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Abstracts submitted for the Third AnnualWorkshop on Decision Making Under DeepUncertainty3-5November,Delft,TheNetherlands

The Local Organizing Committee: The Steering Committee:

Marjolijn Haasnoot, Deltares/Delft University

Jan Kwakkel, Delft University of Tech.

Warren Walker, Delft University of

Tech./Deltares

Vincent Marchau, Radboud University

Pieter Bloemen, Staff Delta Programme

Commissioner

Berry Gersonius, UNESCO-IHE

Warren Walker, Delft University of Tech.

/Deltares

Robert Lempert, RAND Corporation

Judy Lawrence, Victoria University of Wellington

Julie Rozenberg, World Bank

Natalie Peyronnin, Environmental Defense Fund

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Contents

1. ARobustStrategyForImplementingLima’sLong-TermWaterResourcesMasterPlan.6

2. DecideToBuildAndManageWaterResourcesConstructionsInTheMekongRiverDelta........................................................................................................................................................................................8

3. APhilosophicalPerspectiveOnDecisionMakingUnderDeepUncertainty...........................9

4. RobustPortfolioDecisionAnalysis............................................................................................................10

5. AdaptationPathwaysInPractice:MappingOptionsAndTrade-OffsForLondon’sScarceWaterResources............................................................................................................................................................11

6. TolerableWater-RelatedRisks?IntegratingMulti-ObjectiveOptimizationAndStressTestingToIdentifyWaterManagementStrategies.....................................................................................13

7. PolicySelectionWithoutMathematicalModels..................................................................................14

8. ChallengesAndTheState-Of-The-ArtForDiscoveringTradeoffs&VulnerabilitiesInDeepUncertaintyFrameworks..............................................................................................................................15

9. Cost-BenefitAnalysisForLong-TermFloodRiskManagementStrategies.ProsAndConsOfTheMethodAndOptionsForImprovement.................................................................................16

10. BuildingWithNatureUncertaintyMatrix:AnActor-BasedFrameworkForUncertaintyAnalysisInCoastalManagement................................................................................................17

11. Decision-MakingUnderDeepSocio-EconomicAndClimateUncertainty:FloodRiskManagement.....................................................................................................................................................................18

12. ExploringLessonsLearnedFromRDMApplications..................................................................19

13. UsingMinimaxRegretOptimizationToSearchForMulti-StakeholderSolutionsToDeeplyUncertainFloodHazards...........................................................................................................................20

14. EnhancingThePolicyPersistenceOfLong-TermGreenhouseGasTransformationPathways:ADmuApproach....................................................................................................................................21

15. DoggedlyTryingToTameNormativeUncertainty......................................................................22

16. OnBeingPreparedForTheNextDecision:EvaluationArrangementsForTheAdaptiveImplementationOfPolicyDecisionsUnderDeepUncertainty.........................................24

17. MacroeconomicApplicationsOfDMUMethodsAndPractices..............................................26

18. UsingCausalModelsAndExploratoryAnalysisInHeterogeneousInformationFusionForDetectingTerrorists............................................................................................................................................27

19. BetterIntegratingTheoryAndPracticeInDeepUncertaintyDecisionScience...........28

20. DeepUncertaintyInLandslideModellingForUrbanRiskReductionInDevelopingCountries............................................................................................................................................................................30

21. DeepUncertaintyAndPlainUncertainty:SolvingEverydayProblemsFirstForCreatingInstitutionalCapacityInDevelopingCountries.........................................................................31

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22. AGoal-OrientedApproachForDecidingOnPoliciesUnderDeepUncertainty.............33

23. PlanningForUncertainFuturesInDefence.....................................................................................34

24. HindsightAnalysisIdentifiesDeepUncertaintyInInfrastructurePlanning..................35

25. AMulti-MethodApproachToEvaluateTheRobustnessOfPoliciesInTheDutchGasSector36

26. ImprovingTheReliabilityOfATransportNetworkUnderDeepUncertainties...........37

27. Long-TermStrategicPlanningForAResilientMetroColombo:AnEconomicCaseForWetlandConservationAndManagement.........................................................................................................38

28. AdaptationPathwaysInPractice:FutureChallenges.................................................................39

29. DiscountRateAndTheCostOfCapital...............................................................................................40

30. FlexibilityInDesign:AProcedureForEffectiveProactivePlanningOfFloodManagementInfrastructureUnderUncertainty...........................................................................................41

31. ATheoreticalFrameworkForDevelopingResilienceToUrbanPluvialFlooding......43

32. DeepAndShallowUncertaintyInEcosystemServiceAssessments:SomeChallenges,SomeProgress,AndSomeHelpWanted...........................................................................................................44

33. ManagingBusinessRiskUnderUncertainty:DevelopmentPlanningInTheOilAndGasIndustry.....................................................................................................................................................................45

34. Weshareit:ANexusApproachToNileBasinWaterResourcesManagement...............46

35. AllowancesForEvolvingCoastalFloodRiskUnderUncertainLocalSea-LevelRise.47

36. PolicyExperimentationAsAToolToDealWithDeepUncertainty....................................48

37. DecisiveMomentsInAdaptationPlanning:ExperiencesAndChallenges......................49

38. WaterResourcePlanningUnderUncertaintyInTheCauveryRiverBasinInKarnataka..........................................................................................................................................................................51

39. CanInformationFromAdaptiveForestryManagementPathwaysSupportClimateChangeAdaptation?ExperienceFromForestPlanning............................................................................52

40. AdaptivePlanningForTheFlexibleExpansionOfLondon’sWaterSupplySystem...54

41. ExpressingUncertaintyInSystemModelsAsALevelOfUnderstanding........................55

42. ImplementationOfAdaptiveDeltaManagementThroughAnOpportunisticApproach 56

43. EvaluatingClimateAndOtherFutureRisksToTheHydropowerInvestmentOfTheUpperArunDam,Nepal.............................................................................................................................................57

44. ADecisionMakingUnderUncertaintyApproachToIdentifyingEfficientAndRobustHydropowerInvestmentPortfoliosInTheKoshiBasin,Nepal............................................................58

45. AdaptationPathwaysFromThePerspectiveOfRealOptionsAnalysis............................59

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46. DesigningSignpostsAndTriggersAsAdaptationSignalsInTheDynamicAdaptivePolicyPathwaysApproach.......................................................................................................................................60

47. DealingWithRisksandUncertaintiesInUrbanMasterplanningandImplementation.TheCaseOfBeira,Mozambique............................................................................................................................61

48. FloodRiskManagementUnderDeepUncertaintiesRegardingTheCoastalDevelopmentStrategyInJakarta..........................................................................................................................62

49. AssessingTheSustainableUseOfAquiferThermalEnergyStorage(ATES)UnderUncertainty.......................................................................................................................................................................63

50. Decision-MakingForWaterSensitiveDesigns:IncorporatingRealOptionsAnalysisInADynamicAdaptivePolicyPathwaysApproach....................................................................................64

51. AdjustableRobustOptimizationForSustainableWaterPolicyPathways......................66

52. MakingLong-TermInvestmentsInTheSacramento-SanJoaquinDeltaAmidDeepUncertainty.......................................................................................................................................................................67

53. TeachingDMUToPractitioners..............................................................................................................68

54. InfrastructureSystem-Of-SystemsModellingAndDecisionAnalysisForTheUk’sNationalInfrastructure..............................................................................................................................................69

55. ImprovingScenarioDiscoveryWithIterativeBehaviorSpaceSampling.........................70

56. FloodProtection:OptionFlexibilityAndItsValue.......................................................................71

57. PracticeProblemAndDynamicAdaptiveApproachTaken:HuttCityCBDFloodProtectionScheme,NewZealand..........................................................................................................................72

58. DeepUncertainty,Non-Stationarity,Scenarios,RobustnessAndAdaptation:HowDoTheyFitTogetherInEnvironmentalModelling?..........................................................................................73

59. LearningFromFacilitatedScenarioDevelopment.......................................................................74

60. AdaptationPathwaysForEnhancingUrbanResilienceToExtremeRainfallEvents.75

61. CalibratingDecisions:UsingEconomicInstrumentsInSequentialDecisionAdaptationPathways..................................................................................................................................................76

62. DealingWithDeepUncertaintyInLong-TermInfrastructurePlanningInTheNetherlands......................................................................................................................................................................77

63. UsingRobustDecisionMakingToSupportSeasonalWaterManagementInTheChaoPhrayaRiverBasin,Thailand..................................................................................................................................78

64. ExploringAdaptationTippingPointsForFloodRiskManagementInEurope.............80

65. FromTheoryToPractice;ATimelineOfInterventionsByAChangeAgentWithTheDevelopersOfTheDynamicAdaptivePolicyPathways...........................................................................81

66. EvaluatingTheResilienceAndRobustnessParadigmsForWaterResourceSystemsAdaptation.........................................................................................................................................................................82

67. TheDeeplyUncertainLocalSeaLevelResponseToAnthropogenicClimateChange83

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68. AssessmentOfTheApplicationOfDecisionToolsForPolicy-MakingUnderUncertaintyInTheWaterSector...........................................................................................................................84

69. DecisionTreeFrameworkAndDynamicAdaptivePolicyPathways–HowCanTheyComplementEachOtherInManagingUncertaintyInHydropowerProjects?..............................86

70. BangladeshDeltaPlan2100:AHolistic,AdaptiveAndLongTermStrategicPlan......87

71. AdvancesInNationalScaleLongTermInvestmentPlanningForFloodRiskManagementInTheUK..............................................................................................................................................88

72. IsUnlockingLongTermInvestmentAWickedProblemOfDeepUncertainty?...........89

73. Prospectivestrategy:balancingAnticipationandAgility.........................................................90

74. Planning,ProgrammingandBudgetingofInfrastructureandSpatialDevelopmentinUncertainTimes:ExperienceswithAdaptivePlanningintheNetherlands..................................92

75. Dealingwiththeuncertaintyofsevereweatherandassistingemergencymanagerstomakebetterdecisions.................................................................................................................................................93

76. ChallengesandProgressinImplementingDMUmethodsinWorldBankProjects....94

77. Theimpactsofclimatechangeonpovertyin2030,andthepotentialfromrapid,inclusiveandclimate-proofdevelopment........................................................................................................95

78. LessonsandchallengesfromearlyapplicationsofDynamicAdaptivePolicyPathways............................................................................................................................................................................96

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1. A Robust Strategy For Implementing Lima’s Long-Term Water Resources Master Plan

NidhiKalra,nkalra@rand.org,RANDCorporation,UnitedStatesofAmericaDavidGroves,groves@rand.org,RANDCorporation,UnitedStatesofAmericaLauraBonzanigo,l.bonzanigo@gmail.com,WorldBank,UnitedStatesofAmericaEdmundoMolinaPerez,emolina@prgs.edu,RANDCorporation,UnitedStatesofAmericaCayoRamos,cramost@lamolina.edu.pe,UniversidadLaMolina,Lima,Peru,PeruIvanRodriguezCabanillas,irodriguezc@sedapal.com.pe,SEDAPAL,Peru

ABSTRACTInspired by the previous two workshops on Decision Making Under Deep Uncertainty - andparticularlythediscussionsofhowmethodologiescancomplementeachother -thisprojectdrawstogetherprinciplesofseveralmethodologiestohelpLimaplanfor long-termwaterreliabilityamiddeeplyuncertainconditions.

Limafacesmajorwater-relatedchallenges.It isthefifth largestmetropolitanarea inLatinAmericaandthesecondlargestdesertcityintheworld.Arapidlygrowingpopulationwithapproximatelyonemillionunderservedurbanpoor, currentwater shortages, competition forwaterbetween sectors,and climate change impactsmay leave the regionunderperpetualwater stress.SEDAPAL,Lima’swaterutility,hasdevelopedanaggressiveUS$2.5billionMasterPlantoimprovewaterreliabilityinthe coming decades. The Master Plan consists of twelve major infrastructural investments thatSEDAPAL proposes to implement between now and 2040. SEDAPAL is also considering twoadditional projects. These fourteen investments are a mix of reservoirs,water treatment plants,desalinationplants,and tunnels to transferwaterbetweenwatersheds.Together, the investmentsare designed tomeet the 30% increase inwater demand that SEDAPAL projects for the comingdecades.

Consistentwiththestateofpracticeatmanywaterutilities,SEDAPALdevelopeditsMasterPlanbyprojecting futuredemandsbased on recent socioeconomic trends andbyprojecting futurewatersupplybased onhistorical climate conditions.Yet futurewater supply anddemand in Limamaydiffermarkedly from that of thepast.Theseuncertainties raise importantquestions fordecisionmakersconcernedwithwaterreliabilityinLima.IstheMasterPlansufficienttoensurereliabilityinthefaceofdeeplyuncertainfutureclimatechangeanddemand?Ontheotherhand,areallproposedprojectsnecessarytoachievingreliability?Manyprojectsarechallengingtoimplement—howshouldconsiderations of project feasibility shape the city’s investment strategy?Ultimately, how shouldprojectsbe prioritized?Which shouldbe implementednow,which canbedelayeduntil they arenecessary,andwhatspecificindicatorswouldtriggertheirimplementation?

Thisstudydrawsuponstate-of-the-artmethodsfordecisionmakingunderdeepuncertainty(DMU)togiveSEDAPALanddecisionmakers inLimaanswerstothesepressingquestions.Itdrawsuponseveralmethodologies includingRobustDecisionMaking,DecisionScaling,andAdaptivePathways,to prioritize the investments in SEDAPAL’sMaster Plan. Together thesemethods help define aninvestment strategy that is robust, ensuring water reliability across as wide a range of futureconditionsaspossiblewhilealsobeingeconomicallyefficient.Thestrategy isdefined inadecisiontreethatconsistsofasetofnear-term,no-regretinvestmentsthatSEDAPALcanembarkuponnow;signpostsofspecificprojectfeasibility,streamflow,anddemandconditionsSEDAPALshouldmonitorinthemediumand longterm;andsetsofdeferredprojectsthatSEDAPALshould implement ifthesignpostsaretriggered.

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ThisprojecthelpsSEDAPALunderstand itsMasterPlanmore fullyand implement itsMasterPlanrobustly. It also demonstrates how the best principles of different DMU methodologies can beintegratedandtailoredtoyieldhigh-valueanalyses.

Keywords: water resource planning, climate change, multiple methodologies, robust decisionmaking,dynamicadaptivepathways,decisionscaling,interactivedecisionsupport

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2. Decide To Build And Manage Water Resources Constructions In The Mekong RiverDelta

QuangVinhKy,kqvinh@ctu.edu.vn,ClimatechangecoordinationofficeofCanThocity,VietNam

ABSTRACTCanThoCity is located in the low centralof theMekongDelta.MekongRiverwater is avaluableresource,butsometimesalsothegreatdangertothelivelihoodsoflocalresidents.

EveryyearintheMekongRiverDeltahaveadryseasonattheearlymonthsandaseasonoffloodingin the lastmonths. In the year there isnowater the localpeoplewill get low incomedue to thefisheryresourcesaredecliningevenabsentand thenextricecropwillnotmeetrequirements forproduction.Incontrast,intheyearthattherearetoomuchofwater.Itwillcausedeepwaterfloodingin the paddy fields and engulf houses,works, it is a disaster. Flood damages buildings, reducesagriculturalyieldsevencauseslossoflife.WatercometoMekongdeltasomeyearsareenough,someareverylittle,andsomeareverymuchasafirstuncertainty.

Floodwater of theMekong Delta include the following sources: (1) the floodwaters come fromupstreamMekong country; (2) Local rainfallwater; and (3) tide from east sea. These arewaterresourceswhich nature play a decisive role in themajority, particularly in the coming years asclimatechangemakestheuncertainandtherisksaccompanyingwaterresourcesthemorecomplex.Climatechangeisanuncertainelementtothenext.

MekongDeltaattheendoftheMekongRiverBasin.Hydrologicalregimeofthedeltasuffergreatlyfrom the activities in the upstreamwater use. The development activities especially agricultural,urbanization,industrializationandtheconstructionof20damsin5countriesinwhichthedifferentof qualifications and different institutional form. All will contribute to a complex threats andunpredictableforhydrologicalregimeofthedelta.Thatuncertainty3rd.

Inaddition,theriskofdistortionduetogroundsubsidenceandnoexactforecastsatthelocalscalemakesdesigncalculationsworks tominimizedamageofwater resources risksbecomingbaselessthatisthe4thuncertainty.

How to choose anddecide the investmentworks, in order tominimizedamage and increase thebenefitsforthelocalpopulationagainstunexpecteddevelopmentsofwaterresources,onthewholeregionandforeach localitywasaproblemurgent.Especiallytheanswermustbe"noregrets"andhighefficiency.

Keywords:Delta,Mekong,flood,subsidence,dams

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3. A Philosophical Perspective On Decision Making Under Deep Uncertainty

NeelkeDoorn,N.Doorn@tudelft.nl,DelftUniversityofTechnology,Netherlands

ABSTRACTConventional risk analysis is based on careful consideration of probabilities, consequences, andalternativeactions.Inthelightofclimatechange,weoftenhavetomakedecisionsintheabsenceofsuchinformation:Wedonotknowtheprobabilitiesofthepossiblefutureeventsthatarerelevantforthedecision,andsometimeswehavenoteven identifiedtheseevents.Itmayalsobepossiblethatpeopledisagreeaboutthedesirabilityoffutureevents.Together,theseuncertaintiesandambiguitiesmay influenceeachother:policy choicesareaffectedby societaland climatologicaldevelopmentsandviceversa. In the literature, this isoften referred toasdeepuncertainty. Inorder to supportpolicymakers,methods and tools have been developed that are particularly aimed at decision-making under deep uncertainty. These methods and tools often comprise models and otherquantitativemethodsthathelpstrengthentheknowledgebase.

The topic of decision making under deep uncertainty has recently attracted the attention fromphilosophersofriskaswell.Inthislineofresearch,twofocalpointscanbedistinguished.Theformertakesanargumentativepointofview.Methodsfromphilosophicalanalysishavebeenproposedforprioritizingamonguncertaindangers,fordetermininghowdecisionsshouldbeframed,forchoosingasuitabletimeframeforadecisionandforsystematicallychoosingamongdifferentdecisionoptions.Thesecondpointofview focuseson theethical implicationsofpolicydecisionsmadeunderdeepuncertainty.Takingintoaccountthatdecisionstakennowaffectfuturegenerationsandrecognizingthatwe live in apluralistic society inwhichpeoplemaydisagreeon theprinciplesofdistributivejustice, there are strong reasons to take those decisions that involve as little irreversibleconsequencesaspossible.

Inthispresentation, Idiscusssomerecentdevelopments inphilosophyofriskandshowhowtheymaysupportdecisionmakingunderdeepuncertainty.

Keywords:philosophy,ethics,distributivejustice,pluralism,argumentativestrategy

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4. Robust Portfolio Decision Analysis

ValentinaBosetti,valentina.bosetti@unibocconi.it,BocconiUniversity,UnitedStatesofAmericaErinBaker,edbaker@ecs.umass.edu,UMass,UnitedStatesofAmericaAhtiSalo,ahti.salo@aalto.fi,AaltoUniversity,Finland

ABSTRACTIn this paperwe discuss the problem of “deep uncertainty”. This problem–which is pervasive inclimate change–refers to a situation inwhich there is significant disagreement over probabilitydistributions(McInerneyetal,2012).Todate,therehavebeentwodifferingapproachestodecisionmakingunderdeepuncertainty.The first is togo forwardwith traditional,rationalapproachesofdecisionmakingunderuncertainty (e.g.Baker and Solak2014,Kelly andKolstad1999);but thisapproach has been criticized for providing solutions that appear too certain or are lacking in“externally consistency” (Gilboa et al2009).The second approachhandlesmissing or ambiguousinformation through non-traditional decision rules, for example by applying the machinery ofambiguityaversion(Milneretal2013)orotherworst-case-typeanalysis.Thesenon-expectedutilitydecision criteria have been criticized, however, as not being internally consistent (Al Najjar andWeinstein2009).

Oneconcernaboutbothapproachesisthattheytendtoarriveatasingle“best”decision.Wearguethatincaseswherethereisdisagreement,whetheroverpreferencesorbeliefs,analystsshouldnotprovideasingle“best”decision.Whilemodelersbelievetheirmodelsareuseful,decisionmakersarewellawarethatallmodelsarewrong(BoxandDraper,1987).Therearealwaysanumberofaspectsoftherealworldthatcannotbemodeled.Therefore,thereisgoodreasontousemodelstoprovideinsightsandasetofgoodsolutions,andthenallowdecisionmakerstochoosethebest.Inthispaper,weintroducedominancemeasuresthatincorporateriskaversionandmultiplepriors.

Weapply this framework to thequestionofhow toallocate fundsacrossawidevarietyofenergytechnologieswith varying potential for improvement and differing impacts on the economy andenvironment. This question is part of a complex phenomenon - onewhich has been approachedthrough different avenues, including the development of a broad range of different integratedassessment models (IAMs); and studies of expert judgments on the potential for technologicalchange.TheIAMshavebeenusefulfordevelopinginsightsontherelativeimportanceoftechnologiesandthespeedoftheiradoption;neverthelesstherearearangeofchallengesfromtheviewpointofdecisionandpolicymaking, including the largenumberofassumptions thatarerequired,and thesignificant uncertainties that they entail. The studies of expert judgments have provided explicitprobabilitydistributionsoverthepotentialfortechnologicalchange;however,thereareanumberofindependentanddisparatestudies, increasing thechallengeof trying to incorporate them into thealreadycomputationally-complexIAMs.

In this application, we use data derived from three large expert elicitation studies of energytechnologies(Bakeretal2015).Tomodeltheinteractionsofthetechnologieswitheachotherandintheeconomy,weuse two IntegratedAssessmentModels,GCAMandWITCH.We incorporatedeepuncertaintyovertechnologicalprospectsandoverclimatechangedamagestoderivecore,exterior,andmarginalinvestments,andillustratehowthissetcanprovideinsightstodecisionmakersonneartermactions.

Keywords:RobustPortfolioDecisionAnalysis,CleanEnergyRDportfolio,MultiplePriors

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5. Adaptation Pathways In Practice: Mapping Options And Trade-Offs For London’sScarce Water Resources

AshleyKingsborough,ashley.kingsborough@ouce.ox.ac.uk,EnvironmentalChangeInstitute,UniversityofOxford,UnitedKingdomofGreatBritainandNorthernIrelandJimHall,Jim.hall@eci.ox.ac.uk,EnvironmentalChangeInstitute,UniversityofOxford,UnitedKingdomofGreatBritainandNorthernIrelandEdoardoBorgomeo,edoardo.borgomeo@ouce.ox.ac.uk,EnvironmentalChangeInstitute,UniversityofOxford,UnitedKingdomofGreatBritainandNorthernIreland

ABSTRACTAdaptation involves sequences of decisions thatweigh up climate risks, costs and uncertainties.Analysisofsequentialadaptationdecision‘pathways’helpstodemonstratehowclimateriskcan(orcannot)bemanaged,whilst retaining the flexibility to respond to futureuncertainties.Whilst anadaptiveplanningparadigmhasgained increasingattention, theuptakeofsuchmethodshasbeenrelatively limited compared to that of the scale of adaptation that is required around theworld(Walkeretal.,2013).

London’sabilitytoremainaworld-leadingcityinan increasinglyglobalisedeconomy isdependenton it being an efficient and low risk place to do business. However, climate risk from flooding,overheating, water scarcity and supply chain exposure is increasing. The Mayor of London hasidentifiedanticipatoryadaptationasacosteffectivestrategytoincreasethe long-termresilienceofthecity(GLA,2011).Inpracticehowever,theallocationofscarceresourcesneedstobejustifiedbythebenefitsofclimateriskreduction.

Thispaperdemonstrateshowanadaptationpathwaysapproachcanbecombinedwithprobabilisticriskanalysistomakethecaseforadaptation.WefocusontheriskstoLondon’swatersupplies,whicharebeingstretchedbyincreasingpopulation.

Arangeofwatersupplyanddemandreductionactions,andthepotential limitsofthose individualactionswere identified.Through this process, stakeholders began to define a solution space andidentify feasible timescales over which adaptation options could be scaled up. Portfolios ofadaptationactionswere identifiedand illustrativeadaptationpathwaysforLondon’swatersupplydeveloped.

We present a quantified assessment of how risk of water shortages varies dynamically for 12adaptationpathwaysthroughtime,demonstratinghowtransientclimateprojectionscanbeusedtoextendwaterresourceplanninghorizonsto2100.Theapproachconsidersdiscreetactionsandthetiming,rateandscaleofimplementationofmultipledistributedactionsaspartofdynamicadaptiveportfolios.The implicationsofprioritisingflexibleactionsasameansofachievingrobustoutcomesareexploredthroughanumberofpathways.

Theanalysisidentifiedanumberofpathwayscapableofmaintainingtheprobabilityofexceedingatarget frequency ofwateruse restrictionsbelow aprobability of0.01per year, through to2100underamediumemissionsscenario.Withoutfurtheradaptation,theprobabilityofwatershortagewill increasebeyond the0.01 stakeholders considered tolerable.Pathwaysdiagramsdemonstratehow a range of dynamic adaptation portfoliosmay perform, providing an effective stimulus forstakeholderstoconsiderwhatisatolerablelevelofclimateriskandhowthismaychangeovertime.Thisapproachhashelped to reconcilemultipledecision timescales anddemonstrate the value ofstrategic long-termplanning forclimate changeadaptation to stakeholdersbyoutlining long-term

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futures that may influence medium-term decision-making. Adopting a flexible approach toadaptationwillbecritical to themanagementofriskunderuncertainty.Thisadaptationpathwaysapproachdemonstratesaneffectiveframeworkforinformingsuchdecisionprocesses.

Keywords: Adaptation Pathways, Probabilistic Risk Assessment, Transient Scenarios, DecisionMaking

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6. Tolerable Water-Related Risks? Integrating Multi-Objective Optimization And StressTesting To Identify Water Management Strategies

EdoardoBorgomeo,edoardo.borgomeo@ouce.ox.ac.uk,UniversityofOxford,UnitedKingdomofGreatBritainandNorthernIrelandJimHall,jim.hall@eci.ox.ac.uk,UniversityofOxford,UnitedKingdomofGreatBritainandNorthernIreland

ABSTRACTItisimportanttorecognizethelimitationsofconventionalriskanalyticapproachesfordealingwithclimatechangerelatedand informclimatechangeadaptationdecisions.Thisworkpresentsatwo-pronged approach towatermanagement decision-making under uncertaintywhereby, instead oftryingtosimplypredictfuturewateravailabilitybasedonuncertainclimateprojections,riskanalytictools are coupled with multiobjective search algorithms and ‘stress testing’ methods to exploresensitivitytotheunforeseenandidentifyrobustnesstounexpectedhydrologicalconditions.

Amulti-objectivesearchmethodisemployedtoidentifyalternativewatermanagementplanssubjecttodifferentclimaterisktolerabilityconstraints.Themethodallowswatermanagerstounderstandthe implicationsofchoicesaround risk tolerabilityon their investmentdecisionsand the selectedplans.Themultiobjective search is coupledwithnovelmethods to test the vulnerability ofwaterresourcesystemtounforeseendroughtconditions.A largenumberofplausiblesyntheticdroughtsare generated by perturbing the temporal dependence structure of streamflow time series. Thisallowswatermanagerstostresstesttheirdecisionsagainstconditionsthatgowellbeyondhistoricaldroughts.

Themethod isapplied to theLondonwaterresourcesystem(England) to identifyadaptationcostand risk reduction trade-offsand to investigateunderwhichdroughtconditions severewateruserestrictionswould need to be imposed onwater users.Results indicate that thewater resourcesystem isvulnerabletodroughtconditionsoutsidetherangeofhistoricalevents.Thevulnerabilityassessment results were coupled with climate model information to compare alternative watermanagement optionswith respect to their vulnerability to increasingly long and severe droughtconditions.

Traditionalrobustnessassessmentshingeuponriskaversepreferenceswhilstourapproachallowswater managers to gain a more nuanced understanding of the implications that different riskattitudeshaveonrobustnessandonthecostsofachievingthatrobustness.

Keywords:Tolerablerisk,Robustnesstodrought,Risk-based,Watersyooky

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7. Policy Selection Without Mathematical Models

YakovBen-Haim,yakov@technion.ac.il,Technion-IsraelInstituteofTechnology,Israel

ABSTRACTMany real-world planning and decision problems are far too uncertain, too variable, and toocomplicatedtosupportrealisticmathematicalmodels.Inthistalkweexplaintheusefulness,inthesesituations,ofqualitativeinsightsfrommathematicaldecisiontheory.Wedemonstratetheintegrationofinfo-gaprobustnessindecisionproblemsinwhichsurpriseandignorancearepredominant.

Reducinguncertainty is amajor focusofplanninganddecisionanalysisundersevereuncertainty."Reducinguncertainty"canhavetwodifferentmeanings:

1.Reduceignorance,ambiguityorpotentialforsurpriseindescribingrelevantsituations.

2.Reducevulnerabilitytoignorance,ambiguityorsurprise.Reducetheimpactofuncertaintyontheoutcomeofthedecision.

Reducinguncertainty(the firstmeaning) isverydifferent fromreducing the impactofuncertainty(the secondmeaning). It isnotuncertaintyper se that ispernicious,but rather thepossibility foradverse impact of surprise.Uncertainty about irrelevant situationsneedn'tbe reducedbecause itisn't pernicious. More importantly, some policy options are less vulnerable to uncertainty thanothers. These less vulnerable (equivalently,more robust) options can toleratemore uncertainty.Analystsshouldidentifypolicyoptionsthatarerobusttouncertainty.

Reducingtheimpactofuncertaintyrequiresawarenessofpolicymakers'goals.Thismayconflictwithpolicyneutralityofanalyststhatischaracteristicofmuchexpertdecisionsupportforclientdecisionmakers,forexamplegovernmentalagencies.

Wepresentpracticalguidelinesforemployingadaptablechoice-strategiesasaproxyforrobustnessagainstuncertainty.Theseguidelinesincludebeingpreparedformoresurprisesthanweintuitivelyexpect, retaining sufficiently many options to avoid premature closure and conflicts amongpreferences,andprioritizingoutcomesthataresteerable,whoseconsequencesareobservable,andthatdonotentailsunkcosts,resourcedepletion,orhightransitioncosts.Weillustratetheseconceptsandguidelineswithexamplesfrompublichealthandinternationalsecurity.

References

Michael Smithson and Yakov Ben-Haim, 2015, Reasoned Decision Making Without Math?AdaptabilityandRobustnessinResponsetoSurprise,RiskAnalysis,toappear.

YakovBen-Haim,2014,Strategy selection:An info-gapmethodology,Defense &SecurityAnalysis,30(2):106-119.

Keywords:policyselection,robustness,uncertainty,info-gap

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8. Challenges And The State-Of-The-Art For Discovering Tradeoffs & Vulnerabilities InDeep Uncertainty Frameworks

PatrickReed,patrick.reed@cornell.edu,CornellUniversity,UnitedStatesofAmerica

ABSTRACTAlthoughexogenousdriverssuchasclimatechange,populationpressures,systemdemands,etc.arewidelyacknowledgedandexploredintherobustdecisionmakingliterature,thereisaneedtobetteracknowledge and rigorously explore the deep uncertainty associated with eliciting problemdefinitions. There are nontrivial conceptual as well as computational challenges that should beacknowledgedinformalizingourexplorationofthestructuraluncertaintiesassociatedwithdefiningcomplexmanagementproblems(e.g.,choosingobjectives,exploringmanagementdecisions,planninghorizons,representationsofpreferences,etc.)aswellas thechallengesassociatedwithpredictingthe impacts of actions (e.g., imperfect knowledge of system dynamics, external forcings, orenvironmental thresholds). There is a growing recognition and interest in using emergingcomputational tools for discovering the tradeoffs that emerge across complex combinationsinfrastructure options, adaptive operations, and sign posts. As a field concerned with “deepuncertainties”, it is logicallyconsistentto includeamoredirectacknowledgementthatourchoicesfor dealing with computationally demanding simulations, advanced search algorithms, andsensitivity analysis tools are themselves subject to failures that could adversely bias ourunderstandingofhow systems’vulnerabilities changewithproposedactions.Balancing simplicityversuscomplexity inourcomputationalframeworksisnontrivialgiventhatweareoftenexploringhigh impact irreversible decisions. It is not always clear that accepted models even encompassimportantfailuremodes.Moreoverastheybecomemorecomplexandcomputationallydemandingthebenefitsandconsequencesofsimplificationsareoftenuntested.

Manyofthechallengesdiscussedabovehavemotivatedthelastdecadeofmygroup’sresearch.Theyshape our ability to operationalize our “many-objective robust decision making” (MORDM)frameworkforthedesignandmanagementofcomplexengineeredsystems.TheMORDMframeworkhas four core components: (1) elicited problem conception and formulation, (2)many-objectivesearch,(3) interactivevisualanalytics,and(4)negotiatedselectionofrobustalternatives.Problemconception and formulation is the process of abstracting a practical design problem into amathematical representation. We build on the emerging work in visual analytics to exploitinteractivevisualizationofboththedesignspaceandtheobjectivespaceinmultipleheterogeneouslinked views that permit exploration and discovery. Many-objective search produces tradeoffsolutions from potentially competing problem formulations that can each consider up to tenconflicting objectives based on current computational search capabilities. Negotiated designselectionusesinteractivevisualization,reformulation,andoptimizationtodiscoverdesirabledesignsfor implementation.Eachof theactivities in the framework issubject to feedback,bothwithin theactivity itselfand from theotheractivities in the framework.These feedbackprocesses transitionformerlymarginalized “constructive learning”activitiesof reformulating theproblem, refining theconceptualmodelof theproblem,andrefining theoptimization, torepresent themostcriticalandpotentiallydeeplyuncertainprocessfor innovatingrealworldsystems(i.e., learninghowtoframetheproblemsthemselves).Mypresentationwilluseourrecentapplicationsinurbanwaterportfolioplanning, multi-sector reservoir planning and satellite constellation design to demonstrate keychallengesandrecentcomputationalinnovations.

Keywords:robustdecisionmaking,multiobjectivedecisionsupport,problem framinguncertainty,scalabledecisionsupport,learning

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9. Cost-Benefit Analysis For Long-Term Flood Risk Management Strategies. Pros AndCons Of The Method And Options For Improvement

JarlKind,jarl.kind@deltares.nl,Deltares,Netherlands

ABSTRACTOver the last decade, a number of relative new, ‘non-probabilistic’ methods for the (economic)evaluationofinvestmentprojectstoadapttoclimatechange,havereceivedanincreasingamountofattention, both from scientists and practitioners. Themethods include amongst others Info-GapTheory(IGT),RobustDecisionMaking(RDM)and IterativeRiskManagement(IRM).Themethodsarecalled‘non-probabilistic’,sincetheyaredesignedtodealwith‘deepuncertainty’,forexampletheimpactsoffutureclimatechangeonwatersystems,forwhichnoorlimitedprobabilisticinformationexists.Severalpublicationshavecomparedthenewmethodswithtraditionalevaluationmethods,ofwhich the most commonly applied is cost-benefit analysis (CBA). In the comparison, there is atendencytodescribetheCBAinasomewhatcaricaturalway,inwhicha‘mostlikelyfuture’isusedtoevaluate ‘now-or-never’ investment decisions. Consequently, the CBAmethod is judged to be ill-equippedtodealwithclimatechangeuncertaintiesaswellaswithothertypesofuncertainties.

Overthe lastdecades,however,severalmethodologicaldevelopments intheCBAhavetakenplace,whichhave significantly improved theCBAmethod todealwithboth riskanduncertainty.Thoseincludetheuseofreal-optionsanalysistoevaluatetimingandflexibility inthedesignofmeasuresand strategies, the use of multiple scenarios to evaluate robustness of decisions, Monte Carlo-simulationstoprovideprobabilitydensityfunctionsoftheefficiencyofmeasuresandstrategies,theuseofswitchingvaluestoassessthemaximumallowablechangesofcriticalyetuncertainvariables,the valuation of intangible costs andbenefits, the inclusion of riskaversion to value catastrophiclosses inanotherway than simply theproductofprobabilitiesand consequences,andhyperbolicdiscountinginwhichrelativehigherweightsareassignedtocostsandbenefitsthatarise inthefarfuture.

Inmany countries, theCBA is still themost commonlyusedevaluationmethodologyand isoftenneeded to secure government funding, aposition themethod ownsdue to its strong andwidelyacknowledged foundation in economic welfare theory. The CBA framework thus provides solidconceptsforaggregatingcostsandbenefitsovertime(i.e.,discounting),tovaluecostsandbenefitsonbases of consumers’preferences and to aggregate all these.Although those conceptsmaynotalways be ideal and are also being criticized, alternativemethods have not yet come forthwithproblemfreealternativesolutionsforthe-ultimatelynecessary-aggregationfordecisionmaking.Adraw back of the CBAmethod, however, is that it preferably uses expected (that is, probabilityweighted)valuestoassessefficiencyofadaptationoptions.Theauthordiscussesprosandconsandhow theCBAmethodcanbe improvedwithelements fromalternative,non-probabilisticmethods,withanapplicationtotheCBAforfloodriskmanagementdecisions.

Keywords:CostBenefitAnalysis,FloodRiskManagement,Uncertainty

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10. Building With Nature Uncertainty Matrix: An Actor-Based Framework For UncertaintyAnalysis In Coastal Management

ZilinWang,wangzilin0327@gmail.com,DelftUniversityofTechnology,NetherlandsJillSlinger,J.H.Slinger@tudelft.nl,DelftUniversityofTechnology,Netherlands

ABSTRACTBuildingwithNature(BwN)isanemergingmethodologyfordealingwithcoastalerosionbyutilizingnatural processes and materials. Comparing with traditional hard infrastructures (e.g. dams,seawalls) which are reactive schemes of minimizing and compensating for precarious negativeimpacts,BwNaims toproactivelyembraceuncertainties fromnatureandkeeps the flexibility forfurtheradjustment.Therefore,decisionmakingprocessesofBwNprojectsrequiredecisionmakersandstakeholderstoobtainahigherlevelofacknowledgementandacceptanceofuncertainties,whichisincompatiblewithcustomarydecisionmakingmethodsforriskreductionandelimination.Basedon existing theories, this research developed a synthetic analytical framework, BwN uncertaintymatrix,todiscloseuncertaintiesanddifferentperceptionsofuncertaintiesinvolvedinBwNprojectsfromanactor-basedperspective.Fourdimensions,includingthecontent,location,levelandnature,areused todepicteachperceiveduncertaintybyeachactor.DifferentperceptionsofuncertaintiesarerevealedbycomparingdifferentdimensionsofuncertaintiesinBwNuncertaintymatrices.

Furthermore, the BwN uncertaintymatrixwas applied for investigating uncertainties in the firstlarge-scaleBwNsandnourishmentprojectinYstad,Sweden.TheresearchresultsshowedthatintheYstadproject,uncertaintieswereacrossallthenatural,technicalandsocietalsystems(I.e.content),anddifferentperceptionsofuncertaintiesexistedinalltheotherthreedimensions(i.e.location,levelandnature).Uncertaintiesregarding issues inthesocietalsystemwereaddressedmorefrequentlythantheissuesinthenaturalandtechnicalsystems.Theinfluentialuncertainties(e.g.environmentalimpacts of sand nourishment) were located in the natural and technical systems but stronglyaffinitivewithsocialissues.StrategiesdealingwithdifferentperceptionsofuncertaintiesintheYstadproject were analyzed and deconstructed into different strategic scheme, including framing andrationalproblemsolving.

Keywords:BuildingwithNature,uncertaintyanalysis,actor-basedframework,coastalmanagement

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11. Decision-Making Under Deep Socio-Economic And Climate Uncertainty: Flood RiskManagement

CarloGiupponi,cgiupponi@unive.it,Ca'FoscariUniversityofVenice-VICCS,ItalyVahidMojtahed,vahid.mojtahed@unive.it,Ca'FoscariUniversityofVenice-VICCS,ItalyAnimeshGain,animesh.gain@gmail.com,GFZ-GermanResearchCentreforGeoscience,Germany

ABSTRACTFloodriskisamajorsourceofeconomicdamagesandlossoflivesworldwide.Manystructuralandnon-structuralmeasuresareavailabletoreducetherisk,inparticulartopeople.However,decisionmakers are challenged with the identification of effective risk management solutions in highlyuncertain contexts. For successfully reducing risks, it is, therefore, essential to measure theperformanceofeachriskreductionoptioninsuchcontexts.Inthisstudy,weproposeanapproachtosupport decision-making process concerning risk reduction measures for flood risk underuncertainty.For thispurpose,weemploystatisticalandcomputational tools toconstructplausiblefuturescenariosdefinedthrough internallyconsistentcombinationsofclimateandsocio-economicdrivers, preserving dependencies among the uncertain variables. Furthermore, we utilize data-mining algorithms to describe theweaknesses of a set of proposed risk reductionmeasures byexploringunderwhichscenariostheymaysubstantiallyfailtoachievethedecision-makers’targets.TheproposedapproachisappliedtotheEasternpartofDhakacity(Bangladesh),wheretheimpactsof flooding are expected to be severe due to climate,population pressure and urbanization. Theresultsareusedtodescribetherobustnessofeachproposedoption insupportofdecision-making,consideringalsopossibleevolutionsover timeandadaptationneeds.Resultsaresummarizedandcommunicated using decision trees that describe a categorized view of the vulnerabilities of theproposedriskreductionmeasures,by identifyingthestatesandcombinationsofkeyvariablesthatcoulddetermineconsiderablefailures.

Keywords:DeepUncertainty,RobustDecision-making,ScenarioConstruction,FloodRisk

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12. Exploring Lessons Learned From RDM Applications

RobertLempert,lempert@rand.org,RAND,UnitedStatesofAmerica

ABSTRACTRobustDecisionMaking(RDM)andrelatedmethods fordecisionmakingunderconditionsofdeepuncertaintyhavenowbeenapplied to awidevarietyofdecisions in awidevarietyof institutionalcontexts.Applicationsincludewatersupply,floodriskmanagement,energysystems,insurance,anddefense planning. Institutional contexts include public sector planning, regulatory planning,engagementswithbroadstakeholderparticipation,andengagementsfocusedonasmallnumberofdecisionmakers. Ineach context, theanalyseshaveoftenbeen organizeddifferently, for instanceusing simulationmodelswithdifferent levels ofdetail and complexity,and emphasizingdifferentstages of the full “textbook” analyses. This talkwill survey thesemany and diverse applications,situatetheminthelargerliteratureondecisionsupportandscience-baseddecisionmaking,andofferlessonslearnedonapplyingRDMandrelatedmethodsinvariousapplicationareasandinstitutionalcontexts.

Keywords:LessonsLearned,RobustDecisionMaking,DecisionSupport

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13. Using Minimax Regret Optimization To Search For Multi-Stakeholder Solutions ToDeeply Uncertain Flood Hazards

PaulKirshen,paul.kirshen@gmail.com,UniversityofNewHampshire,UnitedStatesofAmericaJoryHecht,joryhecht@gmail.com,TuftsUniversity,UnitedStatesofAmericaRichardVogel,richard.vogel@tufts.edu,TuftsUniversity,UnitedStatesofAmerica

ABSTRACTPrescribing long-termurban floodplainmanagementplansunder thedeepuncertainty of climatechange is a challenging endeavor. To address these challenges, we formulate and test withstakeholders aparsimoniousmulti-stagemixed integerprogram (MIP) that identifies the optimaltime period(s) for implementing publicly and privately financed adaptation measures. Publiclyfunded measures include reach-scale flood barriers, flood insurance, and buyout programs toencouragepropertyowners inflood-proneareastoretreatfromthefloodplain.Measuresprivatelyfundedbypropertyownersconsistofproperty-scalefloodproofingoptions,suchasraisingbuildingfoundations,aswellasinvestmentsinfloodinsuranceorretreatfromflood-proneareas.

Theobjectivefunctiontominimizethesumoffloodcontrolanddamagecostsinallplanningstagesfordifferentpropertytypesduringfloodsofdifferentseverities.Thereareconstraintsovertimeforflow mass balances, construction of flood management alternatives and their cumulativeimplementation,budget allocations, andbinarydecisions.Damagesare adjusted for flood controlinvestments.

In recognition of the deep uncertainty of GCM-derived climate change scenarios,we employ theminimax regret criterion to identify adaptation portfolios robust to different climate changetrajectories. As an example, we identify portfolios of publicly and privately funded adaptationmeasures for a stylizedcommunitybasedon theestuarine communityofExeter,NewHampshire,USA,thatarerobusttochange infloodhazardsofbothriverineandcoastaloriginduringthe21stcentury. We explore the sensitivity of recommended portfolios to climate changes, and costsassociatedwitheconomiesofscaleandflexible infrastructuredesignaswellasdifferentmunicipalbudgetconstraints.

We explicitly represent different stakeholder objectives in floodplain management optimizationmodels,whichaddresstradeoffsbetweenpublicandprivatespendingandtheequityof impactstolow-incomehouseholds.Weshowtheimportanceofrepresentingthesestakeholdersinthemodelbycomparingtheadaptationmeasuresthatthesemulti-objectiveoptimizationmodelsrecommendwiththosesuggestedbythesinglesocialplannerformulation.Wealsoconsidertheintegrationofdecisionsequencesrepresentativeofreal-worldpoliticalhierarchiesintotheoptimizationmodel.

Insummary,theMIPrapidlygeneratesadaptationplanningrecommendationsrobusttoawiderangeofclimatechange thatreflect the interestsofdifferent stakeholdergroups,making itanattractivetoolforexploringthepossibleconsequencesofadaptationalternatives instakeholdermeetings.Inaddition, it provides a means of exploring the partitioning of adaptation responsibilities amonggovernments and property owners of different socioeconomic conditions, a task which will beessentialforcoordinatingfloodplainmanagementunderthedeepuncertaintyofclimatechange.Wealsoreportuponstakeholderreactiontothetoolandpossibleimprovements.

Keywords: Urban Flooding under Climate Change, Adaptation, Multiple Stakeholders, BudgetConstraints

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14. Enhancing The Policy Persistence Of Long-Term Greenhouse Gas TransformationPathways: A Dmu Approach

RobertLempert,lempert@rand.org,RAND,UnitedStatesofAmericaStevenIsley,steve.c.isley@gmail.com,RAND,UnitedStatesofAmericaStevenPopper,swpopper@rand.org,RAND,UnitedStatesofAmericaRaffaeleVardavas,rvardava@rand.org,RAND,UnitedStatesofAmerica

ABSTRACTTo successfully limit climate change, today’sgreenhousegasmitigationpolicies shouldencouragereductions thatcontinue fordecades.History suggests,however, that somepolicy reforms lead tosocietal changes thatpersist over the long-termwhile others fade awaywithoutmuch long-termeffect.Current climatepolicy literatureprovides littleguidanceonhow today’spolicychoices cansuccessfully shape long-termemission reductionpathways.Toaddress suchquestions, thispapercombinesanalyticmethods fordecisionmakingunder conditionsofdeepuncertaintywith anewagent-based, game theoretic model designed to compare how near-term choices regardingalternativepolicyarchitecturesinfluencelong-termemissionreductionpathways.

DrawingonPatashnik’sworkinpoliticalscienceliteratureonpolicypersistence,whichidentifiesthecharacteristicsofpoliciesthatpersistovertime,thissimulationforthefirsttime integratestheco-evolutionofanindustrysector,itstechnologybase,andtheshiftingpoliticalcoalitionsthatinfluencethefuturestringencyofthegovernment’semissionreductionpolicies–allasinfluencedbytheinitialchoiceofpolicyarchitecture. Inparticular,weuseanevolutionaryeconomicsmodelbasedon theworkofDositowhichwehaveaddedagametheoreticcomponentbasedontheworkofGrossmanand Helpman that describes the competition among firms as they attempt to influence futuregovernmentpolicy.Anexploratorymodeling-basedanalysis,using toolsandconcepts fromRobustDecisionMaking(RDM),drawspolicy-relevantconclusionsfromthismodel,whichrepresentsdeeplyuncertain phenomena such as the future potential for innovation and the behavior of futuregovernments. The analysis finds that near-term choices regarding the architecture of a carbonpricingpolicymayaffect long-termdecarbonizationratessignificantly.Inparticular,suchratesarehigherifprogramrevenuesarereturnedtofirmsinproportiontotheirmarketsharethuscreatingapoliticalconstituencyforcontinuingthecarbonpricingpolicy.Moregenerally,theanalysisprovidesaframeworkforconsideringhowwith integratedassessmentmodelsnear-termpolicychoicescanaffectlong-termemissiontransformationpathways.

Overall, thisworkprovides an initial,quantitative,decision analytic evaluation ofhownear-termchoices about greenhouse gas regulatory architectures can affect the long-term co-evolution oftechnology, market shares, and political coalitions that affect the stringency of greenhouse gasregulation.Thistalkwillpresentthisanalysisanditspolicyrelevantresults.Inaddition,thetalkwillalso suggesthow analyticmethods fordecisionmakingunder conditions ofdeepuncertainty canenhanceunderstandingofappropriatepoliciesforsustainabilitytransitionsandsuggestagendasforfutureresearch.

Keywords:RobustDecisionMaking,TransformationPathways,GreenhouseGasMitigation,ClimateChange,Agent-BasedModeling

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15. Doggedly Trying To Tame Normative Uncertainty

SietskeVeenman,S.veenman@fm.ru.nl,RadboiudUniversityNijmegen,NetherlandsKlaasVeenma,k.veenma@overijssel.nl,ProvincieOverijssel,Netherlands

ABSTRACTMost of the traditional (applied) scientificwork ondeepuncertaintydistinguishesbetweendeepuncertaintyforanalystsandforpolicymakers,givingmostattentiontotheformer(Walker,2013).Deepuncertaintyonthelongtermforpolicymakersislessresearched(VanAsseltetal.,2010).

Thispaperanalyseshowdeepuncertainty isdealtwith inpolicymakingprocesses, focusinguponhowpolicymakers and stakeholdersuse existingpolicymethods indeeplyuncertainpolicies. Inorder to do so, we start with developing a framework for deep uncertainty in policy makingprocesses.Deepuncertaintyforpolicymakersdoesencompassmorethanthedeepuncertaintythatismodelled for analysts, as there is aplurality ofpolitical ornormativeperspectives involved inpolicymakingprocesses.Policymakersfacenormativeuncertainty,alsocalledambiguity,everyday.Hence,itplaysaprominentrole.Therefore,thispaperdistinguishesandrelatesdeepcognitiveandnormativeuncertaintyinpolicymakingprocesses.

Over theyears,policyanalystshavedeveloped severalpolicymethods, in thewidest senseof theterm (Dunn, 1981), to dealwith deep uncertainty such as adaptive planning, scenario discovery,scoping,adaptationtippingpointsandadaptationpathways,etc.(Halletal.,2012).However,deepuncertainty isnotnew, aspolicymakershave todealwith it since ever.Over time, though,withincreasingcomplexityandallpervadingmulti-stakeholdersparticipationapproaches,thisissuehasbecome even more complex. Thus far, research lacks upon how existingmethods within policymakingprocesses,suchasmulti-actorparticipation,broadeningthescopeofaproject,MCA,etc.,areusedtohandledeepuncertainty,bothcognitiveandnormative.

While the first part of the paper will present a framework to analyse how policy makers andpoliticiansdealwithdeepuncertainty,thesecondpartofthepaperusesthisframeworkinthecaseofTwenteAirport (theNetherlands). Formore than adecade, thepolicymakingprocess aroundTwenteAirporthasbeencapturedbydeepuncertainty:aboutwhattodowiththe(former)runway,aboutemployment,aboutnature,aboutalternativefutures,etc.Thepolicyprocessshowsclearbackandforthmovementsofthereductionandacknowledgingofnormativeuncertainty,andthestrategicroleofdifferentactors (e.g., theNetherlands’Commission forEnvironmental ImpactAssessment),deliberatelyusingcertainpolicymethodstherein.Withoutanticipatingourconclusions,weseemtoobservestronglinkagesbetweencognitiveandnormativeuncertainty,andoccasionallyattemptstosubstitutenormativeuncertainty or organize a trade-offbetweennormative and cognitive in thepoliticaldebate.

Walker,W.,M.HaasnootandJ.Kwakkel(2013),AdaptorPerish:AReviewofPlanningApproachesforAdaptationunderDeepUncertainty,Sustainability,5,p.955-979.

J. Hall, R., Lempert, K. Keller, A. Hackbarth, C. Mijere and D. McInerney (2012), Robust ClimatePoliciesUnderUncertainty: AComparisonofRobustDecisionMakingand Info-GapMethods,RiskAnalysis,32,p.16527-11672

Dunn,W.(1981),Publicpolicyanalysis:Anintroduction.EnglewoodCliffs,NJ:Prentice-Hall.

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VanAsselt.,N.Faas,F.vanderMolenandS.Veenman (2010),Uit zicht:Toekomstverkennenmetbeleid,WRR,DenHaag:SDU

Keywords: Deep uncertainty, Normative uncertainty, Policy making processes, Policy methods,TwenteAirport

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16. On Being Prepared For The Next Decision: Evaluation Arrangements For The AdaptiveImplementation Of Policy Decisions Under Deep Uncertainty

LeonHermans,L.M.Hermans@tudelft.nl,DelftUniversityofTechnology,FacultyofTPM,NetherlandsArienneNaber,arienne.naber@gmail.com,DelftUniversityofTechnology,FacultyofTPM,NetherlandsTinekeRuijgh-VanderPloeg,M.P.M.Ruijgh-vanderPloeg@tudelft.nl,DelftUniversityofTechnology,FacultyofTPM,Netherlands

ABSTRACTNew methods and tools have been developed to support sound decision-making under deepuncertainty.Manyofthosemethodsemphasizetheimportanceofadaptationintheimplementationtrajectoryofdecisionsthatcombinelong-termambitionswithshort-termactions.ExamplesincaseareDynamicAdaptivePolicy-makingand the relatedDynamicAdaptivePolicyPathwaysmethod.Policy pathways for instance may be used as analytical tool to support planning step-by-stepinvestments in (new) infrastructure systems in response to yet uncertain changes in the systemenvironment. These adaptive policy-making approaches require appropriate monitoring andevaluationarrangements.Decision-makersneed tobeable toseehow implementation trajectoriesdevelop and if there is a need to undertake pre-defined adaptive actions, or if a fundamentalrethinkingofpoliciesisneeded,givenunexpectednewdevelopmentsorinsights.

Thisneed for awell-designedmonitoring system is signalled in the literatureondecision-makingunderdeepuncertainty,e.g.byWalkeretal.(2013).However,thecurrentdebateonthisaspectofdecision-makingunderuncertainty (DMUU) reasonspurely from the logic and requirements thatflow from thedecision-makingprocess and the ex-antepolicyanalyticapproaches.This logichassome distinctive features, which have important implications for monitoring and evaluation ofadaptivepolicies.For instance, theuseofadaptationpathwaysas aplanning techniquerequires amentalshift towards a focusonpathways, insteadofafocusonoutcomes,as iscommon inpolicyevaluation.Also,monitoringandevaluation shouldalsoaddressuncertaintiesexplicitly.Thisgoesbeyond the identification ofuncertaintiesas adisclaimer or confounding factor in observing andexplaining theoccurrenceofpolicyoutcomesand impacts.On theotherhand, theexperiencewithcurrentpolicyevaluationscanenrichthedebatewithintheDMUUcommunity.Forinstancenotionssuchas ‘designedblindness’and insightson learningevaluationsinmulti-actorenvironmentshaveimplicationsformonitoringbeyondsignposts,triggersandtriggerresponses.

Meetingtheneedsofadaptivepolicy-makingmethodsthroughapracticalevaluationdesignisclearlyachallenge.TheDeltaProgrammeintheNetherlandscurrentlyfacesthischallengeandthereforeweuse thisprogrammeas fertileground for amore fundamental investigationof the implicationsofadaptivepolicyarrangementsformonitoringandevaluation.Inthiscontribution,wewillconnecttheinsightsavailableondecision-makingunderdeepuncertainty,tothemaincharacteristicsofexistingapproachesforevaluation.Literatureandempiricalevidenceon(water)policyevaluationsareusedtodrawout the implications for the implementationofadaptivepolicyarrangements in theDeltaProgramme. This results in the proposition of a program of requirements and a set of designprinciples forevaluationarrangements thatsupport theadaptive implementationand follow-upofdecisionsmadeunderdeepuncertainty.

Reference

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Walker,W.E.,V.A.W.J.Marchau,J.H.Kwakkel.2013.UncertaintyintheFrameworkofPolicyAnalysis.Chapter9. In:W.A.H.ThissenandW.E.Walker (Eds),PublicPolicyAnalysis –NewDevelopments,Springer,NewYork,pp.215–261(especiallyp.242)

Keywords:monitoringandevaluation,adaptivepolicy-making,deltamanagement,theNetherlands

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17. Macroeconomic Applications Of DMU Methods And Practices

StevenPopper,swpopper@rand.org,RANDCorporation,UnitedStatesofAmerica

ABSTRACTRecentyearshaveseenadvances intool-buildingandapplicationsforpolicydecisionmakingunderuncertainty. Yet, most have been carried out in only a relatively small number of policyenvironments.

Methodsarebeingexpandedinfieldsrelatedtoinfrastructure,water,climateandotherswhichmaybecharacterizedbywell-definedsystemboundaries.Theseapplicationsoccur inareaswhereDMUmethodshavedemonstratednotableutility forpolicydecisionmaking.The value of expanding onsuccess is obvious. A less obvious reason for re-visitation of such policy problems or their newapplication in settings showing great similaritywithwhat has passed before is that researchersthemselvesdevelopmore classknowledgeaboutandawarenessof thenuancesofpolicy in theseareas.Thisworkstothebenefitofbothmethodologistsandpractitioners.Butitraisesthequestionofwhatareasshouldbetargetednext.

Majorpolicy issuesofthedaydonotoccursolely inwell-definedfieldsorwithinrelativelyeasytocharacterize open or closed systems. Not a few of these problems stem from macroeconomicconcerns.ThemethodssupportingDMUanalysescouldpotentiallyplayapathbreakingroleinthisfieldbydoingwhat theydobest:addressproblemswhichhave long resisted treatmentbymoreformal methods to provide greater insight into policy choices, the consequences of choosingalternative courses of action and the bases for making short term policy decisions from theperspectiveoflong-termgoals.

Thispaperwillbebothanintellectualexplorationandapresentationofinitialexamplesoftreatmentof macroeconomic policy questions through DMU tools. It will first characterize this policyenvironmentanddescribethechallengeswhichmaymakeapplicationofDMUmethodsandmodelsachallengedespitethepotentialbenefitsofdoingso.Itwillpresentsomeoftheinitiallessonslearnedfrom such efforts as well as point in the direction of potential solutions and areas for furthermethodologicalandinstitutionalresearch.

Thepaperwill then showcase threepreliminaryexamplesofefforts toapply theRobustDecisionMaking(RDM)methodinthreeproblemareas.Thefirstwillbeatreatmentoftheissuesrelatedtoplanning for preservation of the Social Security (social insurance) system in theU.S.The secondaddresses theproblem facedby themanagersofsovereigndebtwho find that traditionalrulesofthumb for structuring and issuance of a variety of debt instruments no longer provide sufficientassuranceofbothsolvencyandtheabilitytomeetseveralpolicygoals(whichmaywellconflict)inanenvironmentnowperceivedasmorefraughtwithuncertaintythanhadbeenpreviouslysupposed.Thisstudydemonstratesthepotentialvalueofarobustdecisionsbasisforevaluatingchoiceswhenfuture surprise cannotbe ruled out.The lastprovides themostmacro view ofall:balancingU.S.nationaldebtandchoosingamongavarietyofpolicy instruments fordoingso.Again,preliminaryresults demonstrate the value of shifting from more traditional frameworks toward ones moreformally and systematically cognizant of the trade-offs between uncertainty, policy choice andnationalgoals.

Keywords:dmu,rdm,deepuncertainty,macroeconomics,socialinsurance,sovereigndebt,nationaldebt,strategy,policy

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18. Using Causal Models And Exploratory Analysis In Heterogeneous Information FusionFor Detecting Terrorists

PaulDavis,pdavis@rand.org,RANDandPardeeRANDGraduateSchool,UnitedStatesofAmericaWalterPerry,walt@rand.org,RAND,UnitedStatesofAmericaJohnHollywood,johnsh@rand.or,RAND,UnitedStatesofAmericaDavidManheim,dmanheim@rand.org,PardeeRANDGraduateSchool,UnitedStatesofAmerica

ABSTRACTWedescribebasicresearchthatusesacausal,uncertainty-sensitivecomputationalmodelrootedinqualitativesocialsciencetofusedisparatepiecesofthreatinformation.Itisacognitivemodelgoingbeyond rational-actor methods. Having such a model has proven useful when information isuncertain,fragmentary, indirect,soft,conflicting,andevendeceptive.Uncertaintiesareevenworsethan "deep." Inferences from fusion must then account for uncertainties about the model, thecredibility of information, and the fusion methods—i.e. we must consider both structural andparametric uncertainties, including uncertainties about the uncertainties. We use a novelcombination of (1) probabilistic and parametric methods, (2) alternative models and modelstructures,and(3)alternativefusionmethodsthatincludenonlinearalgebraiccombination,variantsofBayesianinference,andanewentropy-maximizingapproach.Initialresultsareencouragingandsuggest that such ananalytically flexible andmodel-based approach to fusion can simultaneouslyenrichthinking,enhancethreatdetection,andreduceharmfulfalsealarms.

Keywords:Exploratoryanalysis,Exploratorymodeling,Fusion,Uncertaintyanalysis

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19. Better Integrating Theory And Practice In Deep Uncertainty Decision Science

CaseyHelgeson,casey.helgeson@gmail.com,LondonSchoolofEconomics,UnitedKingdomofGreatBritainandNorthernIrelandKatieSteele,K.Steele@lse.ac.uk,LondonSchoolofEconomics,UnitedKingdomofGreatBritainandNorthernIreland

ABSTRACTPracticalmethodsandtoolsforsupportingdecisionmakingunderdeepuncertaintyaredevelopingquicklyandwillbeused evermorebroadly given—among other applications—a loominghost ofclimate change adaptationdecisions.Philosophers, economists,and other researcherswho take amoretheoreticalperspectiveondecisiontheoryhavesofarcontributed lesstothisfieldthantheymight have done, one reason being poor understanding across disciplinary boundaries. Manydecisiontheoristswhoencounterpracticalmethodssuchasrobustdecision-making(RDM),decision-scaling, adaptive policymaking, and adaptive pathways [3, 2], are inclined by the habits of thediscipline to focuson thedecision rule—themethodof comparingactsanddeterminingwhich isbest.Butpracticalmethodsoftenlackadiscernibledecisionrule.RDM,forexample,givesnoadviceabout how to balance robustness against cost and other considerations in the final decision. Inpractice,thisisnotaproblembecausedecisionmakersarecomfortabletakingthisfinalstepwithoutadditionaladvice,but tomore theoreticalresearchers it looks like avoidrightwhere thedecisionmodelshouldbemostexplicit.Conversely,thepartsoftheappliedmethodswhere,sotospeak,theaction is takingplace,arenoteasilymappedonto theusualconcernsofmore theoreticaldecisiontheorists.

Inthisresearch,weanalysetwoapproachestodecisionsupportunderdeepuncertainty:RDMandadaptivepathways,andwecharacterisetheinnovativeaspectsofthesemethodsintermsthathelptobetter locatethemwithinthebroadertheoretical literature.Thefirststep isrecognisingthatthesemethodsarebestcharacterisedasapproachestodecisionframingratherthandecisionmaking(or,similarly,theyaddressthetaskofthedecisionmodellerratherthanthedecisionmaker).Thesecondstepischaracterisingthechallengestodecisionframingunderdeepuncertaintythatthesemethodsaddress,anddescribingtheirstrategiesinmoregeneralterms.Hereweturntoarecentdiscussionofthetypesofuncertaintythatarebracketedoridealisedawaywithintypical‘smallworld’framingsofdecisionproblems [1],andwe redescribeRDMandadaptivepathwaysas strategies formanagingtheseuncertaintiesintheframingofdecisionproblems.

Thedecisionruleisnottheonlylocusfornormsofgoodreasoning;normsofdecisionframing,whiletheywillnecessarilybelessformal,areequallyimportanttoanoverallphilosophyofmanagingdeepuncertainty.Greaterappreciationthatthis iswhatthepracticalmethodsoffermayhelpclarifythecontributionsthatthesemethodsmaketodecisiontheory,andalsohelprecruitmoretheoreticianstofurtherdevelopthosemethods.

References:

[1]Bradley,R.andM.Drechsler(2013).Typesofuncertainty.Erkenntnis,1–24.

[2]Ranger,N.,T.Reeder,andJ.Lowe(2013).Addressing‘deep’uncertaintyoverlong-termclimateinmajor infrastructureprojects:Four innovationsoftheThamesEstuary2100project.EUROJournalonDecisionProcesses1(3-4),233–262.

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[3]Walker,W. E.,M.Haasnoot, and J.H.Kwakkel (2013).Adapt or perish: a review of planningapproachesforadaptationunderdeepuncertainty.Sustainability5(3),955–979.

Keywords:decisionframing,smallworlds,RDM,adaptivepathways

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20. Deep Uncertainty In Landslide Modelling For Urban Risk Reduction In DevelopingCountries

SusanaAlmeida,susana.almeida@bristol.ac.uk,UniversityofBristol,UnitedKingdomofGreatBritainandNorthernIrelandLizHolcombe,Liz.Holcombe@bristol.ac.uk,UniversityofBristol,UnitedKingdomofGreatBritainandNorthernIrelandFrancescaPianosi,Francesca.Pianosi@bristol.ac.uk,UniversityofBristol,UnitedKingdomofGreatBritainandNorthernIrelandThorstenWagener,Thorsten.Wagener@bristol.ac.uk,UniversityofBristol,UnitedKingdomofGreatBritainandNorthernIreland

ABSTRACTLandslide risk is increasing formany informalurban communities indeveloping countries in thehumid tropics, inparticular for those thataresituatedonhighlyweatheredresidualsoils thatarealreadysusceptibletorainfalltriggeredslides.Rapidunplannedurbanisation–alteringslopecover,topography,loading,drainage–andchangingclimatemayfurtherexacerbateurbanlandslideriskinthe future. Slope stability assessment can be used to guide decisions about themanagement oflandsliderisk,butitsusefulnessmayberestrictedbyhighlevelsofuncertaintyinmodelpredictions.Manyoftheseuncertaintiescannotbeeasilyquantified,suchasthoselinkedtoclimatechangeandfuture socio-economic conditions. Addressing this deep uncertainty requires the development ofrobustpoliciesthatareexpectedtoperformadequatelyunderawiderangeoffutureconditionsandother uncertainties (e.g. of subsurface characteristics). In our study, the CoupledHydrologyAndStability Model (CHASM) has been combined with local knowledge of slope characteristics todiagnose themost important drivers of landslides in informal urban communities in the humidtropics.WeassesstheimpactofdeepuncertaintyonslopestabilitypredictionsinCHASMthroughathorough analysis of the feasible input space using structured approaches including CART andregional sensitivity analysis, as well as advanced visualization tools. Our results highlight keyuncertainties and thresholds influencing slope failure, and provide valuable information to guideimproved landslide hazard management. Our findings highlight the potential of robust decisionmaking to aid decision support for landslide hazard reduction and risk management underconditionsofdeepuncertaintyindevelopingcountries.

Keywords:landslidehazard,deepuncertainty,sensitivityanalysis,robustness

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21. Deep Uncertainty And Plain Uncertainty: Solving Everyday Problems First For CreatingInstitutional Capacity In Developing Countries

GeorgedeGooijer,georgedegooijer@icloud.com,NetherlandsMinistryofForeignAffairs,NetherlandsHansvanderKwast,h.vanderkwast@unesco-ihe.org,UNESCOIHE,Netherlands

ABSTRACTClimatechange iscertainlyhappening,but theeffectsaredifferenteverywhere.Tomake therightdecisions,attherighttime,governmentsneedinformationandanalysis.Thespecificinformationandanalysis for each country is currently not or sparsely available. This concept note describes thesupport for such creating this capacity in developing countries. Climate change and othermajordriversthataffectwaterarenotclearcut.There isaneedformonitoringand ‘thinkingcapacity’atnational level to dealwith climate change. Securing a trustworthy, good qualitymonitoring andpolicyanalysis isessential forgovernments.But inmany countries this trustworthy,goodqualitymonitoring and policy analysis are not (yet) there, and if they are there they are threatened bycompetingfinancingneeds,misuseoffundsandbrain-drain.

Climatechangeistoouncertaininitseffects.Countriesneedasolidsetofdataandasolidthinkingcapacity todetermine the specificsof theircase,and the reactionsneeded.Experience (aoBenin)learns that national level institutions alone are vulnerable and lack specific capacity andquality.Definingnationalinstitutionsandtheirkeyresults‘internationalpubicgoods’allowsformoredirectsupport.Institutionscouldbefinancedprovidedtheyadheretocertainprinciples,andsecurespecificqualitystandards.

TheDeltaapproachasdevelopedinNLisbasedonhandlinguncertainty.Theapproachisbasedonadynamic policy analysis where political commitment was secured to take action once specificthresholds have been reached. The approach requires models, policy-analysis capacity andmonitoring. The approach could be applied in developing countries,but for this the institutionalcapacityneedstobesecured.

Both tracks come to the same conclusion: climate change adaptation requires national levelinstitutionsthatprovideuninterrupteddataandmodelstofollowthewater-systems.

Ithasbeeneasy to find funding forprojectsaimedatcreating institutes.Butsustained funding tokeeptheseinitiativesafloatiswhatisneeded.

There is an endless series of smaller and bigger studies being done on and about developingcountries. Impetus,UNWater info sheets:after50yearsof capacitydevelopment, thedevelopingcountriesarestill‘objectofstudy’,notpartners.

InBeninanationalinstitute,aseriousmonitoring,anintegrateddatabaseandapropermodellingofbasinsaretakingplace.Aseriouspolicyanalysisofthemajorbasin(theOueme)wasdone.Butthenational institute lost a major part of its financing after a fraud case in a program that itwasdependingon.

Thesituationshowshowanessentialtoolforansweringtoclimatechangechallengescaneasilybecompromisedbyeverydaylife.

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In thisarticle it isargued that amoreglobalresponsibility isneededand is feasible tosecure themonitoring,modellingandpolicyanalysisatnationallevel.

Keywords: DEEP UNCERTAINTY, CLIMATE CHANGE, NATIONAL WATER INSTITUTE, LOCALAPPLICATION,INSTITUTIONALDEVELOPMENT,METADATABASE

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22. A Goal-Oriented Approach For Deciding On Policies Under Deep Uncertainty

AdnanRahman,adnanrahman64@gmail.com,CambridgeSystematics,NetherlandsWarrenWalker,w.e.walker@tudelft.nl,TUDelft,NetherlandsVincentMarchau,v.marchau@fm.ru.nl,RadboudUniversity,Netherlands

ABSTRACTIn situations where the future is not knowable, traditional analysis and tools evaluate theattractiveness (benefits and costs) of variouspolicy choicesunder a limited set of futures.Thesebenefitsandcosts,however,canchangedramaticallyovertimeasnew informationandknowledgebecomeavailable.Thus,makingachoicebasedontheseestimatesislikelytoleadtoaflawedpolicy.Inthispaperweproposetwothings:1)thatpolicymakersfocusonbroadersocietalgoals,and2)thattheyexplicitly link theattractivenessofapolicy to itsperformancewithregards toreaching thesegoals.Wemakethisclearwithanexamplebelow.

Fortransportpolicymakers,handlingroadcongestionhasbeenacontinuouschallengeforthelast50years. The attractiveness of policy options for reducing road congestion has been traditionallyevaluatedbyestimating theircontributions toreducing travel time lossesand loweringemissions,relative to the cost of doing so. Thus, a policy option can be attractive even if it delivers smallreductions.Butthereisnoexplicitlinkbetweentheattractivenessofapolicyoptionandahigh-levelpolicygoal.Also,thereisnoconsiderationof,forexample,theoverallairquality,ortheexperiencewithregardstothereasonwhythetrip/travelisbeingundertaken.Alternatively,considertheissueofroadcongestion from thegoal-orientedperspectivewearesuggesting.Assume that theexplicitgoalistoreducetraveltimelossesbyX%andemissionsbyY%.Thenpoliciesthatbringaboutlargerreductionswillbemoreattractivethanpoliciesthatbringaboutsmallerreductions.But,wecanalsoaskwhetherreducingroadcongestionistherightquestion.Abetterquestiontoaskmaybehowwecanimprovethecommutingexperience,ortheshoppingexperience?Byconsideringquestionssuchas these,we can considerably broaden the range of options, beyond the range of only transportpolicyoptions,tobeconsidered.

Becauseofdeepuncertainty,theevaluationoftheoptionsshouldbedonewiththeparticipationofthestakeholders.Inthispaper,weproposethatapromisinginitialpolicycouldbechosenbasedonconsensusamongstakeholdersthat,regardlessoftheirsubjective,anduncertainexpectationsaboutthefutureandtheirpreferences,theinitialpolicywillcontributetoreducingtheproblem.Theinitialpolicyshouldincludeflexibilityandadaptivity(so,nolock-ins),enablingadjustments(i.e.changesinthepolicy)asthefutureunfolds.Thestakeholdersneednotagreeontherestofthepolicy;infact,thedifferencesamongthemshouldbemadeexplicitandacknowledged.Amonitoringsystemwouldbeestablished,andpolicychangeswouldbeagreedupon, incaseof thefailureofoneormoreof theassumptions underlying the initial policy (i.e., if someone else’s guess about the futurewere thecorrectone).Thepolicywould,therefore,beadaptivebutwouldbebasedonBayesianthinking(intermsofsubjectivejudgments)andpublicparticipation,ratherthantraditionalanalyticapproachesandreflectingthepublic’swillingnesstopaytoreachtheunderlying,long-termgoals.

Keywords:policymaking,deepuncertainty,goaloriented

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23. Planning For Uncertain Futures In Defence

SimonCollander-Brown,sjcbrown@dstl.gov.uk,Dstl,UnitedKingdomofGreatBritainandNorthernIreland

ABSTRACTTheUKMinistry ofDefence is required, by the practicalities of cost and lead time for research,procurements and changes in force structure, to make long term “strategic” plans which drivecurrentspending.Howeverthefutureisveryuncertainand,inthecaseofmilitarypolicydecisionsonspendingmadenow,canchangethefuture,asalliesandpotentialopponentschangetheirplansinreactiontothosedecisions.

Inplanning formilitaryoperationscommandersarereminded toconsider that “Theenemygets avote”,meaningthat“enemy”decisionswillhaveatleastasmuchimpactonplansasthecommanders’own,making any plan in effect a starting point for a complex adaptive system,with intelligentdecisionmakersactively trying todisrupt theiropponentsplans.For long termstrategicplanningthiscomplexityiscompoundedbothintermsoftheuncertaintyinwhotheopponentmightbe,whattheir objectives and capabilities are and the timescale inwhich those uncertainties have time togrow.

Althoughplanningforcomplexfuturesisaproblemformanyorganisations,theadditionallayersofcomplexity facedbyDefencemakes theproblemunusuallydifficult.Dstlhasrecentlyworkedwithacademia,throughseparatecollaborationswithLancasterandSouthamptonUniversities,toexamineifandhow the latest thinkingcouldbeapplied to theproblemsofdefenceplanning.This talkwilldescribe the layers of uncertaintywhich are faced by defence planning and the results ofDstl’sexaminationofthepotentialmethodsforaddressingthiscomplexity

Keywords:Defence,StrategicPlanning,Complexity,Uncertainty

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24. Hindsight Analysis Identifies Deep Uncertainty In Infrastructure Planning

MarcNeumann,marc.neumann@bc3research.org,BC3-BasqueCentreforClimateChange,SpainJörgRieckermann,Joerg.Rieckermann@eawag.ch,Eawag,SwitzerlandThomasHug,th.thomas.hug@gmail.com,HunzikerBetatechAG,SwitzerlandWilliGujer,gujer@ethz.ch,ETHZurich,Switzerland

ABSTRACTThe planning and design of built infrastructure with large life expectancy requires long-termdemand-andcapacityprojections.Theseprojectionsaredeterminedbyextrapolatingpropertiesofthecurrentsystemoverthedesignhorizon.However,onceinfrastructureshavebeencommissionedit isnotverycommon tocompare theoutcomesagainst theoriginalplanningassumptionsand toreveal thediscrepancybetween the two.Conducting such a comparison forpastdesigndecisionsallowsustorevealphenomenathatareassociatedtosourcesofdeepuncertainty.

Weanalysedthelong-termevolution(160years)ofanurbanwastewatersystemandidentifiedtheforcesthatdrivethesystemoutsideoftheregionofplanningassumptions(Neumannetal.,2015).Forbothendogenousandexogenousdrivers,weassessedthetimescalesatwhichtheyworkandthewaytheyinteractwithoneanother.

First, thecasestudy illustrateshowdrivers fromvariousdomains,suchaseconomic,medicalandengineering, influence thesystemstateand theplanningprocess.Second,we found that the time-scales at which drivers change are repeatedly shorter than typical life-times of wastewaterinfrastructures.Inmanycasesweobservedunexpected,fastandabruptchangesinthesedrivers.Wewitnessedhow spontaneous adaptation takesplace: i.e.how the agentsbecome aware of systemchangesandhowtheyreacttothem.

Our findingsshow that thesystemontologychangesover time.Wedetectedchanges in: thesetofimportant drivers, the interactions between drivers, the system boundaries, the objectives andgoverningparadigms.The realisation thaturbanwastewater systemsbehaveas complexadaptivesystemisinstarkcontrasttotherationaleofdesigninglong-livedinfrastructurebasedonprojectionsorscenarios.

Hindsightanalysiscanbeusefulindifferentways:Itcanactasasafeguardagainstoverconfidenceindesignprojects,helpidentifyingalternativewaysofserviceprovisionwithhigherflexibilityorusedtotestwhetherdecisionsupporttoolscurrentlyproposedfordealingwithdeepuncertaintywouldbeabletohandlethedetectedphenomena.

Reference:

Neumann,M.B.,Rieckermann,J.,Hug,T.andGujer,W.(2015)Adaptationinhindsight:Dynamicsanddriversshapingurbanwastewatersystems.JournalofEnvironmentalManagement151,404-415.

Keywords:Urban Infrastructure,Wastewater,Planning,Adaptivemanagement,Deepuncertainty,Complexity,Hindsight

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25. A Multi-Method Approach To Evaluate The Robustness Of Policies In The Dutch GasSector

SibelEker,s.eker@tudelft.nl,DelftUniversityofTechnology,NetherlandsElsvanDaalen,c.vandaalen@tudelft.nl,DelftUniversityofTechnology,Netherlands

ABSTRACTThelong-termdevelopmentoftheDutchgassectorisfacedbydeepuncertainty,asmanyothergasmarketsover theworld.Thepolicyobjective in the sector isproviding a secure, sustainable,andaffordablegas supply.However,notonly the inherent conflictsbetween theseobjectivesbutalsoseveral deep uncertainties regarding the development of renewable and non-renewabletechnologies, societal acceptance and institutional aspects impede the achievability of these goalsand obscure policy making. To aid decision making, potential policies should be systematicallyanalyzed intermsoftheireffectivenesstodealwithmultipleconflictingpolicyobjectivesandwithdeepuncertainties.

Adoptinganexploratorymodelingapproach,suchananalysisisconductedinthisstudy,basedonalargesetoftransientscenariosgeneratedbyasystemdynamicssimulationmodel.Aframeworkhasbeen developed and implemented on this set of scenarios, to address three aspects of decisionmakingwithmultiplemethodologicaloptions:Todealwiththeuncertaintyaspect,therobustnessofeachpolicyacrosstheuncertaintyspaceiscomputed,withvariousexpectation-based,regret-basedandstatisticalrobustnessmetrics.Todealwith themultiplicityofpolicyobjectives, fourdifferent,butsimpleandtransparent,multi-criteriamethodsareused,suchasalexicographicordering,ortheadditivevalueofrobustnessvaluescorresponding toeachpolicyobjective.Lastly, todealwith thetime aspect, such multi-criteria problems are solved statically with metrics which reduce thetransient nature of scenarios into a singlemeasure, or dynamically in each year in the scenariohorizon(e.g.50years).

The results showed a strong method and time-dependence, yet some policies demonstratedconsiderable robustness against methodological choices, such as the subsidization andcommunicativestimulationofrenewablegasproduction.Namely,thesepoliciesreceivedtoprankswithmanyrobustnessmetrics,multi-criteriamethodsandfor longdurationsoftime.Basedonthisanalysis,noneofthemethodologicaloptionscanbearguedtobestrictlybetterthantheothers,sincethese options reflect preferences and decisionmaking processes of the decisionmakers, yet themethod-dependence impliesprobable fallacies if the robustnessandmultipledecision criteriaaredealtwithsinglemethodologicalchoices.

Further investigation of combining robustnessmetricswithmulti-criteriamethods is a potentialpoint ofdeparture for future study.Besides, the changes in thepreferredpolicies identifiedwithdynamic solutions (i.e. in each year) of the multi-criteria problems can be used as a basis fordevelopingadaptivepolicies.

Keywords:gassectorpolicies,energypolicy,robustness,multi-criteriadecisionanalysis

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26. Improving The Reliability Of A Transport Network Under Deep Uncertainties

JulieRozenberg,julie.rozenberg@gmail.com,WorldBank,UnitedStatesofAmericaLauraBonzanigo,l.bonzanigo@gmail.com,WorldBank,UnitedStatesofAmericaXijieLv,xlv@worldbank.org,WorldBank,UnitedStatesofAmerica

ABSTRACTRoad transport networks are vulnerable to many shocks, and in particular to extreme weatherevents. Floods, for instance, can cause the partial or total disruption of network links, thereforeforcing roadusers to takealternative routes –often longeror inworse conditions than themainroad. A malfunctioning road network may lead to high logistics costs,which in turn may limitcountries’competitivenessandproductivityandsloweconomicgrowth.Thisstudyseekstoincluderesilience to shocks in transport planning, to improve a region’s transport infrastructure andaccelerateeconomicgrowth.

Weproposetohelppolicy-makersanswer:

• Whatisvulnerabilitytofloodsofcriticallinks,nowandinthefuture?

• Whatinvestmentoptionsmay improvethereliabilityofthese links–that is, increasetheirrobustnesstouncertainfutureconditions--inacosteffectiveway?

First,wecalculatethecriticalityoflinksexposedtofloods.Wepre-selectlinkswithhightrafficandweassesstheircriticalityusingthetechniqueofinterdiction,whichcalculateschangeintotalcostoraccessibilityinthenetworkwhenalinkisdisruptedordegraded.

Wethenidentifythecriticallinksthatarelocatedinflood-proneareas.Weconsidermanypossibleevents:weusehistoricalrainfallaswellasdifferent futureclimatechangescenarios,and foreachrainfall scenariowe look at the links exposed to different return period events. In addition, forclimate change scenarios,we considerdifferentGHG concentration scenariosanddifferentGlobalCirculationModels(whichdisagreeonprecipitationchangesattheregionalscale).Wethenselect,among themost critical links, the ones that are themost exposed to floods. For those links,wecalculateexpectedannuallosses,consideringtheuncertaintyonfloodduration,onthepercentageoftrafficthatcanusetheroadduringfloodsandonthetimeandcostofreconstruction.

Finally,welookfortheinvestmentoptionsavailabletoimprovethereliabilityofthesystem,thatistosay itshighdegreeofoperabilityunderanycircumstances.Forall links thatare foundexposed tofuture floodeventsamong themost criticalones,we look for the investmentoptionsavailable toreduceeithertheircriticality–forinstancebyincreasingredundancy,i.e.buildingalternativeroutes–ortheirvulnerability–forinstancebymakingtheroadmorepermeable.

Tocompareinterventions,wecalculatetheminimummaximumregretbroughtbyeachinvestment(usingthenetpresentvalueofthe interventionoranaccessibility index)acrossa largenumberofscenarios (combining uncertainty on climate change and on the impacts of floods on disruptioncosts).Weeventuallyexhibitthetrade-offsbetweenthedifferentpossibleinterventionsandchoosethebestoneusing asocialutility function that incorporates thedecision-makers’objectives (cost,reliabilityandothers).

Keywords:roadnetworks,robustdecisionmaking,floods

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27. Long-Term Strategic Planning For A Resilient Metro Colombo: An Economic Case ForWetland Conservation And Management

JulieRozenberg,julie.rozenberg@gmail.com,WorldBank,UnitedStatesofAmerica

ABSTRACTThisisthefinaliterationofastudythatwaspresentedlastyear

TheColomboMetropolitanRegion(CMR)facesrecurrentfloodsthatthreatenitslong-termeconomicdevelopment. Future flood risk in CMRwill keep increasing due to rapid urbanization, economicgrowth pushing for investments from both the public and private sectors in flood prone areas;changes in land-use (agriculture, transportation, housing development, and other new projectsopportunistically locatedinfloodretentionareasetc.);combinedwithnewrainfallpatternscausedbyclimatechange,bringingmorefrequentandintenserainfallforlongerperiodsoftime.

The Metro Colombo Urban Development Project (MCUDP) is delivering the last set of hard-engineeringsolutionsavailabletothecitytoreducetheimpactoffloodsfortoday’sreturnperiodof30 years.TheColombourbanwetlandshavebeendetermined and taken into consideration as acriticalcomponentofthecity’sfloodreductionsystem,essentialtothe long-termdevelopmentandurbanresilienceoftheCMR,astheyformnaturalinfrastructurethatcurrentlyattenuatesandstoresfloodwateracrosstheCMR,reducingimpactsonpeopleandassets.

ARobustDecisionMakinghasbeenundertakentoexaminethevalueofwetlandstotheCMR,bothintheshort-termandlong-term,andidentifywhatarethemostviablestrategiesavailabletoincreasethe city's flood resilience in anunclear future (in terms of climate change andpatterns ofurbandevelopment).Thishas involved theuse ofnumerous hydrologicaland vulnerability scenarios toexaminethemostrobustapproachestofutureplanningandmanagement.

TheanalysishasdeterminedthatifallurbanwetlandsacrosstheCMRcatchmentwerelost,insomescenariostheCMReconomywouldhavetocopewithanannualaveragefloodlossofapproximately1%ofColomboGDP,whichisintheorderofmagnitudeoftheflooddamagesexperiencedin2010.

Economic analysis of selectedwetland benefits including flood protection, carbon sequestration,climate regulation through reduced use of air conditioning nearwetland areas andwastewatertreatmenthasdemonstratedthatannuallythewetlandsareworthbetween10to12billionRStotheCMR.Thisfarexceeds,forexample,theeconomicbenefitsoflakes,whichprovideareducedrangeofbenefits onlyworthbetween 1 to 2billionRS annually. In addition, if thepotential income fromrecreation, now being demonstrated at the pilot wetland visitor centres at Beddegana andThalawathugoda, is included in the analysis, then annual income for thewetland complex couldincreasetobetween16to18billionRSannually.

Finally, a comparison ofwetland protectionwith land-infilling and development shows that thislatteroption isonlybeneficial inscenarios inwhich theKelaniriver is lowandmore than60%ofprofits from landdevelopmentcanbesharedwithall inhabitants inColombo.Thosescenariosareunlikely and even undesirable, because a low Kelani river would bring water supply issues.ConservingthewetlandsinColombowasthereforedeterminedtobethebestoptionaccordingtothedecisionmakers’criteria.

Keywords:robustdecisionmaking,urbanfloods,wetlands

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28. Adaptation Pathways In Practice: Future Challenges

PieterBloemen,pieter.bloemen@deltacommissaris.nl,StaffDeltaProgrammeCommissioner,NetherlandsTimReeder,tim.reeder@environment-agency.gov.uk,EnvironmentAgency,UnitedKingdomofGreatBritainandNorthernIreland

ABSTRACTApresentationwillbegivenreflectingontheimplementationofadaptationpathwaysintheUKandNL.ItwillcoverwellknownexamplessuchastheThamesEstuary2100planandtheDutchDeltaProgrammeaswellasdevelopinguseinotherareassuchaswaterresourceplanningforLondonandcoastalplanninginEngland.

Commonissuesandchallengeswillbehighlightedincludingmonitoringofindicatorsandtriggersforchangingoptionsintermsoftimingorchoiceofoption.

Theneedforbettertechniquestolinkmonitoringofindicatorstoclimatechangescenarioswillalsobeoutlined.

Alsowewilltouchonchallengesforthefurthermethodologicalelaborationoftheadaptiveapproach,including:

- theuseoftransformationalstrategies

- the‘evaporation’ofshorttermadvantagesoflongtermoptions

- theeffectivenessofadiversesetofparallelstrategies

- determiningtippingpointsinsituationswithlargenaturalvariability

- maximizingbroadcommitmentinsituationsoflowpredictability

Thepresentationshouldprovideapractitioner’sviewofhowtodevelopandimplementadaptationpathwaysaspartoflongtermstrategydevelopmentandgiveinsightgainedfromthisexperiencetotheirfutureuse,monitoringandevaluation.

Keywords: adaptation path ways, climate change, strategy development, methodology, practice,challenges,monitoringandevaluation

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29. Discount Rate And The Cost Of Capital

StephaneHallegatte,shallegatte@worldbank.org,WorldBank,FranceAdrienVogt-Schilb,avogtschilb@worldbank.org,WorldBank,France

ABSTRACTDevelopingcountriesanddevelopmentbanksoperateundertightcapitalrationingandthisneedstobeaccounted for inprojectaccounting.Pragmatically, this isoftendone through theuseofhigherdiscountrate,supposed torepresent ahigheropportunitycostofcapital.Here,weshow that thispractice leads to asuboptimalprojectportfolio,especially for long-termprojectsandwhen futurecapitalrationingisuncertain.

Projectevaluationandselectionneedtoaccountfortwocomponents:(1)preferencesregardingthevalueattributed to futurecostsandbenefits;(2)capitalrationing.Bringing these twocomponentsintooneparameter,thediscountrateisinappropriate:tightercapitalrationingshouldnotaffectthebalance between short-term and long-term costs and benefits. Instead, we suggest to use twoparameters:thediscountrate,basedonethicalconsiderationsandtimepreferences,andtheshadowpricecapital,thatrepresentscapitalrationing.

Introducingthesetwoparametersallowsforanappropriateinvestigationoftheuncertaintyrelatedtothesetwoinputsintodecision-making.

Keywords:discountrate,capitalrationing,opportunitycostofcapital,decision-making

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30. Flexibility In Design: A Procedure For Effective Proactive Planning Of FloodManagement Infrastructure Under Uncertainty

KimSmet,kimsmet@fas.harvard.edu,HarvardUniversity,UnitedStatesofAmericaRicharddeNeufville,,MassachusettsInstituteofTechnology,UnitedStatesofAmericaMaartenvanderVlist,maarten.vander.vlist@rws.nl,Rijkswaterstaat,MinistryofInfrastructureandEnvironment,Netherlands

ABSTRACTDevelopedcountriesaround theworldare facing theemergingchallengeofhow tosystematicallyand efficiently approach the process of replacing ageing infrastructure assets. These long-terminvestmentdecisions inphysicalassetsare increasinglycomplicatedbynon-stationarity innaturalsystems. Increasing thedegreeof flexibilityof infrastructuresystems isamethod tosafeguard theefficacyofcurrentdesigndecisionsgivenfutureuncertainty.

This paper presents a procedure for effective and proactive planning and design of floodmanagement infrastructure, against uncertain future flooding threats. This procedure providesinsightsabouthow long-termreplacementplanningcanbestructured insuch awayas to identifyopportunities to incorporate flexibilitywithin aphysicalstructure,enablingcontinuedsatisfactoryperformanceofthesystem inthefuture inspiteofchanges intheexternaloperatingenvironment.We specifically apply the concepts of Real “In” Options to the process of reinvesting in ageinghydraulic structures, evaluating the relative economic value associated with different possibleoptionstobuildflexibilityintoastructure.

In response to past criticisms ofRealOptions, this procedure incorporates a number of distinctmethodologicalfeatures,relativetomorestandardapplicationsofoptions.First,acknowledgingthedeeplyuncertainnatureofclimateuncertainty,distinctscenariosareusedtodescribeuncertaintiessuchassea levelriseandfutureprecipitation.Withinthesescenarios,probabilitydistributionsareused to characterize remaining uncertainties of interest, forming the basis for an analysis offlexibilityusingMonteCarlosimulation.Second,insteadofutilizingrelativelyarbitrarydecisionrulestodeterminewhentheflexibilitybuiltinastructureshouldbeexercised,thisprocedureincorporatestheconceptofAdaptionTippingPointsasdefiningthemomentwhenimplementationofthebuilt-inoption is first warranted. Finally, we explicitly take into account the fact that most hydraulicstructures fulfilldifferent functions.Thismethod allows exploration ofdifferent options aimed atproviding flexibility in the fulfillment of a specific function, and towhat extent these individualoptionsinteract.

ThisprocedureisdemonstratedusingthepumpingstationofIJmuidenontheNorthSeaCanalintheNetherlandsasanexample.Here,replacementofIJmuidenwithabasecasefixeddesign(alargenewpumpingstationatthelocationofIJmuiden)isevaluatedrelativetomoreflexibledesignsthatembedoptions,allowingthephasedexpansionofadditionalpumpingcapacityandflooddefensecapabilitiesofthestructure,asnecessary.Thedifferentdesignalternativesarecomparedbasedonanumberofdifferenteconomicindicators.Resultsshowthattheincorporationofflexibilitywithinthedesignofhydraulicstructureshasthepotentialtoimprovethelifetimeeconomicperformanceofthestructure,ascomparedtomoretraditional,lessflexibledesigns.However,theaddedvalueresultingfromtheincorporationofflexibilityisshowntobebothfunctionandscenariospecific.

Overall,giventhelong-livednatureofmostengineeringstructuresandthehighcostofanyupgradework after initial construction, necessary replacement planning in fact offers a valuable and

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relativelyinfrequentopportunitytoreassessthesystemandincorporateadditionalflexibilitytocopewithamultitudeofpossiblefutures.

Keywords:flood,planning,flexibility,RealOptions,climatechange

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31. A Theoretical Framework For Developing Resilience To Urban Pluvial Flooding

FilipBabovic,filip.babovic13@ic.ac.uk,ImperialCollegeLondon,UnitedKingdomofGreatBritainandNorthernIrelandAnaMijic,ana.mijic@imperial.ac.uk,ImperialCollegeLondon,UnitedKingdomofGreatBritainandNorthernIrelandKavehMadani,k.madani@imperial.ac.uk,ImperialCollegeLondon,UnitedKingdomofGreatBritainandNorthernIreland

ABSTRACTThe riskofurban flooding isan issueexperiencedglobally (Field,Barros,Mach,etal.,2014).Thelikelihoodoffloodsanditsassociatedimpactsisincreasingduetoglobaltrendsinurbanisationandclimate change. Climate change is driving hydrological non-stationarity (Milly, Betancourt,Falkenmark,etal.,2008),whichhasleadtothe“endofreliability”forwatersystemssuchaswatersupply and flooddefence (Brown,2010). In addition,urbanisation is contributing to increasinglylarge impermeableareaswhilethe increasingconcentrationofpopulation leadstohigherpotentialeconomic losses at risk to events. There is awidely recognised need to adapt to these changingcircumstances.However,thecomplexityofurbanfloodingsystemsandlargeuncertaintiesinfuturelanduseandclimateprojectionsleadtoaconditionofdeepuncertainty.

There is much to explore within long-term adaptation planning for urban flood protection,particularlyas itcanbedifficult to implement large-scalechanges insuchsettings.Thisworkwillpresentatheoreticalframeworkforlong-termadaptationtourbanpluvialfloodingriskunderdeepuncertainty.Thiswouldencompassdecision-making techniquessuchasAdaptationTippingPoints(Walker,Haasnoot&Kwakkel,2013)alongsideatoolboxofpossiblesolutions.It isenvisagedthatthis toolbox of solutions would encompass engineering solutions, policy recommendations andfinancialmechanisms.This isinresponse totheneedforan integratedholisticwatermanagementframeworkascalledforbyHallegatte(2009).

TheidentificationofpotentialAdaptiveTippingPointsandpotentialpathwayswillbeundertakenforahypotheticalcase.Adaptingtothesethresholdswouldbeachievedbyutilisingdifferentaspectsofthetoolboxofsolutions.Thetoolboxwouldidentifyawidescopeofpotentialsolutions.Engineeringsolutions would revolve around a real options approach to systems design in order to provideflexibility and adaptability within systems to allow for incremental adaptation (de Neufville &Scholtes,2011).There isparticular interest inutilisinggreen infrastructureasapossibleadaptionmeasure against urban pluvial flooding. Policy recommendations would include issues such asregulations on new connections to the sewer systems or limitations on the creation of newimpermeable surfaces through the use of Sustainable Urban Drainage Systems. Lastly, financialinstruments can also act as a resilience measure against climate change particularly againstextremely low frequency events with high consequences, for example the overtopping of flooddefences.

Thesethreesetsofsolutionsaretobemergedwithdecisionmakingtechniqueswithinaformalisedholistic framework.The framework is intended todeliveranurbanpluvial flooddefenseplan thathastheabilitytobeeasilyadaptedtomatchawiderangeoffutureconditions.Thisframeworkwillbe thebasis for further research on applying this framework to anumber of case studies acrossdifferentcountriesandclimates.

Keywords:DeepUncertainty,UrbanResilience,UrbanFlooding

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32. Deep And Shallow Uncertainty In Ecosystem Service Assessments: Some Challenges,Some Progress, And Some Help Wanted

BenjaminBryant,bpbryant@gmail.com,TheNaturalCapitalProject,StanfordUniversity,UnitedStatesofAmerica

ABSTRACTEcosystemservices(ES)arethebenefitspeoplereceivefromnature.Theseincludebenefitssuchaswaterpurificationandfloodprotectionfromforestsandwetlands,pollinationfrombeessupportedby improved bee habitat, and enhanced well-being from tourism and exposure to nature viarecreation.Characterizingthesebenefits--andhowtheychangeasaresultofdifferentdecisions--isanincreasinglycommonendeavorundertakenunderthebannerof“ecosystemserviceassessments.”Such assessments are inherently multidisciplinary on both the substantive and methodologicalfronts,combiningfieldslikeecology,hydrology,economics,andgeospatialsciences.

Unfortunately(andperhapspartlybecauseof)thiscomplexmultidisciplinarynature,uncertaintyinESassessmentshasnotreceived theattention itdeserves –and itdeservesplenty,givenboth thehigh-stakesdecision-orientednatureofmanyESassessments,aswellas thepresenceofmanifolduncertainties,bothwell-characterizedanddeep.Theserange fromparametricuncertainty inpriceaccounting for studies that involve economic valuation, to handling extreme data scarcity andstructural uncertainty in hydrologic processes, aswell as incorporatingmanifestations of globalchangethroughout.

At theNatural Capital Project, a decision-oriented ecosystem servicesmodeling organization,wehaveslowlybutsurelybeenattemptingtoaddressthesechallengesforourownmodelingeffortsandfor those who utilize our open-source software products. This talk will highlight many of thechallenges faced in different ES decision contexts, the nature of many uncertainties dealt with,progress todate and remaining challenges. Some challenges are organizational, such as instillinglessons fromdecision-supportmodeling practice andphilosophy acrossmodeling teammembersand stakeholders from diverse disciplines. Other are computational, given that spatial decisioncontextsoftenrelyonextremely largedatasetsthatrequire intermediateparameterizationsbeforetypical“explorethespace”deepuncertaintytechniquescanbeapplied,orrequireapproximationstootherwise infeasible combinatorial spatial optimization problems. As with other policy analysisefforts,tosupporttheappliednatureofESassessments,thesechallengesmustoftenbeaddressedonarelativelyshorttimescaleandinmannerthatiscredibleandcomprehensibletostakeholders.

We illustratemanyofthese issuesbydescribinguncertaintyanalysisona“WaterFund”which isafinancialvehiclewherebydownstreambeneficiariesorexternalactorspayforconservationorientedinterventions upstream in awatershed. Analysis of the economic benefits of a water fund firstinvolves application of an optimization algorithm to identify the location of conservationinterventions,thentranslationofthoseinterventionstohydrologicmodelparametersandrunningofahydrologicmodel,andfinallydevelopmentandapplicationofvariedeconomicandfinancialmodelstoquantifythebenefitstreamsresultingfromthechangesinwateryieldandsedimentretention.Assuch,waterfundsprovideanidealplatformtoconveyandseeksolutionstothepracticalchallengesofhandlingdeepuncertaintyinESassessments.

Keywords:ecosystemservices,spatialoptimization,spatialuncertainty,economicvaluation,multi-criteriaassessment

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33. Managing Business Risk Under Uncertainty: Development Planning In The Oil And GasIndustry

ThomasHalsey,thomas.c.halsey@exxonmobil.com,ExxonMobilUpstreamResearchCompany,UnitedStatesofAmericaXiao-HuiWu,xiao-hui.wu@exxonmobil.com,ExxonMobilUpstreamResearchCompany,UnitedStatesofAmerica

ABSTRACTThe upstream oil and gas industry is distinguished by its dependence on a poorly understoodsubsurfaceastheultimatesourceofvalue.Allphasesofupstreamactivity:exploration,development,and production, incur significant business risk arising from our incomplete knowledge of thesubsurfaceandofthefluidstherein.Therearetwowaysofdealingwiththisrisk:eitherbytryingtoreduce it through additional data collection and better characterization of the subsurface, or bybettermanagingit,bybetterunderstandingtherangeofplausiblepotentialsubsurfacerealitiesthatareconsistentwithagivensetofcharacterizationdataandtheeconomicimplicationsofthisrange,byselectionactionsthatoptimizereturnovertherangeofuncertainty,andby identifyingpossibleresponses to unfavorable outcomes. In this contribution we discuss the differences betweendevelopment and production (ormore informally, green-field and brown-field) oriented uses ofmodelingand simulation,and then focusondevelopmentplanningapplications,whichattempt toaccountforuncertaintyearlyinanassetlifecycle,whenbothuncertaintyandtheeconomicimpactofdecisionsareattheirmaximum.

Keywords:subsurfaceuncertainty,developmentplanning,modelingandsimulation

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34. Weshareit: A Nexus Approach To Nile Basin Water Resources Management

AbbyM.Onencan,a.m.onencan@tudelft.nl,DelftUniversityofTechnology,NetherlandsBertEnserink,B.Enserink@tudelft.nl,DelftUniversityofTechnology,NetherlandsRensKortmann,L.J.Kortmann@tudelft.nl,DelftUniversityofTechnology,NetherlandsWilThissen,W.A.H.Thissen@tudelft.nl,DelftUniversityofTechnology,Netherlands

ABSTRACTTheNile river is the longest river in theworldwith abasinarea of3,176,543 km.2Thebasin isshared amongst 11 countries, namely Burundi, Democratic Republic of Congo, Egypt, Ethiopia,Eritrea,Kenya,Rwanda,SouthSudan,Sudan,TanzaniaandUganda.TherisingNilebasinpopulationcontinues to put extreme pressure on the quantity of the Nile water resources. The currentpopulationof437millionisprojectedtoincreaseby52%in2030 .Theforestareainthebasinhasshrunkby18%from2005to2009.Asignificantnumberofwatershedsandecosystemshavebeenhighlydegraded,therebydrasticallyreducingthewaterflowfromriversandsprings.AccordingtotheUnitedNationsEconomicCommissionforAfrica,noneoftheelevenNileBasincountrieswillbeabletomeettheirwaterneedsby2025,unlessmajorchangesaremadetoaddressthewatersecuritychallenge.

TheNilebasinwatermanagers lack clear information onhowmuchwaterwillbe available at aparticularplace,dateandtime,tosupporttheirdecision-making.Scienceonsuchacomplexissueaswater may never provide such a clear print. One of the biggest challenges for scientists is toacknowledgethattherewillneverbeaclearprintandfocusonsupportingdecisionmakingamidstdeepuncertainty.Thisrequiresanewwayofthinking,alsoknownasthenexusapproach.Thenexusapproachviewswateras cross-cutting:water is linked toEnergy,Environment,Land,Healthandmanyothersectors.

Thepurposeofthispaperistoassesswhetherseriousgamingcanenablelearningonthevalueofanexus approach.WeShareIt is a computer assisted board game designed to explore the tensionsbetweenenergy,foodandnaturewithintheNileBasin.Thegamecomprisesoffiveselectboardsforcountries that share the Nile Basin, namely Egypt, Sudan, South Sudan, Ethiopia and the NileEquatorialLakesRegion.ThegoalofWeShareIt is togainasmany “happy faces”aspossible.Thegame is played in multiple continuing rounds comprising of a payout round (A) and a waterallocationround(B).InroundA,crops,woodfuelandhydro-electricenergyareharvested,boughtandsold.InroundBtheplayerscanadjusttheirwaterallocationstrategieswiththeaimofmakingtheircitizenshappy.

The paper presents the findings of designing and testing of the game. The paper assesses thecontributionofseriousgaminginsupportingdecisionmakingamidstdeepuncertainty.Theresultofplaying thegamewasan instructivegroupexperienceand abetterunderstandingof the interplaybetweenfood,energy,nature,waterandtrade.

Thepaperconcludes thatseriousgamingholds apromise insupportingchangeofperceptionsonwatertosupportdecisionmakingincomplexbasinswhenthefutureisveryuncertain.Futureworkwillentail the improvementof thegame,basedon comments receivedand theapplicationof thegameintheNileBasin.

Keywords: River Basin Management, Uncertainty, Decision Support, Serious Gaming, TradeoffAnalysis,NexusApproach

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35. Allowances For Evolving Coastal Flood Risk Under Uncertain Local Sea-Level Rise

MayaBuchanan,mayakb@princeton.edu,PrincetonUniversity,UnitedStatesofAmericaRobertE.Kopp,robert.kopp@rutgers.edu,RutgersUniversity,UnitedStatesofAmericaMichaelOppenheimer,omichael@princeton.edu,PrincetonUniversity,UnitedStatesofAmericaClaudiaTebaldi,ctebaldi@climatecentral.org,NationalCenterforAtmosphericResearchandClimateCentral,UnitedStatesofAmerica

ABSTRACTSea-levelrise(SLR)causesestimatesoffloodriskmadeundertheassumptionofstationarymeansealeveltobebiasedlow.However,adjustmentstofloodreturnlevelsmadeassumingfixedincreasesofsealevelarealsoinaccuratewhenappliedtosealevelthatisrisingovertimeatanuncertainrate.Toaccommodate both the temporal dynamics of SLR and their uncertainty,we develop anAverageAnnualDesignLifeLevel(AADLL)metricandassociatedDesignLifeSLR(DL-SLR)allowances[1,2].The AADLL is the flood level corresponding to a time-integrated annual expected probability ofoccurrence (AEP) under uncertainty over the design life of an asset;DL-SLR allowances are theadjustment from 2000 levels thatmaintain current average risk over the design life. Given non-stationaryanduncertainsea-levelrise,AADLLfloodlevelsandDL-SLRallowancesprovideestimatesof flood protection heights and offsets for different planning horizons and different levels ofconfidence in SLR projections in coastal areas. Here we employ probabilistic sea-level riseprojections[3]toillustratethecalculationofAADLLfloodlevelsandDL-SLRallowancesforasetoflong-durationtidegaugesalongU.S.coastlines.

[1]Rootzenetal.,2014,WaterResourcesResearch49:5964-5972.

[2]Hunter,2013,OceanEngineering71:17-27.

[3]Koppetal.,2014,Earth’sFuture2:383-406.

Keywords:coastalimpacts,climatechange,sealevelrise,flooding,adaptation,resilience

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36. Policy Experimentation As A Tool To Deal With Deep Uncertainty

SreejaNair,sreeja.nair@u.nus.edu,LeeKuanYewSchoolofPublicPolicy,NationalUniversityofSingapore,Singapore

ABSTRACTPoliciesarecontinuallybeingdesignedforcurrentandfutureconditionsaboutwhichpolicymakersoften have incomplete or no information at all (Walker et al, 2001). Conventional forecastingmethods suchasMonteCarlo simulationsand statisticalanalysesarenotadequatelyequipped tocapture ‘deepuncertainty’(Walkeretal2010,Brugnachetal2008)asthere is littleagreementonthe choice ofmodels to characterize a system’s variables and their interactions and assign likelyprobabilitydistributions(McInerneyetal2011).Climatechangeisagoodexampleofacomplexandunstructured policy problem that is characterized by a high degree of uncertainty. Given thelikelihoodofnon-linearityinthefutureclimate,theimpactsassociatedwithclimatechangemaybemanifestedtovaryingextents(IPCC,2007).Thispaperfocusesontheroleofpolicyexperimentationtodealwithclimateuncertainty.

Giventheuncertaintiesassociatedwithproblemssuchasclimatechange,scholarsandpractitionersemphasize on adaptation efforts to be “flexible and continuous” with a focus on learning andexperimentation(IPCC,2014).Experimentationisimportantinenablingsociallearningtoovercomesystem “lock-in” and facilitate restructuring of existing social–technical systems for changes innorms, values, goals, processes and actors. Enhanced experimentation and learning can beinstrumental in “keeping pacewith the dynamic drivers and expressions of risk” (O’Brien et al,2012).Pilotsformacommonandimportantformofpolicyexperimentationandinvolvethe“phasedintroductionofmajorgovernmentpoliciesorprogrammes,allowingthemtobetested,evaluatedandadjustedbeforebeingrolledoutnationally”(CabinetOffice,2003).

Using cases of policy pilots in India aimed at adaptation in climate-sensitive sectors such asagricultureandwater (forexample those focusingonweather-based insurance, cropproductivityenhancement, technology innovationandclimate services) thispaperwill firstly, identifyhow thelevel of uncertainty projected in the agriculture andwater sectors affects and is affected by thedesign and scaling-up of specific pilots designed to operate under this uncertainty. AQualitativeComparativeAnalysis (QCA)approach isused tocompare thesepilots foradaptation toprojectedimpactsofclimatechangeonwaterandagriculture.

The secondpartof thepaperwill identify challenges todesignofproportionateadaptationpolicyresponsesunderuncertainty,whichcanalsobeaidedbyexperimentation.Adaptationliteraturehaslargelyfocusedonpoliciesandprogrammesfor“accommodatingchange”ratherthanprocessesfor“consciously creatingalternatives” (O’Brienetal,2012).Questionsofhowmuchandhowbest toadapthavegiven rise to issuesof ‘optimality’, ‘proportionality’and ‘appropriateness’.Studies thattestforoptimalityofadaptationoptionsareonlyrelevantforpre-determinedscenariosthatdonotcover thebroad spectrumofuncertainty (Klein,2003).Determining ‘proportionateadaptation’or‘howmuchadaptationisenough’tomatchthescaleofchangeintheclimateandassociatedimpactsunderdeepuncertainty is an ongoing challenge (Hall et al,2012).TheQCAwill thus also aimatdevelopingatypologyofthepolicyexperimentsandtheiroutcomesbasedonthelevelofuncertaintytheyaredesignedtodealwith.

Keywords: Uncertainty, Climate change adaptation, Experimentation, Proportionality, Pilots,Agricultureandwater

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37. Decisive Moments In Adaptation Planning : Experiences And Challenges

WilThissen,w.a.h.thissen@tudelft.nl,DelftUniversityofTechnology,NetherlandsSaskiaWerners,,WageningenUniversity,NetherlandsMaartenvanderVlist,,WageningenUniversity,NetherlandsAdJeuken,,Deltares,NetherlandsPieterBloemen,,MinistryInfrastructureandEnvironment,Netherlands

ABSTRACTAdaptivedeltamanagementhasemergedinresponsetoconcernsoverlong-term,uncertainclimateand other changes.Key elements of the approach are: to explicitly take futureuncertainties intoaccount,toidentifydecisivemomentsfor(future)decision-making,todevelopadaptationpathwaysovertime,toincludeandvalueflexibility,andtoavoid‘lock-in’.

ThispresentationreflectsonsevencontributionstoarecentspecialissueoftheJournalofWaterandClimate Change. Focus is on the use and elaboration of future decisive moments as parts ofadaptationpathways,andonadaptivedeltamanagementingeneral.Wesummarisemainpointsfromthe papers, put these in a broader perspective and conclude with lessons learned as well aschallengesremaining.

First, the ‘adaptation tippingpoint’concept(ATP -"pointswhere themagnitudeofchange issuchthatthecurrentstrategywillnolongerbeabletomeetitsobjectives")borrowsitsterminologyfromecologicalsystembehaviour.Appliedtoadaptationdecisionmakinghowever,tippingpointsalwayscontain a normative component, and non-desired situations are not necessarily irreversible norfundamentallydifferent.Thisiswhysomeauthorspreferthetermadaptationturningpoint.

Avarietyofcriteriaareproposeddefiningcriticalperformanceofthe‘managedsystem’rangingfromrelativelywell-definedphysical thresholds, tomore complex socio-economicparameters like risklevelsandsocialacceptance.Somepapersdefinemultiplelevelsofcriticalperformance.

Moreover,nexttophysicaldrivers,asetofco-driversmaydeterminetheconditionsthatnecessitateadaptation. Also, a variety of adaptation actions is possible. Next to taking (physical)measures,objectivesmaybealtered,forexamplebyallowingfor lowerperformance levels.Inadditiontotheprojectedviolationofperformancelevels,opportunitiesoriginatinginotherdomainscanbeatriggerfortakingaction.

Anothercomplicationisthattrendsindecisionvariableswithahighnaturalvariability(suchaspeakflows)maybehard todetect.Moreover,appropriate timingofdecisionsalsodependson the timerequiredforimplementationofapolicychange,i.e.,thedecisiontoadaptmayneedtobemadewellaheadofthetimewhenthethresholdisreached.

As a result, the ex-ante assessment of the time frameuntilwhen theperformance of the currentpolicywillbesatisfactory,isfoundtobedifficultifnotproblematic.

We concludewith recommendations: First, there is a need to designmonitoring and evaluationschemes that can handle (a) adaptation criteria that are difficult to monitor or evaluateunequivocally;(b)thepresenceofmultipledriversofchange,and(c)situations inwhichchange isgradual.Second,theapproachshouldbeextendedtoincludedevelopmentsinadjacentfieldsinorderto be able to benefit from opportunities for synergy. Third, the governance dimension requiresfurtherattention,regardingboththefeasibilityofimplementationoffutureadaptationdecisions,and

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themonitoring, evaluation and learning over time. Fourth, there is a need formore clarity andconsistency in theuseof terminology.Fifth, there is aneed fordesigning simplevisualisations tosupporteffectivecommunicationoftheresultsofanalysis.

Keywords: Adaptive delta management, Adaptation pathways, Adaptation Tipping points,AdaptationTurningpoints,Governanceofadaptation

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38. Water Resource Planning Under Uncertainty In The Cauvery River Basin In Karnataka

AjayBhave,a.g.bhave@lse.ac.uk,GranthamResearchInstituteonClimateChangeandtheEnvironment,UnitedKingdomofGreatBritainandNorthernIrelandSurajeDessai,S.Dessai@leeds.ac.uk,UniversityofLeeds,UnitedKingdomofGreatBritainandNorthernIrelandDeclanConway,D.Conway@lse.ac.uk,GranthamResearchInstituteonClimateChangeandtheEnvironment,UnitedKingdomofGreatBritainandNorthernIrelandDavidStainforth,D.A.Stainforth@lse.ac.uk,GranthamResearchInstituteonClimateChangeandtheEnvironment,UnitedKingdomofGreatBritainandNorthernIreland

ABSTRACTUncertain regional climate change impacts and rapid socio-economic changes make long-termplanning of water resources particularly problematic in developing countries. Although highlyrelevant,applicationofRobustDecisionMaking(RDM)approachesindevelopingcountrieshasbeenlimited. From a methodological perspective, RDM studies often involve either a computationallyintensivequantitativeanalysisoraqualitativestakeholderjudgementbasedanalysis.Acomparativeassessmentoftherelativemeritsofeachapproachwouldenhanceunderstandingoftheirrolesandapplicability.Recognizingtheseresearchneeds,theCentreforClimateChangeEconomicsandPolicy(CCCEP)isconductingastudyondecisionmakinginwaterresourcesmanagementunderuncertainfutureconditions inIndia, inwhichakeyaim istocomparesimpleandcomplexRDMapproaches.Thechosenstudyarea istheCauveryRiverBasin inKarnataka(area:~35960sq.km),whichhasaunique combination of underlying vulnerabilities including: observed climatic changes, highgroundwaterextraction,rapidlyexpandingcities, irrigationexpansionandwaterresourceconflict.Applying RDM approaches in such a context requires careful thought and this paper presentspreliminary results from initial stakeholder engagement and a formal stakeholder workshopconductedinBangalore.Stakeholdersincludingacademics,watermanagers,planners,agriculturistsandnon-governmental organizations,discussed key functions of the river and outlined adetailedwater resourcesmodel for key elements of the system. Theworkshop process also allowed theelicitationofcurrentand futurevulnerabilitiesalongwithshortand long-termwatermanagementoptions formanaging envisaged future drivers and stressors.Key aspects of this complexwaterresourcesmanagementproblemwhichwererevealed included: increasedpumping from theriverand excessive groundwater extraction in Bangalore, constraints imposed by the water sharingagreementwithriparianstatesandagriculturalexpansioninupstreamareas.Ongoingworkinvolvesfurther stakeholder engagement to discuss results from the quantitative approach and theirimplicationsforsustainablewaterresourcesmanagementintheCRB-K.

Keywords:robustdecisionmakingapproaches,stakeholderworkshop,developingcountrycontext

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39. Can Information From Adaptive Forestry Management Pathways Support ClimateChange Adaptation? Experience From Forest Planning

MichalPetr,michal.petr@forestry.gsi.gov.uk,ForestResearch,UnitedKingdomofGreatBritainandNorthernIrelandLucBoerboom,l.g.j.boerboom@utwente.nl,ITC,UniversityofTwente,NetherlandsDuncanRay,Duncan.Ray@forestry.gsi.gov.uk,ForestResearch,UnitedKingdomofGreatBritainandNorthernIrelandAnnevanderVeen,A.vanderVeen@utwente.nl,ITC,UniversityofTwente,Netherlands

ABSTRACTTomake sound and robust climate change adaptation decisions, decisionmakers need not onlyrelevant information about risks and uncertainty, but also need to utilise information in theirdecisions. Many discourses from a local to national planning have addressed climate changeuncertainty,mainlybecauseofitspotentialharmfulandhardtopredictimpacts.But,inthecontextofadaptation,and in forestry inparticularly,knowledge ismissinghow theavailable informationfrom impactmodels affects or not decision-making process under deep or inherent uncertainty.Therefore,wea)developednewadaptive forestrymanagementpathwaysmaps including climatechangeimpactsandintrinsicuncertainty,andb)investigatedhowdecisionmakers,inourcaseforestplanners,comprehendandrespondtoclimatechangeuncertaintyandambiguity intheirdecisions.Essentially,theirresponsetouncertaintywillinfluencewhetherornotplannerswillbekeentoapplyadaptationmeasures.

Tocombineclimatechange impactsand intrinsicuncertainty,we incorporatedassessedecosystemservicesintoamapofadaptiveforestrymanagementpathwaysforScotland.Thisnewpathwaysmapbuilduponthedynamicadaptivepolicypathwaysmethoddevelopedby(Haasnoot,Kwakkel,Walker,&terMaat,2013)withmoredetailedspatialandtemporalassessmentofmanagementactionsusingdetailedclimatechangeinformation.WeusedthenovelprobabilisticclimatechangeprojectionsfortheUK (UKCP09) toestimate thedrought risk forecosystem servicesprovidedbyBritish forests,whichprovidethekeycriteriatospecifyexpirydates.TheUKCP09providessubjectiveprobabilitiesabout the future climate -quantifyingdifferentassociateduncertainties.The results for combinedquantifiedecosystemservices intoamapofadaptiveforestrymanagementpathwaysshows,whenand where a specific forest management action reaches its environmental limits.We found, forexample, theneed to adapt Sitka spruce and itsmanagementnow in the lowlands if the limitingthresholdvaluewassetto10%reductionofecosystemservicesfromthebaseline(Petr,Boerboom,Ray,&vanderVeen,2015a).

To evaluate the usability of the forestrymanagement pathwaysmaps in practicewith assessingambiguity – representing uncertainty, we conducted three workshops with forest planners inScotland(Petr,Boerboom,Ray,&vanderVeen,2015b).Weprovidedtoplannersinformationintheformofadaptiveforestrymanagementpathwaysmapsfortheirdistrict.Weinvestigatedchangesinplanners’decisionsaboutforestryactionsrepresentingspecieschoiceandforesttourism,andtheirexpirydates-representingenvironmentalconstraintstoprovisionofecosystemservices.Presentedclimate change informationmodifiedplanners’understandings and frames about forestry actionsand related expiry dates. Comparing ambiguity about different forest management actions, ourresultsshowdiverseresponsescausedbynewclimatechangeinformation.Ambiguityunderstandingresulted inpostponingorbringing forwardseveral forestactions,andalso inmaking itharder forplanners to decide.Overall,planners’ ambiguitywas found tobedependent onplanners’diverse

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frames and difficulty to evaluate multiple ecosystem services. These findings imply that due toambiguityforestplannersmightfindithardtochooserelevantclimatechangeadaptationmeasures.

Keywords:uncertainty,forestry,climatechangeadaptation,forestplanning,ambiguity,framing

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40. Adaptive Planning For The Flexible Expansion Of London’s Water Supply System

IvanaHuskova,iva.huskova83@gmail.com,UniversityCollegeLondon,UnitedKingdomofGreatBritainandNorthernIrelandEvgeniiS.Matrosov,evgenii.matrosov@manchester.ac.uk,UniversityofManchester,UnitedKingdomofGreatBritainandNorthernIrelandJanH.Kwakkel,J.H.Kwakkel@tudelft.nl,DelftUniversityofTechnology,NetherlandsJulienJ.Harou,julien.harou@manchester.ac.uk,UniversityofManchester,UnitedKingdomofGreatBritainandNorthernIrelandJosephR.Kasprzyk,joseph.kasprzyk@colorado.edu,UniversityofColorado,UnitedStatesofAmericaPatrickM.Reed,patrick.reed@cornell.edu,CornellUniversity,UnitedStatesofAmerica

ABSTRACTChangingsocietalneedsand increasingvalueplacedonecosystemservicesrequirewaterresourcesystemstoreactandflexiblyadapttosuchdynamicconditions.Inaddition,thesesystemsmustmeetthemulti-sectordemandsofarangeofstakeholderswhoseobjectivesoftenconflict.Understandingthese conflictsnecessitatesexplorationofmanyalternativeplans to identifypossible compromisesolutionsandimportantsystemtrade-offs.Theuncertaintiesassociatedwithfutureconditionssuchas climate change, population growth, and changing preferences pose further challenges for thedecisionmaking process. Planners therefore seek portfolios of supply and demandmanagementschemesrepresentedasdynamictrajectoriesovertime,whichareabletobeadaptedtothechangingenvironmentwhilstconsideringmanysystemgoalsandplausiblefutures.Yetsuchplansaredifficultto identifydue to the largenumber ofalternativeplans fromwhich to choose, theuncertaintyoffuture conditions, and the computational complexity of such problems. Given these complexities,fixedschedulesofpossible interventionsmayprovide inefficientportfoliosas theyarenotable toadapt as time progresses and uncertainties become known. Instead of scheduling the timing ofpossibleinterventions,rulestoguidetheimplementationofoptionsasthefutureunfoldsmayresultinmore flexible strategieswhere adecision ismadebased on observations onhow the future isactually unfolding. We investigate how this dynamic adaptive policy pathways approach can beappliedand communicated to stakeholderswithin theUK’swater supplyplanning context. Inourstudy,weoptimizeLondon’sfuturewatersupplysysteminvestmentsandtheiradaptationovertimeusingmany-objectivescenariooptimization.Inthisoptimization,weuseanefficientwaterresourcesystemsimulator.Toanalysetheresults,weusevisualanalyticsforexploringkeysystemtrade-offs.Weshowhowthevisualanalysisofsolutionscanaiddecisionmakingby investigatingthe impliedperformancetrade-offsandhowtheindividualschemesandtheirtrajectoriespresentintheParetoapproximateportfoliosmayaffectthesystem’sbehaviour.Decisionmakersaregiventheopportunitytodecideonthebalancebetweenthemanysystemgoalsaposteriori,aswellastakeonlynecessaryimmediateactionsleavingthesystemopentofurtheradaptationwhenneeded.Bydoingso,plannerscanidentifyplausiblepathwaysthattheirstrategymayfollowoncefutureconditionsbecomeknowninsteadofasinglefixedlong-termplan.

Keywords:Multi-objectiveoptimization,Planningunderuncertainty,Adaptiveplanning

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41. Expressing Uncertainty In System Models As A Level Of Understanding

RobertSolly,rcsolly@dstl.gov.uk,Dstl,UnitedKingdomofGreatBritainandNorthernIreland

ABSTRACTVarious methods are used to express the uncertainty associated with scientific measurements,descriptions,explanationsandpredictions.But these often containhiddenassumptionsabout thestructureoftheproblembeingaddressedthatcanbemissedornotappreciatedbythereader.Forexample,expressionsofuncertaintyaroundpredictionsneedtotakeintoaccounttheaccuracyofthesystemmodelthathasbeenusedtomakethosepredictions,aswellasuncertainty inthedatafedintothatsystemmodel.Describingtheuncertaintyduetoinaccuracyinasystemmodelisfarmorecomplexthanthesimplemethodsusedtoexpressuncertaintyindata,ortoaggregatetheeffectsofuncertainties inmultipledata items throughanunchangingmodelusing sensitivityanalysis.As aresult,uncertaintyduetoinaccuracyofthesystemmodelisnoteasilycalculatedorcommunicated,anditseffectscaneasilybeignoredbytheresearcherandthereader.

Thispaperproposesreplacing themetricof“uncertainty” in asystemmodelwithamorepositivemetricof“understanding”andexploresoptionsforasimpleframeworktoachievethis.Inthisway,aresearcherwoulddemonstratetheextenttowhichtheyunderstandasystem,leavingthereadertomakeuptheirownmindabouthowcertaintobe intheirconclusions.Ametricof“understanding”wouldalsoallowustotracktheprogressofscienceaswedevelopunderstandingovertime,andtosetreasonabletargetsforunderstanding,dependentuponthenatureofaproblem.Althoughthereisa logicalcontradiction inassessingeither the “uncertainty”or “understanding”of a systemmodel(neithercanbeaccuratelymeasuredwithoutperfectknowledgeofthesystem),itmightbepossibleto estimate, evaluate and improvemetrics of understanding through feedback aswe gather newknowledgethroughdiscovering“knownunknowns”orhitherto“unknownunknowns”.

Keywords: Uncertainty, Understanding, Metrics, Framework, System Model, OR, Simulation,OperationalResearch

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42. Implementation Of Adaptive Delta Management Through An Opportunistic Approach

JeroenRijke,j.rijke@triple-bridge.nl,Triple-Bridge,NetherlandsBerryGersonius,B.Gersonius@unesco-ihe.org,UNESCO-IHE,NetherlandsEllenKelder,ETG.Kelder@dordrecht.nl,CityofDordrecht,Netherlands

ABSTRACTBasedonexperiences from theapplicationofadaptivedeltamanagement (ADM)on the IslandofDordrecht in the Netherlands, this presentation focuses on how an opportunistic approach cancontributetoputtingadaptivepoliciesinpractice.

ADMisastrategicplanningapproachinwhichlongtermdevelopmentsaretakenintoaccountintheassessmentofshorttermdecisions.TheapproachhasbeendevelopedintheDutchDeltaProgrammetodevelopadaptivepoliciesforfloodriskmanagementandwatersecuritywithaplanninghorizonuntil 2100. Ideally, these policies would lead to optimised investments in terms of avoidingexpendituresthatappearinhindsighttobetoomuch,toolittleand/ortoolate.

ADM incorporates tworoutes toachieve itsgoal.The firstroute involves asystemsapproach thattakes into account various spatial scales and values flexibility with regard to the timing ofimplementation.Thisalsoenablesswitchingbetweenstrategies throughadaptationpathways.Thesecond route involvesanopportunisticapproach toachieveadaptationat a relatively lowcostbyinter-linking various investment agendas and looking for opportunities for mainstreamingadaptationwithplanned investments(e.g.roadreconstruction,urban(re-)development,ecosystemrestoration).

ADMwasusedintheDeltaProgrammetodevelopafloodriskmanagementstrategyfortheIslandofDordrecht.Thisstrategyisbasedontheprincipleofmulti-layeredsafetyandcontains:1)protectionagainstflooding,2)preventionofdamageandcasualtiesincaseofflooding,and3)preparednessforemergencyresponseandrecoveryafterfutureflooding.TheregionalauthoritiesinDordrechthaveidentifiedseveralongoing infrastructureandecosystemrestorationprojects thatcouldprovideanopportunityforrealisingadaptationmeasurescost-effectively.

Forexample,theecosystemrestorationproject"NieuweDordtseBiesbosch",southoftheurbanisedareaof the IslandofDordrecht,providesanopportunity todivert the floodwateraway from theurbanisedareaincaseofadikebreachintheeast.Inaddition,theplannedreconstructionoftheN3,whichisaregionalroadthatconnectstheIslandofDordrechtwithotherdikeringsintheNorthandWest,couldpossiblybeusedtorealiseanelevatedaccessroutetoenhanceemergencyresponseandrecoveryafteraflood.

In-depthstudiesofthetechnical,financial, legalandorganisationalfeasibilityofbothopportunitiesarecurrentlyunderwayaspartofanationalpilotstudyonmulti-layeredsafety.PreliminaryfindingsfortheNieuweDordtseBiesboschshowthattheopportunisticapproachmayposenewconstraintstotheland-useoftheisland,becausedivertingthefloodwaterwouldchangethedistributionofriskson the island.As a result, additionalmeasuresmaybecomenecessary, such as spatial zoning. Inaddition, theexampleof the reconstructionof theN3 illustrates thatadaptationpathwaysmaybe(temporarily) closed off and diverted if an opportunity is not taken, since this road is the onlysensibleelevatedaccess route tootherdike rings. Instead,verticalevacuationand self-sufficiencymightbeneededtoestablishthemulti-layeredsafetystrategyfortheIslandofDordrecht.

Keywords:AdaptiveDeltaManagement,FloodRisk,Multi-layeredsafety,Opportunities

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43. Evaluating Climate And Other Future Risks To The Hydropower Investment Of TheUpper Arun Dam, Nepal

LauraBonzanigo,l.bonzanigo@gmail.com,WorldBank,UnitedStatesofAmericaPatrickRay,patrick.ray@gmail.com,UniversityofMassachussets,UnitedStatesofAmericaCaseyBrown,casey@engin.umass.edu,UniversityofMassachussets,UnitedStatesofAmericaJulienHarou,julien.harou@manchester.ac.uk,UniversityofManchester,UnitedKingdomofGreatBritainandNorthernIrelandAnthonyHurford,anthony.hurford@manchester.ac.uk,UniversityofManchester,UnitedKingdomofGreatBritainandNorthernIreland

ABSTRACTHydropower ispotentiallyvulnerable toclimatechange,particularly inSouthAsia,wherecomplexglacier-andmountain-influencedhydrology,highsedimentloads,andhighrelianceonhydropowerasadependablesourceofelectricenergypresentimportantchallenges.

Uncertainty in future climate projections remains, and downscaling efforts do not reduce thisuncertainty. As a result, it is unwise for the World Bank Group to plan and design futureinfrastructurebasedonprojectionsofunknowncredibilityorsolelyon theuseofhistoricrecords(so-called “stationarity”approaches).Moreover, other future conditions aredeeplyuncertain andmayimpactthesuccessoftheproject.Forone,theenergypricesmayvarygreatlyifanagreementtoexport energy to Indiaduring themonsoon seasonwere sealed.Or else, the lifetime of theplantdependsongoodsedimentmanagementand theabsenceofnaturaldisasters.Theseuncertaintiesshouldnothoweverstallthedecisionmakingprocess.

Weappliedaconceptualframeworkforclimateriskassessmentandriskmanagement,the“DecisionTree”developedbytheWorldBankWaterSector,tothehydropowerplanninginNepal.Weappliedthe Decision Tree to the proposed Upper Arun Hydropower Project (UAHP), incorporating bothclimateandnon-climateuncertaintieswhenassessing the infrastructureproject in aparticipatoryprocess with the Nepalese energy sectors and policy analysts. We investigated five possiblehydropowercapacities.

Theresults indicatethattheneteconomicbenefitsofeachofthedesignswererobusttoplausibleclimate changes. The larger the design, themore the net present valuewas affected by climateuncertainties.Amongnon-climaticfactors,thepriceofelectricityandconstructioncostsemergedaskeyriskfactors.Smallerhydropowercapacitiesappearquiterobusttoalluncertainties.

Theserisksandtheirplausibilityoracceptabilityneedtobeconsideredbydecisionmakersandtheythemselvesneedtomakethefinalchoice.Forthefirsttime,theGovernmentofNepalwaspresentedtheserisksandopportunities inananalyticallyrobustand transparent fashion.Thepolicy-makersthemselveswill intheenddecidewhether thepresentedrisksaresufficientlyacceptableto justifythe investment.This ispreciselytheadvantageofDMUapproaches, likethose implemented inthisanalysis via the Decision Tree: the decision is back in the policy-makers hands, and risks andopportunitiesarepresented inas a transparentwayaspossible.These typesofanalysiscanhelpthemmake informed choices,evenwhen they cannothave confidenceaboutwhat the futurewillbring.

Keywords:Climaterisks,socio-economicuncertanties,hydropower,Nepal

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44. A Decision Making Under Uncertainty Approach To Identifying Efficient And RobustHydropower Investment Portfolios In The Koshi Basin, Nepal

LauraBonzanigo,l.bonzanigo@gmail.com,WorldBank,UnitedStatesofAmericaJulienHarou,julien.harou@manchester.ac.uk,UniversityofManchester,UnitedKingdomofGreatBritainandNorthernIrelandAnthonyHurford,anthony.hurford@manchester.ac.uk,UniversityofManchester,UnitedKingdomofGreatBritainandNorthernIrelandCaseyBrown,casey@engin.umass.edu,UniversityofMassachusetts,UnitedStatesofAmericaPatrickRay,patrick.ray@gmail.com,UniversityofMassachusetts,UnitedStatesofAmerica

ABSTRACTNepal is currently developing a national hydropower strategywhere efficient use of capital andnatural resources tomeet electricity generation goals is a government priority.Multiple factorsrelated to thesupplyanddemandofbothenergyandwatercanaffect thereturnsonhydropowerinvestments. Uncertainty surrounds future changes in many of these factors, so a four-phasedecision-makingunderuncertaintyapproachisdesignedandappliedasaproof-of-conceptatbasinlevelasasteptowardsanationalanalysis.Itsaimistohelpidentifyportfoliosofhydropowerassetsthatcouldprovideanacceptablemixofbenefitsunderawiderangeofplausiblefutures,identifyingkeyvulnerabilitiestosocio-economicuncertaintiestohelpmitigatetheirimpacts.

TheapproachisappliedtotheKoshiBasin,consideringcombinationsoffiveproposedhydropowerdams inaddition to thebasin’s fiveexistingdams.Oneof theproposeddamshas fivegeneratingcapacity options leading to 95 possible combinations of dams. Two of the proposed dams arestorage-typeforwhichoperatingrulesaffectthebalancebetweenthebenefitsprovided.Therangeofoperating rules available for the storage dams increases the possible combinations of dams andoperations tomanybillions. Amulti-criteria search algorithm isused to filter these efficiently toidentify thebestones,asdefinedby anumberofperformancemetricsevaluatedby a simulationmodel.

The analysis identifies robust portfolios of investments (those that are efficient over a range ofplausible futures) considering firm,dry season, and total annual electricity generation aswell asenvironmental flow,urbanandagriculturalwatersupplyand floodalleviationcriteria(forstorageschemes). Scenario discovery is then applied to promising portfolios to identify combinations ofsocio-economicfactors,whichcouldleadtounfavourablereturnsoninvestment.

Non-climateuncertainties of construction cost and electricityprice are shown tobe the key riskfactorsfortheachievementofexpectedgainsfromhydropowerinvestments.Operatingstoragedamstobalanceelectricitygenerationwithotherobjectivescouldalsolimitrevenuegeneration.

ThisKoshiBasinanalysisispreliminary,butidentifiesanumberofthebesthydropowerinvestmentportfolios,whichmightbeimplemented,accordingtodecisionmakerpreferencesforrobustnessandtrade-offsbetweendiversewater-dependentbenefits.

Keywords:hydropower,robustportfolios,climateandnonclimateuncertainties,koshibasin

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45. Adaptation Pathways From The Perspective Of Real Options Analysis

TimCapon,tim.capon@csiro.au,CSIRO,AustraliaToddSanderson,todd.sanderson@sydney.edu.au,UniversityofSydney,AustraliaRussellWise,russell.wise@csiro.au,CSIRO,AustraliaGregHertzler,greg.hertzler@sydney.edu.au,UniversityofSydney,Australia

ABSTRACTDeveloping strategies for climate change adaptation is complicated by multiple sources ofuncertainty,regimeshifts,path-dependency,andlongtimeframes.Inthiscontext,itisimportanttounderstandthevalueofpreservingflexibilityinordertolearnandadapttochangingcircumstances.We show how adaptation pathways can be characterized as sequences of alternative regimesdelineatedbydecision thresholds.Thenatureof these thresholds isdeterminedby thesourcesofuncertaintyandthedegreeofreversibilitybetweenregimes.Webuildonrecentdevelopmentsintheapplicationofrealoptionsanalysistomanaginguncertaintyunderclimatechangetoinvestigatethevalue of flexibility and information within adaptation pathways. This provides an approach forunderstandingoptimaldecisionpathwaysintermsofexpectedfuturereturnsandtheoptionvalueoffutureregimes.Inparticular,weshowhowtheresilienceofadaptationpathwayscanbeunderstoodinrelationtokeydecisionthresholdsandhowthisapproachcanbeusedtohelp identifypracticalstrategiesforpreservingflexibilityandmanaginguncertainty.

Keywords:realoptions,climateadaptation,adaptationpathways

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46. Designing Signposts And Triggers As Adaptation Signals In The Dynamic AdaptivePolicy Pathways Approach

MarjolijnHaasnoot,marjolijn.haasnoot@deltares.nl,Deltares/DelftUniversity,NetherlandsJudithTerMaat,judith.termaat@deltares.nl,Deltares,NetherlandsWarrenWalker,w.e.walker@tudelft.nl,DelftUniversity,NetherlandsJanKwakkel,j.h.kwakkel@tudelft.nl,DelftUniversity,NetherlandsWillemOosterberg,willem.oosterberg@rws.nl,MinistryofInfrastructureandEnvironment,NetherlandsLeonHermans,l.m.hermans@tudelft.nl,DelftUniversity,Netherlands

ABSTRACTItisincreasinglybeingrecognizedthatadaptationtoclimatechangeisadynamicprocessovertimeinstead of a static singlemoment decision. Only by adapting over time can one account for thevarious deep uncertainties encountered in planning climate adaptation. TheDynamicAdaptationPolicy Pathways (DAPP) approach aims to support policymakers and analystswith this processthroughthedevelopmentofanadaptiveplan.Adaptationpathwaysformthebasisforsuchaplan.The first part of designing an adaptive plan is the evaluation of adaptation pathways under anensemble of possible futures, which enables policy analysts to recognize potential ‘locked-in’situationsandtoassesstheflexibilityandrobustnessofdecisions.

Monitoringissecondpartoftheprocess.Signpostsareidentifiedandmonitoredtoassesstheneedfor actionwhen pre-specified threshold values (triggers) are reached. This generates both earlywarningsignalsandadaptationsignals.Earlywarningsignalsgiveafirstsignaltostartthinkingthatactionsmayneedtobetaken,whileanadaptationsignalisamuchclearersignalthatanadaptationtipping point,meaning unacceptable performance of a system, is approaching, and that the nextaction(s)ofanadaptationpathwaymayneed tobe implemented.The signals should thus triggerthinkingaboutactions;notonlythenextactionofapathway,butalsocorrectiveactionstostayontrackandpreparatoryactionstoprepareforadaptationortokeepplannedoptionsopen.

In thispaper,wepresent a frameworkfordesigningandusingsignpostsand triggers in theDAPPapproach.TheframeworkhasbeendevelopedincooperationwiththeDutchDeltaProgrammeandwill be applied to two adaptation pathwaymaps developed for decisionmaking on freshwatersupply,whicharecontainedintheDeltaPlanpresentedin2014.Wegivecriteriaforidentifyinggoodsignpostsandtriggersandpresentanexampleoftheuseoftransientscenariosto identifytriggersforclimateadaptation.Fromapolicyperspectiveitseemslogicaltoselecttriggersthatarerelatedtonormvalues,objectives,oracceptabilityvalues,as theseare thevalues thepoliciesareevaluatedupon.However, these are often too extreme todetect (systematic) trends.Our results show thatothertriggerindicators—notnecessarilypolicyrelated—canbeusedinsteadassignalsforchange.

Keywords:monitoring,earlywarningsignal,adaptationpathways,deepuncertainty

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47. Dealing With Risks and Uncertainties In Urban Masterplanning and Implementation.The Case Of Beira, Mozambique

PeterLetitre,peter.letitre@deltares.nl,Deltares,NetherlandsMarioGuina,marioguina@gmail.com,MunicipalityofBeira,Mozambique

ABSTRACTBeira,withapopulationofmorethan500.000,isthesecondlargestcityinthecountryandislocatedintheestuaryofthePungueriver.

Thecityisfacingnumerouschallenges.Accordingtorecentstudies,Beiraisseriouslythreatenedbyclimatechange.Thecityisjustafewmetresaboveaveragesealevelandaclearadaptationstrategyis required toprovide enduringprotectionagainstwater relatedproblems suchas floods, coastalerosionandsaltwaterintrusion.

Spatialdevelopments alsoneed tobe addressed.The expansion of the coal transport and exportactivitiesoftheportofBeiraisrequiredtoutilizethegreateconomicpotential.

The currently poor living conditions of a large part of its inhabitants,mainly due to poor basicinfrastructureandservicecoverage,needtobeimproved.

Torespondtothevariouschallengesitwasdecidedtocreateanintegratedvisionforthecitythroughthe so calledMasterplan Beira 2035.The overall goal of theMasterplan Beira 2035 is tomake asignificantcontributiontoasafe,prosperousandbeautifulBeira.Torealizethisoverallgoal,Beiraessentiallyfacesthreechallenges:

· To utilize the great economic potential of the city and its hinterland,mainly due to itsstrategiclocationattheIndianOceanandattheendofanimportanttransportcorridorandthepresenceofaseaport;

· Toimprovethecurrentlypoorlivingconditionsofalargepartofitsinhabitants,mainlyduetopoorbasicinfrastructureandservicecoverage;

· Toadapt to climate changeand sustainably coexistwith itsnaturalenvironment.Beira islocated in a delta and large parts of the built up areas are prone to flooding and arethreatenedbysealevelriseandarepronetoflooding.

An integrated and planned approach tomeet these challenges has been prepared. The planningprocess was based on socio-economic growth and climate change scenarios to deal with theuncertainties. In addition, a clear implementation and financing strategy was added. A list ofimplementationprojectswasidentifiedforwhichfinancingisprocuredbasedonbusinesscasesandfinancing proposals. These project proposals will be submitted to public and private financingpartners.Theincreasingdependencyonprivateinvestmentcapitalprovidesanadditionalchallengesinceprivatepartiesaregenerallyriskavoiding.Severaluncertaintiesandriskplayanimportantrolein the decision making process of the private investors. Uncertainties regarding politicalcommitment,implementationcapacity,technicalrisksandfinancialeconomicaspectsrequirespecialcarewhenpreparingthesePPPbusinesscases.

Keywords:masterplanning,Climatechange,socio-economicgrowth

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48. Flood Risk Management Under Deep Uncertainties Regarding The CoastalDevelopment Strategy In Jakarta

PeterLetitre,peter.letitre@deltares.nl,Deltares,NetherlandsJanjaapBrinkman,JanJaap.Brinkman@deltares.nl,Deltares,NetherlandsFeirullyIrzal,SpatialPlaningandLandscape,JakartaPlanningandDevelopmentBoard,IndonesiaChandraSari,Head,RiverBasinPlanning,MinistryofPublicWorks,Indonesia

ABSTRACTJakarta is facing seriousproblems related to land subsidence and corresponding flood risks fromupstreamwateraswellasfromseawater.

ToaddressthesinkingofJakarta,theNationalGovernmentandDKIcompletedtheNationalCapitalIntegrated Coastal Development (NCICD) master plan in November 2014. The NCICD strategyconsistsofabroadsetofmeasuresincludingstrengtheningandraisingtheexistingseawallandinthe longtermthecreationofanouterseawalldefense intheformoftheGreatGaruda.NCICDhasbeenacceptedasthedirectiontoaddressthecoastalemergencybydevelopmentofthecoastalzoneofJakarta.InDecember9,2014thespecialparliamentcommitteeconfirmedthestrengtheningofthecurrent seawall (NCICD phaseA),which should be readywithin 3 years, but also requested thefurtherevaluationofNCICDphaseBandC thatconsistsofbuildingagiantseawall.Thiscomplexproject,apartfromthehuge investments itwillrequirecontainsnumerousrisksanduncertaintiesforwhichscenarioanalysisisbeingongoing.Thepresentationwillexpandontheongoingactivitiestodealwiththeserisksanduncertaintiesandwhatmethodsareused.

Keywords:landsubsidence,floodriskmanagement,scenarios

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49. Assessing The Sustainable Use Of Aquifer Thermal Energy Storage (ATES) UnderUncertainty

MarcJaxa-Rozen,M.Jaxa-Rozen@tudelft.nl,DelftUniversityofTechnology,NetherlandsJanKwakkel,J.H.Kwakkel@tudelft.nl,DelftUniversityofTechnology,NetherlandsMartinBloemendal,Martin.Bloemendal@kwrwater.nl,DelftUniversityofTechnology,Netherlands

ABSTRACTAquiferThermalEnergyStorage(ATES)canprovidemajorreductionsinenergyusewithinthebuiltenvironment,bystoringthermalenergy inaquifersfor theheatingandcoolingofbuildings.IntheNetherlands,theuseofATESinlargeresidential,commercialandinstitutionalbuildingshasrapidlygrown over the last two decades, and the number of operational systems is expected to furtherincreasetenfoldby2025.ATESsystemsarethuslikelytobecomethelargestuserofgroundwaterinthe country by 2020, as defined by total pumped volume. Given this rapid evolution and thesensitivityofaquiferresources, thesustainableuseofATESrequires theconsiderationofmultipleenvironmental,technicalandsocialcriteria;althoughthesesystemsdonotresultinanetextractionor injection of groundwater, they create thermal disturbances which must be monitored andmanaged. As such, planning approaches for urban ATES systems must find a balance betweenstimulatingtheadoptionofthetechnologytomaximizecollectiveenergysavings,andpreservingthelong-term thermal storage potential of the subsurface. From this perspective, current permittingpoliciesintheNetherlandsfollowtheprecautionaryprincipleandaimtoavoidthermalinteractionsbetweenneighbouring systems.However, thesepoliciesdonot fullyaccount for theuncertaintieswhichare inherenttoATESadoptionandoperation.For instance,variableweatherconditionsandbuildingoccupancypatternsmakeitdifficulttoaccuratelypredictenergydemandandmaintainthethermalbalance ofATES systems; this creates an incentive fordevelopers to apply for oversizedpermits,artificiallycreatingascarcityofspacefornewsystems.Furthermore,theadoptionofnewsystems is subject to a range of socio-technical uncertainties,while the thermal performance ofsystemsisdependentonlocalgeohydrologicalconditions–whicharedifficulttoassessandmonitor.

Inorder to identifypotentialpathways towards improvedgovernancepolicieswhichacknowledgethese uncertainties, this work first introduces a framework to assess the sustainable use ofsubsurface resources for thermal storage. This framework is then applied to explore the specifictrade-offsbetweencollectiveenergysavings,subsurfaceuse,andATESsystemperformance.Thesetrade-offsarestudiedusingahybridsimulationenvironmentwhichcouplesanagent-basedmodelofATES adoption and planningwith a geohydrologicalmodel of the subsurface,with bothmodelsrepresentingtypicaloperatingconditionsforATESsystemsinurbanareas.Thishybridenvironmentis used to investigate suitable options for the spatial planning of ATES systems under a robustoptimizationapproach.TheBorgmulti-objectiveevolutionaryoptimizationalgorithmisthusappliedto identifyATESwell layoutparameterswhichperformwell in relation to the criteria setby theassessment framework, under a range of socio-technical and geohydrological uncertainties.Techniquesforscenariodiscoveryarethenusedtoidentifythecombinationsofuncertaintieswhichmaycreatesystemvulnerabilitiesundertheselayoutparameters.

Keywords:AquiferThermalEnergyStorage,social-ecologicalsystems,robustoptimization,scenariodiscovery

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50. Decision-Making For Water Sensitive Designs: Incorporating Real Options Analysis In ADynamic Adaptive Policy Pathways Approach

JoostBuurman,joost@nus.edu.sg,InstituteofWaterPolicy,LeeKuanYewSchoolofPublicPolicy,NationalUniversityofSingapore,SingaporeSreejaNair,sreeja.nair@u.nus.edu.sg,InstituteofWaterPolicy,LeeKuanYewSchoolofPublicPolicy,NationalUniversityofSingapore,SingaporeErikKlaassen,erik.klaassen06@gmail.com,freelanceconsultant,Netherlands

ABSTRACTPlanning and design of urban drainage infrastructure has to deal with uncertainties in urbandevelopmentandclimatechange.As investments inupgradingofexistinganddevelopmentofnewdrainagesystemshavelongtimehorizonsandexistingundergroundsystemsareveryexpensivetochange, engineers and decision-makers increasingly look at flexible solutions to complimenttraditional, inflexible drainage designs. New paradigms and approaches such asWater SensitiveUrbanDesignandSustainableUrbanDrainageDesignfocusontemporarywaterstorageresultinginlower peak discharge and hence reducing pressure on the traditional drainage system. Theseapproaches can provide additional benefits beyond drainage, such as improved urban quality,positiveimpactonUrbanHeatIslandandstorageofwaterfordryseasons.

Aquestion is,however,how toplananddesignanoptimaldrainagesystem, taking intoaccount amultitude of complex, inter-related and imperfectly understood processes: what combination oftraditionalandnewapproacheswillprovidethebestprotectionagainstfloodingagainstreasonablecosts?Particularlyfordevelopmentofnewtownsandneighbourhoods,wherenotraditionalsystemexists, thisquestion isdifficult to answer as long-term climatepredictions vary considerably andurban development can followmany different scenarios. In addition, engineers are often unsureabout the performanceof the new approaches, while government decision-makers may havequestionsaboutimplementationandmanagementofthistypeofsolutions.

Althoughnodefiniteanswercanbeprovidedwithoutknowinghowthefuturewillunfold,decision-makingunderdeepuncertainty in thiscasecanbesupportedbyrecentlydevelopedmethodsandtools. Dynamic Adaptive Policy Pathways is a step-wise approach that provides insights insequencingofactionsovertimethroughadaptationpathways.Toprovide insightsinthecostsandbenefits of actions over time, and calculate a value for flexibility in the system,we propose tocomplementtheapproachwithrealoptionsanalysis.Adaptationpathwayscanbereconfiguredintodecisiontrees,whichallowarealoptionsapproachthatcapitalisesonuncertaintyandflexibility.Forrealoptionsanalysistowork,severalquestionswillneedtobeaddressedthough,suchquantificationofuncertainty,costsandbenefits,andtimingofdecisionmoments.

Theapproach isillustratedbytwocases.FirstlyfortheplanningofadrainagesystemforTuyHoacity, a medium-sized city in Vietnam. The proposed planning approaches will be analysed andcompared to a dynamic adaptive planning.We find that a dynamic adaptive planning approachshouldresultinbetterdesigns,thoughhigherupfrontcostsmaybeanimplementationhurdleforacityinadevelopingcountry.InthesecondcasewelookatmegacityBangkok.TheThaigovernmentisputting inplace anew floodprevention responsebyupstreamecosystem restoration forwaterretentionandtechnicalsolutionssuchasa‘wall-defencestructure’protectingkeyinstallationsinthecity.Givensuchpolicyinitiativesandprojectionsof increasingfloodrisksinthefuture,weanalysehowdynamicadaptiveplanningwithrealoptionscanbeusedtodevelopadaptiveoptionsforbetterfloodriskmanagement.

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Keywords: Dynamic Adaptive Pathways, Real Options Analysis, Water Sensitive Design, UrbanDrainageSystems

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51. Adjustable Robust Optimization For Sustainable Water Policy Pathways

DickdenHertog,D.denHertog@uvt.nl,TilburgUniversity,NetherlandsJarlKind,Jarl.Kind@deltares.nl,Deltares,Netherlands

ABSTRACTA few years ago, a new concept for deriving sustainablewater policies has been proposed andelaborated.Thisconcept isproposed in [1],andelaboratedandapplied toconcretecases inmanymorepapers in the last fewyears.In this talkwedescribehow therecentlydeveloped techniquesfromRobustOptimization,andinparticularAdjustableRobustOptimization,canbeusedtocalculateoptimaladaptationpathsforsustainablewaterpolicies.

ThefieldofRobustOptimizationwasfounded inthe late90sbythethreefoundingfathersAharonBen-Tal,ArkadiNemirovskyandLaurentEl-Ghaoui.ThedifferencewiththemoreclassicalStochasticProgrammingapproachisthatinprincipalthereisnoneedtospecifyadistributionfunctionfortheuncertainparameters.Insteadofadistributionfunction,aso-calleduncertaintysetisspecified.Thissetcontainsthevaluesfortheuncertainparameterstowhichthedecisionmakerwantstosafeguardthe final solution. Another advantage of Robust Optimization is that, contrary to StochasticOptimization, the optimization problems remain computationally tractable. For StochasticOptimizationalreadysmall-sizedproblemsbecomecomputationallyintractable.

In 2004 an essential extension of Robust Optimization was proposed: Adjustable RobustOptimization.Thisapproachallowsforso-calledwait-and-seevariables;thevalueofthesevariablescanbedeterminedwhen (apartof) thevaluesof theuncertainparametersareknown.The finaloptimizationproblemthatissolvedcontainsvariablesforthehere-and-nowdecisions,andvariablesthatareinfactfunctionsoftheuncertainparametersforthewait-and-seedecisions.

We apply the framework of Adjustable Robust Optimization to obtain sustainable water policypathways. First, the uncertain parameters and the corresponding uncertainty sets have to beidentified.Second,wehave tospecify the ‘learningprocess’:whatdowe learnwithrespect to theuncertainparametersatseveralpointsoftime?Third,thepossibleactionsateachpointoftimehavetobe specified.Fourth, a finalAdjustableRobustOptimizationproblem is setupand solved.Thesolutionnot only specifies thehere-and-now solutionbut also thedynamic adaptationpathsandsignalstoadapt.WealsodiscussimportantnotionsofParetooptimalityandhowtofindalternativeoptimaladaptationpaths.

The theory is illustratedby a toyproblemand amore realisticproblem inwhichoptimal setsofmeasureshavetobefoundsuchthatthedikessatisfythesafetystandardsforthecomingdecades,andthetotaldiscountedcostsoftakingthemeasuresareminimal.Oneoftheuncertainparametersinthisproblemisthesealevelrise.

[1]M.Haasnoot,Anticipatingchange –sustainablewaterpolicypathways foranuncertain future,Ph.D.thesis,TwenteUniversity,2013.

Keywords:SustainableWaterPolicy,Adaptationpaths,Uncertainty,AdjustableRobustOptimization

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52. Making Long-Term Investments In The Sacramento-San Joaquin Delta Amid DeepUncertainty

NidhiKalra,nkalra@rand.org,RANDCorporation,UnitedStatesofAmericaDavidGroves,groves@rand.org,RANDCorporation,UnitedStatesofAmerica

ABSTRACTThe Sacramento-San JoaquinDelta in theState ofCalifornia is the largest estuary in theWesternUnitedStates. It ishome to auniqueecosystemand cultureandplays a critical role inprovidingwater for23millionCalifornians.Levees in theDeltaareof statewide importance tohelpprotectpeople,property,naturalresources,andnumerousinfrastructuresystems.Catastrophicleveefailurewouldcausedevastatingfloodinganddisruptionoftheassetsthattheleveescurrentlyprotect.Leveemaintenanceandimprovementoverthepast30yearshashelpedmaintainthelevees.However,theStatedoesnothavealong-termstrategytoguidefutureinvestmentsofitslimitedfundinginthefaceofdeeplyuncertainclimatechange,development,andfloodrisk.

Thistalkwillreportonamulti-yearefforttosupporttheDeltaStewardshipCouncilindevelopingaDeltaLevee InvestmentStrategy(Strategy) toprioritizeState investments in levees in the(Delta),reduce risks topeople,property and State interests. For thisproject,wedeveloped an objective,sciencebasedplanningframeworkand aPlanningTool toestimateabroadrangeofriskswithoutandwith additional investment andhighlight key tradeoffs amongportfolios of investments.Theframework and tool are currentlybeingused to supportdeliberations over a suitable strategy toguidemillionsofdollarsofStateinvestmentinthecomingyears.

Keywords:deepuncertainty,delta,levees,long-termstrategy

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53. Teaching DMU To Practitioners

StevenPopper,swpopper@rand.org,RANDCorporation,UnitedStatesofAmerica

ABSTRACTThetechniquesofdecisionmakingunderuncertainty(DMU)beganasaguerillacampaignbyanalystsdissatisfiedwiththetoolsavailabletoperformpolicyanalysiswhendeepuncertaintyprevailed.Thefieldmovedfromvision,todevelopmentoftools,toesotericpracticetothecurrentstateofwideningacceptance. However, the performance of DMU support in policy settings usually requires theservices of external, highly trained analysts who will perform the required steps in service ofplanningstaffsandthepolicymakerswhomtheyserve.

IsthefieldnowcapableofitsnextstageinvolvingtransferofknowledgeandcapabilitiessoplannersinpublicagenciesmaynowperformthenecessaryDMUanalysesthemselves?Thistalkwillpresentinsightsfromtworecentexperimentsindoingso.Itwillthendrawconclusionsbaseduponthedirectexperiencegainedfromtheseeffortstosuggestpossiblepathsforward,challengesandopportunities.

ThefirstexperimentconsistedofaworkshopundertheauspicesoftheNGOSTART.orgheldattheShanghaiClimateCenter.TwentyselectedparticipantsfromfiveAsiancountriesreceivedfourdaysof workshop instruction in the methods associated with Robust Decision Making (RDM). Eachprepared preliminary exercises and during the course of theworkshopworked on assignmentsaccompanying instruction.Theyalsoworked instagesthroughaspecificpolicyproblemrelatedtouncertainty over climate in rapidly developing urban areas. Following the workshop, fourparticipantsreceivedfellowshipstospendfourweeksinresidenceatRANDforfurtherworkontheirplanningproblem.

ThesecondexperimentwasconductedundertheauspicesoftheTransportationResearchBoardoftheU.S.NationalResearchCouncil.Thegoalwas todevelop aprotocolandsetof tools thatwouldpermit individual transportation agencies of varying capacities (the U.S. possesses 52 statedepartments of transportation andmore than350metropolitanplanning organizations) tomakebetter decisions regarding technology adoption despite the profound uncertainties involved. TheSystematic Technology Reconnaissance, Evaluation and Adoption Methodology (STREAM) wasdesigned toprovide localagencieswith themeans tobetterevaluate technologicalalternatives interms relevant to agency missions, integrate such findings into ongoing decision processes andoperate with a more sophisticated understanding of the influence of the various uncertaintiesinvolved.

Thepresentationwillbrieflyoutlinethemainpointsofbothexperiments,presentfindingsanddrawconclusionsforsimilareffortstotrainpractitionersdirectlyinDMUtechniques.

Keywords:Training,Planning,Capabilitytransfer,Skillbuilding

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54. Infrastructure System-Of-Systems Modelling And Decision Analysis For The Uk’sNational Infrastructure

JimHall,jim.hall@eci.ox.ac.uk,UniversityofOxford,UnitedKingdomofGreatBritainandNorthernIreland

ABSTRACTNational infrastructureprovidesessentialservicestoamoderneconomy:energy,transport,digitalcommunications,watersupply,floodprotection,andwastewater/solidwastecollection,treatmentanddisposal.TheOECDestimates thatgloballyUS$53 trillionof infrastructure investmentwillbeneededby2030.TheUK’sNationalInfrastructurePlansetoutover£460billionofinvestmentinthenextdecade,butisnotyetknownwhateffectthatinvestmentwillhaveonthequalityandreliabilityofnational infrastructureservices, thesizeof theeconomy, theresilienceofsocietyor its impactsupon the environment. Such a gap in knowledge exists because of the sheer complexity ofinfrastructurenetworksand their interactionswithpeopleand theenvironment.Thatmeans thatthere is toomuchguesswork, and toomanyuntested assumptions in theplanning, appraisal anddesignofinfrastructure,fromEuropeanenergynetworkstolocaldrainagesystems.

The UK Infrastructure Transitions Research Consortium (ITRC) is a consortium of seven UKuniversities,ledbytheUniversityofOxford,whichhasdevelopeduniquecapabilityininfrastructuresystems analysis,modelling anddecisionmaking.The ITRChasdeveloped anddemonstrated theworld’s first familyofnational infrastructuresystemmodels(NISMOD) foranalysisand long-termplanning of interdependent infrastructure systems. The research is already being used by utilitycompanies, engineering consultants andmany parts of theUK government, to analyse risks andinform billions of pounds worth of better infrastructure decisions. Infrastructure UK in the UKTreasuryisnowusingNISMODtoanalysetheNationalInfrastructurePlan.

Thispaperwilldescribethesystem-of-systemsanalysisthatNISMODisbaseduponanddemonstratehow it is being used to analyse alternative long term infrastructure strategies for the UK. Fourheadlinestrategiesareconsidered:

MinimumIntervention(MI)–withlimitednewinvestment.

CapacityExpansion(CE)–focussingonexpandingthecapacityoftheinfrastructuresystem.

Systems Efficiency (SE) – focuses on deploying the full range of technological and policyinterventionstooptimisetheperformanceandefficiencyofthecurrentsystemtargetingbothsupplyanddemand.

SystemsRestructuring (SR) – focuseson fundamentally restructuringand redesigning the currentmode of infrastructure service provision, deploying a combination of targeted centralisation anddecentralisationapproaches.

Thesestrategiesareanalysed in thecontextof arangeofuncertain factors(population,economicgrowth,energyprices,climatechange)andappraisedwithrespecttomultipleperformancemetrics.Thepaperwilldemonstratethesensitivityofthesenationalinfrastructurestrategiestotheeffectsofdeepuncertaintyandwillidentifyrobuststrategies.

Keywords:Infrastructuresystems,Scenarioanalysis,Decisionanalysis

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55. Improving Scenario Discovery With Iterative Behavior Space Sampling

TushithIslam,t.islam@tudelft.nl,TUDelft,NetherlandsErikPruyt,E.Pruyt@tudelft.nl,TUDelft,Netherlands

ABSTRACTIn this proposedworkshop contribution and paper,we present a new output-oriented samplingapproach that, in combination with classification, clustering, and scenario discovery techniques,allowsforgeneratingthelargestvarietyofbehaviorssimulationmodelscouldgenerate.Theprimaryfocusistodirectthesamplingprocessinsuchawaythatthewidestvarietyofdynamicsofinterestisgenerated.

Sampling is thenumericalpractice of selecting, following specific experimentaldesignprinciples,input values fromdistributions or sets to generate experiments,which canbeused as inputs forsimulationmodelstogeneratelargevarietiesofsimulationruns.Therealreadyexistamultitudeofsamplingmethods;systematic full factorialmethods,randomMonteCarlomethods,and leanLatinHypercube methods. These sampling methods focus on the design of input values in order toassembleapictureofoutputbehavior.

Thetroublewithabovementionedsamplingmethods,isthatthereisnoguaranteeofrevealingthefullbehavioral spectrum a simulationmodel couldgenerate in sufficientdensity,whenapplied tohighlynon-linearsimulationmodels,to identifyregions inthe inputspacethatgenerateparticulartypesofbehavior.Althoughinput-orientedrandomsamplingmaycoincidentallyrevealallbehaviors,in case of non-linearmodels, itmay take some amount of processing time to identify themostinteresting regions in a sufficiently dense way for them to be identified by PRIM-like scenariodiscoverytechniques.

Adaptive sampling approaches use information obtained during the sampling process (i.e., the‘outcomes’ of previous samples) to determine where to sample next. The concept of adaptivesampling is not new; Bucher (1988) and Bishop et al. (2001) use adaptive sampling inweatherforecastingandconstructionsafety. In thispaper,wepresentanddemonstrateanadaptivemulti-stageBehaviorSpace(BS)samplingapproachthat,startingfromaburn-insamplegeneratedwithaLatinHypercubesampler, ineachresampling iterationdrawsaminimumspanning treeon a two-dimensionalrepresentationoftheoutputspacetodeterminethenlargestgapstobefilled,eachwithmLatin-Hypercube samples.Thisadaptiveoutput-oriented samplingapproachextends traditionalsamplingwithiterativegapsearchesinthebehavioralspacebasedonwell-chosentwo-dimensionalrepresentationsofthebehaviorspace.ThecurrentversionoftheBSsamplerisespeciallyusefulforgeneratingandrepresentingthefullbehavioralspectrumofsimulationmodels,foridentifyinginputspacesresponsibleforparticulartypesofbehaviors,andforidentifyingandselectingrepresentativeexemplars,especiallyifintricatenon-linearbehaviorsaregeneratedwithininteriorsubspaces.

Inthispaper,wepresentand illustratethecurrentversionoftheBSsampler.TheBSsamplerhasbeen tested on a large variety of (non-linear)models.We demonstrate how the BS sampler, incombinationwithclassification,clustering,andscenariodiscoverytechniques,enablesonetosampleforthewidestvarietyofdynamicsofinterest,identifytheassociatedregionsoftheinputspaceandforeachoftheseregions,identifyandselectanexemplar.

Keywords: Uncertainty Analysis, Exploratory Modelling and Analysis, Behavior Space Sampling,Dynamiccomplexity,Roughness,Classification,TimeSeriesClustering

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56. Flood Protection: Option Flexibility And Its Value

AdolfStroombergen,Adolfs@infometrics.co.nz,Infometrics,NewZealandJudyLawrence,judy.lawrence.nz@gmail.com,NewZealandClimateChangeResearchInstitute,NewZealand

ABSTRACTChanging risk profiles over long time periods are a challenge for assessing the economics ofinfrastructure projects like flood protection schemes. Several techniques such as robust decisionmakingandrealoptionsanalysisareusefulforanalysingsuchchallenges.However,thesearenotyetwellembeddedindecisionpracticegenerallyandNewZealandisnoexception.Wepresentastudybasedon theHutt river,oneof the largest flood scheme inNewZealand, thatapplies realoptionsanalysistoDynamicAdaptivePathwaysdevelopedforretainingexistingflooddesign levels(1:440ARIor2800cumecs)overthenext100years.We lookedatthevalueofpursuingfloodprotectionoptionsthatareflexible,ratherthanadoptingasinglesolutionthatcannotbeadaptedtodealwithchangingandunpredictableexternalconditions–namelyclimatechangeanditseffectonpeakriverflows.

Theresultsshowthataflexibleinvestmentstrategythatenablesachangeofcourseinthefutureismorelikelytodeliveralowercostoutcomethanpursuingasingleoption,unlesstheprobabilityofaclimate change induced increase in flood frequency and its associated economic loss is almostcertain.Theeffectsofchangingthebenefitmetricfromavoidingexpected loss,toValueforMoneybasedonaMulti-CriteriaAnalysis,arealsopresented.Followingfeedbackfromthedecisionmakers,a subset of investment options and flexible pathways were subjected to further analysis whichconfirmedthevalueofflexibility.Inparticularundermostscenariosexamined,itwasbettertoinvestin a lower cost option initially anddefer investment in ahigher cost optionuntilpolicy triggersindicate that the lowercostoption isno longeradequate tomeet theagreeddesignstandard.Theresults held true regardless ofwhether the outcomewas based onMulti-CriteriaAnalysis or onminimising the expected total cost (cost of flood protection investment plus the residual risk ofpropertylossintheeventofaflood)ofeachoption.

Keywords:realoptions,dynamicadaptivepathways,climatechange,floodriskmanagement

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57. Practice Problem And Dynamic Adaptive Approach Taken: Hutt City CBD FloodProtection Scheme, New Zealand

GraemeCampbell,Graeme.Campbell@gw.govt.nz,GreaterWellingtonRegionalCouncil,NewZealandJudyLawrence,judy.lawrence.nz@gmail.com,NewZealandClimateChangeResearchInstitute,NewZealand

ABSTRACTThe community in theHuttvalley,NewZealandareprotectedbyoneof the largest flood controlschemes in New Zealand. The floodplain is also the most densely populated floodplain in NewZealand, including significant road, rail and water infrastructure essential for the region. Thecommunityhavedecidedonalevelofprotection(1:440ARI)thatshouldbemaintainedforatleast100 years.Climate changewill reduce that level ofprotection as flood frequency andmagnitudeincrease.TheGreaterWellingtonRegionalCouncil,responsibleforfloodriskmanagementalongwiththetwocitycouncilswhomanagelanduseanddevelopmentsprotectedbythefloodscheme,haveachallengetomaintainprotectionlevelswhenthereareaffordabilitylimits.Thenewinformationonclimate change has suggested that the desired standard of flood protection cannot be providedwithin the existing river corridor and that additional land, currently occupied by buildingdevelopment,mayberequiredforfloodmitigationstructures.

This paper outlines how knowledge of the effects of climate change on flood frequency andmagnitudehasinfluencedhowwehaveapproachedthecompletionofthefloodschemeadjacenttotheHuttCBD.Weadopted theDynamicAdaptivePolicyPathways (DAPP) approach in a real-lifedecisionsettingtoassessoptionsanddocostingsfortheschemecompletion.Theproblem,contextanddecisionprocessarepresentedusingtheDAPP.The issuesthataroseduringtheprocess,howtheDAPPwasusedfor longtermmanagementofadynamicriversystem,providesacaseexampleforfeedbackfromworkshopparticipants.

Keywords:climatechange,floodprotection,dynamicadaptivepolicypathways

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58. Deep Uncertainty, Non-Stationarity, Scenarios, Robustness And Adaptation: How DoThey Fit Together In Environmental Modelling?

JosephGuillaume,joseph.guillaume@anu.edu.au,AaltoUniversity,FinlandHolgerMaier,holger.maier@adelaide.edu.au,UniversityofAdelaide,AustraliaHedwigvanDelden,hvdelden@riks.nl,RIKS,NetherlandsGraemeRiddell,graeme.riddell@adelaide.edu.au,UniversityofAdelaide,AustraliaMarjolijnHaasnoot,marjolijn.haasnoot@deltares.nl,Deltares,Netherlands

ABSTRACTTheadventofclimatechangeandtherecognitionthatenvironmentalsystemsareoperatinginnon-stationary environments has increased the importance of considering deep uncertainty in theanalysisofenvironmentalsystemsandassociatedmethodsofdecisionsupport.Withinthebroaderconcept of deep uncertainty, we focus on non-stationary systems for which there are multipleplausiblefutures,therelativelikelihoodsofwhichareunknown.Futuresystembehaviourisaffectedbyprocessesforwhichdatahavenotbeenorcannotbeobserved.Thisnotablyoccursasaresultofdynamics of a system. Interactions between system components over time lead to transitions insystem behaviour. For example, decisionsmay adapt over time due to their interactionwith theenvironment, often introducing path-dependencies. As a result, it is difficult to represent andestimate deep uncertainty using traditional methods of uncertainty analysis, which are gearedtowards stationary systems where probability distributions associated with uncertainties cangenerallybeestimatedwiththeaidofexistingdata.Consequently,anumberofdifferentapproachestodealingwiththetemporalaspectofdeepuncertaintyhaveemerged,includingtheuseofscenariosforexploringplausiblesystemstatesandtheconsiderationofrobustnessasameanstoaiddecision-making.However,given therelative immaturityof this fieldand the fact thatmethods fordealingwith deep uncertainty span a number of disciplinary areas, there has been some inconsistenciessurroundingterminology,methodsofanalysisandapproachestodecision-supportinrelationtonon-stationarityanddeepuncertainty. Inorder togo someway towardsaddressing thisproblem, thepurposeof thispaper is tounpack themeaningof someof the conceptsused indealingwith theaspectsofdeepuncertaintyrelatedtotemporaldynamicsandnon-stationarity,includingscenarios,robustnessandadaptation,andtoprovidesomeguidanceontheirapplicationinordertoassistwithunderstandingandconsistency in this important fieldofresearch. Inparticular, treatmentofnon-stationaritywithindifferentdefinitionsofdeepuncertaintyisdiscussed,aswellasdifferentmethodsfordealingwithnon-stationarityanddeepuncertaintyintheanalysisofenvironmentalsystems.Inaddition,thefactorsinfluencingtheselectionofdifferentapproachestoaddressingdeepuncertaintyindecision-makingcontextsareexplored,specificallyinthecontextofenvironmentalmodelling.

Keywords:non-stationarity,robustness,adaptivity,terminology,modelling

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59. Learning From Facilitated Scenario Development

BirgitFokkinga,b.fokkinga@fm.ru.nl,RadboudUniversiyNijmegen,NetherlandsStephanRaaijmakers,s.raaijmakers@fm.ru.nl,RadboudUniversiyNijmegen,NetherlandsEtiënneRouwette,e.rouwette@fm.ru.nl,RadboudUniversiyNijmegen,Netherlands

ABSTRACTScenario planning helps organizations to scan their environment and assess the importance anduncertaintyofdevelopmentsinitssurroundings.Thisapproachrestsfirmlyontheassumptionthatthe future is inherently uncertain and therefore preparation for multiple plausible futures isrequired. Scenarios are among the most frequently used strategy tools and a wide variety ofapproaches toscenarioplanning isavailable.Surprisingly little isknownabout itseffectiveness.Alimited number of success stories describe how scenarios were used to prepare for futuredevelopmentsandgetaheadof the competition.PierreWack’sanalysisofoilpriceshelpedRoyalDutchShellmanagerstoanticipateanincreaseinoilprices.Whentheoilcrisisbecameareality,Shellreactedfasterthanotheroilcompanies.Instarkcontrast,theunsuccessfulcasebyHodgkinsonandWrightdescribesmanagerswhorefusetoacceptscenariosandtheir implicationsforstrategy.Thewidevariety inreportedoutcomes leadssomeauthorstoconcludethatscenarioplanningdoesnotconsistently meets its expectations, and that success seems to depend at least as much on theconsultantsinvolvedasontheexactapproachused.

Recognizingthatmostscenarioevaluationstudiesaresinglecasereports,andasystematicreviewofscenario projects and their impact is missing, Van der Heijden proposes a theoretical basis forscenario effectiveness. He groups scenario studies along a process axis, separating one-off fromongoinginterventionsandanoutcomeaxis,whichdistinguishesprojectsaimedatopening-upfromthosetryingtoachieveclosure.Hethendescribeseachoftheresultingfourcombinationsandfindsthatsomeofthesearemorelikelytobesuccessfulthanothers.Aone-offintervention,forinstance,isunlikely to generate insights fundamental enough to change the acceptedway of thinking in anorganization,whichmeans thatone-offprojectsattempting toachieveclosure(anactionplan)arelikelytofail.

InthisstudywebringtogetherasetofscenarioplanningprojectsplannedandimplementedbytheMethodologyDepartmentoftheNijmegenSchoolofManagement.WegroupprojectaccordingtotheframeworkproposedbyVanderHeijden.Ourstudy isoneofthefewreviewsofscenarioplanningprojects andpresents adirect test ofVanderHeijden’s theoretical assumptions.Results indicateseveralpossibleclarificationsandextensionsofhisframework.

Keywords:scenarioplanning,review,evaluation,learning

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60. Adaptation Pathways For Enhancing Urban Resilience To Extreme Rainfall Events

CarlosSalinasRodriguez,csalirod@gmail.com,UNESCO-IHEInstituteforWaterEducation,NetherlandsBerryGersonius,b.gersonius@unesco-ihe.org,UNESCO-IHEInstituteforWaterEducation,NetherlandsEllenKelder,ETG.Kelder@dordrecht.nl,MunicipalityofDordrecht,Netherlands

ABSTRACTExtreme rainfall events are becoming more frequent due to climate change. Urban stormwatersystemsaregenerallynotdesignedtocopewithsuchevents,butonlytocomplywithnationaldesignstandards.Theuseofdesignstandardsmakesitpossibletoidentifythresholdvaluesthatthesystemshould meet, and (subsequently) to devise possible adaptation actions that will maintain therequiredperformance. Awell-recognizedmethod for theexplorationand sequencingofactions isAdaptationPathways,whichusestheconceptofAdaptationTippingPointsfordefiningthemomentswhenactionsarelikelytobeneeded.

TheuseofAdaptationPathwayshaspreviouslybeendemonstrated fordesign rainfalleventsandriverdischargeevents;howevernostudieshaveappliedthismethodforextremerainfallevents.Theapplication for this context requires to tailor the Adaptation Pathways method, (among other)becausethedefinitionofthresholdvalues isnotasstraightforwardasfordesignstandards.IntheNetherlands,thelegalrequirementforthemanagementofextremerainfalleventsisdefinedby‘goodhousekeeping’.Theterm ‘goodhousekeeping’givesdesignfreedomtodecisionmakersandaimstopromotedesignsolutionsaccordingtothespecificneedsoftheurbanstormwatersystem.Moreover,itenablesthecombinationofmultipleadaptationactions,inreactiontothedifferentmainstreamingopportunitiesprovidedbytheinteractionwithotherurbansystems,likeroadnetworks,blue-greennetworksorrecreationalareas.

ThreedifferentstormwatermanagementdistrictsinDordrechtwereanalysedusinga1D2Dmodel(SOBEK Urban) for the simulation of design and extreme rainfall events. Firstly, the availablecapacityofthesewersystemwasassessedforthedesignrainfall(20mm/2h,T=2years).Theresultsshowed that few nodes are surcharged and threshold values for the general performance of thesystemsarenotexceeded.Secondly,twosyntheticextremerainfallevents(60mm/2h,T=358yearsand100mm/2h,T=1288years)weremodelled.Themodelresultsshowedthatfloodwaterstartedflowing on streets, affecting buildings, critical infrastructure objects and main roads. As such,adaptationactionsmightbeneeded tokeep theurbanstormwatersystemdelivering itsobjective.Thedefinition of objectives isdone considering the severity of impacts and the frequency of theevents,and zoning forpossibleactions isperformedaccordingly.Differentadaptationactions likechangingstreetprofiles,implementingwaterplazasandchangingsurfacetypeshavebeenproposed,andtheirefficiencywasassessedwiththestormwatermodel.NextstepswillbetodefineAdaptationPathways that take account of the variousmainstreaming opportunities, togetherwith thequick-winsthattheyrepresent(intermsofimpactreduction).MainstreamingopportunitiesinDordrechtarise from the maintenance and renewal works that the municipality has planned for theseneighbourhoods.Itisexpectedthatthistypeofadaptationactionwillnotrepresentsubstantialextracostforthemunicipality,becauseofthetimingtogetherwithongoingworks.

Keywords:Extremerainfallevents,Adaptationpathways,Resilience

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61. Calibrating Decisions: Using Economic Instruments In Sequential Decision AdaptationPathways

JohnMatthews,johoma@alliance4water.org,AllianceforGlobalWaterAdaptation,UnitedStatesofAmericaMarjolijnHaasnoot,marjolijn.haasnoot@deltares.nl,Deltares,NetherlandsKathleenDominique,Kathleen.DOMINIQUE@oecd.org,OECD,UnitedStatesofAmericaMaaikevanAalst,Maaike.vanAalst@deltares.nl,Deltares,NetherlandsDiegoRodriguez,drodriguez1@worldbank.org,WorldBank,Uruguay

ABSTRACTDecisionsaboutinvestmentsinlargelong-livedinfrastructure—balancinginterestsacrossmultiplestakeholders and generations — have always been difficult. These decisions are often definedthrough technicalbodiesofknowledgesuchasengineeringandscience,butmostdecisionmakersoften use economic tools to decide between alternative pathways. The gaps between thesedefinitionsofuncertainty,knowledge,anddecisionraisesprofoundchallengesinaperiodofclimatechange, especially about long-lived investments. Ideally, investment decisions should beeconomically viable and environmentally sustainable over long timescales, robust to anumber ofcredibleriskscenarios,andflexibleenoughtoadapttochangingconditions,preferablyatleastcosttosociety.Water infrastructure investmentdecisions typicallyhave long-lived footprints,affectingcommunities, economies, and ecosystems for decades or even centuries. In some case, theinfrastructure’s legacy can actually outlive the infrastructure itself, as the economic systemreorganizes itself around the infrastructure’s presence. Water infrastructure has the power totransform “difficult hydrologies” and insecure economies into water-secure environments withgrowth-orientedeconomies,reducingclimatevariabilityand increasing theeconomicstabilityof aregion. Here, we show how sequential decision adaptation pathways for water infrastructureinvestments--defined largelyfortechnicaldecisionmakers--canbemarriedtoexistingeconomictoolstoenablepolicyandstrategicdecisionmakerstomakemoreeffective,robust,andsustainablechoices.

Keywords: freshwater, infrastructure, investments, climate adaptation, economics, adaptationpathways

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62. Dealing With Deep Uncertainty In Long-Term Infrastructure Planning In TheNetherlands

VincentMarchau,v.marchau@fm.ru.nlRadboudUniversity,NetherlandsWarrenWalker,w.e.walker@tudelft.nl,TUDelft,NetherlandsJanKwakkel,J.H.Kwakkel@tudelft.nl,TUdelft,Netherlands

ABSTRACTLong-term infrastructure planning must deal with all of elements of deep uncertainty, since itinvolves large investmentswith a long lifetime, and societal impacts that are often irreversible.Moreover,newinfrastructureoftentriggers(uncertain)societalresponses.IntheNetherlands,long-term infrastructureplanning isbasedon anational,high-levelvision for infrastructureandspatialdevelopment(includingambitionsforaccessibility, livability,safety,andeconomiccompetitivenessin2040).This vision is implemented through the Long-RangeProgram for Infrastructure, SpatialDevelopment and Transport (‘MIRT’). TheMIRT involves an annual programming and budgetingsystemofroadway,railway,andwaterwayprojects,aswellasspatialprojectsofnationalimportance(e.g. housing and industry). The MIRT programming process includes four stages: (1) problemanalysis (2) generating alternatives and choosing a preferred solution, (3) planning (forimplementation of thepreferred solution), and (4) realization.Uncertainties canbe identified foreachMIRTstage,aswellasacrossstages.

Theproblemanalysisbeginsbyidentifyingthepotentialgapbetweenfuturetransportdemandandsupply in order to specify the problem. This analysis is based on applying scenarios that havepreviouslybeenshowntobeincomplete.Forexample,theydonotincludeexogenousdevelopmentssuchas thespeedof implementationofautomatedvehicledriving, thepossible implementationofroadpricing,adecreaseinpopulationinsomepartsoftheNetherlands,etc.Thesedevelopmentsareat leastplausibleandwill, if theyhappen,haveseriousconsequences for future transportdemandand/orsupply.Thechoiceof apreferredsolution isbasedon acost-benefitanalysisofpromisingalternatives,whichscarcelyaddressesuncertaintiesrelatedtothefuture impactsofalternativesormonetization of impacts.With respect to theplanningand realization stages,practice shows that(unforeseen) cost overruns and delays often occur. It is, therefore, difficult, if not impossible, torealize the long-termobjectivesbehind theMIRTdue todeepuncertainty, including technologicaluncertaintyassociatedwiththepreferredsolution,anduncertainbehavioroftheactorsinvolved.

Inessence,theMIRTpolicymakingprocessassumesthatthefutureisknowntoacertainextent,anassumptionthatisincreasinglybeingviolated.Thisweaknesshasbeenrecognizedbypolicymakers,andways arebeing studied to incorporateuncertainty into theprocess.We suggest theuse of aflexible or adaptivepolicy framework that enablespolicymakers to take someactions rightaway(basicpolicy)andpreparefutureactionsthatallowforadaptationsofthebasicpolicyovertimeasexperienceandknowledgeabout therealworld functioningof the transportsystem isgathered. Itincludesthespecificationofoptionsthatmightbeimplementedinthefuture,incasecriticaleventsoccur.In thispresentationwepropose aMIRTprocessthatexemplifies theadaptivepolicymakingprinciples.Institutionalizationofsuchaprocesswouldrequirechanges insomeexistingexecutive,legislative,and judicial systems, since they are generallybased ondeveloping, implementing, andenforcing static, robustpolicies.But thesemaynotbe insurmountablebarriers if thebenefitsarelargeenough.

Keywords:DeepUncertainty,AdaptivePolicymaking,InfrastructurePlanning

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63. Using Robust Decision Making To Support Seasonal Water Management In The ChaoPhraya River Basin, Thailand

NielsRiegels,ndr@dhigroup.com,DHI,DenmarkHenrikMadsen,hem@dhigroup.com,DHI,DenmarkOlufJessen,ozj@dhigroup.com,DHI,Denmark

ABSTRACTArobustdecisionmakingapplicationisdemonstratedthatsupportsseasonalwatermanagementintheChaoPhrayaRiverbasin inThailand.Theapproachusesensemblesimulationanddataminingtoolstoidentifyuncertainfactorsthatmayleadtounacceptableperformance.Theapproachhasthepotential tosupportdecisionmaking throughevaluationofdecisionperformanceunderuncertainfutureconditionsthatmaynotbepossibletocharacterizeintermsofprobabilities.

TheChaoPhrayaRiverbasinsupportssignificantdryseasonirrigation,particularlyforgrowingrice,and the management of reservoir storage to support dry season irrigation has emerged as achallenge. Dry season irrigation in Thailand is managed through a mixture of non-bindingrecommendationsaboutthemaximumextentofricecultivation,alongwithincentivestogrow lesswater-intensive crops.Recommendationsaremade at thebeginning of eachdry seasonbased onreservoirstorage.

The extent of rice cultivation during the dry season frequently exceeds recommendations, andmanagementauthorities lackauthoritytopreventriverwithdrawalsfor irrigation.Inpractice,thismeansthatauthoritieshavetoprovideenoughwaterto irrigatetheactualplantedareabecauseofdownstreammunicipalwatersupplyrequirementsandwaterqualityconstraints.Thisresultsindryseasonreservoirwithdrawalsthatexceedplannedwithdrawals,reducingcarryoverstoragetohedgeagainstinsufficientwetseasonrunoff,whichvariesconsiderablyfromyeartoyear.

The dry season planning problem in Thailand can therefore be framed in terms of decisions,objectives,constraints,anduncertainties.Decisions includerecommendationsabout themaximumextent of rice cultivation and types of incentives given for growing less water-intensive crops.Objectivesaretomaximizebenefitstofarmers,minimizetheriskofinadequatereservoirstorageatthe start of the following dry season, andminimize the amount spent on incentives. Constraintsinclude downstream municipal water demands and water quality requirements. Uncertaintiesaffecting the decision include the actual extent of rice cultivation, dry season precipitation andreservoirinflow,andprecipitationandreservoirinflowinthefollowingwetseason.

A robustdecisionmakingapproach isused toprovide analytical support to thisdecisionmakingprocess.Theapproachisbasedonariverbasinsimulationmodelandacropwaterdemandmodel.Thecropwaterdemandmodelestimates irrigationwaterdemands,andtheriverbasinsimulationmodel estimates reservoir drawdown required tomeetdemands given forecasts ofprecipitation,evaporation,andrunoff.Anensembleofuncertainmodelinputsisgeneratedbyrandomlysamplingfromhydrologicaldataandcropareasobservedinthehistoricalrecord.Theinputensembleisusedtogenerateanensembleofresultsand indicatorvalues foreachof thedecisionobjectives: farmerbenefits, end-of-wet-season reservoir storage, and the cost of incentives. Threshold values aredefined for each of the objectives to identify ensemblemembers forwhich objective values areunacceptable.ThePRIMdataminingalgorithmisthenusedtoidentifyinputvaluesassociatedwithunacceptablemodeloutcomes.Theapproachwillbetestedwithstakeholdersanddecisionmakerstoassesswhetheritisusefulforevaluatingandrefiningdecisionsgivenuncertainfutureconditions.

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Keywords:Robustdecisionmaking,Seasonalplanning,Irrigation,Uncertainty

80

64. Exploring Adaptation Tipping Points For Flood Risk Management In Europe

LaurensBouwer,laurens.bouwer@deltares.nl,Deltares,NetherlandsMarjolijnHaasnoot,marjolijn.haasnoot@deltares.nl,Deltares,NetherlandsAndreasBurzel,andreas.burzel@deltares.nl,Deltares,NetherlandsHesselWinsemius,hessel.winsemius@deltares.nl,Deltares,NetherlandsAdJeuken,ad.jeuken@deltares.nl,Deltares,Netherlands

ABSTRACTItisassumedthatpolicychangesinfloodriskmanagementcouldbetriggeredbydifferentcauses:forinstanceasignificantincreaseinthefrequencyofoccurrenceofextremeeventsoranincreaseoftheexpected annual damage resulting from ongoingmonitoring and research.Within the FP7 BASEproject,wesystematicallyexploredifferentthresholds(adaptationtippingpoints)thatcouldindicatea need for adapting flood risk management practices. We assess adaptation options for riskmanagementofriverfloodriskataEuropeanscale,byapplyingaframeworkforanalysingtippingpoints.AEuropeanscalefloodriskmodel isemployedtocalculateannualexpecteddamageacrossriverbasins inEurope.Themodel simulatesboth a referenceperiod (1960-1999)aswellas twoclimatechangescenarios(RCP4.5and8.5)fortheperiods2010-2049and2060-2099.Wetakeintoaccounts best estimates of current flood protection levels across Europe. Model results for thereferenceperiodhavebeenevaluatedusing information from localstudies.The resultsshowhowtippingpoints,underdifferentclimatescenarios,willleadtoanearlieror laterneedforadaptationacross countries in Europe. Tipping points are defined by measured by annual expected flooddamagesaspercentageofnationalGDP.Also,Europeanscalepathwaysaredevelopedforfloodriskmanagement. We assess the performance of the associated adaptation options, aimed at riskreduction.This resulted in amapwith early adaptorsand identification ofpromising options foradaptation,aswellidentificationoftheperiodduringwhichthesemeasureswillhelptoreducefloodrisk to acceptable levels, and associateduncertainties.We show the variations in timing of thesetippingpointsusingarangeofdifferentclimatemodels,aswellastwoRCPscenarios.

Keywords:Adaptation,Flooding,Tippingpoint,Europe,Impact,Climatechange

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65. From Theory To Practice; A Timeline Of Interventions By A Change Agent With TheDevelopers Of The Dynamic Adaptive Policy Pathways

JudyLawrence,judy.lawrence.nz@gmail.com,NewZealandClimateChangeResearchInstitute,NewZealandMarjolijnHaasnoot,Marjolijn.Haasnoot@deltares.nl,DeltaresandTUDelft,NetherlandsJaapKwadijk,Jaap.Kwadijk@deltares.nl,DeltaresandUniversityofUtrecht,Netherlands

ABSTRACTDecisionmakingunderconditionsofuncertaintyanddynamicchangeposechallengesfordecisionmakers and flood riskmanagers.Making decisions about the effects of climate change on floodfrequency, magnitude and timing, is an example. The challenges arise from a combination ofuncertaintiesinclimateimpacts,theirdynamicbehaviourovertime,andtheestablishedinstitutionalframeworks and practices adopted by the decision actors; frameworks and practiceswhich aredesigned to create certainty for those relying on the decisions. We discuss how a theoreticalapproach for managing uncertainty and dynamic change (Dynamic Adaptive Policy Pathways,DAPP)hasbeen ‘socialised’within a localcouncilusingtheSustainableDeltaGameas thecatalyst.Theresult is abetterunderstandingofa) the implicationsofuncertaintyandchangeoccurring infloodrisk,b)adaptationas asequenceofdecisionsover time thatcanpath-dependent,andb) therolethatinstitutionalframeworksandpracticesplayinblindingactorstotheseimpactsresultingininadequateassessmentofuncertaintyanddynamicclimatechange.

Thehistoric timelineof interventions takenwith theGreaterWellingtonRegionalCouncil inNewZealandhasenabled thecouncil to implement theDAPPapproach through thedevelopmentofanadaptiveplanwithflexibleoptions.Moreover,ithasenabledatransitiontooccurindecisionpracticefromastaticplantoadynamicplan.Theactionstaken included;aworkshopusingvisualisationofchanging risk emphasing the effect ofmovingmeans on the tail of rainfalldistributions; a reportrecordingtheworkshopfindingsthatpresentedtheconceptbehindtheDAPP;workshopstodiscussthe effect of climate change on flood frequency; discussion of how taking amean or a numberexpressedasaprobabilitygivesafalsesenseofsecuritywhereuncertaintiesarerifeanddynamicchangeexists;contactfromthedevelopersoftheDAPPinNetherlandsandsubsequenttraininganduse of the Sustainable Delta simulation Game to “socialise” the actors in decisionmaking underconditionsofuncertainty;developingDynamicAdaptivePolicyPathwaysforfloodriskmanagementoptionsand identifyingpotential tippingpoints forpolicyoptions;presentingandusing theGamewiththepoliticallyelectedlocalgovernmentdecisionmakers;introducinganeconomisttotheDAPPwhichleadtoarealoptionsanalysisbeingincludedintheprojectassessment;reviewoftheprojectassessmentsforimplementationoftheDAPP.Theroleofchangeagents,bothexternaltotheprojectandwithinthecouncil,facilitatedthetransitionovera3yearperiodbased.Thishas ledtofurtherdevelopmentoftheDAPPwithitsDutchcreators,tointerfacewiththeGameandbeusedtogeneratepathways,optionsprioritisationand fordevelopingdynamicadaptiveplans inreal-worlddecisioncontexts.

Keywords:Uncertainty,Dynamicchange,Climatechange,Adaptivepathways

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66. Evaluating The Resilience And Robustness Paradigms For Water Resource SystemsAdaptation

TomRoach,t.roach@hrwallingford.com,HRWallingford,UnitedKingdomofGreatBritainandNorthernIrelandZoranKapelan,z.kapelan@exeter.ac.uk,UniversityofExeter,UnitedKingdomofGreatBritainandNorthernIrelandRalphLedbetter,r.ledbetter@hrwallingford.com,HRWallingford,UnitedKingdomofGreatBritainandNorthernIreland

ABSTRACTResilience,asacomponentinfreshwatersupplysystemsevaluation,currentlylackscleardefinitionandclassificationasanoperationalparadigm.MultiplemethodsexistforassessingIntegratedWaterResourceManagement (IWRM) systemsunderdeepuncertainty,however theoutput results fromadaptation investigationscanbehighlydependentontheassessmentmetricsemployed.Resilienceasapotentialprimarymetricformeasuringtheperformanceofawaterresourcesystemisanaxiomincreasing in popularity in current literature. In this research we explore the various potentialcalculations of resilience in terms of likelihood, duration, magnitude and overall system risk toisolatethepotentialimpactsonadaptationstrategyperformancelevelswhenvaryingthisgoverningmetric across uncertain future scenarios. Themetrics are applied to a realworld water supplyadaptation case study and tested on a dynamic monthly time-step supply and demand model.Potentialformsofcalculatingoverallsystemrobustnesstouncertaintyarealsoexaminedundertheselectedresiliencemetrics,isolatingtheeffectofutilisingalocalandglobalrobustnessmethodology,I.e.viatheapplicationofInfo-GapdecisiontheoryandRobustOptimisationrespectively.

Keywords: water resources planning, decision making methods, resilience, robustness, climatechangeuncertainty,RobustOptimisation,Info-Gapdecisiontheory

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67. The Deeply Uncertain Local Sea Level Response To Anthropogenic Climate Change

AlexanderBakker,bakker@psu.edu,EESI,PSU,UnitedStatesofAmerica

ABSTRACTSea-levelrisethreatensmanycoastalareasaroundtheworld.Theintegratedassessmentofpotentialadaptation,mitigation,andgeoengineeringstrategiescriticallyhingesonprojections thatcarefullyresolvetheupper tailsoftheuncertain localsea-levelresponse.Themajorcomponentsthatshapesea-level change respond inverydifferentways to climate changewith respect to time-scaleandpotentialthresholdbehavior.Besides,theyshowverydifferentregionalpatternsof localresponse,mainlyasaresultofmass loss inducedchanges ingravityfield.Therefore,most(notall) localsea-levelprojectionsrelyonmethodsthatexplicitlyassessthecontributionsofthermostericexpansion,theAntarctic IceSheet, theGreenland IceSheet,and the combinedeffectofglaciersand small icecaps.

Theexactbehaviorofthesedifferentcomponents is,however,characterizedbydeepuncertainties.Projecteduncertaintyrangesstronglydependon(necessary)pragmaticchoicesandassumptionson,forexample,theappliedclimatescenarios,the levelofmodelingdetail,whichprocessesto includeand how to parameterize them, and on the error structure of observational data. The relativelikelihoodofdifferentassumptionsishardtoassess.Hence,uncertaintiesoflocalsea-levelresponsearehardtosummarizeinasinglecumulativedistributionfunction.

Inthisstudy,weaimtoidentifythemajordriversofthedeepuncertaintiesthatcharacterizelocalsealevelprojections.First,wesimplycomparerecentlyprojectedrangesandassesstowhatextenttheymightleadtodifferentdecisions.Byinterchangingassumptionsfromdifferentassessmentswetrytoisolate themajordrivers.Finally,weexplore thepossibility todevelop asimplemodel frameworkallows for easily includingand excluding assumptions.Ultimately, this framework canbeused toreproduceearlierassessmentsandtoanalyzeanddiscusswhatothersourcesofuncertaintymightbeimportant.

Keywords:deepuncertainty,localsealevelprojections,assumptions,simplemodeling

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68. Assessment Of The Application Of Decision Tools For Policy-Making Under UncertaintyIn The Water Sector

OliviaJensen,olivia.jensen@nus.edu.sg,InstituteofWaterPolicy,LeeKuanYewSchoolofPublicPolicy,NationalUniversityofSingapore,SingaporeXunWu,sppwuxun@nus.edu.sg,InstituteofWaterPolicy,LeeKuanYewSchoolofPublicPolicy,NationalUniversityofSingapore,Singapore

ABSTRACTOverthe last15years,greaterattentionhasbeenpaidtouncertainty inpolicy-makingboth intheacademic literature and among practitioners in thewater sector and a number ofmethods andcomputationaltechniqueshavebeenproposedtoaddressthedifferent typesofuncertainty.Atthelevelofuncertaintyaboutvalues,forexample,methodssuchasMonteCarlosimulationhavebecomewell established. Real options analysis, meanwhile, is widely used in corporations when takingcapitalinvestmentdecisionsandhasbeenappliedinpolicy-makingregardingclimatechangeintheDutchDelta(vanRhee2011)andwaterresourceplanningintheUK,amongotherexamples.Atthedeepest level of uncertainty, the adaptive policies and policy-making (Walker et al 2001) andadaptationpathwaysapproaches(Haasnootetal2012)offerguidancetopolicy-makers.

These approaches need not be taken as alternatives – indeed, they may be better seen ascomplements.Mostpolicydecisionsarecomplexandhavemultipledimensions:somevariables inthedecisionhavelowuncertaintyandcanbeanalysedintermsofprobabilities,whileothervariablesmayhavehighuncertaintyrequiringadaptiveapproaches.Hence,combinedapproachescouldcoveraspectrumofuncertaintyinapolicydecision.

Theproliferation ofmodels and techniques calls for a systematicassessment of theirdifferences,strengths,weaknessesandscopeforapplication.ThispaperaimstoprovidethatassessmentthroughasystematicliteraturereviewandQualitativeComparativeAnalysis(QCA)oftheapplicationoftoolsfor decision-making under uncertainty in the water sector. It identifies factors related to thesuccessfulapplicationofthetoolsaswellasbarrierstosuccessfulapplication.Thetoolsexaminedinclude:realoptionsanalysis,adaptationpathways,dynamicadaptivepolicy-making,andadaptationframeworks.

Through a literature search,we identifypapers concernedwith thepractical application of thesetools to thewater sector, coveringwater resourcedevelopment,water supply, floodmanagementandwastewatermanagement.Foreachpaper,weidentify:

· Thepolicyobjectiveandthetypeofuncertaintybeingaddressed;· Thetoolused;· Whetherthetoolwasusedinisolationorjointlywithothertools;· Capacityofthedecision-makersinvolvedtousethetool;· Limitationsinthewaythetoolwasapplied;· Indicatorsofthesuitabilityofthetooltoaddressthattypeofuncertainty.

WeuseQCA to identify setsof factorsassociatedwith the successfulapplicationofeach tool.Weconsiderwhetherthesefactorsaresimilaracrosstoolsandtheimplicationsforcombinedapplicationof the tools. We discuss the limitations of the tools both in theory and practice and deliverrecommendationsonhowthetoolsmaybeadaptedandrefinedinthefutureinordertomakethemmoreuseful,andconsiderwhichotherchangesareneededinthepolicyprocesstoallowforthefullintegrationofthesetoolsintothedecision-makingprocess.

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Keywords:Watersector,Uncertainty,Decision-makingtools,QCA

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69. Decision Tree Framework And Dynamic Adaptive Policy Pathways – How Can TheyComplement Each Other In Managing Uncertainty In Hydropower Projects?

EelcovanBeek,eelco.vanbeek@deltares.nl,Deltares/UniversityTwente,NetherlandsPatrickRay,paray@umass.edu,UniversityofMassachusetts,Amherst,UnitedStatesofAmericaJaapKwadijk,Jaap.Kwadijk@deltares.nl,Deltares,UniversityTwente,NetherlandsAdJeuken,Ad.Jeuken@deltares.nl,Deltares,Netherlands

ABSTRACTHydropower projects require huge investments while at the same time these investments areparticularly sensitive to changes inclimateand socio-economic conditions.Formanyhydropowerprojects in developing countries international financing is sought for. After a down period ofinvolvementinhydropowerprojectstheWorldBankisconsideringagaintofinancesuchprojects.Totest the robustness of their investments inhydropower theyhavedeveloped the “DecisionTree”approach,aconceptualframeworkforclimateriskassessmentandriskmanagement.Thisapproachhasbeen testedonseveraldams inNepalandproved tobeveryuseful tosupport thedecision tobuildornottobuild,thecurrentaction.What ismissing inthisapproach istheconsideringfutureoptionsandadaptivity.IntheNetherlandstheDynamicAdaptivePolicyPathways(DAPP)approachhas been developed. Combining theDecision Tree approach andDAPPwill bring in the decisionmakingprocess the timingof(adaptive)actionsand theconsiderationofpath-dependency. In thiscontribution we will present the concept of the combined approach and apply that on twohydropowerprojects.

Keywords:uncertainty,hydropower,climatechange,robustdecisionmaking

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70. Bangladesh Delta Plan 2100: A Holistic, Adaptive And Long Term Strategic Plan

GiasuddinAhmedChoudhury,choudhuryga@gmail.com,BangladeshDeltaPlan,BangladeshWilliamOliemans,william.oliemans@deltares.nl,Deltares,NetherlandsJaapDeHeer,,IVM,TwynstraGudde,NetherlandsZahirulHaqueKhan,,GeneralEconomicsDivision,MinistryofPlanning,Bangladesh

ABSTRACTBangladeshaimsatbecomingadevelopedcountryby2041.Toachievethisgoal,thecountrymustbalance its available resources aswell as plan against uncertainty related to rapid urbanization,population growth, industrialization, land subsidence and environmental degradation aswell asclimate change related pressures such as sea level rise,more frequent drought and floods. It isimperativetohavealongtermplanforthesustainabledevelopmentofthecountry.

Long term planning, has to dealwith (climate and socio-economic) uncertainties and the lack ofconfidence in resourcemanagement.We look to science todevelop a rangeofpossible futuresorscenariostoanalysewhattheseuncertaintiescanmeanintermsofclimatechange,waterresourcesavailability,foodsecurity,populationchangeandeconomicgrowth.

TheBangladeshDeltaPlanistheGovernment’sresponsetothisneedfor‘planningforuncertainties’,andtheurgentneedforsustainableandintegrateddevelopmentofthecountry.Theplanaimstobeaholistic,adaptiveandlongterm(50to100years)strategicplanforlandandwatermanagementinsupportof asustainable livingenvironment. Itprovides avision,scenariosandadaptivestrategieswith interventions for the long termand investmentoptions for the shortandmedium term.TheGovernment’sdraftDeltaVisionisdefinedas:“Ensurelongtermwaterandfoodsecurity,economicgrowth and environmental sustainabilitywhile effectively coping with natural disasters, climatechange and other delta issues through robust, adaptive and integrated strategies, and equitablewatergovernance.”

In addition to traditional assessment methods such as MCA, the adaptive pathway approach,includingtheuseofmultiplescenarios,isusedtoanalysealternativestrategiesandmeasuresintimedealwithmultiple futures and to avoid lock-in situations. Developing alternative pathways alsosupports the preparation of future decisions. Another core principle of the plan is integratedassessmentof the strategiesonwater systemand socio-economicpolicy indicators.Resultsof theDeltaPlanarevisualisedthroughtheClimateAtlas;aninteractivetouchtableinwhichtheresultsofthe19thematicbaselinestudiesarecombined,visualisedandusedasinputforintegratedstrategydevelopment.Strategiesaredevelopedforfreshwaterandfloodriskmanagement,aswellasforthemainriversystemandthecoastalregion.Inadditiontotheselongtermcross-sectoralstrategies,in-depthanalysis – informedbydevelopingadaptivepathways – iscarriedout inHotSpotareas. Intheseareas,investmentneedsandopportunitiesaredefinedanddetailedasShowCasefortheDeltaPlan.

Whereasmakinguseofadaptivepathwaysandintegratedassessmentisalogicalwayofdealingwithuncertainties,theyalso introducea levelofcomplexity intoplanninganddecision-making.Existingplanningpracticeisfocussedonsector-basedneedsandresourcesandstructuredinto5-yearplans.Toensuresustainable implementationandmovebeyond theplanningstage; astrong linkagewiththeexistingplanningandimplementationcycleisthereforekey.

Keywords:adaptivepathways,longtermstrategicplan,DeltaPlan2100

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71. Advances In National Scale Long Term Investment Planning For Flood RiskManagement In The UK

PaulSayers,paul.sayers@sayersandpartners.co.uk,SayersandPartnersLLP/UniversityofOxford,UnitedKingdomofGreatBritainandNorthernIrelandJimHall,jim.hall@eci.ox.ac.uk,UniversityofOxford,UnitedKingdomofGreatBritainandNorthernIreland

ABSTRACT‘Decisionstakentodaywillhaveaprofoundimpactonthesizeoffloodrisksthatfuturegenerationswillneedtomanage.Theywillalsostronglyinfluencetheoptionsavailableformanagingthoserisks’(ForesightFutureFloodStudy)

Floodandcoastalerosionriskmanagementhasalwaysfacedthechallengeofdecision-makinginthefaceofmultipleuncertaintiesrelating to theclimate, theeconomyandsociety. Inresponse recentyearshaveseenasignificantfocusoninvestmentplanningunderconditionsoffutureuncertaintyintheprivatesector(e.g.WaterUtilities); inGovernmentagencies(e.g.EnvironmentAgency)and inacademic communities. Some of these methods are finding their way into investment planningprocesses(suchastheAgency’sLongTermInvestmentStrategy,LTIS,andThamesWaterinvestmentplanningprocesses).

ThefirstpartofthepaperoutlinestheprogressivedevelopmentofthenationalfloodriskassessmentintheUK(sinceoriginaldevelopmentoftheRASPmethods,Halletal,2003).Thepaperexplorestheunderlyingmethods and the various associated developments that have repeatedly been used toassessfloodriskinEnglandandWales.Thesecondpaperfocusonhowtheseapproacheshavebeenused alongside long term investmentdecision analysis (taking account of severeuncertainties inclimate,populationandassetdeterioration)tohelpdeterminethenationalinvestmentneedaspartoftheLTIS.InparticularrecentadvancesinthemethodsunderlyingtheLTIS2014studies,andtheroleitplaysinshapingthefloodriskmanagementagendaatanationalscale,isexplored.Throughoutthepaper,thetensionbetweenscientificrigourandpracticalapplicationisdiscussedtogetherwiththekeyinsightsandlessonsfromtheUKexperience.

Keywords:longterm,investmentplanning,nationalscale,floodrisk

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72. Is Unlocking Long Term Investment A Wicked Problem Of Deep Uncertainty?

AngelaWilkinson.StrategicForesightCounsellor,OECDFreijavanDuijne,PresidentofDutchFuturesSociety

ABSTRACTAvoiding “policy-basedevidence”on theonehandand “uncertaintyparalysis”on theother in thesearchfornewandbetteroptionsfordealingwithmessyandpuzzlingsituationscharacterisedbydeep uncertainty cannot simply rest on better policy briefings and is enabled instead throughcreatingaspaceforinteractiveandimmersivelearning.

We illustratethispropositionwithreferencetotheOECDMinisterialCouncilMeeting2015 whichengagedinascenariobasedpolicydiscussionsasawaytoexchangeknowledgeandforgecommongroundonthechallengesofunlockinginvestmentforsustainablegrowthandjobs.

Our learning from this process centres on the importance of prototyping high-level structureddialogues across diverse policy communities. This prototyping is key to opening up a space fordiscussion of latent futures –which are already in the here-and-now but left tacit, supressed ordeniedbythe‘’officialfuture”ofthedominantpolicynarrative.Deepuncertaintycreatesanxietyintheexpert(includingseniorpolicymakers).Combinedwithinstitutionalincentivesforsteppingupincrisis,ratherthanavoidingmissedopportunity,thisanxietyisexpressedofintermsofthefearthatconflictwillleadtochaosratherthaninformeffectiveaction.

Addressing theweak culture of foresight in policy,which often confuses scenario planningwithconditionalprojectionscalled“baselinescenarios”,requiresattentiontoacombinationofcognitive,behaviouraland institutionalbarriers indiplomaticandpolicyanalysiscommunities. It involves afundamentalshift from“predictandcontrol”and “zerosum”strategies, to “designrationality”andbalancingcompetitivetacticsandcollaborativestrategies.Ratherthanthepredictabilityofdecisionoutcomes, the emphasis shifts to the quality of judgment in terms of the quality of strategicconversationwhich is enabled by the social and intellectual processes of scenario planning thatcontributetotheframing,reframingandre-perceptionthepresentmessyandpuzzlingsituation.

Keywords:

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73. Prospective strategy: balancing Anticipation and Agility

Dr.M.(Martijn)vanderSteen,NetherlandsSchoolofPublicAdministration(NSOB),TheHague,TheNetherlands.Drs.J.Scherpenisse,NSOB,TheHague,TheNetherlands

ABSTRACTAn important strategic function ofgovernment is to adequately anticipate futuredevelopments –even though they are inherently uncertain and unforeseeable (Fuerth, 2009; Slaughter andInayatullah, 2005; Lempert et al, 2003;Newman andHowlett 2014; Schwartz, 1996; VanAsselt,MesmanandVan‘tKlooster,2007).Ascomplexitygrowsandsystemsbecomemoreintegrated,thenecessityofprospectivestrategizinggrows,while itatthesamebecomesharderasdevelopmentsare less linear and less continuous. In order to prepare forwhatmay be coming, organizationsattempt to lookbeyond thepresentstatusquoand toexpectnon-linearanddiscontinuouseventsanddevelopments (Brown,Rappert andWebster,2000; Swanson et al,2009,2010;Walker et al,2010;Inayatullah,2006;Moynihan2009;Riedy,2009;VanderSteen,VanTwist,VanderVlistandDemkes,2011;VanderSteen,2014;Howlett&Ramesh2014;).

Strategy formulation isnotmerely amatter of formulating the right goals and the route towardsachievingthem;itisalsoaboutformulatingtimelyanswerstoemergingproblems.Strategizingisnotonly aboutdoing the right thingsanddoing them right,butalso aboutdoing itat the right time.Therefore,strategizinginvolvesaprospectiveelement,wherestrategiststakeintoaccountnotonlywhat isalready therebut forwhatmaybe coming (VanTwist,PeetersandVanderSteen,2007).Minor developments can become major disruptions, as major drivers start out small andfundamentalchangeoftengrowsfromsmallseeds.Also,trendsanddevelopmentsthataredefiningvariablesfortheorganization inthepresentmaybemarginal inthenearfuture.Justasseeminglyinsignificantcracksinstructureshavethepotentialtobreakdowntheentirebuilding.

Timeandtimeagaintheevaluationsofdisastersandcrisesshowthat,onsecondglance,thereweremanyearlyindicatorsandsignalsfortheunexpectedandunanticipatedevents.Inhindsight,wecanoftenseewhatwehadmissedprospectively.Complexitytheorycallsthistheretrospectivecoherenceofcomplexsystems:inhindsight,whenweknowwhattolookfor,thereisplentytoseeandtherearerecognizablepatternsthatleadtowhattookusbysurprise.Forinstance,thereportbytheUSSenate'9/11Commission'showsanabundanceof ‘clear’signalsoftheupcoming ‘unprecedented’attacks.Thatseemstoindicate incompetenceofsecurityservicestoconnectthedotsbetweensignals;theydidnotmissoneclue,butanentirearray.

Evident as patterns may seem in hindsight, their coherence is essentially retrospective; we‘recognize’ them because we know the outcome. For organizations, the challenge is to turnretrospectivecoherencearoundanddevelopcapacity torecognizeprospectivecoherence.Thatalsoimplies the ability to lookbeyond continuityand ‘foresee’discontinuity evenunder conditions of‘deepuncertainty’(Walkeretal,2010)andfor‘wickedissues’(Rittel&Webber,1973).Therefore,itisimportanttounderstandhowearlywarningscanbecollected,interpretedandusedforstrategyinaproductiveandsystematicway.Howcanthe ‘right’signalsbedistilledfromthe infinitetangleofpossibledevelopments?Howcanearlywarningsbeinterpretedwhentheyareoftenambiguousandopen fordifferent interpretations?Andhow earlywarningsbe linked to andused in the currentstrategywhile they often diverge fromwhatwe currently know and base our strategy on? Thatinvolves the capacitiesofanticipationandagility;systematicattempts to foreseeand ‘know’whatmaybeahead,butalsothecapacitytodealwithinevitablesurprises,unexpecteddevelopments,and

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emerging issues. Amidst complexity and deep uncertainty, prospective strategy is a matter ofbalancinganticipationandagility.

Thispaperdescribesthepracticalattemptsofanorganizationtodeveloptheprospectivecapacitytorecognizeearlywarningsandweaksignalsthatwillormaydefinethefutureoftheorganization.Wefirstconceptualize thedifferentwaysfororganisationsto lookatearlywarningsandweaksignalsanddescribetheinherentdilemmasofthatactivity.Afterthat,weturntoourempiricalcasestudybydescribing thedesignof theEarlyWarning(EW)systemof‘Rijkswaterstaat’, theDutchgovernmentdepartment of Public Works and Water Management. Furthermore, we describe how theorganizationfurtherprofessionalizedandstreamlinedthismethodologyovertheyearsinanattemptto increase the impact on strategic decision- making.We conclude with a discussion about thefindingsonhowearlywarningscanbeusedforprospectivestrategizing,andwhatthebalancingofanticipationandagilitymeansfordesigningpolicy-systemsthatcandealwithdeepuncertainty.

Keywords:

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74. Planning, Programming and Budgeting of Infrastructure and Spatial Development inUncertain Times: Experiences with Adaptive Planning in the Netherlands

JosArts,TaedeTillema,JanvanderWaard,MartjeStorm,MichielRuis

ABSTRACTAswatersafetyandtransportinfrastructureareseenascrucialnationalinterests,anextensivesetofinstrumentshasbeendevelopedfortheplanning,programmingandbudgeting intheNetherlands.Nationalpolicies areprimarily implemented through projects.Accordingly, theDutchMinistry ofInfrastructure & Environment prepares annually the Long-range Programme for Infrastructure,SpatialDevelopmentandTransport(‘MIRT’); aprogrammingandbudgetingsystem thatregulatesthebudgetsandisupdatedeveryyear.ThisMIRTprocessinvolvesaratherextensivestagedprocessof developing plans, analysis, stakeholder involvement, review and decision-making resulting inprojects thatmightbe implemented.Thebasic ideabehindMIRT seems tobe a rather technical-rationalplanningconcept,inwhichthereisonedominantactorandastrongfocusongoodprojectmanagement(controllingscope,timeandbudgets),onmanagingrisksandonjuridicalacceptability.

However,incurrentplanningweareconfrontedwith(deep)uncertaintiesofclimatechange,ageinginfrastructures, a shift from new infrastructure development toward replacing existinginfrastructure, societal and spatial transformation processes, financial-economic dynamics andcritical stakeholders, which are all challenging this rather technical-rational planning concept.Important issues inpracticeare:theprotractedplanningprocess,dependencyonnationalfunding,costandtimeoverruns, limitedpublicsupport,detailedmodellingandcalculations,vulnerabilityofdecisionsfornegativecourtdecisionsand limitations inflexibilityduringallstagesoftheplanningprocess. These complexities call for a more adaptive planning, programming and budgetingapproach.

This has been acknowledged by national government, which is currently renewing the MIRT frameworkfocussing on 1) a broad scope focusing on challenges instead of solutions (projects), 2) a tailor-madeapproach and 3) cooperation between multi-stakeholders (co-creation). Also more adaptive planningapproaches are developed relating to modelling, using scenarios, new ways of financing, programmaticapproaches and innovative concepts for cooperation between public and private parties. A shift is soughtfrom a sectoral, project-oriented planning towards more task-/goal-oriented planning in which the variouschallenges in a region and the network are central (‘opgave-gericht werken’). In addition, in recent practiceexperiences have been gained with more adaptive planning such as in the ‘Room for the River’-programmeand the ‘RRAAM’-project (integrated regional development Amsterdam-Almere).

ThispaperaimstodiscussthechallengesandapproachesincurrentDutchinfrastructureandspatialplanning fordealingwithdeepuncertainties.Although thispaper focuses onDutchplanning,webelieve that thediscussion isalsorelevant foran internationalaudienceasmanyof the issuesareapplicable in other (western) societies. To this end, the paper describes first the current MIRTframeworkandplanningprocessintheNetherlands.Subsequently,currentdilemmasandchallengesofdealingwithdeepuncertaintyinplanningpracticearediscussed.Nextadiscussionfollowsonthenewavenuesthatareexploredtodealwiththesechallengesandrecentpracticalexperiencesgainedwithmoreadaptiveplanning.Finallysomeconclusionsaredrawnandpromisingavenuesandissuesforfutureexplorationarediscussed.

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75. Dealing with the uncertainty of severe weather and assisting emergency managers tomake better decisions

J.Perkins,BureauofMeteorology,J.Perkins@bom.gov.au,Australia,R.Webb,BureauofMeteorology,Australia

ABSTRACTAustralia has experienced a decade of intense tropical cyclones, monsoon lows, severethunderstorms and extreme riverine and flash floods with the state of Queensland the mostsignificantly affected. The total damages for weather related disasters in Queensland alone isestimatedatover$15billiondollarsstartingwithover$500milliondollarsfromTropicalCycloneLarryin2005/06andpeakingin2011/12withover7billionindamagesfromTropicalCycloneYasiandtheextremefloodsintheQueenslandcapitalcityofBrisbane.

TheBureauofMeteorology isAustralia'snationalweather,climateandwateragency.Itsexpertiseand services assist Australians in dealingwith the harsh realities of their natural environment,includingdrought,floods,fires,storms,tsunamiandtropicalcyclones.TheBureauisanorganisationthatmakes risk based decisions on uncertain forecasts every day and especially during extremeevents.Eventsevolverapidlyandourkeyroleistopresentandcommunicateuncertaininformationis such away that leads to quality risk-based decisionmaking by emergencymanagers and thecommunity.

Thefocuswillbeonthedeepuncertaintyinvolvedinpredictingthemovement,intensityandwindandstormsurgeimpactsoftropicalcyclonesandthecomplexitiesofpredictingintenserainfallandfloods.TheweatherforecastershaveaccesstoeightdifferentNumericalWeatherPrediction(NWP)models providing forecasts of the cyclone movement and all have equal likelihood. The floodforecastingserviceoperatesata localscaleandpredictsflood levelsatspecificpointsalongariverbutreliesonrainfall forecasts from thesameNWPmodelsand theuncertainty in time,spaceandintensity are considerable.TheBureau isdeveloping ensemblebased rainfall forecasting systemsthattrytoquantifytheuncertaintybuthowthisisthenusedbyforecastersanddisastermanagers.

Thispresentationwillcoverhowwecommunicateuncertaintyinouroperationalproducts,briefings,liaisonandeducationprogramsfocusingonTopicalCyclonesandFloodsandusingacasestudyofevents that occurred during the summer of 2014/2015 including Tropical Cyclones Marcia andNathan.

TropicalCycloneMarciahad ingredients thatchallenged thewarningsystemwithextremelyrapiddevelopment, rainfall impact that occurredwell away from the system centre and it struckmuchfurthersouththanothersystemsofthisstrengthhadpreviouslydone.

TropicalcycloneNathandevelopedthemonthafterTCMarciaandprovidedanopportunitytobetterdescribetheuncertaintywithinroutineproductsandmediabroadcasts.

The presentation will explore these differences, bringing decision making into the frame of theemergencymanagersandthecommunitytakingactionontheground.

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76. Challenges and Progress in Implementing DMU methods in World Bank Projects

JulieRozenberg,jrozenberg@worldbank.org,LauraBonzanigo,lbonzanigo@worldbank.orgStéphaneHallegatte,shallegatte@worldbank.org

ABSTRACTOverthepastthreeyears,theWorldBankSustainableDevelopmentgroupandClimateChangegrouphavebeen tailoringandapplying anumberofdecision-makingunderuncertainty tools tomanagedeep uncertainties and disagreement in long-term infrastructure projects. In Lima, Peru, weintegratedandadaptedseveralmethodologiestohelpthewaterutility,SEDAPAL,buildtheirMasterPlan. InNepal,wesupported thegovernment in thehydropowersectorplanning,evaluatingbasinlevelplanningandanindividualprojectdesign,andfollowingthe“DecisionTree”developedbytheWorldBankWaterSector.InColombo,SriLanka,weappliedRobustDecisionMakingtohelpthecitydevelop and build consensus around a Colombo Wetland Management Plan. In Peru again, weworkedwiththeMinistryofTradeandCompetitivenessandtheMinistryofTransporttoidentifythecriticalsegmentsofthePeruvianroadnetworkandtheirexposuretofloodsandstormsurges.WethenusedDMUtechniquestoprioritizeinterventionsnowandinthenextdecades.

Theseprojectswere conducted in close collaborationwith the client countries,achieved their fullbuy-in,andeventuallymodified thedecisionmakers’ initialplans.SEDAPAL, for instance,receivedthegreenlightfortheimplementationoftherevisedMasterPlanofwatersupplyinvestments,whilethegovernmentofSriLankadecidedtofreezedevelopmentontheurbanwetlandsandisdevelopingpilotprojectstomanageandfully integratewetlands inthe lifeofthecity.InNepal,DMUmethodsarenowbeingusedtoprioritizeprojectstobefinancedbytheIFC.Overall,moreandmoreprojectleaderswithintheWorldBankarenowwillingtoapplythesetechniques.

These successeshoweverdidnot comewithout challenges. First,access togooddata and lack ofappropriatemodels is often a challenge in our client countries.As a result, significant time andbudgethavetobespentonbothdatacollectionandmodeldevelopment.Whensufficientresourceswerenotavailable,wetreatedmostparametersoftheanalysisasuncertain,butthiscomplicatesthedecisionmakingprocessasdecisionmakersstrugglenotfindconfidenceintheresultswhentheyaredeterminedby toomanyuncertainties.Nevertheless, theanalyses still raise interestas aproofofconceptforfutureprojects.

Second,supportinmonitoringandimplementationoftheprojectsisnotensuredafterthedecisionmakingprocess.Resourcesareavailabletoassistclientstomakedecisionsbutmaynotbeavailableto help them through the (political, often) implementation process. In Sri Lanka for instance,althoughtheMinistryofUrbanPlanninghasdecidedtofreezethedevelopmentonthewetlands,thisdecisionmaybereversedinthenextfewyearswhentheMinisterchangesandprioritieschange.Away tomitigate this issue is tobuild capacity in the client countries, ingovernmentagenciesanduniversitiesinparticular.

Finally, the scaling up ofDMUmethodswithin theWorld Bank is challenged by limited internalresources, either technical, to carry the analysis in house, or financial, to contract externalconsultants.Evenwithsufficientresources,thenumberofDMUexpertsisstillcontainedcomparedtotheprojectsthatwouldneedanalyticalsupport.Therefore,trainingisagainparamount.Asastart,wearebuildingacommunityofpracticewithintheWorldBankthatwehopewecan linkwiththecommunityofthisworkshop.

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77. The impacts of climate change on poverty in 2030, and the potential from rapid,inclusive and climate-proof development

JulieRozenberg,,jrozenberg@worldbank.org,StéphaneHallegatte,shallegatte@worldbank.org,,ClimateChangeGroup.TheWorldBank

ABSTRACTThe impactsofclimatechangeonpovertydependonthemagnitudeofclimatechange,butalsoondemographic and socio-economic trends.This analysis createshundreds ofbaseline scenarios forfutureeconomicdevelopmentintheabsenceofclimatechangeandineachofthe92countriesoftheI2D2 database. It combines household surveys andmicro-simulation techniques in a frameworkinspired from robust decision-making techniques, in which all uncertain parameters are variedsystematically to the full range of possible outcomes.Then, the conditions underwhich extremepoverty can be eradicated by 2030 are identified. The drivers of success are different acrosscountries:forinstance,demographyd

ominates inmanypoorercountries,whileredistributiononlymatters inmiddle-incomecountries.Outofthesescenarios,tworepresentativescenariosareselected.Oneisoptimisticregardingpovertyandislabelled“prosperity”;theotheroneispessimisticandlabelled“poverty”.

Results frommultiple sector-scale analyses of climate change impacts are introduced in the twoscenarios, looking at agriculture, health, and natural disasters. The analysis is partial, disregardspossibly important impacts, and results remain highly uncertain. It also looks only at 2030, atimescale forwhichclimate change remainmoderate comparedwithexpected long-term changes.Conclusionsaretwofold.

First,by2030climatechangecanhavea large impactonpoverty,withbetween3and122millionmorepeopleinpoverty,butclimatechangeremainsasecondarydriverofpovertytrendswithinthistimehorizon.Climatechangeimpactsdonotonlyaffectthepoorest:in2030,thebottom40percentlosemorethan4percentofincomeinmanycountries.TheregionalhotspotsareSub-SaharanAfricaand–toalesserextent–IndiaandtherestofSouthAsia.Themostimportantchannelthroughwhichclimatechangeincreasespovertyisthroughagriculturalincomeandfoodprices.

Second, by 2030 and in the absence of surprises on climate impacts, inclusive climate-proofdevelopment canpreventmost of (butnot all) the impacts onpoverty. In a scenariowith rapid,inclusive and climate-proofdevelopment, climate change impact onpoverty isbetween 3 and16million,vs.between35and122million ifdevelopment isdelayedand less inclusive.Developmentappears toreduce the impactofclimatechangeonpovertymuchmore than itreducesaggregatedlossesexpressedinpercentageofGDP.

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78. Lessons and challenges from early applications of Dynamic Adaptive Policy Pathways

MarjolijnHaasnoot,marjolijn.haasnoot@deltares.nl,JanKwakkel,J.H.Kwakkel@tudelft.nlWarrenWalker,w.e.walker@tudelft.nlVincentMarchau,v.marchau@fm.ru.nlDecisionsonadaptationandother investmentsare takenover time,often inresponse tochangingconditionsandeventsthatilluminatecurrentorfutureproblemsandopportunities.Exploringstageddecisionmaking throughadaptationpathways isreceiving increasedattentionboth inscienceandpractice.Underdeepuncertainty, the exploration ofpathwaysunder various changing conditionshelps in identifyingbothactionsthatshouldbetaken intheshorttermand long-termoptionsthatcan be taken if needed. One approach, for which several applications already exist, is DynamicAdaptivePolicyPathways(DAPP).AkeyelementofDAPPisavulnerabilityassessmenttoassesstheconditionsunderwhichapolicystartstoperformunacceptably(an‘adaptationtippingpoint’),whichis then used to explore various adaptation pathways (sequences of actions after an adaptationtippingpoint).Pathwaymapsenablepolicyanalysts,decisionmakers,andstakeholderstorecognizepotential ‘locked-in’ situations and assess the flexibility, robustness, and efficacy of decisionalternatives. ‘Signposts’ and ‘triggers’ can then be specified to get earlywarning signals for theimplementationofthenextactionsinanadaptationpathway.MostoftheapplicationsofDAPPhavebeenindeltas,coastalcities,andfloodplains,oftenwithinthecontextofclimatechangeadaptation.

Inthistalk,wewilldescribetheDAPPapproach,discussdifferentmethodsandtechniquesthathavebeen employed in applications of DAPP, and closewith lessons learned and key challenges thatrequirefurtherattention.FromearlyapplicationsoftheDAPPapproach,differentwaysofidentifyingadaptationtippingpointsemerged,including(a)sensitivityanalysisandexpertjudgment,(b)semi-staticassessment,and(c)transientscenarios.Givenanoverviewoftippingpoints,pathwayscanbespecified.Thishasbeendonea)byexploring(combinationsof)actionsafterthesepoints,b)throughnarratives,andsimulationgaming,andc)computationallythroughtheuseofmulti-objectiverobustoptimization and agent basedmodelling. Early DAPP applications showed that the evaluation ofalternativepathwayshasreceived littleattentionandappearsnotstraightforward,asassumptionsabout the project time horizon, discount rate, and assessment of costs of switching betweenpathwaysarecrucialfortheresults.Moreover,thewayinwhichamonitoringplanistobedesignedin lightofanadaptationpathwayhasreceived littleattentionso far.Earlyapplicationsshow that,althoughfromapolicyperspective itmakessensetoselecttriggersthatcomefromnorms,values,andobjectives,itmightbebettertousesignpoststhatoccurearlierintheimpactchainassignalsforchanges.