ContentslistsavailableatScienceDirect
Journal
of
Hydrology:
Regional
Studies
jou rn a l h om ep a ge :w w w . e l s e v i e r . c o m / l o c a t e / e j r h
Relating
stream
function
and
land
cover
in
the
Middle
Pee
Dee
River
Basin,
SC
A.D.
Jayakaran
a,∗,
Z.T.
Smoot
b,
D.M.
Park
c,
D.R.
Hitchcock
d aWashingtonStateUniversity,Puyallup,WA98371,USAbWoolpertInc.,Columbia,SC29210,USA cClemsonUniversity,Clemson,SC29634,USA dClemsonUniversity,Georgetown,SC29442,USA
a
r
t
i
c
l
e
i
n
f
o
Articlehistory:
Received17September2015 Receivedinrevisedform 25December2015 Accepted29December2015 Availableonline17February2016 Keywords:
Flashiness Streamhabitat Flowindices Landcoveranalysis Wetlands Coastalplain Bedmaterial
Partialleastsquaresregression PeeDeeRiver
SouthCarolina
a
b
s
t
r
a
c
t
Studyregion:Thestudyregioncomprisedsixteenstreamsitesandassociatedcontributing watershedslocatedintheMiddlePeeDeeRiverBasin(MPDRB)ofSouthCarolina,USA.
Studyfocus:Thestudywasconductedbetween2008and2010toquantifyhowindices ofstreamflowvariedwithlandcovercharacteristicsanalyzedatmultiplespatialscales andfluvialgeomorphiccharacteristicsofsampledstreamsintheMPDRB.Studyobjectives weretorelatethreeindicesofstreamflowthatreflectrecenttemporalflowvariabilityin astream,withsynopticstreamgeomorphologicalmeasurements,andlandcovertypeat specificspatialdomains.
Newhydrologicalinsightsfortheregion:Modificationstothelandscape,hydrologicregime, andalterationtochannelmorphology,aremajorthreatstothefunctioningofriparian ecosystemfunctionsbutcanrarelybelinkedtoasinglecommonstressor.Resultsfromthe studyshowedthatintheMPDRB,wetlandcoverintheripariancorridorwasan impor-tantfactor,correlatingsignificantlywithstreamflashiness,channelenlargement,andbed substratecharacter.Itwasalsoshownthatacombinationofstreamgeomorphological characteristicswhencombinedwithlandscapevariablesatspecificspatialscaleswere reasonablepredictorsofallthreeindicesofstreamflow.Thestudyalsohighlightsan inno-vativestatisticalmethodologytorelatelandcoverdatatocommonlymeasuredmetricsof streamflowandfluvialgeomorphology.
©2015TheAuthors.PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCC BY-NC-NDlicense(http://creativecommons.org/licenses/by-nc-nd/4.0/).
1. Introduction
In 2010, the South Carolina Legislature sought to regulate withdrawals from surface water sources in the state (A247—SouthCarolinaSurfaceWaterWithdrawal,Permitting,Use,andReportingAct,2010).Thepotentialalterationto flowregimesbysurfacewaterwithdrawalsandtheirimpactsonriparianecosystemsisstilltosomeextentanunknown inseveralwatershedsthatareaffectedbythelaw.Inorderforregulatoryagenciestomakesounddecisionsingranting surfacewaterpermits,agreaterunderstandingoftherelationshipofcurrentstreamflowrates,channelmorphology,and landcoverdriversinSouthCarolina’swatershedsbecameofcriticalimportance.Thisstudywasconductedfrom2008to 2010todeterminethefluvialgeomorphiccharacteristicsoftheMiddlePeeDeeRiverBasin(MPDRB),andtherelationship
∗ Correspondingauthorat:CollegeofAgriculture,Human,andNaturalResourceSciences—WSUExtension2606WestPioneer,Puyallup,WA98371, USA.Tel.:+12534454523;fax:+12534454522.
E-mailaddress:anand.jayakaran@wsu.edu(A.D.Jayakaran). http://dx.doi.org/10.1016/j.ejrh.2015.12.064
2214-5818/© 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
262 A.D.Jayakaranetal./JournalofHydrology:RegionalStudies5(2016)261–275
oftheseripariansystemstolandcover.Whilethephysicalcharacteristicsofaripariansystemareintimatelyintertwined withthebiologicalandecologicalcharacteroftheecosystem,thisstudyfocusedsolelyontheabioticstructureofstream andlandscape.Thegoalofthisworkwastoinvestigatetherelationshipbetweenlandscapecharacteristicsandthreeindices ofstreamflow.Theoverallobjectiveofthisworkwastodetermineifbymeasuringcommonlandscapeandstream geomor-phologicalparametersintheMPDRP,couldonereasonablyestimatecharacteristicsofstreamflowregimewithouthaving toinvestthetimeandresourcesneededtomeasurecontinuousstreamflowatalocation.Ultimately,wehopedthatthis workwouldprovideinsightonlandscapefactorsthatmostinfluencedflowregimefortheirinclusioninthedevelopment ofplanned,state-regulatedflowregimesthatwouldmaintainecologicalviabilityintheMPDRB.
1.1. Watershedscaleanalysesandstreamhealth
Ithasbeenwidelydocumentedthatanthropogenicchangestothelandscapeimpactripariansystems(Brabec,2009;
Boothetal.,2004;Allan,2004;Poffetal.,1997;Hammer,1972)andinmanycasescanleadtoalterationsthatsurpassthe
system’sabilitytoreturntoitsoriginalstate(Blannetal.,2009).Blannetal.(2009)identifiedmodificationstohydrology, geomorphology,nutrientcycling,andsedimentdynamicsasbeingmajorthreatstoripariansystemfunctions.Landcover changescanresultindrasticchangestowaterquality(Bedoyaetal.,2009),hydrologicregime(BoothandJackson,1997), andincreasedsedimentinputsthatsubsequentlyimpairstreamhabitat(Tuffordetal.,2003;Gergeletal.,2002).However, suchdrasticchangesarerarelylinkedtoasinglestressor(Bedoyaetal.,2009).Thereareseveralmetricsusedtoquantify anthropogenicinfluenceonalandscape,theseincludesummedtotalimperviousarea(IMP)(Hammer,1972), Landscape-DisturbanceIndex(LDI)asdefinedbyStanfieldandJackson(2011),andtheextentofagriculturalandcommercialland coverwithinawatershed.Eachmetrichasbeenfoundtoinfluencethephysicalandecologicalconditionofastreamsystem
(Brabec,2009;BoothandJackson,1997).Imperviousareahasbeenshowntohavedeleteriousimpactsonstreamprocesses
(Brabecetal.,2002)andthresholdsformaintainingstreamhealthtendtobewatershed-specificrangingfrom4to15%
imperviousness(Schueler,1994;Klein,1979;BoothandJackson,1997;HicksandLarson,1997;Bakeretal.,2004;Brabec, 2009).Agriculturallanduseswithinhighlymodifiedwatershedsareoftensynonymouswithhighernutrientinputstostream systems(Kingetal.,2005;Howarthetal.,1996;Vitouseketal.,1997;Tilmanetal.,2001)aswellashydromodification associatedwithstreamchannelization(JayakaranandWard,2007;RhoadsandHerricks,1996).
1.2. Theanalysisoflandscapemetricsatmultiplescales
Withevidenceoflandscapeimpactsonstreamfunction(Blannetal.,2009;Frimpongetal.,2005;Sutherlandetal.,2002;
Fitzpatricketal.,2001;Daviesetal.,2000;Staufferetal.,2000;Rothetal.,1996;BerkmanandRabeni1987;Oswoodand
Barber,1982),thereisalsoevidencethatcertainlandscapedrivershavegreaterinfluenceoninstreamfunctionatspecific
spatialscales(e.g.Kingetal.,2005;Sponselleretal.,2001;Maddock1999;Rankin,1995).Whilesomeaspectsofastream’s character(suchasbedmaterialtype,presenceofwoodydebris,channelroughness)tendtobeinfluencedby localized/reach-scalefactors,others(suchaschannelshape,bedmaterialtransport,streamflashiness)aremoreinfluencedbyfactorsatlarger landscape/catchmentscales(Bedoyaetal.,2009;McRaeetal.,2004;Wangetal.,2003;Richardsetal.,1996;Allanetal., 1997).However,itisimportanttonotedistinctionsbetweenlandscapeandreachscaleprocessesaremostlysemantic, andpragmaticallythereisconsiderableoverlapbetweenthetwo.Forexample,Allanetal.(1997)showedthatlandcover couldbeastrongindicatorofreach-specificbiologicalandhabitatintegrityfor100-mreaches,wherebiologicalandhabitat integrityweremeasuredbyahabitatindex(HI)andanindexofbioticintegrity(IBI),respectively.Inthatstudy(Allanetal., 1997),agriculturallandcoverexplainedasmuchas50%ofthevarianceinIBIand75%ofthevarianceinHI.Theauthors alsodocumentedthatagriculturalcoveratthecatchmentscalewasfarmoreindicativeofbiotaandhabitatatasitethan reach-scalelandcoverinformation,althoughcorrelationswerefoundatbothscales.
1.3. Characterizingstreamflow
Synopticphysicalhabitatassessmentsandfluvialgeomorphicmeasurementsprovideinsightintothecurrentecological conditionofastream,butdonotincludeinformationonstreamfunctioningthatcanonlybederivedfromarecordof recentstreamflowdata.Thelackofinformationonrecentflowhistoryisusuallyafunctionofthecost-prohibitivenatureof installing,andmaintaining,continuousstreamflowloggingequipment.Withthisstudy,wehopedtoshowthatthroughthe synopticmeasurementofspecificcharacteristicsofchannelmorphologyandlandcover,certaincharacteristicsofstreamflow atasitemightberevealed.Secondly,wealsohopedtodevelopinsightintowhatlandcoverparametersmostinfluenced flowinthestreamsoftheMPDRB.Threeindiceswerechosentocharacterizestreamflow:
a)Ameasureofchannelenlargement(Pizzutoetal.,2000)requiringknowledgeofbankfullflowatthatlocation—Hammer number(H).
b)Anestimateofstreamflashiness(Bakeretal.,2004)requiringacontinuousflowrecordatasite—RichardsBakerFlashiness Index(RBI).
c)Anestimateofbed materialtransport (Brownlie,1981)requiring bothstreamflow record,channeldimensions,and channelsubstratedata—BedMaterialYield(BMY).
Thethreeselectedindicesofstreamflowprovideinformationonstreamfunctioninlightofprevailingreach-scaleand landscape-scalecharacteristicsofthewatershed.Theseindicescouldpotentiallybeusedtocharacterizehowstreamfunction mightchangeovertime,givenchangestolandscape(landusechange)orflowregime(dams,waterwithdrawals).
Hammernumber(H)wasametricproposedbyPizzutoetal.(2000)asameanstoquantifythephenomenonofchannel enlargementduetourbanization(1972).Mathematically,Hisdefinedastheflowconveyedbythebankfullchannelperunit watershedareaor,bankfullflowrateperunitdrainagearea(units:m/s).Hreflectsthehydraulicpropertiesofthestream channelreachandnotthehydrologiccharacteristicsofthewatershed(Pizzutoetal.,2000).ThisisnottosaythatHis unaffectedbydrainagearea,buttosaythatHisameasureofhowthebankfullchannelhasadjustedtoprevailinghydrologic conditions.
Flashiness(RBI)quantifiestherateofchangeofstorm-associatedflowwithrespecttobaseflowconditionswithhigherRBI valuessignifying“flashier”streams.Flashinessinstreamsistypicallyassociatedwithincreasedwatershedimperviousness (e.g.Walshetal.,2005)buthasalsobeenassociatedwithstreamchannelizationandhighgroundwaterconditions(e.g.
Jayakaranetal.,2014).RBIisaunitlessindexthatdoesnothaveamaximumlimitalthoughBakeretal.(2004)reporteda
maximumRBIof1.3inastudyof515Midwesternstreams.
BedMaterialYield(BMY)isthetotalbedmaterialtransportedbyastreamexpressedperunitwatershedarea(units: tons/ha/yr).BMYwaschosenasanindexofstreamfunctioningasitintegratesthehydraulicpropertiesofastreamreach, hydrologiccharacterofthewatershed,andbedmaterialcharacteristicsofstreamsubstrate.Forthisstudy,wecalculated BMYusingBrownlie’s(1981)resistanceequationsforsand-bedstreams(USDA-NRCS,2004)usingflowandbedmaterial information.
1.4. Studyobjectives
Objectivesofthisstudywereto:(a)relatethreeindicesofstreamflowtoobservedstreamgeomorphologicalfeatures, (b)identifywhichlandcovertypesandatwhatspatialresolutionmostinfluenceindicesofstreamflow,(c)determineif combinationsoflandscapeandgeomorphologicalvariablescanadequatelypredictcertainstreamflowcharacteristics.
2. Studyareaandmethods
StreamsandtributarieswithintheMPDRBclassifyaslowgradientblackwatercoastalplainstreamswithsandor sand-gravelmixstreambeds.All16siteswerelocatedinthelevel3SoutheasternPlainsecoregion(Olsenetal.,2001)andwithin twolevel4ecoregions:AtlanticSouthernLoamPlainsandSandHills(Fig.1).TheSoutheasternPlainsecoregionliesbetween thePiedmontandtheMiddleAtlanticCoastalPlain.Studysiteswereselectedtorepresentawiderangeofwatershedareas (17–1,718km2).Siteselectionwasalsodependentuponlandusewithinthewatershed,easeofaccess,andsecurityof
instrumentation.Sixofthechosensiteswereco-locatedwithUnitedStatesGeologicalSurvey(USGS)flowmonitoring gauges,andfivesiteswerechoseninconjunctionwiththeSouthCarolinaDepartmentofNaturalResources(SCDNR) fish-monitoringprogram.Averageannualrainfallintheregionis1,197mmwhileevapotranspirativedemandis762mmannually (Luetal.,2005).
2.1. Landscovermetricsandscalesofspatialanalyses
SixlandcovermetricswereanalyzedatfivespatialscalesperSponselleretal.(2001):theentirecatchmentscale,a ripariancorridorscale,andthreeriparian‘sub-corridor’scales(200,1000and2000mupstreamofstudysite).Theentire catchmentscalecomprisedtheentirewatershedupstreamofasamplingsite.Theripariancorridorscalecomprisedariparian bufferdefinedinthelateral(landscape-to-stream)directionbyahydraulicflowlengthof180mextendingtoeitherside ofthestream.Thehydraulicflowlength(orflowtraveldistance)wasderivedfroma30-mdigitalelevationmodelwithin ageographicinformationsystem(GIS)usingtheArcHydrotool(ArcMapversion10.0,EnvironmentalSystemsResearch Institute,RedlandsCA).Theripariancorridorinthelongitudinalupstreamdirection(along-channel)includedallstreams andtributariesupstreamofthesamplingsite.Theripariancorridorwasfurthersubsetintothreeripariansubcorridorsthat extendedtooneofthreedistancesupstreamfromasamplingsite—200m,1000m,and2000mupstreamofthesite.Theonly departurefromSponselleretal.’s(2001)methodologywasourchoiceofdefiningthelateralcorridorwidthbyhydraulicflow length.Thesixmetricsoflandcoverwerederivedfromthe2006NationalLandCoverDatabase(NLCD)geospatialdataset withinaGISenvironment.Thelandcovermetricsusedinthisstudywere:landdisturbanceindex(LDI),curvenumber(CN), totalimperviousarea(IMP),percentforestedland(FOR),percentagriculturalland(AGR)andpercentwetlands(WET).
LDI(StanfieldandJackson,2011)wasclassifiedinaGISenvironmentpermethodologyprescribedbyMorrisonetal.
(2006).Thefollowingsimplificationsofthe2006NLCDdatasetwereperformedtobeconsistentwiththeclassification
systemusedbyStanfieldandJackson(2011):agriculturalareasincludedalllandcoverclassifiedasrow-cropagriculture; forestedareasincludedallpine,deciduousandmixedforestclasses;andwetlandsareasincludedallherbaceouswetland,and emergentherbaceouswetlandclasses.Landcoverclassifiedasopenwater,barrenland,andherbaceousgrasslandswere
264 A.D.Jayakaranetal./JournalofHydrology:RegionalStudies5(2016)261–275
Fig.1.Locationofstudysites,majorstreamnetworksandcontributingdrainageareas.Insetfigure(a)showsallsitesarelocatedwithintheSoutheastern Plainslevel3ecoregion.Insetfigure(b)showsSites1,2,11,12,15,and16arelocatedintheAtlanticSouthernLoamPlainsecoregion(level4).Theremaining sitesfallwithintheSandHillsecoregion(level4).SeeTable1formoresite-specificinformation.
omittedfromallanalyses.Hydrologiccurvenumber(CN)wasderivedbycross-referencinggeospatialdatarepresenting landcoverandhydrologicsoilgrouping,whereallgeospatialdatahada30×30mspatialresolution.Hydrologicsoilgroups (HSG)werederivedbyreclassifyingdatafromtheNationalResourcesConservationService’sSoilSurveyGeographicdatabase (SSURGO).HSGdatawerethencross-referencedagainstlandcoverinformationfromthe2006NLCDdataset.Asaresult, uniqueCNswereobtainedforevery30×30mpixelrepresentingtheMPDRBregion.
2.2. Streamgeomorphologyandflowmeasurements
Forthetenwadeablestreamsites,topographicalsurveyswereusedtomeasurechannelpattern,profile,anddimension
perHarrelsonetal.(1994).Ateachsite,thestreamprofilewassurveyedforthirtybankfullwidthsandincludedthalweg,water
surfaceandbankfullelevations.Atleastthreerepresentativecrosssectionsalongthesurveyedprofilewerealsomeasured. Atthesixnon-wadeablesites,channelpattern,profile,anddimensionbelowthewaterlevelwerecharacterizedusinga floatingacousticdopplercurrentprofiler(ADCP)unit(SontekRiverSurveyorM9,SanDiego,CA).Topographicsurveyswere carriedouttocompletetheabove-waterportionsofthestreamcrosssectionsthatcouldnotbeprofiledwiththeADCPunit. SurveydatawereprocessedusingtheReferenceReachSpreadsheetforChannelSurveyDataManagement(Mecklenburgand
Ward,2004).RiparianconditionwasassessedusingtheQualitativeHabitatEvaluationIndex(QHEI)developedbyRankin
(1989).QHEIisasemi-quantitativephysicalhabitatindexdevelopedtoprovideanevaluationofhabitatqualityforfish.
Scoresrangefrom0to100withscoresabove60consideredtobegoodtoexcellentforaquaticlife,andscoresbelow45 consideredlimiting.Forthisstudy,QHEIwasusedpurelyasameanstocomparerelativehabitatqualityamongsites,and notforcomparisonwithsitesfromotherstudiesandregions.
Flowvelocitiesatwadeablesitesweremeasuredusingahandheldflowmeter(YSI-SontekFlowTracker,SanDiego,CA)
perJohn(2001),andatnon-wadeablesitesusingtheADCPunitperMuellerandWagner(2009).Bedmaterialsamplesat
eachstreamsitewerecollectedatfivelocationswithashallowwaterbottomdredgesamplerfollowingagriddedsampling approach.Bedmaterialsampleswerethendried,analyzedbysieveanalysisforparticleslargerthan2mm,andbyalaser diffractionparticlesizeanalyzer(BeckmanCoulterTM,Brea,CA)forparticlesbetween0.001mmand2mm.Particlesize
distributionwascharacterizedbycalculatingthe16th,50th,and84thpercentiles(D16,D50,andD84,respectively)aswell asthegeometricsorting()coefficient(Kondolfetal.,2003).Bankfulldefininghydraulicgeometrywasnotestimatedat site15assignificantbeaveractivityimmediatelydownstreamofthesiteearlyinthestudylimitedflowestimation.Forthis study,allbankfullvaluesweredeterminedbasedonindicatorsoutlinedbyDunneandLeopold(1978).Aweightofevidence approachtoestimatebankfullelevationwasmade,satisfyingasmanyindicatorsaspossible.
Fifteen-minute streamflow data for the six USGS sites were obtained from the USGS real time water website
(http://waterdata.usgs.gov/sc/nwis/rt);dataavailabilityrangedfrom3to52years.Forthetenremainingsites,flowwas
determinedfromatmosphericpressurecompensatedstreamstagedata(Levelogger®andBarrologger®,Solinst,Ontario,
Canada)inconjunctionwithstage-flowratingcurvesdevelopedforeachsite.Sensorswereinplaceforaperiodofalmost 3yearsfromJuly2009toJune2012.USGSflowrecordsweretruncatedtotheperiodbetweenJuly2009andJune2012 ensuringthattheperiodforstreamflowdatawasconsistentacrossall15sites.Theonlyexceptionisashortenedstreamflow recordfromsite16(JeffriesCreek,USGS)duetodecommissioningofthatsiteinSeptember2010.Fifteen-minuteflowand streamstagedatawereconvertedtomeandailyvaluesforestimationofstreamflowindices.
2.3. Indicesofstreamflow
Streamflowwascharacterizedbyevaluatingthreeprimaryindices–theRichards-BakerFlashinessIndex(RBI)(Baker etal.,2004),Hammernumber(Pizzutoetal.,2000),andbedmaterialyield(BMY)asestimatedusingBrownlie’sequation
(1981)forsandbedstreams.Calculatedbedmaterialtransportwassummedovertheperiodofstudyandconvertedtoa
yieldperunitwatershedarea.
2.4. Statisticalanalysis
Theclassifyingoffluvialgeomorphicvariablesstrictlyasdependentand/orindependentiscomplicatedbythe interde-pendenceofvariablesbroughtaboutbyreinforcingfeedbackloopsbetweenwater,sediment,vegetation,landscapeand channelshape(SchummandLichty,1965;AshworthandFerguson,1986);aswellastheself-organizingcharacteroffluvial processes(JayakaranandWard,2007;Rodríguez-IturbeandRinaldo,2001;Parker,1996).Tohandlethiscomplexity,we deliberatelychosenottotestapriorihypotheses.Insteadwechosetoclassifystatisticalanalysesinthisstudyintotwotypes: causaltypeanalyseswhereweidentifiedpredictorandresponsevariablesandtestedtheirrelationshipbybivariate regres-sion;andpredictivetypeanalyseswheremultipleregressionmodelsweredevelopedtopredictanindexofstreamflow, basedonselectedlandscapeandchannelmorphologicalparameters.
Alldataweregroupedintothreeclasses:(1)threestreamflowindices(RBI,H,andBMY)treatedasbothdependentand independentvariablesdependingonthetypeofanalysis(2)thirtylandcovervariablescomprisingsixlandcoverclassesat fivespatialscales,alltreatedasindependentvariables,and(3)twelvechannelgeomorphologicalvariablesdescribingriparian habitat,bankfullfeatures,bedmaterial,streamslope,andstreamroughnesstreatedasdependentorindependentdepending ontheanalysis.AsummaryofhowvariablesweretreatedandstatisticalanalysesusedisoutlinedinTable2.
AlldatawerefirsttestedfornormalityusingShapiro–Wilkes’testandwhennon–normal,transformedusingBoxCox transformations(BoxandCox,1964).Thosevariablesthatdidnotachieveanormaldistributionpost-transformationwere omittedfromfurtheranalyses.Thestrengthofrelationshipsbetweenindicesofstreamfunctioning,andinfluential geo-morphologicalandlandcovervariablesweretestedbysimpleandmultipleregressiontechniquesat˛=0.10.Duetothe largenumberofindependentvariables,onlyselectedgeomorphologicalandlandcovervariableswereusedforsubsequent regressiontesting.Toparedownvariables,onlythosemostcorrelatedwithindicesofstreamflowbyPearsoncorrelation werechosenforfurtheranalyses.Toselectlandcovervariablesthatmostinfluencedindicesofstreamfunction,thevariable importanceinprojection(VIP)procedureforpartialleastsquaresregression(PLSR)wasused(seeChongandJun,2005). PLSRisparticularlyamenableforusewithhighlymulticollineardata(Woldetal.,2001),aconditionthatcharacterizedthe landcoverdatausedinthisanalyses.Multicollinearityoflandcoverdatawascompoundedbythefactthatriparian corri-dorandsubcorridorscaleswerenested.ThePLSR-VIPprocedurewasimplementedinatwo-stepproceduretodetermine whatlandcover-spatialscalecombinationmostinfluencedanindexofstreamflow.Asafirststep,aparticularlandcover atallfivespatialscaleswereanalyzedbyPLSR-VIPtodeterminewhichspatialscaleofthatlandcovermostinfluenceda streamflowindex.Thisprocesswasrepeatedforeachlandcovervariable,andforeachstreamflowindex.Withsixland cover-spatialscalevariablesperstreamflowindexchosenfromthefirststep,asecondPLSR-VIProutinewithamodified jackknifeproceduretoestimateparametersignificance(perMartensandMartens,2000)wascarriedout.Significantland cover-spatialscalevariableschosenfromthesecondstepandimportantstreamgeomorphologicalvariables(bypreviously describedcorrelationanalyses)werethenrelatedtoeachstreamflowindexusingmultiplelinearregression.Thestrength ofthepredictiveregressionmodelswereevaluatedbycomparingthepredictiver2statisticgeneratedbyeachregression
model.
3. Results
3.1. Landcoveranalysis
Atthecatchmentscale,AGRrangedfrom23%to58%,FORrangedfrom13%to64%,WETrangedfrom4%to27%,and IMPrangedfrom0.4%to5.2%.Wetlandstypicallydominatedlandcoveratthethreesmallestripariansub-corridorscales (200m,1000m,and2000m),withWETdecreasingwithincreasingupstreamextentofripariansubcorridor.Streamsites intheASLPecoregionhadfractionallymorewetlandsinthecatchmentandripariancorridorscomparedtothosestreams intheSHecoregion(Fig.2a).ThedifferencebetweenWETatthecatchmentandripariancorridorscalesisameasureof
266 A.D. Jayakaran et al. / Journal of Hydrology: Regional Studies 5 (2016) 261–275 Table1
Sitecharacteristicsincludingsitelocationbylevel4ecoregions(ASLP,SH:AtlanticSouthernLoamPlainsandSandHills,respectively),drainagearea(DA),bankfullchanneldimensions(Wbkf,Dbkf,Qbkf:bankfull width,depth,andflow,respectively),riparianhabitat(QHEI)andlandcover(For,Ag,Wet,Imp:Forest,Agriculture,Wetland,andImpervious,respectively).Severalsitescoincidedwithlocationsmonitoredby USGSandSCDNR.FlowwasnotmeasuredatSite15duetobeaveractivity.
Name Eco-region DA Wbkf Dbkf Qbkf Slope D50 QHEI For Ag Wet Imp LDI RBI H BMY Notes
km2 m m m3/s % m %oftotalDA *10−6m/s t/ha/yr
1 CrookedCreek ASLP 167.4 14.3 1.0 6.3 0.110 382 66.5 26.3 42.8 19.9 1.5 11.1 0.15 0.038 1.34
2 CrookedCreekDNR ASLP 72.1 8.9 0.8 2.3 0.069 289 57.5 25.5 33.5 26.5 0.7 13.4 0.19 0.032 0.33 DNR,wadeable
3 HuckleberryBranch SH 17.3 3.4 0.4 0.5 0.420 471 67.5 16.2 51.4 13.6 4.0 15.9 0.14 0.029 1.09 wadeable
4 ThompsonCreek SH 385.0 19.8 1.5 15.7 0.039 853 55.5 61.1 28.6 3.9 0.6 5.5 0.19 0.041 0.27 wadeable
5 JuniperCreek SH 50.9 9.2 0.8 1.4 0.023 304 43.0 49.4 28.9 13.5 1.0 6.2 0.21 0.027 0.02 wadeable
6 JuniperCreekDNR SH 96.5 6.8 0.9 2.3 0.170 354 61.5 50.0 28.3 13.8 1.0 6.0 0.14 0.024 1.27 DNR,wadeable
7 HamsCreekDNR SH 45.6 6.9 0.7 1.9 0.200 242 78.0 62.7 26.4 6.9 0.4 3.2 0.23 0.043 1.32 DNR,wadeable
8 LynchesRiveratHwy1 SH 998.3 28.9 2.0 42.7 0.033 505 50.0 53.8 34.2 6.3 0.7 5.7 0.31 0.043 0.57
9 LittleLynchesRiverDNR SH 154.5 20.7 1.0 11.6 0.140 764 48.0 63.9 23.3 5.4 0.8 4.4 0.42 0.075 0.51 DNR,wadeable
10 LittleForkCreekUSGS SH 39.3 8.1 0.6 2.1 0.280 866 65.0 49.5 35.4 3.7 1.3 7.1 0.46 0.053 1.01 USGS,wadeable
11 LynchesRiver@BishopvilleUSGS ASLP 1717.9 46.7 3.2 68.1 0.029 295 43.5 52.8 32.9 9.0 0.7 5.6 0.21 0.040 0.14 USGS
12 BlackCreek@QuinbyUSGS ASLP 1137.1 26.7 2.1 31.5 0.141 319 57.5 30.1 45.1 14.0 2.1 11.2 0.10 0.028 1.39 USGS
13 BlackCreek@McBeeUSGS SH 295.6 17.2 1.6 8.1 0.024 176 55.0 49.5 31.9 11.2 1.1 5.4 0.15 0.028 0.42 USGS
14 BlackCreeknearChesterfieldUSGS SH 134.1 12.8 1.0 6.8 0.064 400 63.5 38.4 40.7 9.7 1.9 7.9 0.30 0.051 0.83 USGS,wadeable
15 JeffriesCreekDNR ASLP 44.9 465 48.0 13.4 57.6 18.8 2.0 15.4 DNR
16 JeffriesCreekUSGS ASLP 121.1 15.6 1.1 7.7 0.042 594 34.5 15.0 47.9 18.0 5.2 17.7 0.30 0.064 0.19 USGS,wadeable
Table2
Summaryofdependentandindependentvariables,modeofindependentvariableselection,typeofanalyses,andstatisticaltestapplied.
Dependentvariables Independentvariables Independentvariableselection Analysestype Statisticaltestused Channelmorphology RBI,H Correlation Causal Linearregression BMY Channelmorphology Correlation Causal Linearregression RBI,H,BMY Landcover PLSwithVIP Causal Linearregression RBI,H,BMY Channelmorphology+landcover Fromprevioussteps Predictive Multipleregression
isolatedornon-riparianwetlandsinthecatchment.AgriculturewasexpectedlytheprimarylandcoveracrosstheMDRP, withgraduallyincreasingintensityasthespatialscaleunderconsiderationincreased.Therewasmoreagriculturewithin theentireripariancorridorintheASLPecoregionwhencomparedtotheSHecoregion.However,atsmallerripariansub corridorscales,therewasnodiscernibledistinctionbetweenagriculturepracticesbetweenASLPandSH.Forestsdominated thetwolargestspatialscales(ripariancorridorandentirecatchment),andFORincreasedwithincreasingspatialextent ofsubcorridorscales.FORwassignificantlynegativelycorrelatedtoWETacrossallthespatialscales,withthegreatest correlationatthecatchmentscale(r=−0.76,p<0.01),andtheleastbutstillsignificantcorrelationattheripariancorridor scale(r=−0.53,p=0.04).Whencomparedbyecoregion,FORwasmoreprevalentacrossallspatialscalesintheSHecoregion (Fig.3c)thanintheASLPecoregion.Near-zerovaluesforIMPwereobservedwithinalltheripariansubcorridorscales,while thehighestLDIandIMPweremeasuredconsistentlyatthecatchmentscale(Fig.2dande),reflectingthatmostintense urbanizationoccursoutsideoftheripariancorridorintheMPDRB.TherangeofIMPwasgreaterintheASLPecoregiondue tothepresenceofseverallargetownsclosetooursamplinglocations.Similarly,LDIwasalsohigheracrossallscalesinthe ASLPmostlylikelyduetothegreatercombinedpresenceofagricultureandurbanizationinASLPinrelationtoSHecoregion. AverageCNweresimilaracrossthefivespatialscalesrangingfrom36.6to75.0atthecatchmentscale,and25.7to75.9across thefourripariancorridorscales.Whenexaminedbyecoregion,CNatthecatchmentandripariancorridorscaleswerehigher intheASLPthaninSHthoughthistrenddiminishedwithspatialextentoftheripariansubcorridorunderconsideration (Fig.2f).
Fig.2.(a–f):Boxplotdiagramsforlandcovermetricsbymajorecoregionwithinthecatchmentandripariancorridorscalesofspatialanalyses.Thewhiskers extendtothemostextremedatapointwhichisnomorethan1.5timestheinterquartilerangefromthebox.Pointsoutsidetherangeofthewhiskers representoutliersandareillustratedbyopencircles.
268 A.D.Jayakaranetal./JournalofHydrology:RegionalStudies5(2016)261–275
Fig.3. Streamflowat15studysitesmeasuredovera2.9yearperiodofstudyshowingdrainageareaandflashiness(RBI).Thestudysitesincludesix long-termUSGSsites,however,onlydatacontemporaneouswiththisstudywereused.Horizontalbluelinesrepresentbankfullflowateachsite.To facilitatecomparisonofflowdatafromstreamsofvaryingsizes,allflow(volume/time)arerepresentedasflowperunitareaofwatershedperday (volume/area/time=depth/time).(Forinterpretationofthereferencestocolourinthisfigurelegend,thereaderisreferredtothewebversionofthis article.)
3.2. Streamgeomorphology
Bedmaterialwastypicallycharacterizedbyparticlesintherangeofsand(0.0063–2.00mm),withD16rangingfrom 0.063mmto0.391mm,D50from0.176mmto0.866mm,andD84from0.393mmto3.705mm.Thedistributionofbed materialasmeasuredbythegeometricsortingcoefficienthadameanvalueof2.74(rangeof1.73–4.43)suggestingthatbed materialatthesitesrangedfromwelltopoorlysorteddistributions.Streamssloperangedinbetween0.023%and0.42%. Bankfullfeaturesidentifiedbyaweightofevidenceapproachwerewellcorrelatedwithdrainagearea(Smootetal.,2015). QHEIscoresrangedfrom34.5(JeffriesCreekUSGS)to78(HamsCreekDNR),withameanof56.Eightstreamswereinfair condition(52≤QHEI≤70.9),oneingoodcondition(71≤QHEI≥89.9),and4inpoorcondition(27≤QHEI≤51.9).
3.3. Indicesofstreamflow(H,RBI,andBMY)
Hammer(H)numbersrangedfrom0.024×10−6m/sto0.075×10−6m/s,withameanvalueof0.041×10−6m/s.
Flashi-ness(RBI)rangedfrom0.11to0.42withameanvalueof0.23acrossallsites(Fig.3).Theaveragecalculatedbedmaterial yield(annualaveragecalculatedloadperunitdrainageareaorBMY)rangedfrom0.02t/ha/yrto1.4t/ha/yrwithanaverage of0.71t/ha/yracrossallsites.ThemeandailystreamflowrecordusedinthestudyispresentedforallsitesinFig.3and expressedasdepthperunitareaofwatershed.Thestreamflowrecordfromsite16(JeffriesCreek,USGS)isonlypartialdue todecommissioningofthatsitebyUSGS.
3.4. Correlatingindicesofstreamflowtolandcoverandstreamgeomorphology
Ontherelationshipsbetweenstreamflowindicesandappropriatelytransformedstreamgeomorphologicalvariables, RBIwassignificantlycorrelatedwithD50(r=0.61,p=0.017)andD16(r=0.59,p=0.021).Hwaspositivelycorrelatedwith D50(r=0.62,p=0.013),D16(r=0.53,p=0.041),andbankfullvelocity(r=0.46,p=0.085).BMYwaspositivelycorrelatedwith QHEI(r=0.80,p<0.001),slope(r=0.79,p=0.001).OthercorrelationsarepresentedgraphicallyinFig.4a.Correlationswithin thesetofstreamgeomorphologicalvariablesshowedthatbankfulldimensions(bankfullwidth,bankfulldepth,andbankfull channelcrosssectionalarea)weresignificantlycorrelatedwitheachother,aswellaswithbankfullflow.Therelationships
Fig.4. CorrelationmatrixplotshowingPearson’scorrelationcoefficientbetween(a)flowindicesandgeomorphologicalvariables,(b)crosscorrelation amonggeomorphologicalvariables,and(c)crosscorrelationamongstreamindices.
betweenbankfulldimensionsandbankfullflowaredetailedinSmootetal.(2015).Othercorrelationsthatwerenotable weretherelationshipsbetweenaveragebankfullvelocityandthreemeasuresofbedmaterialcomposition:D16(r=0.64,
p=0.010),D50(r=0.48,p=0.073),andthecoefficientofgradation(r=−0.55,p=0.034).Averagechannelslopeandcalculated Manning’scoefficientwerealsosignificantlycorrelated(r=0.64,p=0.011).QHEIwassignificantlypositivelycorrelatedwith streamslope(r=0.69,p=0.004).Othersignificantcorrelationsnotreportedduetovariablenon-independencewerethose relationshipsamongbankfulldimensions,bankfullvelocity,andaveragestreamslope.Correlationsamongindicesofstream function(Fig.4c)showedthatRBIandHweresignificantlypositivelycorrelated(r=0.87,p<0.001).
3.5. Relatinggeomorphologytoindicesofstreamfunction
Bivariatelinearregressionmodelswereusedtorelatestreamindicestothemostwellcorrelatedstreamgeomorphological variablesthroughbivariateregression.Choiceofresponseandpredictorvariableswerebasedontheheuristicoutlinedin
Table2.Bivariatelinearregressionrelationshipsexplained34%ofthevariationoftransformedD50withRBI(p=0.014,
Fig.5a),andH(p=0.013,Fig.5b).Abivariateregressionmodeldescribed59%ofthevariationinBMYwithtransformed streamslope(p<0.001).Similarly,anotherbivariateregressionmodelexplained63%ofthevariationinBMYwithQHEI (p<0.001).
3.6. Relatinglandscapetoflowindices
H:Basedonthetwo-stepPLSR-VIP(Fig.6a)analysiswithjackknifeestimationofparameteruncertainty,percentwetland coverwithintheentireripariancorridor(WETALL)wastheonlyvariableofsignificance(p=0.066).Asimpleregressionmodel describingthevariationofHwithWETALLwassignificant(adj.r2=0.32,p=0.017)(Fig.7a)andshowedthatHdecreased
withincreasingwetlandcoverintheripariancorridor.AtwocomponentmodeldescribingHwithintermsofWETALLand transformedD50valuesasexplanatoryvariableswasalsosignificant(adj.r2=0.36,p=0.028).Thistwo-parametermodel
hadapredictedr2of0.19(Fig.7b).
RBI:BasedonthetwostepPLSR-VIPanalysis(Fig.6b)withjackknifeestimationofparameteruncertainty,percentwetland coverandcurvenumberwithinthe2000mripariansubcorridor(WET2000,p=0.014;CN2000,p=0.083)werevariablesof significance.AsimplelinearregressionsignificantlydescribedthevariationinRBIwithtransformedWET2000(adj.r2=0.46,
p=0.003,Fig.8a),withRBIdecreasingwithincreasingwetlandcover.Asimplelinearregressionalsosignificantlydescribed thevariationinRBIwithCN2000(adj.r2=0.26,p=0.031,Fig.8b),withRBIincreasingwithcurvenumber.Giventhepreviously
presentedsignificantregressionmodelbetweenRBIandD50(Fig.5a),atwo-parameterpredictivemultipleregressionmodel wasdevelopedrelatingRBItoD50andWET2000.ThetwoparametermodelforRBIhadapredictedr2statisticof0.40(Fig.8c).
270 A.D.Jayakaranetal./JournalofHydrology:RegionalStudies5(2016)261–275
Fig.5. Scatterplotsdepictingthreeflowindiceswiththemostcorrelatedgeomorphologicalvariable.Dataandregressionlinesareplottedinuntransformed space,whiletheadjustedcoefficientsofdetermination(adj.r2)werederivedusingtransformedindependentvariables.
BMY:BasedonthetwostepPLSR-VIP(Fig.6c)analysiswithjackknifeestimationofparameteruncertainty,wetland coverwithinthe200mripariansubcorridorzone(WET200)wastheonlyparameterofsignificance(p=0.051).However,a bivariatelinearregressionmodelwithWET200asapredictorofBMYwasnotsignificant(adj.r2=0.08,p=0.16,Fig.8d).The
bestcombinationoflandcovermetric(WET200)andgeomorphologicalvariable(averagestreamslope)aspredictorsofBMY yieldedapredictedr2of0.44(Fig.8e).However,theregressionmodelthatbestpredictedBMYwasamultipleregression
modelwithtransformedstreamslopeandQHEIaspredictorvariables(pred.r2=0.66,adj.r2=0.71,p<0.001,Fig.8f).
4. Discussion
TheMPDRBispredominantlyaforestedandagriculturallandscapelocatedintheSoutheasternPlainslevel3ecoregion ofSouthCarolina.Thetwolevel4ecoregions(SandHillsandAtlanticSouthernLoamPlains)demarcatedacleartransitionin landcoverdistribution,withwatershedsintheSandHills(SH)ecoregioncharacterizedbyforestedlandcoverwhilethose intheAtlanticSouthernLoamPlains(ASLP)byagriculture.Withincreasingproximitytoastream,forestedandagricultural landcoverintheMPDRBdiminishedgivingwaytoriparianwetlandcomplexes.Atallspatialscales,wetlandsweremore
Fig.6. Partialleastsquaresregressionbiplotsshowinghowlandscapevariablesatparticularspatialscalesrelateto:(a)Hammernumber(H),(b)stream flashiness(RBI),and(c)calculatedbedmaterialyield(BMY).
Fig.7.LinearregressionmodelsthatexplainthevariationofHwith:(a)wetlandcoverintheripariancorridor(WETALL),(b)atwo-parameterregression equationthatincludesWETALLandlogtransformedD50.
Fig.8.RegressionequationsthatexplainthevariationofRBIwith(a)transformedwetlandcoverinthe2000mripariansubcorridor(WET2000)bybivariate regression,(b)curvenumberinthe2000mripariansubcorridor(CN2000)bybivariateregressionand(c)transformedWET2000.Linearregressionmodels thatexplainthevariationofBMYwith:(d)wetlandcoverinthe200mripariansubcorridor(WET200),(e)atwo-parameterregressionequationthat includesstreamslope(Slope)andWET200,(f)atwo-parameterregressionequationthatincludesstreamslope(Slope)andQHEI.
272 A.D.Jayakaranetal./JournalofHydrology:RegionalStudies5(2016)261–275
Fig.9.Bivariaterelationshipsbetween(a)streamhammernumberandstreamflashiness,and(b)D50ofmeasuredbedmaterialandwetlandpresencein theripariancorridorexpressedasapercentage.
prevalentintheASLPecoregionthanintheSHecoregion.Wedefinedaripariancorridoras180mofDEM-derivedflow distanceextendingtobothsidesofthestreaminthecross-valleydirection,andincludedalltributariesupstreamofthe samplingsiteinthealong-valleydirection.Withinthisdefinedripariancorridor,agricultureandwetlandweresimilarly distributedintheSHecoregion,whileagriculturewastheprevalentlandcoverintheASLPripariancorridor.Theriparian corridoracrossallsampledstreamsreflectedthelowestanthropogenicinfluenceasmeasuredbythepercentimpervious landcoverandLDI.Withintheripariansubcorridorspatialscales,wetlandprevalencedecreasedwithupstreamdistance, whileagricultureandforestcorrespondinglyincreased.Thisobservationisconsistentwiththefactthatwithincreasing upstreamdistance,streamgradientsarelikelytoincreasewhilevalleywidthdecreases.Thecombinedfactorsofsteeper streamsandnarrowervalleyslimitwetlandspatialextentandfrequency.Itisalsopossiblethatcommercialinterestshave convertedmanyofthelessextensivewetlandcomplexestoforestandagriculturallandcoverintheheadwaterriparian corridorsintheMPDRB.
Flashiness(RBI):Therewasasignificantrelationshipbetweenthemedianparticlesizeofbedmaterialandflashinessover theperiodofstudy.Ahigherflashinessnumberindicatesthatthestreamissubjecttoshortperiodsofhighvelocityflows relativetoaverageflowconditions(Bakeretal.,2004;Poffetal.,1997),aconditionthatcanresultinacoarseningofbed material(Dinehart,1998)duetohigher,albeitbrief,periodsofincreasedsedimenttransportcapacity(Robinson,1976a,b;
Finkenbineetal.,2000;Pizzutoetal.,2000).However,moststudiesreportingbedmaterialcoarseningwererelatedto
depletionofsedimentsupplyingravelbedstreams(e.g.Rubinetal.,1998;Dietrichetal.,1989)orthoserelatedto water-shedurbanization(e.g.Hawleyetal.,2013).Thesignificantrelationshipinthisstudybetweenflashinessandbedmaterial suggestsamechanismwheresedimenttransportcapacityexceedssedimentsupply(e.g.Schummetal.,1984a,b),where thestreamflashinessthatweobservedisameasureofexcesstransportcapacitywithinthestudyreaches.Flashinesswas significantlyrelatedtowetlandcoverinthe2000mripariansubcorridorzone,withdecreasingstreamflashinessassociated withincreasingwetlandcover.Thisresulthighlightstheassimilativecapacitiesofriparianwetlandecosystemsandtheir inherentabilitytoattenuateflows,decreasingflowpeaksandextendingeventdurations(Gedanetal.,2010;Hillman,1998;
WooandWaddington,1990).ThedatapossiblyalsoreflectthefactthatwetlandpresenceintheripariancorridorofMiddle
PeeDeeRiverwatershedimpliestheabsenceofanthropogenicactivitiesthattypicallyinvokestreamflashiness(Bakeretal.,
2004;Poffetal.,1997).Thisresultholdsimplicationsfortheregulationofriparianareaofstreams,especiallywithregards
toamoresystematicprotectionofriparianwetlandecosystemsintheMiddlePeeDeeRiverwatershed.
Hammernumber(H):ThesignificantpositivecorrelationbetweenHammernumber(H)andmedianbedmaterialsize (D50)mirrorstheothersignificantrelationshipbetweenRBIandD50.Further,RBIandHwerealsofoundtobesignificantly correlatedwitheachother,aresultthatunderscoresthefactthatRBImeasuresstreamflashiness,andHmeasureschannel enlargement—awell-documentedconsequenceofstreamflashiness(O’Driscolletal.,2009;Walshetal.,2005;Henshaw
andBooth,2000).AsimplelinearregressionrelationshipbetweenRBIandHexplainedover66%ofvariationofHwithRBI
(p<0.001,Fig.9a).AswithRBI,themostsignificantlandcovervariableassociatedwithHwaswetlandcover.However,unlike RBIthatwasnegativelycorrelatedwithwetlandcoverinthe2000mripariansubcorridor,Hwasnegativelycorrelatedwith wetlandcoverwithintheentireripariancorridorscale.ThisresultillustratesthedependenceofHonareachequivalent spatialscaleechoingPizzutoetal.’s(2000)observationthatHwasameasureofchannelcharacteristicsandnot watershed-scalefactors.Theresultfurthersuggeststhatforagivendrainageareaand streamslope,bankfullflowand associated bankfullchanneldimensionsdiminishwithincreasedwetlandcoverintheripariancorridor.Perhapstheverymechanisms offlashinessattenuationprovidedbyriparianwetlandsystemsalsomitigatechannelenlargement(asmeasuredwithH)
andbedmaterialcoarsening.Infact,medianbedmaterialsizesignificantlyreduced(adj.r2=0.43,p=0.004)withincreased
presenceofwetlandwithintheripariancorridor(Fig.9b).
Bedmaterialyield(BMY):Thetotalcalculatedbedmaterialmovedateachsiteovertheperiodofstudywassignificantly relatedtodrainagearea,assiteswithlargerdrainageareasexperienceagreatervolumeofrunoffatthewatershedoutlet thatinturnmovedmorebedmaterial.ThemostinfluentialgeomorphicparametersonBMYwereaveragestreamslope andQHEI.Wetlandcoverwithinthe200mriparianwasshowntobeimportantbythePLSR-VIPprocedurebutwasnot significantwhentestedbylinearregression.GiventhatstreamslopeisanintegralpartofBrownlie’stransportequation, itsinfluenceonBMYwaswellwithinreason.ThefactthatincreasedBMYwasassociatedwithhighQHEIvaluesreflects thefactthatstreamswithhighergradientsandcoarseexposedbedmaterialscorehighbytheQHEIframework—thelatter twoparametersalsobeingindicatorsofhighbedmaterialtransport.TheutilityofBMYestimatesinthisstudy(range: 0.02–1.4t/ha/yr)isprimarilyasaconsistentmetricforcomparisonbetweenstudysites.Thebodyofpublishedstudieson bedmaterialyieldsforCoastalPlainwatershedsislimitedtothosethatmeasuresuspendedsedimentand/ortotalsediment yields(e.g.Gellisetal.,2009;Slatteryetal.,2002;Calvo-AlvaradoandGregory,1997;Phillips,1995;Simmons,1988;Ursic
andDendy,1965).Resultsfromthisstudyarecomparabletosedimentyieldspublishedbytheseworkers,however,since
weonlyestimatedbedmaterialyield(afractionoftotalsedimentyield),ourresultsareclearlybiasedhigh.StottandMount
(2004)publishedasynthesisofbedloadyieldestimatesfromforesteduplandcatchmentsintheUnitedKingdom,reporting
meanbedloadyieldfromamatureforestedcatchmentas0.17t/ha/yrandfromaharvestingforestas0.58t/ha/yr.
4.1. Implicationsfordevelopingwetland-specificregulationsinSouthCarolina
Themedianbedmaterialparticlesize(D50)wascloselyrelatedtoinstreamflowconditionswithcoarserbedmaterial associatedwithflashierstreamsandlargerhammernumbers.Thisresultsuggeststhatonemightpotentiallyestimatea stream’sflashinessorhammernumberintheMPDRBbymeasuringparticlesizedistributionofbedmaterial,aparticularly usefulresultespeciallywhentheresourcestoinstallastreamgaugeandtoestimatestreamflowoverasufficientperiodof timearenotavailable.Fromtheperspectiveofhabitatprotection,QHEIscoreswereclearlygreateratsiteswithsmalldrainage areas—suggestingtheimportanceofprotectingheadwaterstreamsintheMPDRBasimportanthabitatforaquaticfauna. WetlandcoverintheripariancorridorsoftheMPDRBplayedstatisticallysignificantrolesinregulatingstreamflashiness, hammernumber,andbedmaterialtransport.AstypicalanthropogenicactivitiesintheMPDRBinvolvetheconversionof wetlandandforestedlandscapestoagricultureanddevelopment,wearelikelytoseegreaterflashiness,hammernumbers, and possiblyincreasedbed materialyieldfromtheMPDRB.In termsofthespatialextentthatstreamflowindicesare influenced,streamflashinesswasinfluencedbywetlandcoverwithintheripariancorridorextendingto2kmupstreamof thesampledsite.Thisincludedtheripariancorridorofalltributarystreamswithin2km(upstreamalongchannel)ofthat site.Channelenlargement(Hammernumber)wasevenmoresensitivetowetlandcover,beinginfluencedbywetlandcover withintheentireripariancorridor(includingallupstreamtributaries).Currently,therearenostate-specificregulations pertainingtowetlandmanagementorregulationinSouthCarolina.TheUnitedStatesArmyCorpsofEngineersadministers Section404oftheCleanWaterActlimitingwetlandalteration,andtheSouthCarolinaDepartmentofNaturalResources protectsnon-coastalwetlandsbyadministeringthefederalWaterQuality(401)CertificationprogramundertheClean WaterAct.However,thelatterislimitedtowaterqualityanddoesnotaddresswaterquantitymetricssuchasflashiness.In thesoutheasternUSA,thepredominantcauseforchangeinacreageofforestedwetlandswasagriculture,urbanizationand forestry(WearandGreis,2002)thoughthemajorityofwetlandconversiontookplacepriorto1980.Between1986and1997 however,around3%offorestedwetlandshavebeenlostinthesoutheasternUSAascomparedto15%between1950and
1970(WearandGreis,2002).Itthereforestandstoreasonthatprotectingriparianwetlandsisintimatelyintertwinedwith
streamfunction,andthereforedevelopingwetland-specificregulationforSouthCarolinaacriticalsteptowardsensuring thefuturestabilityandhealthofstreamsintheMPDRB.Finally,webelievethatwhileanecoregionistheappropriateunit withinwhichtoevaluatestreamfunctionforthedevelopmentofstate-specificenvironmentalregulations,thegeographic extentofsuchstudiesshouldnotextendbeyondtheboundariesofasinglelevel3ecoregion.
4.2. Futurework
Whilemostrelationshipspresentedinthisstudybetweenlandcover,channelmorphologicalmeasurements,andindices ofstreamflowweresignificant,theabilitytopredictstreamflowindicesfromlandscapeandchannelmeasurementsalone werelow.Webelievethatvariationamongsiteswithinlevel4ecoregionsispartlythereasonforthislowpredictivepower. Futurestudiesincorporatingalargernumberofstudysitesstratifiedbylevel4ecoregionislikelytoproducemultivariate modelswithgreaterpredictivepower.
5. Conclusions
Withthiswork,wehavepresentedthreeindicesofstreamflowthatmaybeusedtoquantifyinstreamfunctioningas wellaspresentedhowfluvialgeomorphicandlandcovervariablesaffecttheseindices.Theeffectofwatershedlandcover type,andthescaleatwhichspecificlandcoversalterstreamflowregimeprovidesinsightintohowfluvialgeomorphological characteristicswillchangewithchanginginlandcover.Thestudyalsooffersinsightintohowfarupstreamonemightneed
274 A.D.Jayakaranetal./JournalofHydrology:RegionalStudies5(2016)261–275
tomanagetheupstreamripariancorridorinordertoensurethataspecificlocationinthedrainagenetworkisprotected. Lastly,theprotectionofriparianwetlandsiscriticalinensuringthattheflowregimeinMPDRBisbuoyedfromdestabilizing anthropogenicactivitiesonthelandscape.
Acknowledgments
WewouldliketoexpressgratitudeforfundingofthisworkprovidedbythePeeDeeResearchandEducationCenter Endowment.Thesponsordidnothaveanyroleinstudydesign,datacollection,analysis,interpretation,decisiontopublish, ormanuscriptpreparation.Theauthorsarealsogratefultoseveralundergraduate,graduatestudents,andtechnicianswho facilitateddatacollection.
AppendixA. Supplementarydata
Supplementary data associated with this article can be found, in the online version, at
http://dx.doi.org/10.1016/j.ejrh.2015.12.064.
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