Jersey Sea Level and Coastal Conditions Climate Review · New observational techniques developed at...

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Jersey Sea Level and Coastal Conditions Climate Review

3rd March 2018

Dr Thomas Prime

Revision/Purpose Date Issuedby Checked

InitialDraft:Revision1 15/12/16 TP FinalDraft:Revision2 30/01/17 TP CS&CBUpdatedtoreflectcomments 20/03/17 TP CSUpdatedTable12tochartdatum 08/05/17 TP JBFinalDocument 08/06/17 TP JBFinalDocument‐Updatedtoreflectcomments 17/02/18 TP JB/CS

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Executive Summary

TheNationalOceanographyCentrehasbeencommissionedbyTheStatesofJerseytoundertakea coastal conditions climate review toprovide tailored information suitable for contributionstowardpolicydecisionsand to identify furtherareasofstudy.Thereviewcoveredup todateregionalsea‐levelprojections,anestimationofextremewaterlevels,probabilityofcombinationsofextremesealevelsandwaveheights(consideringverticallandmovement),andabsolutesea‐leveltrends.Extremeeventmodellingwasundertakenwhich considered four1Dprofiles, runningEast toWestacrossStAubin’sBay.Thestudysimulatedarangeofextremeeventstoassesstheamountofovertoppedwaterandchangesinparameterssuchaswaveperiodanddirection.Themodellingalsoassessedtheimpactoftheextremeeventsonthebeach,assessingwhethersandwaslostorgained along the 1D profile, or lost or gained from the profile entirely. Finally, the workinvestigatedtheimpactofSeaLevelRise(SLR)onextremewaterlevels,andtheimpactofSLRonanextremeeventofcombinedwaveheightandextremewaterlevels.ThereportfoundthatitislikelythatJerseyisexperiencingadownwardverticallandmovement,althoughthereisalargerangeinthepotentialrangeofratesfromsurroundingGPSstations.ItwouldbebeneficialtosetupaGPSstationonJerseytogetamoreaccuraterate,as,ifthelandissinking,thentheimpactofrisingsealevelsisexacerbated(e.g.iflandissinkingat1.5mmayearandsealevelsrisingat2mmayearthenariseof3.5mmayearwillbeobserved).ComparingthecombinedratesfromnearbytidegaugesthathadGPSstationslocatedwith15km,givesarangeofabsolutesealeveltrendrates.Itwasfoundthattherateof2mm/yrusedpreviously,andthisinstudy,wasagoodmatchtothesurroundingrates.Usingthelatestmethods,extremewaterlevelreturnperiodanalysiswasperformedandfoundtobeconsistentwithpreviousstudies,althoughanapproximate0.33mdifference inextremewater levelwasnotedacrossall returnperiods. It is thought that this isdue todifferences inverticaldatumbetweenthisandpreviousstudies.Analysisofthejointprobabilitywasperformedusing the latest methods, the results were different due to the unrealistic and pessimisticassumptionsmadebypreviousstudies.Thesestudiesnotedthatitwouldbebeneficialtoredothejointprobabilitywithouttheseassumptionswhichhasbeensuccessfullycompletedforthisreport.Wavesarenotprojected tohaveanychange insignificantwaveheight, although20th centuryhindcastdatadoesshowasmalllinearincrease.Focusingonextremewaterlevelsonly,itwasfoundthatmeanoutcomesfor2100couldresultinextremewaterleveleventsrepresentativeof1in150yearconditionsoccurringeveryyear.Withtheadditionofanywavespresentduringtheextremeevent,theimpactondefenceswillbeevengreater.Thechangeintidalrangefora2mincreaseinmeansea‐levelisestimatedtoresultinareductioninthetidalrangeof0.49mforspringand0.24mforneaptides.ThiswouldreducetheimpactoffloodingbyaquarterunderhighimpactlowprobabilitySLRscenarios,providingatangiblebenefitinthefuture.

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Itwasfoundthatincreasinghypotheticalsignificantwaveheightresultedinalargeramountofsedimentchangealongthebeachprofiles.However,whenlookingattotalchangealongthewholeprofile, it was found that 2 m, long period waves resulted in the greatest loss of sediment.Comparing thebeforeandafterprofiles for the scenarioswith thebiggest changes show thatextremeeventsthathavebeensimulateddonotsignificantlyimpactonthebeachvolume,withamaximumlossof2.5m3ofsandpermetreacrossthebeach.Withrespecttoovertoppingofdefences,itwasshownthatapeakintotalvolumewasapparentat2m.Thereisamaximumvalueatwaveheightsof5.3mbutitisnotknownifthesehighwavesarerepresentativeofthewaveclimateinStAubin’sbay.Thegreatestovertoppingamountsarerelatedtothescenarioswiththelongestwaveperiods,withwavedirectionhavinglittleimpact.Allwaveheightsassessedresultinsomeovertoppingofdefences,dependingonthepeakperiodvaluebeingused.Forthestillwateronlysimulations,anincreaseinthemeansea‐levelshowedthatdifferentprofileshadverydifferentresponses,however,a0.6mriseinmeansealevelwasrequiredbeforeanyovertoppingoccurred.Whenaddingmeansealevelincreasestoascenariothat includeswaves, itwas found that theresponse toSLRwasa relatively linear increase involumeovertoppedrelativetoSLR.Itwasfoundthat,duringanextremeevent,forevery0.1mofSLRapproximately300m3ofextrawaterwasovertoppedforeverymetreofseadefence.Asaresultoftheresearchcarriedoutbythisstudy,identificationoffurtherworkthatwouldbebeneficialtoJerseyhasbeenundertaken.Somelimitedinundationmodellingwasplannedtobecarriedoutwithinthescopeofthisstudy,butduetotimeconstraintsithasnotbeenachieved.Inundationmodelling isbeneficialas itwill showthe impactofagiven totalvolumeofwaterdischargingoverthedefences.Itwillalsobebeneficialtoassessandmodeltheimpactofextremerainfalleventsontheislandwhichcanbeachievedusingasurfacefloodmodel.TheXBeachmodellingcompletedforthisstudyconsistedof1Dprofiles;a2Dstormimpactmodelwillprovideamoredetailedanalysisoftheabilityofseadefencestowithstandextremeeventsacrossthewholebay,orisland,ratherthanatfourpointsacrossStAubin’sBay.Althoughchangesinthebeachprofilewerenotfoundtobesignificantduringthesimulatedextremeevents,thelongtermcumulativeimpactofeventsonthebeachesandcoastlineofJerseyisrecommended.Theassessmentcantaketheformofmodelsorobservations,butideallyacombinationofboth.NewobservationaltechniquesdevelopedattheNationalOceanographyCentre,useexistingradarinfrastructure (X‐Band) canderive inter‐tidalbathymetry, surface currents andwave climate.This techniquecouldbeused tomonitorbeachesandbuilda spatiallyand temporally robustdatasetofcriticalcoastalareas.Additionally, improvements insatellitemonitoringtechniquescouldalsopotentiallybeusedtosupplementin‐situobservations.Therefore,itisrecommendedthatfurtherworkshouldconsistof:

Floodinundationmodellingtoshowtheimpactofextremeeventsoncoastalcommunities

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An assessment of the probability of wave peak periods occurring for projectedwaveheights

Useofmodellingtechniquescombinedwithobservationstoassessthelong‐termimpact

ofclimateonbeachmorphology

2Dstormimpactmodellingtoassessinmoredetailtheimpactofextremeevents

An assessment of pluvial (rainfall) flooding and the impact of extreme rainfall eventscombinedwithSLRandextremewaterlevels

Investigationofthepotentialtoestablishlongtermcost‐effectivemonitoringusinge.g.satellitedatatosupplementin‐situobservationsandmodels

Beachsurvey’stoprovidebettervaluesforsandparticlessizesanddistribution(requiredforbeachmodellingstudies)

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ContentsExecutiveSummary.........................................................................................................................................................2

1 Glossary.......................................................................................................................................................................7

2 Acronyms...................................................................................................................................................................9

3 Introduction...........................................................................................................................................................10

4 StudyLocation.......................................................................................................................................................10

5 StudyContext‐HistoricalExtremeEvents...............................................................................................11

5.1 Detailsof2008surgeprovidedbyJerseyMetOffice...................................................................11

5.2 Extremeeventsin2014............................................................................................................................12

6 GlobalandRegionalSea‐LevelRiseProjections.....................................................................................13

6.1 Introduction...................................................................................................................................................13

6.2 RepresentativeConcentrationPathways..........................................................................................13

6.3 Projectedglobalsea‐levelrise...............................................................................................................14

6.4 Futureprojectionsofregionalsea‐levelrise...................................................................................16

6.5 Limitationsanduncertaintyofprojections......................................................................................18

7 VerticalLandMovementTrends...................................................................................................................18

8 RegionalSea‐LevelTrends...............................................................................................................................21

9 ExtremeStillWaterLevelReturnPeriodAssessment.........................................................................22

9.1 Introduction...................................................................................................................................................22

9.2 Skewsurgejointprobability–methodologyoverview...............................................................23

9.3 Skewsurgejointprobability–analysisresults..............................................................................25

9.4 ComparisonofextremestillwaterlevelswithHRWallingford2009report....................27

10 ProjectionsofStormSurgesandSignificantWaveHeight............................................................28

10.1 Waves...............................................................................................................................................................28

10.2 Projectedchangestoannualmeansignificantwaveheight......................................................28

10.3 Projectedchangestostormsurges......................................................................................................28

11 HistoricalChangesinWinds,WavesandStorminess......................................................................29

12 JointWaterLevelandWaveHeightProbabilityAssessment.......................................................30

12.1 Introduction...................................................................................................................................................30

12.2 Previousjointwaveheightandwaterlevelprobabilityassessments..................................31

12.3 JOIN‐SEAjointprobabilityassessment..............................................................................................32

12.4 Transformingwavesfromoffshoremodeltowavebuoy..........................................................33

12.5 Resultsofjointprobabilityassessment.............................................................................................34

12.6 Comparisonofjointprobability............................................................................................................36

13 ChangestoTidalRangefromProjectedSea‐LevelRise..................................................................37

13.1 Introduction...................................................................................................................................................37

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13.2 SLRscenariotidalmodelling..................................................................................................................37

13.3 Resultsoftidalsimulations.....................................................................................................................38

14 ExtremeEventModelling:StormImpactModel................................................................................39

14.1 Beachmorphology:responsetopresentdayextremeevents..................................................49

14.2 Overtoppingofdefences:vulnerabilityofdefencestoovertoppingduringpresentdayextremeeventsandfuturestormsurges.........................................................................................................54

14.3 Increaseinimpactofextremewaterlevelswithprojectedsea‐levelrise..........................58

14.4 IncreaseinovertoppingofdefencesduringextremeeventsduetoprojectedSLR........61

15 KeyFindings......................................................................................................................................................64

16 Recommendations..........................................................................................................................................66

17 References..........................................................................................................................................................68

18 Appendix:PositionDatum’s.......................................................................................................................71

18.1 JerseyTransverseMercatorandlocalordnancedatum.............................................................71

19 Appendix2:DataSources............................................................................................................................73

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1 Glossary

Absolutesea‐levelrise:changesintheheightoftheoceanasaresultofmeltingiceorwarmingseas.Beachmorphology:thestudyoftheinteractionandadjustmentofseafloortopographyandfluidhydrodynamicprocesses,seafloormorphologies,andsequencesofchangedynamics,involvingthemotionofsediment.BusinessasUsual:Baselinecasewherenomitigationoradaptationtoaddressclimatechangeismade.Chainage:Animaginarylineusedtomeasuredistance,withvaluesrelativetoasinglearbitrarypoint.Computationalcost:Thecostofrunningacomputationalmodelintermsoflengthoftimeandprocessorrequirements.Oceanandcoastalmodelscanoftenhaveaveryhighcomputationalcost.GIA: Glacial isostatic adjustment is the ongoingmovement of land once burdened by ice‐ageglaciers.Hindcast: a statistical calculation determining probable past conditions (e.g. marine wavecharacteristicsatagivenplaceandtime),rramodelsimulationofhistoricevents/conditions.M2tidalconstituent:Inmostlocations,thelargestconstituentofthetideisthe"principallunarsemi‐diurnal",alsoknownastheM2(orM2)tidalconstituent.TheperiodofM2isabout12hoursand25.2minutes,exactlyhalfatidallunarday.MeanHighWaterSprings:Theheightofmeanhighwaterspringsistheaveragethroughouttheyear(whentheaveragemaximumdeclinationofthemoonis23.5°)oftwosuccessivehighwaters,duringperiodsof24hourswhentherangeofthetideisatitsgreatest.North Atlantic Oscillation (NAO): The North Atlantic Oscillation (NAO) is a weatherphenomenonintheNorthAtlanticOceanoffluctuationsinthedifferenceofatmosphericpressureatsealevelbetweentheIcelandiclowandtheAzoreshigh.Peakperiod:Thepeakwaveperiod(inseconds)isdefinedasthewaveperiodassociatedwiththemostenergeticwavesinthetotalwavespectrumataspecificpoint.Waveregimesthataredominatedbywindwavestendtohavesmallerpeakwaveperiods,regimesthataredominatedbyswellwavestendtohavelargerpeakwaveperiods.Radiative Forcing: Also known as climate forcing, is defined as the difference of insolation(sunlight)absorbedbytheEarth,andenergyradiatedbacktospace.

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RCP:RepresentativeConcentrationPathways(RCPs)arefourgreenhousegasconcentration(notemissions)trajectories,adoptedbytheIPCCforitsfifthAssessmentReport(AR5)in2014.Relativesea‐levelrise:Relativesealevelisthesealevelrelatedtothelevelofthecontinentalcrust(i.e.landmovement).Relativesealevelchangescanthusbecausedbyabsolutechangesofthesealeveland/orbyabsolutemovementsofthecontinentalcrust.Resilience: The capacity for a socio‐ecological system to: (1) absorb stresses and maintainfunction in the face of external stresses imposed upon it by climate change, and (2) adapt,reorganize,andevolveintomoredesirableconfigurationsthatimprovethesustainabilityofthesystem,leavingitbetterpreparedforfutureclimatechangeimpacts.Returnperiod:Areturnperiod,alsoknownasarecurrenceinterval(sometimesrepeatinterval)isanestimateofthelikelihoodofanevent,suchasanearthquake,floodorariverdischargeflowto occur. This commonly referred to as a number of years that relate to the probability ofoccurrence,e.g.a1in10yearreturnperiodhasa10%chanceofoccurringinanygivenyear.S2 tidalconstituent: Principal solar semidiurnal constituent designated S2. Constituents aredescribedbytheirtidalperiod(thetimefrommaximumtomaximum),T.TheperiodforS2is12.00solarhours.Semidiurnal:Anareahasasemidiurnaltidalcycleifitexperiencestwohighandtwolowtidesofapproximatelyequalsizeeverylunarday.Significantwaveheight:Significantwaveheight(Hs)isdefinedasthemeanwaveheight(troughtocrest)ofthehighestthirdofthewaves(H1/3).ThereforeHs=mean(H1/3)Stillwaterlevel:Waterelevationduetoastronomicaltideandatmosphericinteractionsonly,neglectingtheimpactofwaves.Stormsurge:Achange insea level asa resultofmeteorological influencessuchaswindandatmosphericpressure.Thiscanboth increaseordecreasethe levelpredictedbyastronomicalforcingalone.Swellwaves:Wavesthatarenotgeneratedbytheimmediatelocalwindbutbydistantweathersystems.Thesegenerallyhavealongerwavelengthwhencomparedwithwindwaves.Tidalamphidrome:Anamphidromicpointisapointofzeroamplitudeofthetide. Windwaves:Thesearearesultofthewindblowingovertheocean,theparametersofthewavearedeterminedbythespeedanddurationofthewindandbythedistanceithasbeenblowingoverthesea(fetch).

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2 Acronyms

Acronym DefinitionACD AboveChartDatumAR5 IPCC5thAssessmentReportBaU BusinessasUsualCD ChartDatumDir WaveDirection(clockwisefromnorth)EWL ExtremeWaterLevelGIA GlacialIsostaticAdjustmentGPD GeneralisedParentoDistributionGPS GlobalPositioningSystemHAT HighestAstronomicalTideHs SignificantWaveHeightIPCC IntergovernmentalPanelonClimateChangeJ14RCP8.5 HighImpactLowProbabilityClimateScenarioMHWS MeanHighWaterSpringsNAO NorthAtlanticOscillationNCAR NationalCentreforAtmosphericResearchNCEP NationalCentre’sforEnvironmentalPredictionNOC NationalOceanographyCentreRCP RepresentativeConcentrationPathwaySLR Sea‐LevelRiseSMB SurfaceMassBalanceSoJ TheStatesofJerseySSJPM SkewSurgeJointProbabilityMethodSWL StillWaterLevelTp PeakPeriodUKCP09 UnitedKingdomClimateProjection2009

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3 Introduction

TheStatesofJersey(SoJ)arenotsubjecttoUKlegislationonclimatechange,andhavenotbeendirectlyconsideredunderanypreviousUKclimateprojectionssuchasUKCP09[1].HenceJerseyisnotdirectlycoveredbytheregionalsealevelriseprojectionsundertakenbytheUKin2009.SoJarethereforeseekingprojectionsontheimpactofclimatechangeoverthedecadalto100‐yeartimescale.SoJalsorequiregeographicallyrelevantdataontheeffectsofclimaticchangestosea‐levelandtheassociatedimpactonthecoastalenvironment.Thistailoredinformationwillprovidethescientificbackgroundtoinformpolicyinthecontextofclimatechangeupto2100.Theaimof this report is toestablish,using thebestavailable science, abaselineofprojectedregionalchangesinsealevel,surge,offshorewavesandtidalrange,andtouseacasestudytoexploretheimpactofthesechangesonbeachmorphologyandovertopping.Thereportprovidesdetailsofthemodelsandmethodologiesusedtoderivetheseprojectionsandexplorestheimpactofextremeeventsonthecoast,inthepresentday,andundertheinfluenceofsea‐levelrise.Thereportconcludeswithimplicationsandrecommendations.TheNationalOceanographyCentre (NOC)haveworkedcloselywith representatives from theDepartmentoftheEnvironment,theJerseyMeteorologicalDepartmentanddiscussedthereportandworkwithotherkeydepartmentssuchastheDepartmentofInfrastructure,andDepartmentofPlanning.Thesedepartmentscontributedpreviousstudiesandsurveydata.

4 Study Location

JerseyislocatedintheEnglishChannel23kmfromtheFrenchmainland,itisinanareawithalargespringtidalrangewithamaximumrangeofaround12.07m.Thishighrangemeansthatsignificantcoastalfloodingismostlikelytooccurwhenastormsurgeandhighwaterspringtidescoincide.Thehightidalrangealsomeansthatevenduringfloodevents,waterovertoppingseadefenceswillquicklyrecede,assuminggooddrainageoftheinundatedarea.Waveimpactduringextremeeventsislimitedtoawindowaroundhighwater.Jerseyhasvulnerablecoastlines,particularlyintheSouthoftheIslandwherethecapitalStHelierislocated(Figure1).ThisreporthasfocusedontheStAubin’sBayareaasacasestudy,selectedduetothehighvalueinfrastructure,largecoastalcommunitiesandavailablesurveydata.

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Figure1:MapofJerseyshowinglocationofStHelierandStAubin’sBay

5 Study Context ‐ Historical Extreme Events

Jerseyhassufferedextremeevents(surgecombinedwithhightide)inthepast,inparticularin2008and2014.Abriefoverviewoftheseeventshasbeenincludedheretoprovidecontexttothereport.ThesehighlightJersey’svulnerabilitytothecoincidenceofastormsurgepassingathighwater,generatingextremewaterlevelsandwaves.

5.1 Details of 2008 surge provided by Jersey Met Office

In2008a1in10yearextremeeventledtoseawalldamagetotallingupto£500,000,theeventwaswellpredictedby the JerseyMetOfficeandwarningandpreparationshadbeenmade toimprovetheabilityoftheseadefencestoresistthestormsurgeandwaves.Earlyonthe10thMarchthesoutherlywindatJerseyAirportstrengthenedtostrongforce7.By5am,andatabout5:45am,thestormveeredsouthwestandincreasedtemporarilytoameanspeedof37knots(galeforce 8)with gusts up to 52 knots. This coincidedwith a squall line passing over the Island,accompaniedbyhailandheavyrain,withathunderstorminthevicinity[2].For the rest of themorning the southwest windwas strong force 6 to 7 at the Airport, butincreasedmarkedlytoseveregaleforce9,gustingto55knotsaround1pm.Awesterlywindofforce8to9persistedfortherestofthedayandonlyeasedbelowgaleforceearlyonthe11th.

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Thereweregustsof60knotsormorefrom2pmuntillateonthe10th,thehighestrecordedwas67knotsbetween4and5pm.AnanemometeronthetankerberthatSt.HelierHarbourrecordedslightlystrongerwindsthantheAirport,reachingamaximumof52knots(stormforce10)withagustto72knotsataround2pm[2].Stormsurgeforecastsestimatedresidualsof0.71to0.85m,thesecalculationssuggestedthatthepredictedtideof11.56m(CD)waslikelytopeakat12.26m(CD).ThisisanexceptionallyhightideforJerseywithahighestastronomicaltide(HAT)of12.16m.Withtheforecastsoutherlygaleforcewinds,floodingwasexpected.Duringtheextremeeventthewindveeredfromsouthtosouthwestnearly2.5hoursbeforehighwater.Table1showsthepredictedtidalheightsalongwiththeresiduals.

Table1:Detailsofthehighandlowtidesduringthestormsurgein2008

Date Tide Time PredictedTide

ForecastResidual

Observedtide

Actualresidual

10/03/2008 High 08:09 11.56 +0.71 12.33 +0.7710/03/2008 Low 14:51 0.73 +1.07 1.94 +1.2110/03/2008 High 08:27 11.29 +0.80 11.58 +0.2911/03/2008 Low 15:06 0.96 +0.32 1.26 +0.3011/03/2008 High 08:45 11.29 +0.43 11.61 +0.41LookingattheStHeliertidegauge,thehighestmorningsurgewasnearly2.5hoursbeforehightide.Asthewindveeredanddecreasedinspeed,thisreducedthewindcomponentofthesurgeand resulted in a sudden drop of 0.2m inwater level. The data also shows that the highestresidualsoccurrednearthetimeoflowtide,exceeding1.2metresforaboutanhour,peakingat1.26m.With the approaching high tide, the warnings issued by the Jersey Met Office proved to beaccuratewithfloodingoccurringonthemorningtidebetweenStAubinandSeasidetotheEastofBeaumont.Therewerevarioussites thatexperienced flooding,suchasStAubin, theLaHaulearea, Beaumont roadway and the Gunsite area. That evening the high tide resulted inmoreflooding,withFirstTowerandWestParkexperiencingfloodinganddamagetotheseawall.Followingthestorm,itisestimatedthatthecostincleanupandrepairwouldtotal£436,000withsomeun‐costed itemspotentiallybringing thecostup to£500,000.The time tocarryout therepairswasoverayear.Whilethisfloodingisnotunprecedented,itisarareeventwithareturnperiodofaround1in10years[2].

5.2 Extreme events in 2014

In2014,betweenJanuaryandOctober,aclusterofextremeeventsresultedinlargeamountsofdamage, requiring emergency repairs in excess of £1.1 million. During this period variousdefenceswerebreachedathightidesuchastheseawallsandpiersatGorey,Beaumont,StAubin,StAubin’spierandStCatherine’s,causingfloodingandroadclosures.RecordhightidesinMarch

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2014causedthecollapseoftheseawallatLeBourg,andresidentialgardensontheseafrontatStClementscollapsed intotheseawallandontothebeach.Clusteringofextremeeventscreatesadditional stress on defences or can cause loss of beach volume, exacerbating damage andresultingingreateroverallcostsincleanupandrepair.

6 Global and Regional Sea‐Level Rise Projections

6.1 Introduction

The impact of future stormeventswill be influencedby sea‐level rise (SLR).While there arerobust global projections, sea‐level rise at the regional scale is not uniform and may differsubstantially fromtheglobalaveragesea levelrise[3].Thesevariationsareduetodynamicaloceanprocesses,changesingravitationalfieldsassociatedwithicemasslossandair‐seaheatandfreshwaterfluxes.RegionalsealevelprojectionsproducedfortheUnitedKingdomin2009[1](duetobeupdatedin2018)donotcoverJersey,anddonotbenefitfrommorerecentresearch.Thesearenowconsideredtobeconservativeprojections[3].TheRISES‐AMprojectaimedtoaddresscoastalimpactsofclimatechangeforhigh‐endemissionsscenarios[4].Theprojecthasupdatedthe2009regionalsea‐levelriseprojectionsusingglobalsea‐level projections for different emission scenarios (low, medium or high) as input andproducing sea‐level patterns ormaps that show the contribution of each individual sea levelcomponent suchas thermalexpansion, contribution fromglaciers, ice sheet inGreenlandandAntarcticaandcontributionfromlandwater.Theregionalsea‐levelriseprojectionscalculatedbyRISES‐AMhave been used for this study to provide themost up to date projections that arecurrentlyavailable.TheprojectionscalculatedbyRISES‐AMwillbeusedinthe2018regionalsea‐levelriseprojectionsupdate.

6.2 Representative Concentration Pathways

ThelatestresearchIntergovernmentalPanelonClimateChange(IPCC)AR5hasdefinedfournewclimatescenariosreferredtoasrepresentativeconcentrationpathway(RCP)scenarios[5].ThesefourRCP’sareaconsistentsetofprojectionsofthecomponentsoftheradiativeforcingnamedaccordingtotheir2100radiativeforcinglevelestimatedfromgreenhousegasesandotherforcingagents.Thesescenariosareproducedbyintegratedassessmentmodelsupto2100.ItshouldberecognizedthatwhiletheRCP’sspanawiderangeoftotalforcingvalues,theydonotspanthefullrangeofplausibleemissionsintheliterature[6].Of the fourRCP’s the twoselected tobeusedwithin the latest researchareRCP4.5 (mediumemissions)andRCP8.5(highemission)theseRCP’sbothinferaglobalaveragewarminggreaterthan20Cwithrespecttopre‐industrialtemperatures.UsingthelatestIPCCreport[7]inwhichprojectionsof changes in theclimatearemade.Thechangesrelate toscenarios that combinenatural(solarradiation)andanthropogenic(radiationchangeduetoatmosphericgreenhousegases and aerosols) forcing. The different scenarios are performed with prescribed CO2concentrations, which are unique for each scenario. Table 2 shows the different expected

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outcomesintemperaturechangerelativetoabaselineaveragetemperaturebetween1986and2005foreachRCP.

Table2:Projectedresponseofclimatetodifferentrepresentativeconcentrationpathwaysshowingmeantemperatureincreaseandrange5thto95thpercentiles.

ClimateScenario

Mean (⁰ C) (+/‐ 1standarddeviation)

Range (5th to 95thPercentiles)

OutcomesofRCP

RCP2.6 1.6(0.4) (0.9–2.3) CarbonEmissionspeakby2040andthenreduce

RCP4.5 2.4(0.5) (1.7–3.2) Potential outcome if Paris climatechangeagreementisadheredtoo.

RCP6.0 2.8(0.5) (2.0–3.7) Potential outcome if Paris climatechange agreement is not fullyadheredtoo.

RCP8.5 4.3(0.7) (3.2–5.4) BusinessasUsualTheRCP2.6scenarioisdefinedbyamid‐centuryradiativeforcingaround3.1Wm‐2whichdropsto2.6Wm‐2by2100.Toachievethisscenario,greenhousegasconcentrationsmustsubstantiallyreduceovertime.RCP4.5and6.0arebothstabilisationscenarioswheretheradiativeforcingisstabilizedbeforeandafter2100respectivelybyemployingpolicyanddeployingtechnologicalsolutionstoreducegreenhousegasemissions.RCP8.5isdefinedashavingradiativeforcingthatincreasesmorerapidlythantheotherRCP’sandcontinuestoincreaseuntil2200.Thisisinspiteofastabilizingofemissionsinthescenariopost2100andatmosphericconcentrationspost2200.This highlights the fact that the climate has a long feedback response time to short termanthropogeniceffects.ThismakesRCP8.5akinto“BusinessasUsual”andRCP4.5equivalenttothemitigationthathasbeenproposedundertheParisagreementin2015.

6.3 Projected global sea‐level rise

Theprevious section shows thatRCP4.5 andRCP8.5 represent scenarioswith global averagewarming greater than 2⁰C with respect/ to pre‐industrial levels. These were the two RCP’sselectedforglobalandregionalsealevelprojections(Figure2).Theconventionalapproachtoprojectedsealevelrise isbasedonthesimulationof individualsealevelcomponents:suchascontributions fromocean thermalexpansion,melting/dynamicsofglaciersand the icesheets.These contributionsare then summedup to give anoverall SLRvalue.TheRISES‐AMprojectfollowedthisapproachandconsideredprojectionsofthemainsealevelcomponents:

Thermalexpansion Glaciersurfacemassbalance(SMB) GreenlandSMBanddynamicalchanges AntarcticaSMBanddynamicalchanges Changesinlandwaterstorage

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ThelatestIPCCreportgivesalikelyrange(66%)forglobalsea‐levelriseby2100,implyingthatthereisa34%chancethatsea‐levelrisemaylieoutsidethisrange,inpartduetothedifficultiesinassessingicemasslossfrombothGreenlandandAntarctica[8].

Figure2:Projectionsofglobalmeansealevelchangeoverthe21stcenturyrelativeto1986‐2005.Thelikelyrangeisshownasashadedbandwiththecorrespondingmedianvaluegivenasasolidline[6].

Table3:Medianvaluesandlikelyrangesforprojectionsofglobalmeansealevelriseinmetresat2100relativeto1986‐2005forthefourRCPscenarios.

ClimateScenario Median(m) LikelyRange(m)

RCP2.6 0.43 0.28to0.60RCP4.5 0.52 0.35to0.70RCP6.0 0.54 0.37to0.72RCP8.5 0.73 0.53to0.98With mean sea levels continuing to rise in the 21st century the impact assessment, riskmanagement,adaptationstrategyandlong‐termdecisionmakingforcoastalareasdependsonfutureprojectionsofsealevelandcrucially,thelowprobability,highimpact,projections.Whilethesehighimpactprojectionsareunlikelytoberealised,theyarestillplausibleandshouldnotberuledoutwhenconsideringadaptationandmitigationpolicies.Itisprojectedthatby2100whencomparedwith1986‐2005,globalsea‐levelwillbe0.53‐0.98mhigher (likely range66%only),with amedian of a 0.73m increase for the higher impactingclimatescenarioRCP8.5.ForRCP4.5,theglobalmeansea‐levelwillbe0.35–0.70mhigher(likelyrange,66%only),withamedianincreaseof0.52m(Table3).Thereisalsoanupperlimitscenario

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(J14_RCP8.5)basedonRCP8.5whichdeterminesthataglobalaveragesea‐levelrisegreaterthan1.8m has less than 5%probability of occurring by 2100 [9]. Figure 3 shows the probabilitydistribution for J14_RCP8.5, which is a high impacting low probability representativeconcentrationpathway,producedaspartoftheRISES‐AMproject.

Figure3:Projectedglobalmeansealevelriseby2100relativeto2000forhighendemissionsscenarioJ14_RCP8.5.Verticalgreybarsindicatethe5th,17th,50th,83rdand95thpercentilesintheprobabilitydistribution[9].

6.4 Future projections of regional sea‐level rise

OneoftheoutputsoftheRISES‐AMprojectistheproductionofregionalsealevelriseprojections,in 10 year intervals, forRCP4.5 andRCP8.5, up to 2100. For the Island of Jersey, the closestregionaldatasetpointwasidentified,thelocationofwhichisshowninFigure4.TheregionalSLRprojectionsforthetwoRCPpathways,andtheupperlimitscenario,areshowninTable4.ThedataconsistsofthethreeRCPscenarios,fourtimeperiodsforeach,and6percentilevalues.ThishighlightstherangeofpossibleregionalSLRvaluesthatcouldberealisedin2100,andwillbedifferenttotheglobalvaluesthathavebeenprojectedinsection5.3.

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Figure4:ClosestdatapointfromregionalSLRmodeltoJerseyforlatestregionalSLRprojections

The54different regional SLRprojections inTable4highlight theuncertainty inpresent SLRprojections,bothacrossdifferentclimatescenarios,andacrossthesametimeepoch.Ratherthanconsideringeachoftheseprojections,amanageableselectionofeightSLRscenarioshavebeenused,thatcovertherangeofpotentialSLRoutcomes.Table5liststheselectedSLRvaluesfromTable4roundedtoonedecimalplace.

Table4:Projectedregionalsea‐levelrise(m)foreachclimatescenarioacrossthe5th,17th,50th,83rd,95thand99thpercentilesforthethreetimeepochs,2030,2050,2080and2100correspondingtothedatapointshowninFigure5.

Climate Scenario Percentiles

Year 5th 17th 50th 83rd 95th 99th

AR5_RCP4.5 2030 0.08 0.10 0.12 0.15 0.16 0.18

AR5_RCP8.5 2030 0.09 0.11 0.13 0.15 0.17 0.19

AR5_RCP4.5 2050 0.15 0.18 0.22 0.26 0.29 0.32

AR5_RCP8.5 2050 0.17 0.21 0.25 0.30 0.33 0.36

AR5_RCP4.5 2080 0.25 0.31 0.39 0.46 0.52 0.58

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AR5_RCP8.5 2080 0.33 0.40 0.48 0.56 0.62 0.69

AR5_RCP4.5 2100 0.31 0.38 0.48 0.58 0.65 0.73

AR5_RCP8.5 2100 0.43 0.53 0.65 0.77 0.86 0.97

J14_RCP8.5 2100 0.40 0.54 0.77 1.21 1.82 2.69

Table 5: List of SLR scenarios used in the study that cover the range of regional SLRprojections.

SLRParameterNumber SLR(m)

1 0.1

2 0.2

3 0.3

4 0.5

5 0.6

6 1.0

7 1.2

8 1.8

Themajorityofprojectionsareatthelowervalues,hencebeingcoveredby0.1,0.2,0.3and0.5mwiththesmalleramountofmiddleprojectionsbeingcoveredby0.6m.Thelowprobabilityhighimpact(yetstillplausible)SLRvalues,arecoveredby1.0,1.2and1.8m.However,itshouldbenotedthattherateofsea‐levelriseisprojectedtodecreaseoverthelongtermduetoreducedemissions.

6.5 Limitations and uncertainty of projections

AlotofuncertaintyisassociatedwithEuropeanclimateprojections,duetovariabilityinclimatemodelpredictions,andthestronginfluenceofphysicalprocessessuchasstormtracksandjetstreams,whicharecurrentlynotwellrepresentedwithinmodels[10].Europe’sclimateisoneofthe world’s most variable due to the location of the end of the Atlantic jet stream and theassociated storm track configuration. Translating global climate studies to the impact of theglobalclimateonthecoastisstillnotfullyexplored[11],withcurrentregionalclimatestudiesfocusing on rainfall and temperature [12], with storm winds, surges and waves underrepresented.ItisthereforeimportanttonotethatwhilethisresearchisthemostuptodateintermsofregionalSLRprojections,thereareinherentlimitationsanduncertainties.

7 Vertical Land Movement Trends

It is important to understand the direction and rate of vertical landmovement at the coast,particularlyforregionsoutsidethepreviousicemarsh,suchasJersey.Itcanhaveasignificantpositiveornegativeimpactontheapparentrateofsea‐levelrise.Iftheverticalrateispositive,then the land is rising andwill help to reduce the impact of sea‐level rise.Conversely, if it isnegative,thelandissinkingandwillexacerbatesea‐levelrise.

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Postglacialrebound(alsoknownasGlacialIsostaticAdjustment(GIA))istheriseoflandmassesthatweredepressedbytheweightoficesheetsduringthelastglacialperiod.IntheUK,ScotlandandtheNorthofEnglandwerecoveredbytheseicesheetsandarecurrentlyrisingasaresultofthisreboundwhichisalsocausingacorrespondingdownwardmovementofthesouthernhalfofthecountry.ThiseffectwillincreasetheapparentrateofSLRinSouthernareasoftheUKmakingcoastalfloodingmorelikely.UsingavailabledatafromFrenchandUKGPSlandmovementstations,theverticalmovementratefortheregionsurroundingJerseyhasbeencalculated.ThelocationsofthelandmovementGPSstationsareshowninFigure5.

Figure5:LocationsofGPSverticalmovementstationsforareasurroundingJersey

Table6:VerticallandmovementratesforallstationssurroundingJerseyincludingtimespanandcompletenessofdata.

StationName Vertical landmovement rate(mm/yr)

Time span ofdataset(years)

Data completeness(%)

Newlyn ‐0.17+/‐0.14 15.25 89.43Portsmouth 0.07+/‐0.23 12.13 86.61

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StationName Vertical landmovement rate(mm/yr)

Time span ofdataset(years)

Data completeness(%)

Roscoff ‐1.28+/‐0.33 4.35 97.42LampualPlouarzel

‐0.53+/‐0.2 6.32 86.02

Guipavas ‐0.49+/‐0.15 11.2 91.01Brest 0.01+/‐0.11 15.16 73.90DinardPleurtuit ‐0.84+/‐0.38 5.42 94.14SaintMalo ‐0.63+/‐0.47 3.87 97.95Heauville ‐0.3+/‐0.19 11.26 81.32BeaumontHague ‐0.21+/‐0.35 6.78 94.02It can be seen that there is large variability in the rate of vertical landmovement across allstations.However,asidefromBrest,thedatashownegativeordownwardslandmovement.Thiswouldbeexpectedforareasjustoutsidetheicesheet,presentduringthelastglacialperiod.Itislikely Jerseywill also be subject to vertical landmovement in the samedirection i.e. sinking.However,thereislargeuncertaintyonexactlywhattherateislikelytobe.LookingatTable6theratesvaryfrom‐0.84mm/yratDinardPleurtuitto0.01mm/yratBrest.ThiscouldmeanthatthereiseitherlittleimpactontherateofSLR,oranalmost50%increase,assumingarateofSLRofaround2mmperyear.Contrasting this with the contribution that vertical land movement makes to the RISES‐AMregionalglobalSLRprojections fromsection5, for2030,2050,2080and2100(Table7); thecontributionremainsthesameforeachrepresentationconcentrationpathway.ThisisbecauseGIAisdependentontheicesheetsthatwerepresentduringthelastglacialperiodandhavesincemelted,andnottheamountofCO2projectedtobeemittedintotheatmosphere.

Table7:VerticallandmovementorGIAcontributiontoregionalsealevelprojections

TimePeriod

AR5_RCP4.5 AR5_RCP8.5 J14_RCP8.5

2030 0.0069 0.0069 0.00692050 0.0109 0.0109 0.01092080 0.0168 0.0168 0.01682100 0.0207 0.0207 0.0207

Table 7 shows that regional projections estimate a contribution of around 0.021m by 2100,whereas thehigher ratesofvertical landmovementwouldsuggest this contributioncouldbecloser to 0.075 m. Thus, the regional sea level projections could be underestimating thiscontributionby0.054m.Thiscontributionincontexttotheoverallsea‐levelriseprojectedby2100,showsthatverticallandmovementhasarelativelyminorimpactontheSLRprojectionsforJersey.

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Duringapost‐studydisseminationeventinJerseyitwasidentifiedthatthereisaGPSbasestationonJerseyoperatedbytheplanningdepartmentthatcouldallowameasurementoftheverticallandmovement to bemade. Efforts are being undertaken to acquire this data and any ratescalculatedwillbeappended to this report induecourse.Anyratescalculatedwill reduce theuncertaintysurroundingtheverticallandmovementratethatJerseyisexperiencingandprovidemoreconfidenceinsealeveltrendsandregionalsealevelriseprojections.

8 Regional Sea‐Level Trends

Inadditiontoverticallandmovementandregionalsealevelprojections,thereisalsovariationinthesea‐leveltrendatspecificlocationsalongthecoast.Thesevariationscanbeoverrelativelyshortdistancesduetodifferentfactorssuchasverticallandmovementandchangestothetidalrange and timing. Having a vertical landmeasurement located near to a tide gauge allows arelativesealeveltrendtobemeasured.Thesesea‐leveltrendscanbecalculatedovervaryingtimeperiodsdependingontherelevanttidegauge.Threetimehorizonshavebeenconsidered;1900to2013,1960to2013,and1970to2013,thesetakeintoaccountthevaryinglengthsoftidegaugerecords.Table8showstheabsolutesea‐leveltrendforeachtidegauge, foreachtimehorizonwheredataexists.SomelocationssuchasBresthavemorethanoneGPSstationnearbysohavemultipleentries.Figure6showsthelocationofthesetidegauges.

Table8:AbsolutesealeveltrendfortidegaugeswithrobustGPSrecords.

ABS_SLT=absolutesea‐leveltrendandABS_SLT_U=absolutesea‐leveltrenduncertainty.

TideGauge GPS Distanceapart(m)

ABS_SLT1900(mm/yr)

ABS_SLT_U1900(mm/yr)

ABS_SLT1960(mm/yr)


ABS_SLT1970(mm/yr)


BREST BRST 292 1.539 0.11 1.623 0.11 2.58 0.11

BREST GUIP 9213 1.039 0.15 1.123 0.15 2.08 0.15

NEWLYN NEWL 2 1.599 0.14 1.613 0.14 2.272 0.14

CHERBOURG BMHG 14006 NoData NoData 1.079 0.35 1.079 0.35

CHERBOURG HEAU 12930 NoData NoData 0.989 0.19 0.989 0.19

LECONQUET LPPZ 9790 NoData NoData NoData NoData 2.178 0.2

ROSCOFF ROTG 11 NoData NoData NoData NoData 0.392 0.33

WhiletherearemoretidegaugesthatcouldbeusedontheUKandFrenchcoastlines,onlyoneswithanearbyrobustGPSvelocitywereused.Allstationsandgaugesrequiredatleast70%validdata.Twoassumptionshavebeenmadetogeneratethesea‐leveltrends,thefirstassumptionisthatthelinearverticallandmovementestimatedbytheGPSstationisconsistentoverthemulti‐decadaltocenturytimescaleofthetidegaugerecord.ThesecondassumptionisthelandmotionbytheGPSantennaisconsistentwiththataffectingthetidegauge,atthelevelofafewtenthsofamillimetreperyear.

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Figure6:Locationsofthedifferenttidegaugesforabsolutesealeveltrends,(somelocationshavemorethanoneGPSstationlinkedsohavemultipletrends.)

The data shows that there is quite a variation in the absolute sea‐level trend, ranging from1mm/yratBrestfrom1900to2013to2.6mm/yratBrest,butforadifferentGPSstation9kmaway,fortheperiod1970to2013.ThishighlightstheimpactthatalongerdatasetanddistancebetweentheGPSandTidegaugehas,i.e.theGPSstationatBrestthatiswithin300mofthegaugehasa0.5mm/yrincreaseovertheGPSstationlocatedjustover9kmaway.Whenconsideringatimeperiodof1970to2013,theratesincreasebyaround1mm/yrto2.6mm/yrand2.1mm/yrrespectively.ThisincreaseinrateisalsopresentintheNewlyngauge.BothNewlynandBresthavenoticeablechangesintheratebetween1960and2013,andbetween1970and2013.Thereislittlechangebetween1900to2013,and1960to2013,suggestingthatbetween1960and1970therateoftheabsolutesealevelrisehasaccelerated.However,thisaccelerationisnotpresentatCherbourg.Theassumptionisthattherateofsealevelriseis2mm/yrwhichisconsistentwithpreviousreportsandisalsoagoodmatchtotheobservedtrendinmeansea‐level.

9 Extreme Still Water Level Return Period Assessment

9.1 Introduction

In 2008 the Environment Agency took on the role of producing a strategic overview of thecoastlineinEngland,givingitanoverarchingroleinthemanagementoftheEnglishcoastline.In

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response to outdated and inconsistent approaches to flood and erosion risk management, aresearch and development project was set up to deliver better information using improvedmethodsand longerdata records.Theprojectprovidedaconsistent setof extremesea levelsaroundthecoastofEngland,WalesandScotland.Theimprovementsaffordedbythisresearchareusedtosupportsuccessfulriskbasedfloodandcoastalerosionriskmanagement.Thisstudyreplicatesthismethodologyknownasskewsurgejointprobability(SSJPM),forthecoastofJersey.Theoutputsfromthemethodologyconsistofextremepeaksealevelsofannualexceedance,rangingfrom1in1yearto1in10,000years[13].

9.2 Skew surge joint probability – methodology overview

Skewsurgejointprobabilityisusedtoderiveextremewaterlevelsaroundthecoastline.Stormsurgesariseswhengradientsorchanges inatmosphericpressureaffect the levelof thewatersurface.Lowpressure(e.g.duringstormconditions)actstoraisetheseasurfacelevel,wherehighpressurewilllowerit.Windscanalsodrivecurrentsthatwillactonthesurfacechangingthesealevele.g.offshorewindsthatareorientatedparalleltothecoastline,withthecoastlinetotherightrelativetothedirectionofwind.Thesewindswillresultincurrentsorientatedtowardsthecoastcausingariseinthelocalsealevel.Thecombinationofallthesecomponentsisknownasstormsurge,andcanincreaseordecreasesealevels.Astheseprocessesaremeteorologicalinorigin,theyareindependentfromtheastronomicaltideandsocanoccuratanypointofthetidalcycle.Skew surge is defined as the height difference between the predicted astronomical tide andnearestexperiencedhighwater(Figure7).Usingthisdefinitionresultsintheremovalofallphasedifferences (timing differences), between predicted and observed data, which eliminates theimpactofillusoryresiduals.Relyingonsurgeresidualsratherthantheskewsurgecanresultinillusory surge residuals which can over predict the extreme water level, if for example, theobserved tide occurs slightly earlier than predicted. This is particularly applicable to surgeresidualsinthemidtiderange(Figure7)[13].

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Figure7:Illustrationofskewsurge

ToapplySSJPM,thetidegaugedatawasde‐trendedbyarateof2mm/yr.ThisrateisthenetcombinationoflandmovementandchangesinwaterlevelduetoSLR.Analysisfromsection7hasshownthatthishistoricriseisappropriatetouseforthestudy.Therefore,thede‐trendeddatawillbeconsistentforallyearsandindependentofsealevelrise.Thepeakobservedwaterlevel for each high tide was extracted, and the predicted high tide was also calculated. AsmentionedthedifferencebetweentheseisknownastheSkewSurge.Thisprocesswasrepeatedacrossthewholetidalgaugedataset[13].AGeneralisedParetoDistribution(GPD)wasfittedtotheskewsurgedistribution,theparametersoftheGPDweresettoprovidethebestfitpossibletotheextremeskewsurgesaboveaspecifiedthresholdintheuppertailofthedistribution(Figure8).

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Figure8:SchematicoftheGeneralisedParetoStatisticalDistribution

JointProbabilityanalysiswasusedtoformaprobabilitydistributionofallpossibletotalsealevelsfromtheskewsurgedistributionandpeaktidelevelsfromthefullnodalcycle.Theanalysishasassumedindependencebetweenskewsurgeandpeaktidallevels.ThefinalstageoftheSSJPMwastoexpresstheprobabilitydistributionoftotalsealevelsintermsofreturnperiods[13].

9.3 Skew surge joint probability – analysis results

TheresultsoftheSSJPManalysisforStHelierareshownbelowintheformofa linearplotofreturnperiodagainstextremewaterlevel(Figure9)andatabulardatashowingthereturnperiodvaluesandthe95%confidenceinterval(Table9).

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Figure9:Linearplotofreturnperiodagainstextremewaterleveluptoa1in200‐yearevent,thesolidlinerepresentsthereturnperiodvaluesandthedashedlinesindicatethe95%confidenceintervals.

Table9:SSJPMResultsforStHelier,showingstillwaterlevelforarangeofreturnperiods.

ReturnPeriod(years) Extreme Still WaterLevel(mCD)

95thConfidenceInterval(mCD)

1:1 12.12 12.11 12.12

1:2 12.18 12.18 12.19

1:5 12.28 12.27 12.29

1:10 12.34 12.33 12.36

1:20 12.41 12.4 12.44

1:25 12.43 12.42 12.47

1:50 12.5 12.48 12.56

1:75 12.54 12.52 12.62

1:100 12.57 12.55 12.66

1:150 12.61 12.58 12.71

1:200 12.64 12.61 12.76

1:250 12.66 12.63 12.8

1:300 12.68 12.64 12.83

1:500 12.74 12.69 12.93

1:1000 12.81 12.76 13.08

12.1

12.2

12.3

12.4

12.5

12.6

12.7

12.8

0 50 100 150 200

Extrem

eWaterLevel(mCD)

ReturnPeriod(Years)

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ReturnPeriod(years) Extreme Still WaterLevel(mCD)

95thConfidenceInterval(mCD)

1:10,000 13.06 12.93 13.78

Theseextremewaterlevelresultshavebeencomputedwiththebestqualitydataavailable,usingthe most up to date methodology, and are suitable for use in assessing the probability ofoccurrenceofpresentdaystormsurges.

9.4 Comparison of extreme still water levels with HR Wallingford 2009 report

ApreviousstudybyHRWallingfordin2009calculatedextremewaterlevelreturnperiods.TheextremewaterlevelswerebasedontidallevelsfromapreviousHRWallingfordstudyin1991.The tidal levelshadbeenupdated to account for changes inmeansea levelover the last twodecades,basedonanassumedrateofSLRof2mm/yr.Thetidal levelswerethenanalysedtoprovideestimatesofexceptionallyhightidallevels,withestimatedreturnperiodsbetween1and100years.Table10showstheseestimatedstillwater levels,whichincludeatideandasurgecomponentforthedifferentreturnperiods.

Table10:ExtremestillwaterlevelsextractedfromTable2.1HRWallingford2009

Return Period(years)

ExtremeStillWaterLevels(mACD)

FirstTower,StAubin’sBay1:1 12.4371:10 12.6681:20 12.7371:50 12.8291:100 12.899

ComparingtheresultsfromTable9withtheHRWallingford’svaluesinTable10showsthattheHRWallingford’s values aremore pessimisticwith extremewater levels for the same returnperiodbeingaround0.33mhigher.Itwasunexpectedthatthedifferencebetweeneveryreturnperiod levelwouldnearlybe the same and it is suspected that this differencemaybedue todifferentverticaldatum’sbeingusedasareferencepoint.ThereturnperiodscalculatedinHRWallingford’sreportwerecalculatedusingdatafromaprevioustidegauge,beforethecurrentonewasinstalledin1992.Thenewgaugeisahigh‐qualitybubblergaugeinstalledaspartoftheUKNationalTideGaugeNetwork.Thisstudyuseddatafromthecurrenttidegaugetodetermineextremesealevels.Itisunknownwhattheverticaldatumofthepreviousgaugewas.Theoffsetof0.33mispotentiallyadifferencebetweenOrdnanceDatum’s,e.g.Newlyn(used in theUK)versusJersey’sownverticaldatum.IftheoldtidegaugewassettoNewlynOrdnanceDatum,thenthiswouldexplainthedifference,however,ithasnotbeenpossibletoclarifyifthiswasthecase.Asidefromthis,thetwodatasetsshowsimilarextremewaterlevelreturnperiodslevelslendingconfidencetotheresultsfrombothreports.

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10 Projections of Storm Surges and Significant Wave Height

10.1 Waves

Previouslyglobalclimatemodelsdidnotincludetheabilitytosimulateoceanwaves.Thismeansthatwaveclimateprojectionsarenotdirectlyavailable fromtheUKCP09work.Theavailableresearchfromothersourcesaresummarisedbelow.The COWCLIP (Coordinated Wave CLImate Projection) project has derived multi‐modelensemblesofwaveclimateprojections [14].The resultsof thiswork showagoodagreementamong themodels of a consistentwide spreaddecrease inwave climates, particularly in thesubtropicsandNorthAtlantic.Anincreasewasonlyfoundtooccuroverabout7%oftheglobalocean,predominantlyintheSouthernOcean,associatedwithastrengtheningofwesterlywinds[14].MorerecentresearchusingRCP8.5andRCP4.5dataasinputs,showsthatforbothscenarioswindspeedandwaveheightwillincreaseintheArcticandSouthernOcean,anddecreaseinthePacific.FortheNorthAtlantic,thetrendreducesinthemediumtolongterm[15].Statistical projectionsof changes in oceanwaveheights, using sea‐level pressure informationfrommultiple global climatemodels, has shown that significantwave height increases in thetropics,andinhighlatitudesintheSouthernHemisphere.UnderRCP8.5,itisprojectedthattheclimatecondition for2070‐2099 is that theprobabilityofoccurrence,ofpresent1 in10yearextremewaveheights,arelikelytodoubleortripleinseveralcoastalregionsaroundtheworld.Thesewaveheightincreasesareprimarilydrivenbyincreasedsealevelpressuregradients,andthereforeincreasedsurfacewindenergy[16].GiventhatJerseyisnotlocatedinthetropicsorhighlatitudesintheSouthernHemisphere,itisnotcurrentlyprojectedtoexperienceanyincreaseinsignificantwaveheightsupto2100.

10.2 Projected changes to annual mean significant wave height

Projectedchangesofannualmeansignificantwaveheight(Hs),showthatthelargestchangeisprojected tobe in theSouthernOcean,where themeanHs at theendof the21st centuryareapproximately5to10%higherthanpresentdaymeans[17].This is thoughttobeduetotheprojected strengthening of westerlies over the Southern Ocean, particularly during australwinter.AnotherregionofHsincreaseisthetropicalSouthPacific,associatedwithaprojectedstrengtheningofaustralwintereasterlytradewindsinthemulti‐modeldataset.Forallotherregionsnegligiblechangeoradecrease isprojected,withdecreasesassociatedwith the tradewindregionoftheNorthPacific,themidlatitudewesterliesinallbasins,andinthetradeandmonsoonwindregionsof the IndianOcean[17].As Jersey isnot located in theseregions it isunlikelytobeaffectedbyincreasestoannualmeanHs.

10.3 Projected changes to storm surges

Surgesarenotusuallymodelledattheglobalscaleastheyareonlyappreciableinshallowwaterandarepredominantly generatedoncontinental shelves.This ignores tsunamisgeneratedby

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displacementoftheseabedinthedeepocean.However,highermeansealevelsasaresultofSLRcansignificantlydecreasethereturnperiodforexceedinggiventhresholdlevels[18].Figure10showstheimpactofanincreaseof0.65m,whichisconsistentwiththemostlikelyoutcomeforRCP8.5in2100.Itshowsalargedecreaseforallreturnperiods,e.g.apresentday1in500‐yeareventwouldnowbea1in1‐yearevent.Therefore,evenquitesmallincreasesinmeansea‐levelswillhavealargeimpactonthereturnperiodexperiencedduringextremeevents.

Figure10:Impactof0.65mofSLRonreturnperiodvaluesforJersey.Purpleshowstheextremewaterlevelforagivenreturnperiodforanincreaseinmeansealevelof0.65m.Thebluelineshowsthepresent‐dayrelationshipwithassociatedconfidenceinterval

11 Historical Changes in Winds, Waves and Storminess

Ithasbeenarguedthatwind‐seaandswellwavesmayshowdifferent inter‐annualvariability[19].Thereforeanincreaseinthefrequencyofstormeventswillresultinareductioninthetimeofswelldecaybetweenstorms,andprovidesahigherresidualswelllevel[20].This,asaninitialconditionforthegrowthofnewlygeneratedyoungwaves,meansthatswellwavevariabilityisprimarilyassociatedwiththeoccurrenceofstorms,andthewindseachangeswiththemagnitudeofthewindspeedandlocalfetch.Previousresearchhasinvestigatedthispossiblerelationship,andfoundthattheintensity,frequency,trackandspeedofstormshaslesseffectonthemonthlymeanandmaximumwaveheight, than the strengthofwesterlywinds.This suggests that therecent observed increase in wave height is more likely caused by an intensification of thebackgroundwesterlyatmosphericcirculation,thanbychangingstorminess[21–23].

12.1

12.3

12.5

12.7

12.9

13.1

13.3

13.5

0 50 100 150 200

Extrem

eWaterLevel(mCD)

ReturnPeriod(Years)

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Globalsatellitealtimeterdata(TOPEX/Poseidon)spanningaperiodofmorethan20yearshasbeenanalysedforanyindicationsofmeasurabletrendsinextremevaluereturnperiodestimateofwindspeedandwaveheight[24].Thereappearstobeapositivetrendinthe100yearreturnperiodvaluesofwindspeed,butnoconsistenttrendsforthe100yearreturnperiodwaveheight.Howeverdue to the limiteddurationof the altimetrydataset available, associated confidencelevelsinthemagnitudeoftheseestimatesarelow[24].There is ahistoryof strongvariability in thenorthwestEuropeanwave climate. Inter‐annualvariability in the modern wave climate is strongest in the winter, and can be related toatmospheric modes of variability such as the North Atlantic Oscillation (NAO) [25]. Ratherdramaticincreasesinwaveheightshavebeenobservedbetween1960and1990,butthisisseenasonepartinalongerhistoryofvariability.Since1990therehasbeennoclearpattern,naturalvariabilityisstrongandanthropogeniccontributionsisuncertain.TwopossibleexplanationsfortheobservedincreaseinwaveheightwithNAOareincreasesinzonalwind,increasingthebuild‐upofwavesoverseveraldays,oranincreaseinthefrequencyandintensityofstorms[26].Variousclimatereanalysisprojectshavebeencarriedoutrecently.Aclimatereanalysisconsistsofaclimatemodelrunforahistoricalperiod,usingdataassimilationoftheavailableobservationdata, toobtain thebest analysis fields that represent the stateof theatmosphere throughoutdecadalsimulations.TwowavenumericalhindcastswererealisedfortheNorthAtlanticOceanbasedonthemodelWaveWatchIII.Thefirsthindcastuseswindfieldsoriginatingfromthe20CRreanalysis which produced wind data for the period 1900 to 2008 [27]. This hindcast onlyprovides significant wave height [28]. The second wave hindcast used winds from theNCEP/NCARreanalysiswhichcoverstheperiod1948‐2012andusesahigherspatialresolution[29].Thishindcastprovidessignificantwaveheight,peakperiodandwavedirection[30].TheclosestpointinthishindcasttoJerseythatproducesvaliddatawasusedtoassessthechangesinwaves throughout the20th century (Figure12). Itwas found thatbothhindcastshada linearincreasingtrendinsignificantwaveheight,bothweresmallincreaseswithgradientsof5.3x10‐6forthe1900to2008and8.3x10‐6for1948to2012.Ultimatelythisresultsinaverysmallincreaseinsignificantwaveheightwithnoobviousincreaseintheextremewaveheightexperiencedoverthe20thcentury.

12 Joint Water Level and Wave Height Probability Assessment

12.1 Introduction

With respect to coastal engineering, joint probability refers to two ormore partially relatedenvironmentalvariablesthatoccursimultaneously.Examplesofthesearehighwavesandhighwaterlevels,highwind‐seaandhighswell,andlargeriverflowsandhighsealevels.Ascoastalfloodingisassociatedwithtimesofhighwavesandhighwaterlevels,itisthereforebeneficialtoconsiderthejointprobabilityofthesevariableswhenconsideringaresponsetoclimatechange.This study will focus on the joint probability of high water levels and high wave heights.Determinationofthejointseastatedependsonanassessmentoftheprobabilityofagivenwaterlevel,andagivenwavecondition.Thecorrelationbetweenthesetwovariablesdependsuponthe

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meteorologicalconditionswhichproducethem,andtheexposureofthecoastlineunderstudy.Everyprobabilityofoccurrenceor returnperiodwillhavea rangeof a combinationofwaterlevels,andsignificantwaveheights,thatsatisfythesameprobabilityofoccurrence.Foranycoastlinethereissomecorrelationbetweentheoccurrenceoflargewavesandhighsealevels,asextremestormeventstendtocausebothstormsurgesandhighwaves.However,asthestormdoesnotcontributetotheunderlyingtidallevelwhichisdependentonrelativepositionoftheMoon,Sun,Earth,andotherveryslowlychangingfactorssuchascoastlinetopographyratherthanmeteorologicalconditions,thenthedegreeofcorrelationwillvary.AsJerseyhasaverylargetidalrangeof12m,thenthiswillhaveamuchlargerimpactthancoastlineswithmicro(<2m)ormeso(2m–6m)tides.ForJersey,thelargeststormsurgesarecausedbydepressionsmovingeastwardsuptheEnglishChannel,becausethetracksareoftentothenorthofJersey,thesedepressionscausestrongsouth‐westerlywinds,veeringwesterly.WithJersey’spositionrelativetothemainlandofFrance,theseconditionsgiverisetowindwavesfromsouthwestandwest,withswellwavesfromthewest.Thismeansthatthewesterncoastisthemostexposed,andwillbesubjectedtomoreextremeeventsthanothercoastlines.Thedegreeofthisgreaterexposureisexpressedasacorrelationfactor.This factor takes intoaccount thevariation in theassociationbetweenwater levelandwaveconditionsastheseverityofeitherincreases.

12.2 Previous joint wave height and water level probability assessments

HRWallingfordperformedjointprobabilityassessmentsforJerseyin1991and2009.Thestudyin1991assessedtheFauvicseawallandassignedacorrelationfactorof1betweenextremewaterlevel,andextremewaveheights.Thiswasthenusedasthebasisforassessmentofthedefences.Jointprobabilityresearchhasmovedsince1991andbettermethodsarenowavailabletoallowmoreaccurateassessmentsofthedependenceandjointextremesofacoastline.Table11showsthejointprobabilityresultsfromtheHRWallingford2009studyforStAubin’sBay.

Table11:HRWallingfordjointprobabilityconditionsforStAubin’sbaytakenfromTable2.3inHRWallingford2009.

Site Likelihoodofeventoccurringinanyoneyear(ReturnPeriod)

1:1year 1:10year 1:20year 1:50year 1:100yearEWL Hs EWL Hs EWL Hs EWL Hs EWL Hs

StAubin’sBay(HR7)

11.746 3.10 12.331 3.80 12.459 4.00 12.506 4.20 12.700 4.4312.004 2.97 12.506 3.49 12.506 3.83 12.714 4.00 12.614 4.3312.414 2.57 12.576 3.29 12.69 3.29 12.714 3.80 12.863 3.50‐ ‐ 12.714 3.03 12.714 3.16 12.814 3.29 12.899 3.46

Key:EWLextremewaterlevel(mACD),HssignificantwaveheightThejointprobabilityresearchundertakenbythisstudywilladdresstheconcernsraisedbytheHRWallingford2009report,as itwas felt themethod it followed inboth the1991and2009studieswaslikelytoresult inamorepessimisticassessmentofthefrequencyandintensityofflooding.

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12.3 JOIN‐SEA joint probability assessment

The approach used by this report is based on proposals by Coles and Tawn 1990 [31]. Themethodologyfollowedhasbeenextensivelyusedandiswellvalidated,andisknownasJOIN‐SEA[32–34].JOIN‐SEAusesabivariateormixtureoftwobivariateprobabilitydistributionsthatisthenfittedtothelargestvaluesoruppertailsofthewaveheightandwater leveldataset.Theoutputoftheanalysisisintheformofjointprobabilitycurves(Figure13).Thecurverepresentsa given annual probability of occurrence, for example a 1 in 200 year, and the differentcombinationsofwater levelandwaveheightalong thecurveallhave thesameprobabilityofoccurrence.Thecurvesshowthatincreasingtheextremewaterlevelrequiresareductioninthewaveheighttoretainthesameannualprobabilityofoccurrence.ForthisstudythetidegaugelocatedinStHelier’sharbourwasusedtoprovidewaterleveldata,theobservedhighwaterelevationvalueswereextracted,andtheclosestwaveheightintimefromthewavedatasetwasassignedasthehighwaterwavevalue.Thewavedatasetpredominantlycomprisesanoffshorewavemodelthatprovidedsignificantwaveheightanddirectionathourlyintervals.Alljointprobabilityanalysisisverydependentonthelengthandqualityoftheinputwaterlevelandwaveheightdata,andeffortsweremadetoensurethebestdataavailablewasused.Theclosestmodelpointthathadsuitabledatawasoutinthemainchannelapprox.100kmfromJersey.Figure11showsthelocationusedtoprovidewavedatawhichislocatedtowardsthemiddleofTheEnglishChannel,italsoshowsthelocationofthewavebuoyoperatedbytheJerseyMet Office. As the offshore model wave data originates so far from Jersey it needs to betransformedsoitismorerepresentativeofthewavesnearshoreatJersey.

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Figure11:LocationsofdatapointsforJerseywavebuoy,wavehindcastmodelandoffshorewavemodel.

12.4 Transforming waves from offshore model to wave buoy

ThewavesthataregeneratedasoutputfromtheoffshoremodelwillnotberepresentativeofthewavesthatwillbepresentduringextremeeventsclosetothecoastlineofJersey.Ideallyamodelwouldbeusedtotransformthesewavesintoonesthatwouldbepresentatthecoast.Howeverduetotimelimitationsthiswasnotpossiblesothenextbestoptionwastouseavailablewavebuoydataanddetermineifaclearrelationshipispresentbetweenthewavesoffshoreandwavesatthebuoy, thatcouldthenbeusedtotransformthewaves.Byplottingbothsetsofwaves,alinearregressioncanbeperformed,resultinginatransformequation.Figure12showsaplotofboth the significant waves offshore, and at the buoy. The linear regression trend line andassociatedequationcanalsobeseen.

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Figure12:Significantwaveheightfromoffshoremodelagainstsignificantwaveheightatwavebuoy.

Thisderivedequationwasapplied to theoffshoremodelwavedata to “transform” them intowavesthatwouldberepresentativeatthewavebuoylocation.However,whilethewavebuoyismuchclosertoJerseyitisstillaround12kmdistancefromStAubin’sBay.TocheckthatthesewavesarerepresentativeofthewavesattheentrancetoStAubin’sBay,thewavebreakerdepthwaschecked toensure that thesewaveswouldnothavebrokenbeforeentering thebay.Thebreakerindexdefinesthatthemaximumwaveheightpossibleis78%ofthewaterdepth.Giventhe large tide range at Jersey,waves at thewavebuoy are representative ofwaveswithin StAubin’sBayduring an extreme event. This approachwas considered tobe suitable given theconstraintsofthestudy.Ideallyawavemodelwouldbeusedtotransformthewavesgeneratedoffshoretothespecificpointswherethestormimpactmodeltakesover.

12.5 Results of joint probability assessment

TheresultsofthejointprobabilityassessmentareshowninFigure13.Thedatashowthateachreturnperiodendsupbeingacontourorcurve,andthateverycombinationofwaterlevelandsignificantwaveheightonthecurvehasthesameprobabilityofoccurrence.Figure13onlyshowsfourdifferentreturnperiodsalthoughmorearepresentedinTable12(whichshowstabulatedresults).DuetothehightidalrangeatJerseythecurvesareelongatedwithsmallchangesinthewaterlevelresultinginlargereductionsinsignificantwaveheightatheightsaboveMeanHighWaterSprings(MHWS)of10.69mCD.

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Figure13:JointprobabilityassessmentresultsforStHelier,fourdifferentreturnperiodsaredisplayed.

Table12:Tabulatedresultsofjointprobabilityanalysisextremewaterlevelsarerelativetochartdatum(mCD)

Likelihoodofeventoccurringinanyoneyear(ReturnPeriod)1:1year 1:10year 1:20year 1:50year 1:100year 1:200year

WL/HsCombination(m)

EWL Hs EWL Hs EWL Hs EWL Hs EWL Hs EWL Hs

1 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ 6.88 7.40

2 ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ ‐ 7.38 7.40

3 ‐ ‐ ‐ ‐ ‐ ‐ 6.88 6.57 ‐ ‐ 7.88 7.40

4 ‐ ‐ 6.88 5.64 6.88 5.99 7.38 6.57 6.88 7.05 8.38 7.30

5 ‐ ‐ 7.38 5.64 7.38 5.99 7.88 6.56 7.38 7.05 8.88 7.30

6 ‐ ‐ 7.88 5.63 7.88 5.97 8.02 6.50 7.88 7.05 9.38 7.27

7 ‐ ‐ 8.38 5.60 8.38 5.93 8.38 6.47 8.38 6.90 9.67 7.00

8 6.88 4.36 8.88 5.55 8.88 5.90 8.88 6.40 8.88 6.90 9.88 6.90

9 7.38 4.36 9.01 5.50 9.38 5.78 9.38 6.32 9.38 6.57 10.38 6.90

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Likelihoodofeventoccurringinanyoneyear(ReturnPeriod)1:1year 1:10year 1:20year 1:50year 1:100year 1:200year

WL/HsCombination(m)

EWL Hs EWL Hs EWL Hs EWL Hs EWL Hs EWL Hs

10 7.88 4.35 9.38 5.39 9.88 5.71 9.88 6.09 9.86 6.50 10.78 6.50

11 8.38 4.30 9.88 5.32 10.38 5.60 10.34 6.00 10.38 6.47 10.88 6.37

12 8.88 4.24 10.38 5.10 10.5 5.50 10.88 5.69 10.88 6.00 11.38 6.07

13 9.38 4.16 10.58 5.00 10.88 5.20 11.19 5.50 11.38 5.61 11.5 6.00

14 9.88 4.04 10.88 4.79 11.16 5.00 11.38 5.13 11.45 5.50 11.69 5.50

15 10.01 4.00 11.19 4.50 11.38 4.60 11.45 5.00 11.69 5.00 11.88 5.30

16 10.38 3.86 11.38 4.26 11.41 4.50 11.74 4.50 11.88 4.63 11.91 5.00

17 10.88 3.53 11.57 4.00 11.74 4.00 11.88 4.17 11.91 4.50 11.98 4.50

18 10.92 3.50 11.78 3.50 11.88 3.62 11.93 4.00 11.98 4.00 12.07 4.00

19 11.36 3.00 11.88 3.29 11.92 3.50 12.04 3.50 12.07 3.50 12.13 3.50

20 11.64 2.50 11.95 3.00 12.06 3.00 12.13 3.00 12.21 3.00 12.26 3.00

21 11.83 2.00 12.07 2.50 12.15 2.50 12.24 2.50 12.27 2.50 12.28 2.50

22 11.88 1.79 12.18 2.00 12.24 2.00 12.28 2.00 12.31 2.00 12.33 2.00

23 11.95 1.50 12.23 1.50 12.27 1.50 12.31 1.50 12.33 1.50 12.36 1.50

24 12.05 1.00 12.26 1.00 12.29 1.00 12.32 1.00 12.35 1.00 12.36 1.00

25 12.1 0.50 12.28 0.50 12.31 0.50 12.34 0.50 12.35 0.50 12.37 0.50

Key:WL=extremewaterlevel,Hs=significantwaveheight

12.6 Comparison of joint probability

Comparingthetwojointprobabilityresults,itiscleartherearenoticeabledifferences,withtheHRWallingford2009studyreportingmuchhighersignificantwaveheightsandslightlyhigherextremewaterlevelsacrosstherangeofcombinationsofwaterlevelandsignificantwaveheight.Theslightlyhigherwaterlevelsarepotentiallyduetoinconsistenciesinwaterlevelreturnperiodlevelsbetweenthisreportandthe2009report.The2009versionwasbasedona1991reportusingdatafromaprevioustidegaugeratherthanthegaugeusedinthisstudy,whichhasbeeninplacesince1992. It isnotknownif thetwogaugesuseddifferentverticaldatum’swhichmayaccountforthe0.33moffsetpresentintheextremewaterlevelonlyanalysis.The2009HRWallingfordreportusedthesameassumptionofaprevious1991study;that,forJersey, the largest waves and the highest tidal levels would occur simultaneously. Thisassumptionwasmadetoallowaconsistentapproachtothecomparisonoftheperformanceofthecoastaldefencesaroundtheisland,ratherthantopreciselyquantifytheperformanceofthedefences.Duetothisitwasconsideredthattheaccuracyofthisassumptionisnotasignificantconcernandrepresentsa“worstcase”scenario.However,researchhasshownthatthisassumptionisonlylikelytobevalidalongcoastsaffectedbyhurricanes.TheHRWallingford2009reportisthereforepessimisticinitsassessmentofthefrequencyandintensityoffloodingthatitpredicts.

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13 Changes to Tidal Range from Projected Sea‐Level Rise

13.1 Introduction

Therearemanyimpactsfromincreasingmeansea‐levels,onesuchimpactisonthetiderangeand duration. For an area such as the European shelf the tide is dominated by semidiurnalconstituents. This means that focusing on the response of the M2 tidal constituent is anappropriatemetrictoinformtheimpactofSLRonthetidefortheregion.TheM2 tidal amplitude responds to SLR in a spatially non‐uniformmanner,with substantialamplitudeincreasesanddecreasesfor2and10mSLRscenarios.Aswellasbeingspatiallynonuniform,theM2tidalresponseitselfisalsonon‐linearbetween2and10mofSLR,somethingthatisparticularlyprevalentintheNorthSea.Under2mofSLR,theM2constituentisparticularlyresponsive in resonant areas of the Bristol Channel and Gulf of St Malo with increases anddecreasesobservedrespectively.Fora2mSLRthespringtiderangeincreasesbyupto0.35matCuxhavenanddecreasesbyupto0.49matStMalo[35].TherearealsochangesinshallowwatertidessuchthatwithincreasedSLR,thetidalwavespeedandwavelengthareincreasedinnearresonantareas.ForlargeshallowareasSLRcausesreduceenergydissipationbybottomfriction.Thecombinationoftheseimpactsresultsinthemigrationoftheamphidromesandacomplexpatternofchangethatisnon‐linearwithrespecttoSLR.AstheamountofSLRprojectedisuncertain,ifahighendSLRscenarioisrealisedthansubstantialalterationstotidalcharacteristicscanbeexpected.Thesealterationscouldhavewidereachingimplicationsontherequirementsforflooddefenceresilienceduetoincreasedtidalrangeandchangestothetidalphase.

13.2 SLR scenario tidal modelling

Toexplorethisimpactfurther,analysishasbeencarriedoutusingtheDutchContinentalShelfModel, based on non‐linear shallow water equations. The model encompasses most of theEuropeanShelf,andhasbeendevelopedjointlybyDelftHydraulics,RijkswaterstaatandtheRoyalNetherlands Meteorological Institute (KNMI). The model has been in development since the1980’sandisusedoperationallyforstormsurgeforecasting.Themodelhasbeencontinuouslyredeveloped,calibratedandvalidated,hencethereishighconfidenceinitsoutput[35].Fivedifferentsimulationswererun,threewiththeM2constituentinthetideonlyforthepresentday,2mofSLRand10mofSLR.Thefinaltwosimulationssimulatethepresentdayand2mSLRfor34tidalconstituents.The34tidalconstituentsrepresent98%oftheobservedtidalrange.Themodelwasspunupfora5dayperiodinallsimulationsthenfortheM2runsthesimulationwasrunforafurther5dayswhichwastheperiodanalysed,resultingina10daysimulationoverall.Forthe34tidalconstituentmodel,thespinupwas5daysbuttotalruntimewas30days,giving25daysofanalysistouse.

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ThepercentagechangeindepthacrossthemodeldomainforbothvalueshighlightedJerseyasanareawheresignificantalterationstothetidemightbeexpected.Thisisbecauseitisashallowareawithalargepercentagechangeinabsolutedepth.

13.3 Results of tidal simulations

TheGulfofStMaloisaregionidentifiedashavingaparticulardecreaseintheM2tidalamplitude.Table13providesmoredetailonthemagnitudeofthechangesintheM2tidewithboth2and10mofSLR.ThetablealsoshowsthechangesinthephaseoftheM2tideitwasfoundthatthearrivalofthepeakoftheM2tidewasalteredinthe2mSLRsimulationinaspatiallyvariablemanner.ForStMalothiswasanegativechangeintheorderof2⁰/hr.Thisincreasestoadecreaseof13⁰/hrforthe10mSLRsimulation.Intermsofdifferencesfromthepresent‐daysimulationthisresultsinareductionto91%for2mSLRand54%for10mSLR.

Table13:Resultsofthe2mand10mSLRsimulationsforStMaloM2TidalConstituent.(↓↑‐reductionorincrease)

Location M2Amplitude(m) %controlamplitude M2Phase(degree/hr)

Control +2m +10m +2m +10m Control +2m +10mSaint‐Malo 381 ‐0.33↓ ‐1.75↓ 91↓ 54↓ 170 ‐2 ‐13SaintMalowasoneoftheportswiththelargestchange,Figure14presentsthechangeintidalcurvesfromthepresentdayandunder2mSLRand10mSLR.

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Figure14:Changestothetidalcurvefor2mSLRand10mSLRforSaint‐Maloportwithblueshowingthepresentdaycontrolcurve,thegreenrepresenting2mSLRandredidentifying10mofSLR[35].

Thesimulationrunswith34tidalconstituents,toenableacomparisonwiththespring(M2andS2inphase)andneap(M2andS2outofphase)tides.ThechangesinamplitudeandphaseforbothM2andS2willshowwhatimpactSLRwillhaveonspringandneaptides.Only2mofSLRwassimulated,Table14showstheresultsforStMalo.

Table 14: Results for StMalo for tidal simulationwith 34 constituents for 2m SLR. (↓↑‐reductionorincrease)

Location M2 S2 M2‐S2(Neap) M2+S2(Spring)

ControlAmplitude

Change+2m ControlAmplitude



Change+2m

(m) (m) (%) (m) (m) (%) (m) (m) (%) (m) (m) (%)

SaintMalo 0.392 ‐0.37 91↓ 1.60 ‐0.13 92↓ 0.232 ‐0.24 90↓ 0.552 ‐0.49 91↓

AtStMalo, thechange inneap tidal range is smaller than theM2 tidalamplitudechange.TheresultsshowthatthechangesinamplitudetotheM2andS2constituentsarepositivelycorrelated,withgreaterchangesoccurringforspringtides,andfortheM2constituent,thanforneaptides.Thechange intidalrangeforthe2mSLRsimulation forspringtides forStMaloshowthat itexperiencesalargerchangeinrangeonthespring,ratherthantheneaptide.BoththeM2andS2experiencechangesofthesamesign,whichresultsinthelargealterationtothetidalrangeshownbythe2mSLRsimulation.Onthespringtidethechangeintidalrangeisareductionof0.49mwhichis25%ofthe2mofmeanprojectedsea‐levelincrease.ThisisoneofthebiggestreductionsforthewholeEuropeanShelf.ThedifferenceinrangebetweentheM2onlysimulationsandthe34tidalconstituentsshowthat St Malo has large contributions from other semidiurnal, diurnal and other harmonicconstituents.However,tofullyunderstandthesechangesamuchlongermodelsimulationof1yearwouldberequired.Insummary,thisanalysishasshownthatbasedonmodellinga2mSLR,JerseywouldexperienceoneofthegreatestdecreasesontheEuropeanShelfintidalrangeforagivenincreaseinmeansealevel.

14 Extreme Event Modelling: Storm Impact Model

Theresultsofthejointprobabilityanalysisfromsection12havebeenusedtoassesstheimpactofextremeeventsonthebeachinStAubin’sBay.Ofthedifferentreturnperiodsthatwerecalculatedaspartofthejointprobabilityanalysis,twowereselected,1in10year,and1in200yearcombinations.The1in10wasselectedtorepresent

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a“common”extremeeventthatisconsistentwithpastevents,suchasthestormsurgein2008.The1in200yearrepresentstheextremeeventthatseadefencesarecommonlydesignedtoberesilientagainst.Giventhelargerangeofwaterlevelsandwaveheightsthatcorrespondtobothreturnperiods,selectionsweremadetoreduceeachofthesedowntofourwhilealsocapturingthevariabilitypresent.Figure15showsthefourdifferentcombinationsthatwereselectedforbothofthereturnperiods.ThesecombinationswerethenusedasthebasisfortheextremeeventsimulatedwithinastormimpactmodelknownasXBeach[36].Thecombinationsselectedhavethewidestrangeinbothwaterlevelandwaveheightacrossthetworeturnperiodsforwaterlevels aboveMeanHighWater Springs (MHWS). Any combinationswith awater level belowMHWS (10.69 mCD) were removed. Combinations below MHWS while having the sameprobabilityofoccurrencewillhaveaminorimpactonthecoastduetothelowwaterlevelsandhighwaveheights,resultinginwavesbreakingonthelowerbeachratherthanthedefences.

Figure15:Closeupofjointprobabilitycurvesshowingthe8combinationsselectedforsimulation.Thegreenlineshows1in10yearvaluesandtheredrepresents1in200yearevents.

ThemodelusedtosimulatetheimpactofextremeeventsisXBeach.XBeachisatwo‐dimensionalmodelforwavepropagation,longwavesandmeanflow,sedimenttransportandmorphologicalchanges of the nearshore area, beaches, dunes and back‐barrier during storms. XBeachconcurrentlysolvesthetime‐dependantshortwaveactionbalance,therollerenergyequations,

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thenonlinearshallowwaterequationsofmassandmomentum,sedimenttransformationsandbedupdateon thescaleofwavegroups. It canalsocalculate theovertoppingof seadefencesduringextremeevents.Figure16showsanexample2DHsimulationthatshowstheimpactofHurricaneSandyontheNorthAmericancoastline.Aswellrunningin2DHthereisa1DHversionwhereasinglebeachprofileperpendiculartotheshorelineisusedtoreducethecomputationcostandallowmultiplesimulationsinashorttimeframe(Figure17).

Figure16:Exampleofa2DHXBeachsimulation.

Source:KeesNederhoff:https://www.youtube.com/watch?v=qw7kvt‐aBdU

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Figure17:Exampleoutputof1DHXBeachsimulationforaprofileinStAubin’sBay,topgraphshowsbeachprofilewithsimulatedextremeeventconsistingofsurgeandwaves.Thebottomgraphshowsthevolumeofwaterthatovertoppedthedefencesthroughoutthesimulation.Asthemodelconsistsofa1Dprofile,cross‐shoremodelwithdimensionsintheverticalandcross‐shore.Whiledischargeistypicallym3/swhenthereisnoalongshoredimension(m2/s)isoftenused,adischargeperlinearmeterandthealongshorevariabilityisassumedtobeuniform.

Forthisstudythemodelwasusedin1DHmodeduetothetimelimitationsoftheprojectandtheassociated computational cost. Four 1DH profiles were selected from east to west across StAubin’sBay.Eachoneterminatingontheshoreatapointofhistoricalfloodingorvulnerability.Profile1atLaHauleslipway,Profile2atGunsite,number3atFirstTowerandnumber4atWestPark.Figure18showsthelocationandextentoftheseprofiles.

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Figure18:Beachprofilesusedin1DXBeachsimulations

BathymetrydatacollectedduringasurveyundertakenbyGeoSurvin2012wasprovidedbytheDepartmentofInfrastructure.Thiswasusedtogeneratethelandelevationsofthemajorityofthebeachprofile(lowerandmiddlebeach)withtheupperbeachgapsbeingfilledbydatacollectedduring a site visit by NOC. Figures 19 and 20 show the location of the Department ofInfrastructure’sdataandourowndatarespectively.Thisdatawascombinedtogethertoproduce1DbeachprofilesandtheresultingprofilesareshowninFigure21.Eachoftheseprofilesarethenusedasthemodeldomainforeachofthestormimpactscenarios.

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Figure19:BathymetrydatacollectedonbehalfofDepartmentofInfrastructurebyGeoSurvin2012.

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Figure20:GPSsurveytrackfollowedbysurveyvehicleduringNOCandJerseyMetOfficesurvey

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Figure21:Beachprofilesusedasaninputforextremeeventsimulations,profilesincludeheightofanyparapetspresent

Once the beach profiles had been selected, parameters that match the extreme event beingconsideredareassignedtothemodelsimulation.Thisrequiresdetailsofthewavesandwaterlevelduringtheextremeevent.Whilethejointprobabilityanalysisprovidesasignificantwaveheight and water level, other parameters such as peak period and wave direction are alsorequired.Usingwavebuoydata,significantwaveheight,peakperiodandwavedirectioncanallbe plotted against each other. This allows the selection of suitablewave directions and peakperiodsthatcouldoccurtogetherforagivensignificantwaveheight.Histogramshavealsobeenusedtoidentifythemostcommonandextremepeakperiodsfordifferentrangesofsignificantwave height. For each significant wave height, the most common and extreme values aresimulatedtorepresentthepotentialrangeofpeakperiods(Figure22).Duetotheshortdatasetsthatcontainedpeakperioddata,values0.1meithersideoftheselectedHsvalues(Figure15)wereused ingeneratingahistogramofpeakperiod.AsshowninFigure22, forallsignificantwaveheightsbetween0.9mand1.1m.Itcanbeseenthatthemostcommonperiodwas10.3sandthemostextremewas19.7sTheseweretheonesusedforsignificantwaveheightsof1m.Thiswasrepeatedforallthedifferentwaveheightssimulated.

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Figure22:HistogramforallHsvaluesbetween0.9mand1.1mforthewavebuoybetween2011and2012.

Forwavedirection,iftherangeindirectionsloggedbythebuoyforthesignificantwaveheightbeingconsideredwassmall,e.g.between250⁰and270⁰,thenthemiddlewavedirectionintherangewasused i.e.260⁰.Waveswithheightsof3mormorewere found tohave thesesmallranges in wave direction. Waves below 3 m had a much larger range in wave direction, sominimum,middleandmaximumvalueswereusedtoassesstheimpactofwavedirection.ThesevaluescoveredarangeinwavedirectionthatcouldimpactonthecoastlineinStAubin’sBay.Thisresultedinthreedifferentdirectionsbeingsimulatedfor1and2mwaves.Figure23showstherelationshipofsignificantwaveheightandwavedirectionthatdemonstratestheincreaseintherangeofsuitabledirectionsfordecreasingsignificantwaveheights.Itshouldbenotedthattheconfidenceinthewavedirectiondatafromthebuoyislow.Asthewavemonitoringequipmentismountedtoanavigationbuoyratherthanapurpose‐builtbuoy.Thefulllistofparametersusedineachscenariosimulatedisavailableasaspreadsheetprovidedalongsidethisreport.

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Figure23:Wavedirectionagainstsignificantwaveheightatwavebuoy

Oncethewaveparametershavebeenselected,anunderlyingstormsurgeneedstobecreated.Thisisatimevaryingwaterlevelthatpeaksatthedesiredextremewaterlevelfromthejointprobabilityanalysis.Italsoneedstobeagoodrepresentationofastormsurgeforthelocation.Toproducethisrepresentation,ahistoricalstormsurgewasusedasthebasisofthecurve.Thestorm surge that occurred on the 10th March 2008 was converted into a representativenormalisedcurvewithvaluesofzerocorrespondingtonosurgeand1forthepeakofthesurge.Thisrepresentativecurvecanthenbecombinedwithanextremewaterlevelvalue,andaddedtoanunderlyingMHWSpredictedtidalcurve.Thisresultsinastormtidecurvethatpeaksatthedesiredwaterlevelandisrepresentativeoftheregion(Figure24).

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Figure24:Diagramshowingexampleofproducingstormtide,solidbluelineisapredictedMHWScurveforJersey,greendottedlineistherepresentativesurgecurve,andreddashedlineistheoutputstormtideforinclusioninXBeachsimulations.

Thistimevaryingextremewaterlevelcurvecanthenbeusedalongwiththewaveparametersasinputs tosimulateanextremeeventacrosseachof the fourbeachprofiles.Thestorm impactmodelisabletoprovidemanydifferentparametersasoutputbuttheonesconsideredforthisreport are the total volumeovertoppedduring the event and thepositive, negative and totalchangeinthevolumeofsedimentonthebeach.Thepositiveandnegativevaluesindicatehowmuch sediment has eroded or accreted across the beach profile while the total will show ifsedimentislostorgainedacrossthewholeprofile.

14.1 Beach morphology: response to present day extreme events

Figure25showsanexampleofboththestartingbeachprofileandthesimulatedbeachprofileaftera1in200yearextremeevent.Itcanbeseeninthisscenariothattherehasbeenaccretionofsanddirectlyatthebaseofthetoeofthedefencesanderosionofthebeachslightlyfurtheroffshoreinfrontofthedefences.

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Figure25:Exampleofchangestobeachmorphologyduetoanextremeeventofa1in200RPwithanWLof6.45m,Hsof2mandaDirof270withaTpof19.7s.

TheresultsofeachofthedifferentscenariossimulatedareshowninFigure26wheretheamountofsedimentthathasaccretedalongeachbeachprofileisplottedagainstsignificantwaveheight.Thisisrepeatedwithsedimentthathaserodedalongtheprofile.FinallyFigure27showsthetotalchangealongeachprofileshowingifanysedimenthasbeenlostorgainedoverall.

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Figure26:Positive(reddots)andnegative(bluedots)sedimentchangeacrossthewholeprofilesagainstsignificantwaveheightusedintheextremeevents.

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Figure27:Totalsedimentchangeforeveryscenarioshowingsedimentlostorgainedfrombeachprofile.

Figure26 shows that as the significantwaveheight increases, both thepositive andnegativechangeinsedimentincreases.Thisisduetothegreaterwaveenergyfromlargersignificantwaveheightsbeingabletomovemoresediment.Thisisthenabletomobiliseandmovesedimentalongtheprofile.Alevellingoftheamountofchangeisevidentfromaround5msignificantwaveheightsuggestingthatheightsabovethisthresholddonotsignificantlyincreasetheamountofsedimentbeing mobilised. Figure 27 shows that the absolute change over the whole profile does notincreasewithincreasingsignificantwaveheight.Ittendstobearoundzeroformostwaveheightsandprofiles.However,itreachesamaximumlossat2mofsignificantwaveheightwithtotallossof2.5m3ofsedimentpermetreacrossthebeach.Amaximumgainisalsoevidentat6.4mwaveheightwherearound1.5m3ofsedimentisgainedforeverymetreacrossthebeach.Thefigurealsoshowsthatprofile1ismoresensitivetosedimentlossandgain.Theotherprofileshavelittleoverallchangewithprofile4exhibitingsomesmalllossesof1m3.Generally,itcanbeseenthathigherwaveheightsresultinthegreatestsedimentmovementalongtheprofile,butitisthe2mwaveswithlongerwaveperiodsthatresultinthegreatestremovalofsediment fromprofile 1 although themagnitude of the loss is small and for only oneprofile.Therefore, itcanbeseenthatwhile largesignificantwaveheightsresult in largererosionandaccretionalongthebeachprofile,itdoesnottranslateintosedimentbeinglostorgainedfromthe

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beachitself.ThereisalsosomeuncertaintyregardingthepresenceoftheselargesignificantwaveheightsduetotheassumptionthatwavesatthewavebuoywillbethesameatthemouthofStAubin’s Bay. Without a wave transform model, it cannot be assessed whether these arerepresentative.Forthelargestsedimentchangescenario,thestartingprofile,endprofileaftertheextremeeventandpointsofmaxandminsedimentchangeareallshowninFigure28andFigure29.Figure28showsthewholeprofilewiththepointsofmaxandminsedimentchangemarkedandFigure29shows a close up of the two pointswith the addition of the end profile showing the changebetweenthetwo.OverallitwasfoundthattheimpactofSLRandclimaticchanges(i.e.sensitivitytowavedirection)onStAubin’sBaybeachprofilearenegligible.

Figure28:Profiletwoshowinglocationsofmaxandminsedimentchangeforgreatestsedimentchange(Scenario10).

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Figure29:Closeupofprofile2showinglocationsofmaxandminsedimentchange,boththestartingprofile(blue)andtheendprofile(dashedred)areshown.

AsFigure28showsthegreatestoverallchangescenarioacrossallprofiles,theimpactofextremeeventsonbeachmorphologyover thecourseof theextremeeventsbeingsimulated isminor.However,itshouldbenotedthatthesedimentparametersusedinthesimulationhavenotbeenvalidatedsowouldbenefitfrombeachsurveystocalculatethesanddistributiononthebeach.

14.2 Overtopping of defences: vulnerability of defences to overtopping during

present day extreme events and future storm surges

The total volume of water that overtops the defences during each extreme event has beencalculatedforeachscenario.Eachscenariowassimulated5timeswiththetotalvolumeforeachbeingaveragedtoprovideameantotalvolumevalue.Thiswasrequiredtotakeintoaccountthevariations inwave spectrums that are generated from the inputwave parameters. Figure 30showstheresultsforaselectionofscenariosforeachprofile.Table15showsthelistofscenariosthat have been selected. (For full list and results please see associated spreadsheet) For thescenariosthathadarangeofwavedirectionsbeingsimulated,thedirectionthatresultedinthegreatestvolumewasused.Itwasnotedthatthevariationinwavedirectiondidnotresultinmuch

55

variationinmeantotalvolumes.Forthesimulationsitwasalsoassumedthatthewaveheightwouldbethesameacrossthebay.

Figure30:Meantotalovertoppingvolumeforeachprofileforaselectionofscenariossimulated.

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Table15:ListofparametersusedforeachoftheselectedscenariosdisplayedinFigure31.

Profile ReturnPeriod(yr)

WL(m) Hs(m) Dir(⁰) Tp(s) AverageTotalVolume(m3)

Standarddeviation

%STtoMean

1 10 5.00 4.79 260 13.30 150.3 21.3 14.21 10 5.90 3.50 260 11.80 198.0 37.1 18.81 10 6.30 2.00 235 19.70 960.5 129.5 13.51 10 6.38 1.00 270 33.00 529.6 57.5 10.91 200 5.00 6.37 260 9.20 10.7 4.5 41.91 200 6.00 5.30 260 11.80 782.5 129.0 16.51 200 6.45 2.00 235 19.70 1203.1 58.4 4.91 200 6.48 1.00 270 33.00 645.2 40.6 6.32 10 5.00 4.79 260 13.30 193.6 46.9 24.32 10 5.90 3.50 260 11.80 652.5 51.7 7.92 10 6.30 2.00 200 19.70 1086.0 189.4 17.42 10 6.38 1.00 195 33.00 343.3 73.8 21.52 200 5.00 6.37 260 9.20 13.5 4.3 32.32 200 6.00 5.30 260 11.80 1470.7 130.7 8.92 200 6.45 2.00 270 19.70 1204.4 82.1 6.82 200 6.48 1.00 120 33.00 379.6 52.4 13.83 10 5.00 4.79 260 13.30 42.1 21.9 51.93 10 5.90 3.50 260 11.80 221.7 32.9 14.93 10 6.30 2.00 200 19.70 584.8 75.7 12.93 10 6.38 1.00 195 33.00 231.8 42.9 18.53 200 5.00 6.37 260 9.20 5.0 9.6 189.73 200 6.00 5.30 260 11.80 458.5 97.9 21.43 200 6.45 2.00 200 19.70 749.2 115.7 15.43 200 6.48 1.00 120 33.00 268.2 37.8 14.14 10 5.00 4.79 260 13.30 60.5 29.7 49.24 10 5.90 3.50 260 11.80 221.2 21.1 9.54 10 6.30 2.00 270 19.70 613.6 93.0 15.24 10 6.38 1.00 120 33.00 227.7 13.9 6.14 200 5.00 6.37 260 9.20 4.6 6.4 139.54 200 6.00 5.30 260 11.80 442.4 82.0 18.54 200 6.45 2.00 200 19.70 758.6 165.3 21.84 200 6.48 1.00 270 33.00 259.7 78.1 30.1

The peak period used in each scenario has been plotted against mean total volume for thatscenariotoshowtheimpactofwaveperiodontheamountofwaterovertoppingthedefences(Figure31).Itcanbeseenthatthereisamaximuminthevolumeofwaterovertoppedatpeakperiodsofaround12seconds.Thiscorrespondstothescenariothathasa6mWLand5.3msignificantwaveheight.Peakperiodsofaround20secondsalsocontributea largeamountof

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volume.Thesescenariosaretheresultofa6.45mextremewaterleveland2msignificantwaves.Whilethereissomedoubtoverthe5.3mwavesbeingrepresentativeattheentrancetoStAubin’sBay,aquestionawavetransformationmodelcouldanswer.The2mwavesincontrasthavenosuchdoubtsaboutthem.Itcanalsobeseenthatthereisathresholdinovertoppingvolumeataround12secondswherepeakperiodsbelowthisresultinlittleovertoppingandabovethislargevolumescanbeexpected.Thisshowsthatthecoastlineismorevulnerabletowaveswithlongperiodsthatarealsoknownasswellwaves.

Figure31:Peakperiodwhencomparedwithtotalvolumeofovertoppedwater

Aspreviouslymentioned,eachscenariothatwassimulatedwasrun5timesandaveragedtogiveameanresult.Thiswastotakeinaccountdifferencesinthewavespectrumsgeneratedbytheinputwaveparameters.Inadditiontothemean,thestandarddeviationacrossthe5runswascalculatedanditspercentagesizewhencomparedwiththemeantotalvolumevaluewasplottedagainstmeantotalvolume.Thisshowshowrepresentativethemeanovertoppedvolumeisoftheextremeevent.Figure32showsthisrelationshipandhighlightsthatsmallovertoppedvolumesareveryvariableacrossthe5runsandthushavestandarddeviationsexceedingthemeanvolumei.e. the percentage size is greater than 100%, whereas for greater overtopped volumes this

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quicklydecreasestobelow20%meaninglowvariationinthevolumeofwaterovertoppingthedefencesacrossthe5runsmakingthemeanvaluerepresentativeoftheextremeevent.

Figure32:Meantotalvolumeforaselectedscenarioagainstthepercentagesizeofthestandarddeviationagainstthemeantotalvolume.

14.3 Increase in impact of extreme water levels with projected sea‐level rise

A1in200‐yearextremestillwaterlevelevent(valuetakenfromresultsinsection8)hasbeensimulatedwithincreasingamountsofSLR.Fromthepresentdayat0minintervalsof0.1mtothehighestprojectedplausiblevalueof1.8m.Thiswillgiveanindicationofthevulnerabilityofthecurrentdefencestoincreasingmeansealevels.Thestormimpactmodelwasagainusedbutwithnowaveparametersdefined, justthesamestormsurgecurvewithallwaterlevelvaluesincreasedbytheSLRparameterofagivensimulation.Table16showsthedifferentovertoppingvolumesthatwerearesultofincreasingmeansea‐levelsforeachprofile.ThisisalsodisplayedinFigure33.

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Table16:Listofeveryscenariosimulatedforextremewater leveleventandincreasingmeansea‐levels

Profile ReturnPeriod

EWL(m) Sea‐levelrise(m) Totalvolumeofwaterovertopped(m3)

1 200 6.48 0.0 0.0

1 200 6.48 0.1 0.0

1 200 6.48 0.2 0.0

1 200 6.48 0.3 0.0

1 200 6.48 0.4 0.0

1 200 6.48 0.5 0.0

1 200 6.48 0.6 21.1

1 200 6.48 0.7 146.8

1 200 6.48 0.8 387.9

1 200 6.48 0.9 774.0

1 200 6.48 1.0 1304.0

1 200 6.48 1.1 1964.6

1 200 6.48 1.2 2744.1

1 200 6.48 1.3 3643.6

1 200 6.48 1.4 4685.1

1 200 6.48 1.5 5862.7

1 200 6.48 1.6 7205.3

1 200 6.48 1.7 8729.8

1 200 6.48 1.8 10400.7

2 200 6.48 0.0 0.0

2 200 6.48 0.1 0.0

2 200 6.48 0.2 0.0

2 200 6.48 0.3 0.0

2 200 6.48 0.4 0.0

2 200 6.48 0.5 0.0

2 200 6.48 0.6 0.0

2 200 6.48 0.7 0.0

2 200 6.48 0.8 0.0

2 200 6.48 0.9 0.0

2 200 6.48 1.0 0.0

2 200 6.48 1.1 0.0

2 200 6.48 1.2 0.0

2 200 6.48 1.3 3.3

2 200 6.48 1.4 83.4

2 200 6.48 1.5 294.0

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2 200 6.48 1.6 653.5

2 200 6.48 1.7 1168.8

2 200 6.48 1.8 1837.9

3 200 6.48 0.0 0.0

3 200 6.48 0.1 0.0

3 200 6.48 0.2 0.0

3 200 6.48 0.3 0.0

3 200 6.48 0.4 0.0

3 200 6.48 0.5 0.0

3 200 6.48 0.6 0.0

3 200 6.48 0.7 0.0

3 200 6.48 0.8 0.0

3 200 6.48 0.9 0.0

3 200 6.48 1.0 0.0

3 200 6.48 1.1 0.0

3 200 6.48 1.2 0.0

3 200 6.48 1.3 0.0

3 200 6.48 1.4 0.0

3 200 6.48 1.5 0.0

3 200 6.48 1.6 0.0

3 200 6.48 1.7 0.0

3 200 6.48 1.8 0.0

4 200 6.48 0.0 0.0

4 200 6.48 0.1 0.0

4 200 6.48 0.2 0.0

4 200 6.48 0.3 0.0

4 200 6.48 0.4 0.0

4 200 6.48 0.5 0.0

4 200 6.48 0.6 0.0

4 200 6.48 0.7 0.0

4 200 6.48 0.8 0.0

4 200 6.48 0.9 0.0

4 200 6.48 1.0 0.0

4 200 6.48 1.1 0.0

4 200 6.48 1.2 0.0

4 200 6.48 1.3 0.0

4 200 6.48 1.4 0.0

4 200 6.48 1.5 0.0

4 200 6.48 1.6 0.0

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4 200 6.48 1.7 0.0

4 200 6.48 1.8 0.0

Figure33:Impactofincreasingmeansea‐levelsontotalvolumeovertoppedfora1in200‐yearextremewaterlevelevent.

Figure33showsthatprofile1isbyfarthemostvulnerabletosea‐levelrise,buteventhisprofileisabletowithstandsea‐levelrisesofover0.5mbeforeanyoverwashingoccurs.Profile2isalittlemoreresilientrequiringSLRover1.2mbeforeoverwashingandfinallybothprofile3and4bothhavenooverwashingevenatthemaximumSLRvalueof1.8m.However,itshouldbemadeclearthatthesesimulationshavebeenundertakenwithnowavesandconsistofjustsurgeandtidesoanywavesthatwouldbepresentduringtheseextremeeventswouldhaveafargreaterimpactandwouldreducethethresholdforwaterovertoppingdefencesandincreasethevulnerabilityofthecoastline.

14.4 Increase in overtopping of defences during extreme events due to projected

SLR

Duetothecomputationalcost,onlyoneextremeeventforoneprofilewasselectedtosimulatetheimpactofincreasingmeansea‐levels.The1in10‐yearjointprobabilityeventwiththelowest

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variation (i.e. lowest % standard deviation to mean) was selected from the Profile 2 jointprobabilityresultsandrunwithincreasingsealevelsinintervalsof0.1mfrom0mto1.8m,Table17showsdetailsofthescenariosselected.Figure34showstheresultsofthese19simulations,asexpectedthevolumethatovertopsthedefencesincreasessignificantlywithincreasingmeansealevelrise.Italsoshowsthatwavesgreatlyincreasethevulnerabilitywhencomparedwithstormsurgesalone.

Table17:Detailsofthescenariosimulatedwith19differentSLRparametersfrom0mto1.8mincludingtotalvolumeofwaterovertoppingdefences


WL(m) Hs(m) Dir(⁰) Tp(s) SLR(m) TotalVol(m3)

2 10 5.9 3.5 260 11.8 0 7562 10 5.9 3.5 260 11.8 0.1 9642 10 5.9 3.5 260 11.8 0.2 10502 10 5.9 3.5 260 11.8 0.3 12652 10 5.9 3.5 260 11.8 0.4 14192 10 5.9 3.5 260 11.8 0.5 15752 10 5.9 3.5 260 11.8 0.6 15832 10 5.9 3.5 260 11.8 0.7 19712 10 5.9 3.5 260 11.8 0.8 25502 10 5.9 3.5 260 11.8 0.9 28412 10 5.9 3.5 260 11.8 1.0 29442 10 5.9 3.5 260 11.8 1.1 32262 10 5.9 3.5 260 11.8 1.2 30632 10 5.9 3.5 260 11.8 1.3 41662 10 5.9 3.5 260 11.8 1.4 48402 10 5.9 3.5 260 11.8 1.5 46702 10 5.9 3.5 260 11.8 1.6 54512 10 5.9 3.5 260 11.8 1.7 59792 10 5.9 3.5 260 11.8 1.8 5967Dueto thedifferentextremeeventsbeingsimulatedwithSLR, i.e.a1 in200‐yearwater leveleventanda1in10‐yearjointprobabilityevent.Thewaterlevelwith1.8mofSLRinthejointprobabilityeventisroughlyequaltoanSLRof1.2mfor1in200‐yearextremewaterlevelevent.Thisisduetoadifferenceinthewaterlevelof0.58m(6.48m–5.90m).Fortheextremewaterlevelevent,at1.2mofSLRthis is justunderthethresholdof floodingwhereaswith the jointprobabilityeventresultsinavolumeof6000m3waterovertoppingthedefences.Thismeansthatthecombinationofsurge,waterlevelandwavesleadtothemostsignificantimpactoncoastaldefences,leadingtoovertoppingandinundation.TheincreaseinovertoppedvolumeandSLRislargelylinear,withtotalvolumeincreasingbyaround3000m3forevery1m(300m3per0.1mSLR)increaseinSLR.

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Figure34:Relationshipbetweensea‐levelriseandtotalvolumeovertoppingdefencesforscenariooutlinedinTable17

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15 Key Findings Thisstudyhasestablishedsea levelrise(SLR)asan increasingenvironmentalhazardforTheStatesofJersey.Thestudyhasinvolvedacomprehensivereviewofavailableinformation,andhasuseduptodatemethodsandoutputsfromthescientificresearchcommunitytoestablishbaselineSLR projections, and probabilities of occurrence of extreme events (defined as water levelresultingfromhightideandsurge,combinedwithwaves).ThestudyfocusedonStAubin’sBayas a specific case study location, which involved gathering field data to enablemodelling ofextremeeventscenariosandanassessmentofseadefenceovertopping.Anumberofstakeholdershavehad input into thestudywhichhasendeavouredtosourceallrelevant local data as input. Data from the local GPS station (used to refine landmovementestimates)wasnotavailableintimetocombineintothisstudy,howeverthestudyhasestablishedthatlandmovementisaverysmall(negligible)factorintheoverallprojectedSLRchangesforJersey.Thekeyfindingsfromthestudyarethat:

1. The impact of future storm eventswill be influenced by sea‐level rise (SLR). SLRprojectionsvarydependingontheemissionsscenariobeingconsidered,andontherateofchangeofthephysicalprocessesthatinfluencesealevels.Globalandregionalprojectionsarenon‐uniformduetovariationsintooceandynamicprocesses,changesin gravitational fields from icemass loss, and air‐sea heat and freshwater fluxes.There are differences between the global projections and the regional projectionsinvestigated for this study, therefore it is important tocontinue to investigateandmonitorthesechangesonalocal/regionalbasis

2. The seas around Jersey are rising and the trend indicates an accelerating rate ofincrease. From 1900 to 1960 the rate of increase was c. 1 mm/year, from 1960onwards this increased to approximately2mm/yr.Theprojections suggest that asuitablebaselinefigureforfutureratesofincreaseis3mm/year.

3. Vertical land movement is taken into account when assessing SLR. Regionalassessmentshowsthat themagnitudeof landmovement for Jersey,relative tosealevelriseisnegligible(currentlyestimatedasmaximumof7.5cmupto2100).Thedatasourcedfromaroundtheregionshowsthattimespanfordataisimportantwithlongerspansshowing lowerrates.Thebiggerchangesaregenerally related to thesmallesttimespans.Thissuggeststhatideally15yearsofdataisrequiredtoestablisharobustrateofverticallandmovement.

4. Usingthemeanemissionsscenarioforclimatechange(basedonachievingthetargetsidentifiedinthe2016ParisAgreement)andusingthemostlikelyoutcomefromthatscenario, Jersey isprojectedtoexperienceanSLRof0.48mby2100.Onthesamebasis,thelowprobability,highimpactscenario(basedon‘businessasusual’i.e.nocurbingofemissions)isprojectedtoresultin0.77mofSLRby2100.Witha1in20

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chance(95thpercentile)ofa1.8mSLRbeingrealised.ThelowestpossibleSLRrangebasedonaggressivecurbingofemissionsisbetween0.28mand0.6mby2100.Thesevaluesareallrelativetosealevelsin2010.Fornearertermestimatesthestudyhasestablishedbaselinefiguresofbetween10cm(bestcase)and20cm(worstcase)ofSLRby2030,andbetween20cm(bestcase)and40cm(worstcase)for2050.

5. Jointprobabilityanalysishasbeencompletedforcombinedextremewaterlevelsandwaves.Theresultsareausefulguide for futurestudiesandpolicyandareamuchgreaterimprovementoverpreviousworkbyHRWallingfordastheassumptionmadethat largewavesoccur at the largest extremewater levels is bothpessimistic andunrealistic.

6. Forthispartoftheworld,wavesarenotprojectedtohaveanysignificantchangeinsignificantwaveheight, althoughhindcastdatadoes showa small linear increase.However,thegreaterimpactwillbefromincreasingmeansealevels.Thecombinationofexistingwaveconditionswithincreasingsealevelswillresultinahigherfrequencyofextremeevents.Underamediansealevelriseprojection(0.48mby2100)a1in150yeareventwilloccuronanannualbasis

7. Thecombinationofincreasedsealevelsandwaves(modelledusingthecurrentwaveclimate)willresultinsignificantlygreaterovertoppingofdefences.Allwaveheightsresultinsomeovertoppingofdefences,withthelargestovertoppingamountsrelatedto the scenarios with the longest periods. Wave direction has little impact. Peakovertoppingvolumeoccursatasignificantwaveheightof2mwithapeakperiodof19.7s.

8. Forprofile2,whichisvulnerabletocombinedextremewaterandsignificantwaveheightevents,every0.1mofSLRwillleadtoapproximately300m3ofextrawaterpermetre overtopped during an extreme event. This work has shown that it is thecombinationofwaves,surgeandSLRthatwillimpactthecoastthemostasforprofile2thehighestSLRparameterduringthejoint1in10‐yeareventwasequalto1.2mofSLRfortheextremewateronlyevent.Thiswasjustbelowthethresholdofflooding,theadditionofwavestothemodelmeantthatthedefenceswentfrombeingresilientandabletoresisttheextremeevent,tobeingovertoppedby6000m3ofwaterpermetreofdefences.Beingabletoassessthelikelihoodofagivenwaveheighthavingaspecificperiodwouldbeusefulinassessingthevulnerabilityofthecoast.

9. ThecasestudyworkhasshownthatforStAubin’sBaytheareatotheWestismostatriskfrominitialfutureriseinsea‐level.Comparingthebeforeandafterprofiles,showsthat for the simulated extreme events there is no significant impact on beachmorphology.Itwouldbebeneficialtouseamodeltosimulatetheimpactoflongtermwaveclimateandassesstheimpactonthebeachmorphologyratherthantheimpactofextremeeventsonly.

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10. SLRwillimpacttidalrange.ThestudyhasinvestigatedtheimpactarisingfromhighvaluesofSLRandhasshownthatthechangeintidalrangefora2mincreaseinmeansea‐levelisestimatedtoresultinareductionofthetidalrangeof0.49mforspringand0.24mforneaptides.ThiswillreducetheimpactoffloodingbyathirdunderhighimpactlowprobabilitySLRscenarios,providingatangiblebenefitinthefuture.

16 Recommendations

Thisstudyhasestablishedthedataavailableforsealevelstudies,andcompletedmodellingfortheselectedcasestudyarea,producingbaselineoutputdatathatclearlyshowssealevelriseasanincreasinghazardforjersey.Therecommendationsarefocusedonthreetopicareas:

ProgressingandrefiningtheSLRmodellingtogivegreaterspatialcoverageandextendtheoutputstoincludeeconomicimpactandrisks

Workingincollaborationwithotherdepartmentsandstakeholderstobuildacohesiveunderstandingandresponsetothebaselineinformationproduced.

Toputinplacenowastrategyforin‐situandremotemonitoringofspecificenvironmentalparametersthatwillreduceuncertaintiesinmodellingworkandformthebasisofalong‐time serieswhichwill providehighly valuable insights and enablemoreeffective riskmanagementovertime.

ProgressingSLRmodellingThereisclearvalueinprogressingthisworkfurthertoassesstheimpactoncoastalinfrastructureandcommunitiesthroughinundationmodelling.Inundationmodellingwillshowwhattheimpactofagiventotalvolumeofwaterdischargingoverthedefenceswouldbe.Ourrecommendationisthatthe1DXBeachmodellingisexpandedintoa2Dstormimpactmodel,thiswouldprovideamoredetailedanalysisoftheabilityofseadefencestowithstandextremeeventsacrossthewholebayorislandratherthanatfourpointsacrossStAubin’sBay.This2Dmodelwouldthenbeusedto‘drive’theinundationmodel.Theinundationmodellingshouldbefocusedinitiallyonspecificvulnerablelocationsandshouldbecarriedoutwithinputfromtheinfrastructureandplanningdepartments.The impact of inundation is clearly heavily influenced by hydrological factors thereforeopportunities to carry out combined modelling or co‐analysis of results is stronglyrecommended. Amodel showing the impact of extreme rainfall events on the island, can beachievedusingasurfacefloodmodel.AschangesinthebeachprofilewerefoundtobeminimalduringthesimulatedextremeeventsitwouldbeworthwhiletoassessthelongtermcumulativeimpactofeventsonthebeachesandcoastlineofJersey.Theassessmentcantaketheformofmodelsorobservations.Insummary:

Developmodelfrom1Dto2D

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Carryoutinundationmodelling,combinewithhydrologicalmodel Useoutputtoquantifyimpact/identifyrisks,includingcumulativeimpactsoncoastline

WorkingincollaborationCoastalchangehaspotentialimpacton,andthereforeinterestfromawiderangeofstakeholders.Asthisstudy,hasshownthereareseveraldepartmentsandorganisationswithinTheStatesofJerseywhoholddata,modelsorotherinformationrelevanttothiswork.Tomaximisethevalueofthisandanyfurtherworkwestronglyrecommendthatacrossdepartment/multidisciplinary‘steering group’ is established who can comment on and shape future efforts, ensure crosscompatibilityofanymodelling(asfaraspracticable)andactonresultsandrecommendations,aswellasreducetheriskofduplicationofeffort.In‐situandremotemonitoringofspecificenvironmentalparametersAllworkonsealevelscienceisbuiltonobservationaldata,themostpowerfulofwhicharethehighqualitylongtimeseriesrecords,suchasthoseheldathttp://www.psmsl.org/hostedbytheNOC.Thesedatacombinedwithsatelliteobservations,landmovementmeasurementsandahostofothersourcesenablethesciencethathelpstomanagerisksfromSLR.Jerseyhaveahighqualitytidalrecord,aGPSstationandanoffshorewavebuoyalreadyinplace,howeverthereisanopportunitytoaugmentthesemeasurementsusingothersources,andalsopotentiallytolinkintootherexistingmarineobservationsystemstoenhancemanagementofthecoastal environment. Further work is needed to establish options and costs, however as anexample,newcoastalobservationaltechniquesdevelopedattheNationalOceanographyCentreuseXBand radar tomonitor critical ordynamic coastal zones, thekeybenefit being that thisinfrastructureisubiquitousinthemarineenvironment.Thealgorithmsuseradarcluttertoderiveinter‐ tidal bathymetry, surface currents and wave climate. This technique could be used tomonitorbeachesandbuildaspatiallyandtemporallyrobustdatasetofcriticalcoastalareas.Inmany cases in‐situdata canbeused tovalidatemodels and longer time serieswill over timereduceuncertaintiesconsiderably.Werecommendthereforecarryingoutanassessmentofoptionsandcostsforincreasingmarineobservationalmonitoring around Jersey. This should be considered in collaborationwith theJersey Met Office, coastguard and harbour authorities, and take into account wider regionaleffortssuchasthosebeingcarriedoutbyIFREMERinBrittany.

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18 Appendix: Position Datum’s

18.1 Jersey Transverse Mercator and local ordnance datum

GeoSurvLimitedundertookageophysicalsurveywithinthebaysofStAubinandGreveD’Azete,Jerseyin2012.VariousdatasetswerecollectedincludingbathymetrywithinStAubinbay.Thiswas used to produce beach profiles that were used as part of the extreme event modellingundertakenbythisreport.NationalOceanographyCentrewiththehelpoftheJerseyMetOfficealsoundertooksomesurveyworkinNovember2016thatcoveredthetopofthebeachlinkingnicelywiththesurveydatafromGeoSurv.Thissectiondetailstheverticalandpositionaldatum’sused.GeoSurvwasaskedtoprovidethesurveydatainJerseyTransverseMercator(JTM)andNOChascopied thisprocess.Theparametersused toproject thedata fromWGS84datum to JTMwasprovidedtobothGeoSurvandNOCinthedocument;PositionTransformationDateSurveyReportontheJerseyNetworkandtheJerseyTransverseMercatorGrid.ThepositiondatumusedbybothGeoSurvandNOCwasWGS84.DetailsofWGS84areprovidedbelow:

Table18:ParametersofWGS84

Parameter Definition

Ellipsoid WGS84Datum WGS84Semimajoraxis 6378137.00

metresSemiminoraxis 6356752.314

metresFlattening 298.257223563EccentricitySquared(e2)

0.00669437999

JTMparametersusedtocomputeandcollatethesurveyoperations,position,dataacquisition,dataprocessingandallsubsequentcalculationsarepresentedinTable19:

Table19:ParametersofJTMProjection

Parameter Definition

Projection JerseyTransverseMercatorLatitudeoforigin 49.225⁰Longitude of central meridian(CM)

‐2.135⁰

Falseeastingoforigin(metres) 40000.000Falsenorthingoforigin(metres 70000.000

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Parameter DefinitionScalefactoratcentralmeridian 0.9999999

TheverticaldatumusedbyboththesurveyvesselsusedbyGeoSurfandthevehicleusedbyNOCwereobtainedrelativetotheWGS84referenceellipsoidandweresubsequentlyreducedtoChartDatum(GeoSurv)andlocalOrdnanceDatum(NOC).TherelationshipsbetweenEllipsoidDatum,OrdnanceDatum(local)andChartDatumprovidedbyGeoSurvaregiveninFigureA1.

FigureA1:EllipsoidDatum,OrdnanceDatum (local) andChartDatum relationship forJersey,offsetsprovidedbyGeoSurvsurveyin2012.

TherelevantoffsetswereappliedtothesurveydatacollectedbyNOCandwerefoundbeingoodagreementwiththesurveydatacollectedbyGeoSurvin2012.

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19 Appendix 2: Data Sources TypeofData Source

WaveParameters JerseyWaveBuoy(1996–2012)NOC(NationalOceanographyCentre)EuropeanShelfModel

SeaLevel StHelierTideGauge:https://www.ntslf.org/(1992–2015)

(Wave)Hindcast SONEL:http://www.sonel.org/(1900–2012)

VerticalLandMovement SONEL:http://www.sonel.org/(2001orlater‐2016)

SeaLevelTrends PSMSL:http://www.psmsl.org/SONEL:http://www.sonel.org/(1900–2016)

SeaLevelProjections NOC(NationalOceanographyCentre):(2010–2100)

GPSBeachSurveyData November2016fieldvisit

Bathymetry GeoSurv:Surveyed2012

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