumdischarge.AllthreescenariosetswithlargewoodydebrisdamsonStrahlerthreechannelshadareductioninpeakdischargewithameanreductionof-4.33%andamedianof-4.61%.

SummaryandConclusions• ThecombinationoftherapidriskandopportunitymappingwithSCIMAP-Floodandthedetailedhydrological

modellingwithCRUM3providesapowerfultoolkittospatiallytargetandassesstheperformanceofnaturalfloodriskmanagementschemes.

• SCIMAP-Floodenablestherapidandcosteffectiveidentificationofsub-catchmentsandtheareaswithinthosecatchmentsthataremostlikelytobecontributingtothefloodpeakatthedefinedpointofinterest,suchasCarlisleorAppleby-in-Westmoreland.

• CRUM3canthenbeimplementedtotestNFMschemesandprovidequantitativepredictionsofthechangeinfloodpeakmagnitude,asrequiredforprojectfunding.

Beven,K.andBinley,A.,1992.Thefutureofdistributedmodels:Modelcalibrationandpredictiveuncertainty.HydrologicalProcesses,6,pp.279–298.Heathwaite,A.L.,Quinn,P.F.&Hewett,C.J.M.,2005.Modellingandmanagingcriticalsourceareasofdiffusepollutionfromagriculturallandusingflowconnectivitysimulation.JournalofHydrology,304(1),pp.446–461.LaneSN,ReaneySMandHeathwaiteAL2009:Representationoflandscapehydrologicalconnectivityusingatopographically-drivensurfaceflowindex;WaterResourcesResearch,45,W08423ReaneyS.M.,LaneS.N.,HeathwaiteA.L.andDugdaleL.J.2011:Risk-basedmodellingofdiffuselanduseimpactsfromrurallandscapesuponsalmonidfryabundance;EcologicalModellingVolume222,Issue4,24February2011,Pages1016-1029Wenzel,R.,Reinhardt-Imjela,C.,Schulte,A.&Bölscher,J.,2014.Thepotentialofin-channellargewoodydebrisintransformingdischargehydrographsinheadwaterareas(OreMountains,South-easternGermany).EcologicalEngineering,71,pp.1–9.