1
FLOODRISKMAPPINGFROMORBITALREMOTESENSING1
2
Manuscriptfor“GlobalFloodHazard:applicationsinmodeling,mappingand3
forecasting”,G.J-PSchumann,P.D.Bates,G.T.Aronica,andH.Apel,editors.4
(Inreview)5
6
G.RobertBrakenridge7
DartmouthFloodObservatory8
CSDMS/INSTAAR,UniversityofColorado,Boulder,COUSA9
10
Introduction11
StandardizedmethodsforfloodriskevaluationintheUnitedStateswere12
developedbytheUnitedStatesGeologicalSurveyovermorethanacentury13
(Klingeman,2005;Wahletal.,1995).Theyuseanextensivenetworkofriver14
gaugingstationsandassociatedtimeseriesofannualfloodpeakdischarge;manyof15
theseextendfor50-100y.Tomeetregulatoryandinsurancerequirements,flood16
riskassessmentsmustbenotonlyobjectiveandscientificallydefensible,butalso17
uniformlyapplicableacrosshighlyvariablehydrologicalregimes.Theresultsare18
commonlysubjecttolegalchallengesaspropertyownerscontestthelevelofrisk19
assigned;consistencyofmethodisthuscritical.Throughthesestandardmethods,20
riskismodeled:aflooddischargeofparticularcalculatedrecurrenceintervalis21
2
routedthroughthechannelandacrossthelandscapeviaregulatoryagency-22
approvedhydrodynamicmodelssuchasHEC-RAS(FEMA,2002).23
24
ManydevelopednationsoutsidetheUnitedStateshavesimilarriskevaluation25
methodologies.Quitecommonly,a“100y”dischargeandassociatedfloodplainare26
defined:thisfloodplainisthelandareaalongariverwhere,atitsmargins,a1%27
annualexceedanceprobabilityiscalculatedforinundationbyfloodwater(interior28
portionsmayexperiencemuchhigherinundationfrequencies).Thus,the29
probabilityPethatoneormorefloodsoccurringduringanyperiodwillexceeda30
givenfloodthresholdcanbeexpressed,usingthebinomialdistribution,as31
Pe=1–[1–(1/T)]n (Equation1)32
whereTisthethresholdreturnperiod(e.g.100y)andnisthenumberofyearsin33
theperiod.Forfloods,theeventmaybemeasuredinpeakm³/sorheight;most34
commonlythecalculationusesatimeseriesofannualfloodpeakdischarges(Flynn35
etal.,2006;Klingeman,2005).36
37
Inregardtothisapproach,manydevelopingnationshavealessdeveloped38
hydrologicalmeasurementinfrastructure,andrelativelyfewreliableinsiturecords39
ofpastfloodpeakdischarges.Theneedforreliablefloodhazardinformationmaybe40
evenmorecritical,however,asagriculturalandmanufacturingeconomiesexpand,41
andpopulationgrowthandmigrationincreasesettlementoffloodplainlands42
(Brakenridgeetal.,2016b).Intheselocations,adifferentkindofhydrological43
modelingoffloodhazard,generallyonarelativelycoarsespatialscaleandwithout44
3
abundantstreamflowrecords,isoneapproachtowardsaddressingtheneed(as45
discussedelsewhereinthisbook).Suchapproachesdonotrequireinsituflood46
measurements,butinsteadreconstructthefloodhistoryfromclimatologicaldata47
inputandtopography-assistedmodeling.48
49
Thepresentchapteroffersathirdapproach:combinedanalysisof:50
1) A1998-presenttimeseriesofsatellitepassivemicrowavedatathatrecords51
floodhydrographsatselectedmeasurementsites(Brakenridgeetal.,52
2012a;DeGroeveetal.,2015a;VanDijketal.,2016),and53
2) Opticalsensorimagingandmappingoffloodevents,alsosustainedovera54
similartimespan.55
Thesetogetherproduceaninundationrecordwhichiscoupledtothe56
microwaveinformation:inordertoassignexceedanceprobabilitiestothemapped57
inundationlimits.58
59
Usingthisapproach,standardfloodprobabilitydistributionscanbeappliedto60
agloballyconsistentobservationalperiodofrecordofnearly20y(1998-present).61
Notethatastandard“ruleofthumb”forextrapolationoffloodprobability62
distributionsis2x:iftheperiodofannualpeakflowrecordis20y,the“40y”event63
canbeestimated.Thus,theserecordsshouldallowestimationat-a-siteofthis64
discharge,andsomemappedfloods,iftheyarethelargestofrecord,willbeassigned65
recurrenceintervalsinexcessof20y.Evenareliable25yfloodplain(annual66
exceedanceprobability=4%)isveryusefulriskinformationinanyregionwhere67
4
riskinformationisotherwiselacking,andthesegeospatialdatacanbemadequickly68
availableviathemethodologyanddatadescribedhere.69
70
Orbitalremotesensinginthelate20thandearly21stcenturieshasprovideda71
richarchiveofactualfloodinundationextents.Forsuchdata,seeforexample72
(Brakenridgeetal.,2016a).Somenationsalreadyusesatellite-basedmapsofany73
extremefloodeventforfloodplainregulation,onthesimpleprinciplethatwhathas74
occurred,mayoccuragain(deMoeletal.,2009).Exploredhereisaglobally75
applicablestrategy,however,towardstransformingsuch“mappedlargeflood”76
informationintoquantitativefloodrisk.Suchmapscan,inturn,alsobeusedto77
validateandcalibratefloodriskmapscreatedusingmodelingapproaches.78
MicrowaveRadiometryforMeasuringRiverDischarge79
Asnoted,oncealargefloodhasbeenmappedfromspace,theneedisto80
constrain“howlarge/howrare”isthemappedevent.Inthisregard,satellite81
microwavesensorsprovideglobalcoverageoftheEarth’slandsurfaceonadaily82
basisand,atcertainwavelengths,withoutmajorinterferencefromcloudcover.83
Griddeddataproducts,updatedinnearrealtime,areavailable(DeGroeveetal.,84
2015a).Theproductsarelowinspatialresolution(bestavailableresolutionfor85
theseglobalcoveragesensorsis8-10km).However,usingastrategyfirstdeveloped86
forwide-areaopticalsensors(Brakenridgeetal.,2005;Brakenridgeetal.,2003b),87
sensorssuchasAMSR-E,AMSR-2,TRMM,andGPM(figure1)canmeasureriver88
5
dischargechangesatcertainlocations,bymonitoringthesurfacewaterareasignal89
fromindividualimagepixelsovertime.90
91
Themethodissimpleinconcept:asriversriseanddischargeincreases,water92
areawithinthesingle-pixelsatellitegaugingsites(~10kmx10km),asselected93
fromagriddedglobalimageproduct(figure2),alsoincreases(Brakenridgeetal.,94
2012a;Brakenridgeetal.,2007;DeGroeveetal.,2015b;DeGroeveetal.,2006;De95
GroeveandRiva,2009).Thiswaterareachangetracksriverwidthanddischarge96
variationinamanneranalogoustohowstage(riverlevel)tracksdischargeatinsitu97
gaugingstations.Therelationshipofflowareatodischargeisviathecontinuity98
equation99
Q=wdv (Equation2)100
101
whereQiswaterdischargeinm3/s,wisflowwidth,diswaterdepth,andviswater102
flowvelocity(m/sec),asintegratedacrosstheflowcrosssection.Asdischarge103
increases,andprovidedthechannelisnotrectangularinshape,flowwidth104
increasesatacrosssection,andflowareaincreasesoverallwithinariverreach:in105
thiscase,a10km2measurementsite.106
107
6
108
Figure1.Temporalcoverage,1998topresent,ofpassivemicrowavesensorsbuilt109
andoperatedbyNASAandbyJAXA(theJapaneseSpaceAgency).Eachsatellite110
providesdailyornear-dailyimagingoftheglobe.111
112
Notethata~10km37GHzimagepixelinthesegriddedproducts,centered113
overariver,iscommonly"mixed";itincludesbothwater(lowemission)andland114
(highemission).Astheproportionofwaterarearises,thenetemittedradiation115
declines.Themicrowavesignalisthusverysensitivetoflowwidthchanges.The116
physicalmechanismsareexploredelsewhereforthisfrequencyradiation(e.g.,117
reasonsforlowemissionfromwaterandmuchhigheremissionfromland,118
Brakenridge,etal.,2007).However,thesamemethodologycanalsousethenearIR119
bandsofopticalsensors:again,watersurfacesprovidemuchlowerradiancethan120
adjoininglandsurfaces,butcloudcoverwillintermittentlyinterfere(Brakenridgeet121
al.,2005;VanDijketal.,2016).122
123
7
124
125
126
Figure2.LocationofSatelliteGaugingSiteDFO#30overAyeyarwadyRiverandits127
floodplaininMyanmar.ThesiteisasinglepixelselectedfromtheJRCgrid;pixelis128
10kminsizeandproducesthedailyMvalue.The95thpercentileofthehighest129
(driestandwarmest)valuesfroma9x9pixelarrayinthesurroundingarea130
producesthebackgroundcalibrationCvalue.131
132
Asdischargealongariverincreases,theflowarea,asseenfromabove,should133
generallyincreasemonotonically(hysteresiseffectscanlocallyoccur,however).134
Althoughinsitugaugingstationsinsteadcommonlyusestage,thereisnoapriori135
reasonwhythisisamoresensitiveflowmonitor.Ifriverchannelsarenot136
rectangularinshape,dischargevariationisexpressedbybothstageandwidth137
variations;and,alongmanyrivers,widthvariationwithflowisquiterobust.Also,138
sinceareachinsteadofasinglecrosssectionismonitored,thesensitivityoftheflow139
8
areameasurementdependsonthecompletesuiteofriver/floodplainmorphologic140
featureswithinthereach,andincludingin-channelbarsandlowfloodplainsurfaces,141
slip-offslopesalongmeanderbends,braidedchannelsandislands,andfloodplain142
oxbowlakeswhichareconnectedtothemainchannel.Asforinsitustations,the143
bestsatellitegaugingsitesthusmustbecarefullyselected;inthiscase,forreaches144
wheresurfaceareachangessignificantlyoverthefullrangeofin-channelandflood145
discharges.146
147
Oneimplementationofsatellitemicrowave-basedflowareainformationfor148
operationalhydrologicalmeasurementsistheRiverWatchprocessoratthe149
DartmouthFloodObservatory(DFO),UniversityofColorado,150
http://floodobservatory.colorado.edu/.RiverWatchusestheNASA/JapaneseSpace151
Agency(JAXA)AdvancedScanningMicrowaveRadiometer(AMSR-E)bandat36.5152
GHz,theNASA/JapaneseSpaceAgencyTRMM37GHzchannel,and37GHzdata153
fromthenewAMSR-2andGPMsensors.Thedischargeestimator(theremote154
sensingsignal)istheratioofthedaily"M",microwaveemissivityfroma155
measurementpixelcenteredovertheriveranditsfloodplain,andacalibratingvalue156
("C"),the95thpercentileoftheday'sdriest(brightest)emissivitywithina9pixelx157
9pixelarraysurroundingthemeasurementpixel.(figure2).The95thpercentile158
excludesoutliersduetosensornoisewhilestillprovidingasuitablenon-hydrologic159
backgroundmeasurement.At~37GHz,C/Misprimarilysensitivetochanging160
surfacewaterareawithintheMpixel;usingtheratioremovesotheremission161
9
variability(e.g.fromsurfacetemperature)thataffectsallpixelsinthearea(De162
Groeveetal.,2015b;DeGroeveetal.,2006;DeGroeveandRiva,2009).163
164
ThetimeseriesatsiteswithinreachofTRMM(<50degreeslatitude)beginin165
January1998(figure1).ThenAMSR-Edata(mergedwiththeTRMMinformation)is166
addedwhensuchbecomesavailableinmid-2002.TheseriescontinuesusingTRMM,167
only,duringtheAMSRhiatusbetweenAMSR-EterminationandinitiationofAMSR-168
2;figure1)andthenitaddsAMSR-2andGPM(nowmergingthetwodatastreams,169
into2016).Themicrowaverecordathigherlatitudesitesbeginsinmid-2002170
(followinglaunchofAMSR-E),andthereisdatagapin2012-2013betweenthe171
terminationofAMSR-EandinitiationofAMSR-2.Thegriddingalgorithmthat172
producestheglobaldailyimagesisperformedattheEuropeanCommission’sJoint173
ResearchCentre(JRC);theoriginaldataarenearrealtimeswathinformationfrom174
eachsensorprovidedbyNASAand/orJAXA.AJRCtechnicaldocumentprovides175
furtherinformationincludingdatasources(DeGroeveetal.,2015b).176
177
JRCproducesadailyglobalgridat10km(neartheequator)pixelresolution,178
andpublishesdailyratiodataforfixedpixelswithinthat4000x2000pixelgrid.At179
lowerlatitudes,thecoverageislessthandailyfromAMSR-EandAMSR-2:thelatest180
RiverWatchversionusesaforwardrunning,4-daymeanofthedailyresultsto181
avoidsuchdatagaps.Becauseriverdischargeexhibitsstrongtemporal182
autocorrelation,suchaveragingalsoprovidesusefulsmoothingandnoisereduction.183
10
Also,whenmultiplesamplesforonepixelareavailableinoneday,thelatestsample184
valueisusedatJRCinthegriddedproduct.185
186
AtDFO,thelatestratiodatafromtheJRCareingestedtwiceeachday,andthe187
web-hosteddisplaysandcalculateddischargedataforeachsatellitegaugingsiteare188
thenupdated.Eachsitedisplayincludestwo(html)onlinewebpages:oneprovides189
plotsoftheresultsbutalsosometabulardata:190
(E.g.,http://floodobservatory.colorado.edu/SiteDisplays/30.htm).191
Thesecondpresentsthesignal/dischargeratingcurve(seebelow)andaccesstothe192
completerecordofsatellite-measureddischarge:193
(http://floodobservatory.colorado.edu/SiteDisplays/30data.htm).194
Forcomparisonpurposes,areference20thpercentileofthemeasureddischargefor195
eachdayoftheyearisalsoprovidedandprovidesausefullowflowthreshold.196
ProductionofSignal/DischargeRatingCurves197
Asisthecaseforriverstagemeasuredatinsitugaugingstations,independent198
informationisneededtotranslatethedischarge-sensitiveobservable(inthiscase,199
watersurfacearea)tothecorrespondingdischargevalue.Thetransformationis200
accomplishedbyanempiricalratingequationthatmatchesthesignalto201
independentdischargeinformation.ForRiverWatch,thecalibratingdischarge202
valuesareobtainedbyrunsofaglobalrunoffmodel(WBM)(Cohenetal.,2011).203
Fiveyears(2003-2007)provideabundantdailymodeloutputforcalibration;204
additionalyearscomparingmodelandremotesensingcouldfurtherrefineand205
11
possiblyextendtheresultingratingcurves(iflargermodeledflowsoccurthan206
previously).TheWBMmodel,alsousingaglobalgridresolutionof~10km,inputs207
climateandlandsurfacevariablesandproducesdailyriverdischargevaluesfor208
theseyearsateachmeasurementsite.Earlierworkdeterminedthatadequate209
calibrationinformationforeachsite’sratingcurvecanbeobtainedbycomparing210
justthemonthlydailymaximum,minimum,andmeanvalues,son=180forthe5y211
run(Brakenridgeetal.,2012a;Cohenetal.,inpreparation,2013;Cohenetal.,212
2011).Figure3providessampleresultsatonesiteasascatterplot;figure4213
illustratesthesamedataintimeseriesform.Inthelattercase,thesignaldataare214
firsttranslatedtodischargevaluesusingthescatterplot’sratingcurveinorderto215
showthetwotimeseriesonthesamescale.216
217
218
Figure3.ScatterplotcomparingWBM-modeleddailydischargeovera5y(January-219
Decembermonthlydailymaximum,minimum,andmeandischarges)totheC/M220
ratioforRiverWatchsite30.Therelationshipisempiricalandabettercurvecould221
befittothesedata,butastraightlineisausefulfirst-approximationratingcurve.222
12
223
224
Figure4.Samedataasinfigure3,butarrangedastimeseriesofmaximum(left)225
mean(middle),andminimum(right)dischargevalues.Theredlineshowsthe226
modelresultsandthebluelineistheremotesensingastransformedbytherating227
equationinfigure3.228
229
Withoutotherinformation,itisnotpossibletodeterminewhichdeparturesin230
asmoothmonotonicrelationinfigure3isfromerrorsintheremotesensingsignal231
andwhichfromerrorsinthemodel.Forthepurposeofthefloodriskassessments232
tobedescribedhere,however,thecorrelationofindependentmodeltoremote233
sensingfurtherestablishesthatthemicrowavewaterareasignalisindeed234
respondingtodischargevariation.Also,andwhetherornotWBMisstrongly235
affectedbymodelbiasandisreportingconsistentlytoo-highortoo-lowdischarge236
numbers,suchbiaswillnotaffecttheriskprobabilities.Figure5providestheentire237
remotesensingdailytimeseriesatthissatellitegaugingsite,andusingtherating238
curveinfigure3.Becausetheratiosignalisrespondingtosurfacewater(and239
flooding)extentwithintheMpixel,therelativeheightsofthefloodhydrographs240
shownshouldaccuratelyreflectthetruetimeseriesoffloodingthere:regardlessof241
anymodelbiasinthedischargecalibration.Thisresultthenprovidestheessential242
13
informationneededforfloodhazardmapping:amethodtoconstraintheobserved243
frequency/exceedanceprobabilityofanimagedflood.244
245
Figure4.Daily(4-dayforwardrunningmean)dischargevaluesforsatellitegauging246
site30ontheAyeyarwadyRiver.Thelowflowthreshold(greenline)isthe20%247
percentiledischargeforeachday;thefloodthresholdsuserecurrenceintervals248
computedusingtheLogPearsonIIIdistributionandtheannualmaximumdaily249
values.Majorfloodingin2015approachedthecalculated5yrecurrenceinterval;250
thefloodofrecord,in2004,wasproducedbyaverydamagingtropicalstorm251
(Brakenridgeetal.,2016b);floodinghereexceededthe25ythreshold.252
253
Thereisanimportantfactorthatmaychangetheexactreturnperiodstobe254
assignedtotheannualfloodpeaksshowninfigure4.Thatis,thestraightlinerating255
equationshowninfigure3clearlyproducessomewhattoohighdischargesforthe256
highestwaterareasignalvalues(figure3).Adjustingtheratingequationtoflatten257
theslopewouldproducesomewhatsmallerfloodpeaksandalsoalterthe258
correspondingreturnperiodsforthelargerevents.Thisdependencyindicatesthe259
importanceofdevelopingthehighestqualityratingcurves(thesameneedexistsfor260
insitugaugingstations).261
14
AssessingRiverWatchAccuracy262
Asnoted,theaccuracyofthesatellitegaugingsiteresultsdependsinparton263
riverandfloodplainmorphology.Othersite-specificfactorssuchasvegetationare264
alsoimportant(Revilla-Romeroetal.,2014).Usingboththemodelandtheremote265
sensingresults,withoutanyground-basedinformation,itisalsopossibleto266
calculateusefulstatisticscomparingtheoverallaccuracyofthedischargetime267
seriesresults.Forexample,flowareasmaynotchangeverymuchinresponseto268
dischargealongsomereaches,inwhichcasetheexpectedsignalrangeissmall269
comparedtothedailynoisethatcanbeinducedbyotherfactors(seebelow).Two270
descriptivestatisticsforasampleofsitesinMyanmaralongtheAyeyarwadyanda271
majortributary(theChindwinRiver)areprovidedasTable1toillustratetheir272
utilityandapplication.Thesignal/modelagreementisasimplerankingand273
classificationofthesignal/modelleastsquaresregression(coefficientof274
determinationr2)results,asinfigure3(eitherforstraightlinefitsorsecondorder275
polynomialsthatcanbettermatchthedata).Amongdifferentsites,higherr2276
indicatesastrongercorrelation;itismorelikelythattheremotesensingsignalis277
accuratelytrackingriverdischargevariationifitisstronglycorrelatedtomodeled278
dischargeoutput.Thesethresholdswerechosentogroupther2valuesintoclasses:279
>.7,Excellent,.6-.69,VeryGood,5-.59,Good,.4-.49,Fair,<.4,Poor.280
281
Second,thesitesvaryinmaximumsignalrangeovertheperiodofrecord(in282
thetable,fromalowof.08to.20,ormorethan2-fold).Theyalsovaryintheaverage283
dailysignalchange(fromalowof.08to.14,ornearly2-fold).Thus,somesitesmay284
15
exhibitaverysmalltotalrange,butsignificantdailyvariation,muchofwhichmay285
benoise;othersalargetotalrangeandrelativelysmalldailyvariation(stronger286
signal/noise).Theratioprovidesaconsistent“signalstrength”measurethatcanbe287
similarlyclassifiedfromexcellenttopoor.Thefollowingthresholdswerechosento288
groupthesignal/noisevaluesintoclasses:>.8,Excellent,.7-.79,VeryGood,.6-.69,289
Good,.47-.59,Fair,<.47,Poor.290
291
Thetwometricsseparatelyprovideanobjectiveassessmentofhowwellthe292
remotesensingagreeswiththemodeling,andhowstronglythesignalisrecording293
dischargevariationcomparedtotheday-to-dayvariationthatmaybemainlynoise294
alongmanyrivers.Knownsourcesfornoisemayinclude:1)geolocationerror(the295
geographicfootprintoftheswathimagedataincorporatedintothegriddedglobal296
productvariesslightly);2)sensornoise(theradiancemeasurementshavefinite297
precision);and3)non-surfacewaterareaeffectsontheratio(soanydifferential298
environmentalfactorsaffectingtheMpixelovertheriverandthedriestpixelsinthe299
Ccalibrationarray.300
301
Site Signal/Model SignalRange DischargeRange Signal/Noise r2302
Agreement anddaily303
304
108 VeryGood .11,.008 21,091m3/s Good .66305
23 Good .08,.009 25,507m3/s Fair .57306
26 VeryGood .09,.013 17,242m3/s Fair .67 307
29 Good .12,.014 35,891m3/s Fair .57308
16
30 VeryGood .20,.013 35,245m3/s VeryGood .70309
Table1.Summaryofmicrowavedischargemeasurement(RiverWatch)sitecharacteristics310
andaccuracyforsitesalongtheChindwin(108and23)andAyeyarwady(26,29,30).The311
signalrangestatisticrecordsthetotalmeasuredvariabilityofthedischarge-estimator312
signal;largervaluesindicateasitewheretheremotesensingsignalismoresensitiveto313
dischargevariation.Thenoisestatisticreferstotheaveragesignalvariabilityonadaily314
basis;largervaluesindicatemorenon-hydrologicnoise.Ther2valuesarecoefficientsof315
leastsquaresregressionoftheindependentWBMmodelingdischargeresultstotheremote316
sensingsignal(over5years,2000-2010,monthlydailymaximum,mean,andminimum317
values,n=180).318
319
Wheregroundgaugingstationsandsatellitegaugingsitesareco-located,the320
remotesensingcanalsobedirectlycalibratedtodischargedirectlyviatheground321
information.SelectedU.S.sites(e.g.,figure5)thereforecomparemodel-basedand322
groundstation-basedratingcurves:providingbothanassessmentofmodelbiasand323
oftheoverallaccuracyoftheRiverWatchinformation.Intheexampleshown,the324
riverchannelismeandering,butonly45mwide;thusalsodemonstratingthatthe325
RiverWatchmethodisnotlimitedtolargeriversbutinsteadrequiresonly326
floodplain/channelreacheswheretotalsurfacewaterextentchangesrobustlyas327
dischargechanges.328
329
17
330
Figure5.Model-andgroundstation-basedratingcurvesforTrinityRiver,331
Texas,RiverWatchsite446intheDartmouthFloodObservatory/Universityof332
Coloradoarray.TheWBMmodelwasusedtoproducetheblacklineratingcurve,333
whichisfittowidelyscattereddata.Aco-locatedUSGSgaugingstationwasusedto334
producetheredlineratingcurve,withmuchbettercorrelationtotheremote335
sensing.ComparisonofthetwocurvesindicatesaWBMmodelpositivedischarge336
biasincreasingwithhigherdischarges.Also,atthislocation,theWBMmodelmay337
performrelativelypoorlybecauseitdoesnotincorporateupstreamrivercontrol338
structures.339
SatelliteGaugingSiteSelection340
Thereareseveralfactorsaffectingtheselectionofgauginglocations.Itis341
importantthattheMpixelbelocatedtoavoidsaturation(completefillingofthe10342
kmmeasurementpixelbywater)duringfloodevents.Itisalsonecessarythatthe343
pixelmonitorsarelativelyuniformstretchofriverwithoutmajortributary344
junctions,ornearbystreams,orothervariablewaterbodiesthatmaychangein345
18
surfaceareawithoutdirectlyindicatingdischargechangesatthesiteintended.The346
measurementsitecan,however,include,suchriver-connectedfeaturesasoxbow347
lakesandotherwater-fillednegativerelieffloodplainfeatures(Lewinand348
Ashworth,2014)thatareconnectedtotheriver:theirexpansionorcontractionis349
responsivetolocalriverdischargechanges.350
351
Notethattheremaybesignificanttimelagsandhysteresisbetweenthefilling352
anddrainingoffloodplainsandthedischargestraversingthetrunkstreamchannel353
(Brakenridgeetal.,2007).Considerinthisregardthatthemicrowavemethodisnot354
usingreachwatersurfaceareaasasimpleproxyforriverflowwidth.Instead,a10355
kmx10kmparceloffloodplainandchannellandwithinterconnectedwater356
featuresisrecordingdischargevariation.Thesitesmustbevisuallyinspectedin357
mapformtoensurethat,ineachcase,theflowareachangesrelatetotheriverbeing358
monitoredandtoevaluatethepotentialinfluenceoftimelagsandalsoflowcontrol359
structuresalongtheriver.Anotherimportantconfoundingfactorisirrigated360
agriculture,especiallyricepaddies.Suchfarming,ineithertheMortheCpixel,can361
produceanentirelyerroneouschangeinthesignalratioasregardsdischarge;362
insteadthesignalrecordsirrigationchanges.363
364
Despitetherequirementforcarefulevaluationofeachpotentialriver365
measurementsite,thereareatleastseveralthousandsofadditionalRiverWatch366
sitesthatcouldbeestablishedandbeyondthe~300nowbeingpublishedonline367
(http://floodobservatory.colorado.edu/DischargeAccess.html).Themicrowave368
19
ratiosignalinformationisalreadyavailableforeachcelloftheglobalgrid.Aswell,it369
ispossibletouseobservedsitenumericalcorrelationstoknowndischargevariation370
enmasse:toselect,viathedegreeofcorrelation,thebestsitestoexaminefurther371
(VanDijketal.,2016).Throughthissatelliteobservationalmethod,insitugauging372
stationsarenotrequiredtoconsistentlyevaluatefloodriskalongsatellite-373
monitoredriverreachesandfloodplains:atleastforpredictedrecurrenceintervals374
ranginguptoapproximately40y.375
FloodMappingFromOpticalSatellites376
OneusefulmethodformappingfloodsandfloodhazardusesthetwoNASA377
MODISsensors(aboardthesatellitesTerraandAqua).Theseprovide36optical378
spectralbands;mostbandsofferspatialresolutionof1000or500m.However,two379
bands,inthevisibleandnear-IRportionsofthespectrum(620–670nm,band1,380
and841–876nm,band2)providespatialresolutionof250m;band2inparticular381
stronglydifferentiatessurfacewaterfromland.Suchinformationhasbeenusedto382
maptheinundationextentsreachedbyfloodsatmanylocationsworldwide383
(Brakenridgeetal.,2003a;Brakenridgeetal.,2012b;Policelli,2016),figure6.Allof384
the(twicedaily,globalcoverage)imagedatasincelate1999areavailableinvarious385
formatsinpublicNASAandotherdataarchives.386
387
Asfloodsevolve,dailymappingoftheinundationextentsprovideanearreal388
timeindicationoffloodseverity.Floodingcanbecomparedtopreviouslymapped389
water,suchaswinterlowflowconditionsandtypicalannualhighwater(figure6).390
20
Thus,accurate“flood”mappingdoesnotonlyinvolvemappingmaximumflood391
extentreachedbyanevent,butalsocomparisontowaterextentthatistypicalfor392
thesametimeofyear.Figure6illustratesthelargeamountofnormalannualwater393
variabilityinasummermonsoon-affectedregion,whichmustfirstbemaskedbefore394
unusualfloodingcanbediscerned.Mappingoversomeyearscantherebyprovide395
bothincreasinglycomprehensivefloodhazardinformation(moreprobabilityof396
imagingandmappingtheunusualhighfloods)andbetterinformationconcerning397
whataretypicalandatypicalhighwaterconditions.398
399
21
400
Figure6.MODISremotesensing-producedmapofmajor2015floodinginMyanmar401
(lightred),andalsothetypicalannualhighwater(2014,lightblue).Recurrence402
intervalsattheRiverWatchmeasurementsitesforthe2014“flood”are403
approximately1.5y.DarkblueisapermanentwatermappedbytheShuttleWater404
BoundaryData(https://lta.cr.usgs.gov/srtm_water_body_dataset)fromFebruary,405
2000,andrepresentstypicalwintersurfacewaterextent.406
407
22
RemoteSensing-basedFloodHazardQuantification408
Floodinundationmappingcanbecoupledwitheitherground-orspace-based409
rivergaugingtoconstrainthefrequencyofthemappedflood.Thus,usingriver410
dischargetimeseries,standardfloodfrequencymethods(Flynnetal.,2006)can411
analyzetheseriesofannualpeakdischargeswithintheperiodofrecordtoevaluate412
floodrecurrenceintervals/annualexceedanceprobabilitiesforanyparticularevent.413
IntheU.S.,theLogPearsonIIIprobabilitydistributionisused.Thereareother414
potentialissuesinvolvedincreatingariskassessmentatagaugingstation,415
particularlyforlarge,rareevents,andincludingthepossibilitytoapplyskewness416
coefficientsusingregionaldataandwithinthestandardizedLogPearsonIIIorother417
distributionfunctions.Thesetechniquesarewelldescribedintheliterature,and418
providevariousmethodsforextendingand/orextrapolatingthedataprovidedby419
anysingleriverpeakdischargetimeseries.420
421
Inanycase,however,theneedforspatialextrapolationoveraflood-prone422
landscaperemains.Asingleimageofalargefloodeventshowstheinundation423
extentoverlongreachesoffloodplain,andthelocalexceedanceprobabilitymay424
varysignificantlywithlocation.Theprobabilityestimatesobtainedfromatime425
seriesatadischargetimeseriesmeasurementsitestrictlyapplyonlytofloodingat426
thatsite.Thisposesaninterestingcontrasttomodel-basedriskmapping(other427
chaptersinthisbook):suchmodelspredictinundationfromaspecificrecurrence428
intervalanddischargevalueinaspatiallycontinuousmanner,andusing429
informationaboutchannelandfloodplainmorphologyandflowroutingequations.A430
23
floodimageinsteaddirectlyprovidestheinundationextent,withoutknowledge431
everywhereoftherecurrenceinterval.432
433
Infloodmodeling,thespatialcontinuityissueisimplicitlyaddressedby434
interpolation.Forexample,the20yfloodatsiteAmaybecalculatedat12,000m3/s435
andthatatdownstreamsiteB,16,000m3/s.Atariverlocationmid-waybetween436
thetwostations,andiftherearenomajortributaryjunctions,a20ydischargeof437
14,000m3/smaybemodeledforinundationpredictionthere(ingrid-based438
modeling,thisinterpolationisatthegridresolution).Borrowingfromthis439
approach,ifthesatelliteimagemapsafloodatbothstationlocations,witha440
calculatedrof12yatAbut18yatB,100kmdownstream,theimagedfloodlimits441
mayhave,inthiscase,arangeofrsomewherewithin12to18y.Theriskvaluesand442
mapinformationthenbecomesevenmorecomplex,asadditionalfloodsofdifferent443
returnperiodsaremapped.Suchcomplexitywouldnotaddresstheneedtoidentify444
inaconsistentwayfloodplainlandareasataparticularriskofflooding.445
446
Amorepracticalapproachistoinsteaddividethefloodeddrainagenetwork447
intoaseriesofsegmentedriverreaches:eachmonitoredneartheirmidpointsby448
eitheraground-basedorspace-baseddischargemeasurementsite(figures7and8).449
Underthisapproach,theassociatedrisassumedtoapplytotheinundationextent450
throughoutthereach,andlargerorsmallerfloodsimagedandmappedforthesame451
reachwilleachalsohavespecificrecurrenceintervals.Inthiscase,noattemptis452
madetointerpolatebetweenriverdischargemeasurementsites,butinsteadrisk453
24
454
455
456
457
458
25
Figure7.RecurrenceintervalandpeakdischargeestimatesforRiverWatchsite30459
alongthelowerAyeyarwadyRiver.Themicrowavemeasurementsiteisdefinedby460
thewhite10kmsquare.Inundationfor,top,anormalwinterflowof6253m3/son461
February11-22,2000;middle,observedviaMODISat250mspatialresolution,462
floodedareaforatypicalsummermonsoonal“flood”,r=1.5y(27,138m3/s,463
observed2013),andbottom,observedviaMODISagain,floodedareaformajor464
floodingin2004,r=24y(50,579m3/s.Notethatduringthisfloodamajor465
distributarytotheeast(theareaisattheheadoftheAyeyarwadydelta)isalso466
flooded.467
468
mapsarepreparedseparately,foreachmonitoredriverreach.Acombined469
mappingandmodelingapproach,whereinthemodelingprovidesthecontinuityand470
abilitytomapaparticularrecurrenceintervalflood,andtheremotesensing-based471
mappingprovidestheobservationalvalidation,reachbyreach,appearstobethe472
mostproductivewayforwardforlarge-regionmappingoffloodrisk.(DeGroeveet473
al.,2015a)474
475
476
477
478
479
480
481
26
482
483
484
485
Figure8.RecurrenceintervalandpeakdischargeestimatesforRiverWatchsite26486
alongtheupperAyeyarwadyRiver.Inundationfor,top,anormalwinterflowof487
27
~200m3/sinFebruary,2000;middle,atypicalmonsoonseasonflood,recurrence488
intervalof1.1y,~9000m3/s,in2002,and,bottom,inundationduringarareflood,489
recurrenceintervalof21y,18,200m3/s,in2013.490
Conclusion491
Theoutlinedapproachcouplesmicrowaveandopticalremotesensingto492
producequantitativefloodriskmaps.Thischapterdescribeshowthetwocanbe493
integrated:theincreasinglycomprehensiveglobalsatellitemaprecordofflood494
eventscanbematchedtoexceedanceprobabilitiesfrommicrowavedischarge495
recordstoproduceriskmapswithoutanyinsituinformation.Forthetwoexamples496
provided,theperiodofsatellite-microwave-observedflooddischargesbeginsin497
1998andisnowapproaching20y.Byaddingtheassociatedmicrowaverecord,the498
reach-levelfloodmapspreparedfromMODISopticalremotesensingshownotonly499
actualmappedfloods,butalsotheassociatedannualexceedanceprobabilities.Asis500
thecaseforfloodmodelingproducts,thesemapsareaquantitativeguidetofuture501
risk.502
503
Thereisalsoanimportantadditionaluseofsuchmaps:fornearrealtime504
floodinundationprediction.Unlesschannelsandfloodplainshavechangedsince505
previouslymappedfloods(e.g.,throughleveeconstructionorremoval),similar506
flooddischargesinthefuturealongthemonitoredreachesshouldcontinueto507
producesimilarinundationextents.Thispresentsanobservationalratherthan508
modelingpathforwardforfloodinundationprediction.Thatis,ifaparticularflood509
28
hydrographwasmeasured,eitherviaaninsitugaugingstationorthesatellite510
microwaveapproach,andtheresultingfloodplaininundationwasalsoobservedand511
mapped,thenthemapcanbeusedtounderstandwhatlandareaswillbe512
submergedwhenthatdischargeisonceagainattained.Alibraryofinundationmaps513
canbeassembled,andreferredtowhenfloodingagainoccurs.Notehowever,that514
floodhydrographvolume,aswellassimplypeakdischargeandstage,mayalso515
affectmaximuminundationextent,andespeciallyoverlargefloodplains.Flooded516
areaisarelativelynewhydrologicalobservablethatismadepossibleviaorbital517
remotesensing.Productiveresearchcannowbeaccomplishedrelatingdifferent518
aspectsoffloodhydrographstothesocietallyandecologicallyrelevantvariablesof519
inundationextentandduration.520
521
Thissatellite-basedfloodriskmethodispresentedinoutlineformhere,but522
therearecomplexitiesinvolvedinitspracticalimplementationandvalidation.For523
example,shorteningthereachlengthsandobtainingdatafromadenserarrayof524
dischargemeasurementsiteswouldincreasetheaccuracyanddetailofrisk525
mapping:bytestingandcomparingindividualmeasurementsiteresults.Asinmany526
otherareasofwork,replicationofthehazardresultsobtainedareimportantforthe527
resultstobetrusted.Also,considerthattheremayberelativelylargestepchanges528
betweencontiguousreachesinthecalculatedreturnperiodsforaparticular529
mappedflood,forexample,duetotheinfluenceoftributarydischarges:thiscould530
poseachallengeinthepreparationofregionalmaps,butalsoreflectstherealityof531
theactualfloodhistoryandfuturerisk.Ifregionalmapsareneeded,anotheruseful532
29
strategymaybetocouplethedescribed,reach-specificobservationalapproachwith533
regionalandevenglobalfloodhazardmodelingmethodssuchasaredescribedin534
otherchaptersinthisbook.Forthis,continuousspatialcoverageviaremotesensing535
isnotneeded(itisprovidedbythemodeling).Instead,thediscretereacheswhere536
riskischaracterizedbyremotesensingcanprovidecriticalmodelvalidation.537
538
Finally,thereisevidentutilityinfocusedattemptstoimageandmapthevery539
largestfloodeventsintheperiodofrecord(e.g.,the2004floodinginfigure4and6).540
Suchworkprovidesanunambiguousmappedhazardareafromthemostinfrequent541
andoftenexceptionallydamaginglargeevents,andnowtheirexpectedfrequency542
canalsobeapproximatelyconstrained.Indeed,thesesatelliteimagesand543
associatedmapsneedtobepreservedas“memorials”forposterityandinthesame544
waythatmanycommunitiesacrosstheglobepreservehighwatermarksfrom545
historicextremefloods(Davies,2014).Givenachangingclimate,andalsochanges546
inwatershedlandcoverandothercharacteristics,thereisalackofsupportfor547
assumingtemporalstationarityintheseriesofannualpeakdischarge(Millyetal.,548
2008).Yetitisonlybyusingthisassumptionthatprobabilitydistribution-based549
exceedanceprobabilitiescanbecalculated.Thiscautionsagainstmappingflood550
hazardasastaticquantity.Instead,quantitativefloodriskmapscanbeusedasa551
startingpoint,andpredictivemodelsthatprovideinformationforhowfloodregime552
maychangeintothefutureshouldbeincorporatedintofloodhazardmappingas553
well.554
30
References555
Brakenridge,G.R.,Anderson,E.,Nghiem,S.V.,Caquard,S.andShabaneh,T.,2003a.556
Floodwarnings,flooddisasterassessments,andfloodhazardreduction:the557
rolesoforbitalremotesensing.,Proceedingsofthe30thInternational558
SymposiumonRemoteSensingoftheEnvironment,Honolulu,pp.4.559
Brakenridge,G.R.,Anderson,E.,Nghiem,S.V.andChien,S.,2005.Space-based560
measurementofriverrunoff.EOS,TransactionsoftheAmericanGeophysical561
Union,86.562
Brakenridge,G.R.,Carlos,H.,Anderson,E.andInternationalSocietyforOptical563
Engineering(SPIE),C.,Greece,andProceedingsofSPIE,Vol.4886,p.479-564
485..2003b.Satellitegagingreaches:astrategyforMODIS-basedriver565
monitoring.9thInternationalSymposiumonRemoteSensing9th566
InternationalSymposiumonRemoteSensing.567
Brakenridge,G.R.,Cohen,S.,Kettner,A.J.,DeGroeve,T.,Nghiem,S.V.,Syvitski,J.P.M.568
andFekete,B.M.,2012a.Calibrationoforbitalmicrowavemeasurementsof569
riverdischargeusingaglobalhydrologymodel.JournalofHydrology,570
http://dx.doi.org/10.1016/j.jhydrol.2012.09.035.571
Brakenridge,G.R.,Kettner,A.J.,Slayback,D.andPolicelli,F.,2016a.GlobalAtlasof572
Floodplains,Sheet090E030N.DartmouthFloodObservatory,Universityof573
Colorado,Boulder,CO.574
Brakenridge,G.R.,Nghiem,S.V.,Anderson,E.andMic,R.,2007.Orbitalmicrowave575
measurementofriverdischargeandicestatus.WaterResourcesResearch,576
43(W04405,doi:10.1029/2006WR005238).577
31
Brakenridge,G.R.,Syvitski,J.P.M.,Nieburh,E.,Overeem,I.,Higgins,S.A.,Kettner,A.J.578
andPradesh,L.,2016b.DesignwithNature:CausationandAvoidanceof579
CatastrophicFlooding,Myanmar.Earth-ScienceReviews,Inreview.580
Brakenridge,G.R.,Syvitski,J.P.M.,Overeem,I.,Stewart-Moore,J.A.andKettner,A.J.,581
2012b.Globalmappingofstormsurges,2002-presentandtheassessmentof582
coastalvulnerability.NaturalHazards,DOI10.1007/s11069-012-0317-z.583
Cohen,S.,Kettner,A.J.andSyvitski,J.P.M.,2011.WBMsed:adistributedglobal-scale584
riverinesedimentfluxmodel-modeldescriptionandvalidation..Computers585
andGeosciences,doi:10.1016/j.cageo.2011.08.011(2011).586
Davies,T.,2014.FloodandHighWaterMarks.FloodList.587
DeGroeve,T.,Brakenridge,G.R.andParis,S.,2015a.GlobalFloodDetectionSystem588
DataProductSpecifications.JRCTechnicalReport.,589
http://www.gdacs.org/flooddetection/Download/Technical_Note_GFDS_Dat590
a_Products_v1.pdf.PublicationsOfficeoftheEuropeanUnion.591
DeGroeve,T.,Kugler,Z.andBrakenridge,G.R.,2006.NearRealTimeFloodAlerting592
fortheGlobalDisasterAlertandCoordinationSystem.Proceedings593
ISCRAM2007(B.VandeWalle,P.BurghardtandC.Nieuwenhuis,eds.):33-39.594
DeGroeve,T.andRiva,P.,2009.Earlyflooddetectionandmappingfor595
humanitarianresponse.Proceedingsofthe6thInternationalISCRAM596
Conference–Gothenburg,Sweden,May2009,J.LandgrenandS.Jul,eds.597
deMoel,vanAlphen,J.andAerts,J.C.J.H.,2009.FloodmapsinEurope-methods,598
availability,anduse.Nat.Hazards.EarthSyst.Sci,9:289-301.599
32
FEMA,2002.HEC-RASproceduresforHEC-2modelers.FloodplainModeling600
Manual.FederalEmergencyManagementAgency,Washington,DC,78pp.601
Flynn,K.M.,Kirby,W.H.andHummel,P.R.,2006.User’sManualforProgramPeakFQ,602
AnnualFlood-FrequencyAnalysisUsingBulletin17BGuidelines.U.S.603
GeologicalSurvey,Reston,Virginia:42.604
Klingeman,P.,2005.AnalysisTechniques:FloodFrequencyAnalysis.Streamflow605
evaluationsforwatershedrestorationplanninganddesign.OregonState606
University,Corvalis,Oregon,USA.607
Lewin,J.andAshworth,P.J.,2014.Thenegativereliefoflargeriverfloodplains.608
EarthScienceReviews,129:1-23.609
Milly,P.C.D.,Betancourt,J.,Malin,F.,Hirsch,R.M.,Kundzewicz,Z.W.,Lettenmaier,610
D.P.andStouffer,R.J.,2008.StationarityIsDead:WhitherWater611
Management?Science,319:573-574.612
Policelli,F.,2016.TheNASAglobalfloodmappingsystem,.In:V.Lakshmi(Editor),613
RemoteSensingofHydrologicExtremes.Springer-Verlag.614
Revilla-Romero,B.,Thielen,J.,Salamon,P.,DeGroeve,T.andBrakenridge,G.R.,615
2014.Evaluationofthesatellite-basedGlobalFloodDetectionSystemfor616
measuringriverdischarge:influenceoflocalfactors..Hydrol.EarthSyst.Sci.,617
18:4467-4484.618
VanDijk,A.I.J.M.,Brakenridge,G.R.,Kettner,A.J.,Beck,J.E.andDeGroeve,T.,2016.619
Rivergaugingatglobalscaleusingopticalandpassivemicrowaveremote620
sensing.WaterResourcesResearch,52:6404-6418.621
33
Wahl,K.L.,Thomas,W.O.andHirsch,R.M.U.,RestonVA,1995.Stream-gaging622
programoftheU.S.GeologicalSurvey,USGSCircular1123.U.S.Geological623
Survey.624
625
