optimisation of flood risk management strategies - developments in frmrc

Optimisation of flood risk management strategies- Developments in FRMRCMichelle Woodward1,2, Ben Gouldby1 and Zoran Kapelan2International workshop on the science of asset management9th December 20111 HR Wallingford 2 University of Exeter

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Presentation OverviewDecision Support system overviewDescription of each componentFlood risk management intervention strategiesRisk analysis modelCost ModelOptimisation AlgorithmDecision support Case study on the Thames Estuary

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Decision Support System

Description of flooding system (Present day)(S-P-R)

Flood System Risk Analysis Tools (e.g. simplified RASP)

Loss of Life surrogate model (e.g. reduction in loss of life on the floodplain)

Expenditure / Option Cost Tools (cost functions for improvement, reconditioning and replacement, channel and beach management etc)

People at risk

Costs

Optimisation EngineOptimise flood risk management options

User input

Output

Optimal option sets and decision support

External constraints and objective functions (preferences)

Autonomous future change (e.g. climate / socio-economic / deterioration etc)

External futures




Costs


User input

Output




External futures

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Decision Support System INPUTIntervention Strategy constraints: - Length of intervention strategy (e.g. 10yrs, 15yrs, 20yrs) - Number of time steps (e.g. 1, 2, 3) - Length of time steps (e.g. 5yrs, 10yrs ) - Types of intervention measures (e.g. Structural interventions, flood proofing) - Constraints between time steps (e.g. Account for previous epochs) - Constraints to ensure realistic measures (e.g. max height increase)Selection of Objective Functions - Single objective (e.g. NPV, BCR) - Multi objective (e.g. Benefit, Cost, Loss of life )

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People at risk

Costs


User input

Output




External futures




Costs


User input

Output




External futures

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Flood risk modelUtilises a structured definition of the flood system(For a more detailed description see Hall et al 2003., and Gouldby et al 2008.)

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Intervention measures implemented in risk model SOURCE PATHWAYRECEPTORRaise crest level of defenceWiden base of defencesSet back defencesDefence maintenanceFlood proof propertiesFlood warningsClimate Change ScenariosSocio Economic Scenarios

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Simplified risk modelModel approximation replaced Monte-Carlo simulation with an average volume approachNumber of inundation simulations from:

>20,000 goes to 5

Ok For optimisation?97.97%

Option 1

Object A

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People at risk

Costs


User input

Output




External futures




Costs


User input

Output




External futures

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Cost Model

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Flood Defence

Tidal?

Type 1 :Vertical Wall

Type 7 :Beach

No

Yes

Fluvial Defence

Coastal Defence

Type 6 :Sloping Seawall

Type 5 :Vertical Seawall

Type 4 :Culverts

Type 3 :High Ground

Type 2 :Slope or Embankment

Maintenance / Construction Costs

(see Figure 4.2 for an example)

Overheads / Mobilisation Costs

Single Cost ItemsOfficeOffice FurnitureOffice ExpenditureKitchenChanging / Rest AreaPhones / email / faxWater

Cost Items per GangSurveying Equipment (0.5/gang)ToiletStoreGenerator / FuelTransformer

OtherHeating / Lighting (1 per building)Local RatesTemporary Hard SurfacesTemporary Portable SurfacesPlant Hire (2 per gang)

General Overheads

General Site Clearance1.5% of total mobilisation costsOther Costs10% of total mobilisation costs

General Costs (%)Non Productive Site SalariesSite Staff ExpensesPlant MaintenanceTransport Costs

Extra Labour CostsSmall ToolsProtective EquipmentOther

Temporary Works

InsuranceEmployers LiabilityVehicleAll RisksPublic LiabilityProfessional IndemnityLoss of MoneyFidelityOther

Security

Bonds (per annum)

ConstructionMaintenance

Flood Defence

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Cont


Flood Defence

Tidal?

Type 1 :Vertical Wall

Type 7 :Beach

No

Yes

Fluvial Defence

Coastal Defence

Type 6 :Sloping Seawall

Type 5 :Vertical Seawall

Type 4 :Culverts

Type 3 :High Ground

Type 2 :Slope or Embankment

Maintenance / Construction Costs

Overheads / Mobilisation Costs

Single Cost ItemsOfficeOffice FurnitureOffice ExpenditureKitchenChanging / Rest AreaPhones / email / faxWater

Cost Items per GangSurveying Equipment (0.5/gang)ToiletStoreGenerator / FuelTransformer

OtherHeating / Lighting (1 per building)Local RatesTemporary Hard SurfacesTemporary Portable SurfacesPlant Hire (2 per gang)

General Overheads

General Site Clearance1.5% of total mobilisation costsOther Costs10% of total mobilisation costs

General Costs (%)Non Productive Site SalariesSite Staff ExpensesPlant MaintenanceTransport Costs

Extra Labour CostsSmall ToolsProtective EquipmentOther

Temporary Works

InsuranceEmployers LiabilityVehicleAll RisksPublic LiabilityProfessional IndemnityLoss of MoneyFidelityOther

Security

Bonds (per annum)

ConstructionMaintenance

Flood Defence


Type 1 Defence:Vertical Wall

Wide

Crest Protection

Remove Vegetation(Crest, Rear)

Remove Vegetation(Rear)

No

No

Yes

Yes

Rear Protection

No

CG=1

CG=2

CG=4

CG=3

No

No

No

S=0.0%M=0.0%E=0.0%

S=0.0%M=25.0%E=75.0%

S=30.0%M=30.0%E=30.0%

S=12.5%M=12.5%E=0.0%

S=2.5%M=0.0%E=0.0%

Yes

Yes

Yes

Yes

No

S : Remove and replace top 0.25m of embankment

M : Remove and replace top 1.00m of embankment

E : Demolish and rebuild embankmentE : Demolish existing brickworkE : Excavate and reinstate backfillE : Bonding to existing workE : Replacement brickwork

M+E : EarthworksM+E : Cut-out and replace defective masonry

S+M+E : Preparation for new rip-rapS+M+E : Compaction and TrimmingS+M+E : Replacement, new rip-rap

Identify CG to determine amount of structural improvement required before height raise

S+M+E : Repoint MortarS+M+E : Clean Moss and Lichen

Yes

Levee Type 2: Slopes and Embankments

Output: quantity of work required for defence

Input defence subtype

Input current condition of defence

Set levels of work required based on CG

Input additional works based on height of defence increase (m) and defence dimensions

CG12345

SubclassDescriptionMaterialsWidth10FPTurfNarrow11FPRigidNarrow12FP, CPRigidNarrow13FP, CP, RPRigidNarrow14FPRip-rapNarrow15FP, CPRip-rapNarrow16FP, CP, RPRip-rapNarrow17FPFlexibleNarrow18FP, CPFlexibleNarrow19FP, CP, RPFlexibleNarrow45FPTurfWide46FPRigidWide47FP, CPRigidWide48FPRip-rapWide49FP, CPRip-rapWide50FPFlexibleWide51FP, CPFlexibleWide

Input defence dimensions

CGSlight defectModerate defectExtensive defect10.0%0.0%0.0%22.5%0.0%0.0%312.5%12.5%0.0%430.0%30.0%30.0%50.0%25.0%75.0%

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People at risk

Costs


User input

Output




External futures




Costs


User input

Output




External futures

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Optimisation AlgorithmsOptimisation techniques are beneficial in flood risk management because

they can handle a large portfolio of possible intervention options at different sequences through time

- they can give consideration to multiple conflicting objectives

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Evolutionary Algorithms Powerful Search Process Based on Darwins Theory of Natural Selection and survival of the fittest Methods include:Genetic AlgorithmsShuffled Complex EvolutionAnt Colony OptimisationMulti-Objective Genetic Algorithm

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Genetic AlgorithmGenerate initial populationSTARTEvaluateobjectivefunctionAreoptimisationcriteriamet?BestindividualRESULTGenerate new populationMutationCrossoverSelectionSingle Objective Optimisation: Maximise NPV or Maximise BCRMultiobjective optimisation: Maximise Benefits and Minimise Costs

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People at risk

Costs


User input

Output




External futures




Costs


User input

Output




External futures

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Decision Support OUTPUTSingle Objective Optimisation:- Single Optimal Intervention strategy- Optimised according to chosen objectiveMulti Objective Optimisation:- A trade off curve (Pareto Front) of the conflicting criteria- A set of optimal intervention strategies to support decision makers

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The Pareto Front

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The Pareto Front

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The Pareto Front

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Case Study on the Thames EstuaryWestminsterGreenwichTilburyRiver LeeRiver RodingPurfleetGravesendRichmond

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Flood Defence Examples1. Concrete vertical wall2. Embankment3. Sheet-pile vertical wall1.2.3.

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Results

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Summary/conclusions Risk models are useful decision support tools

These models can be simplified for use in optimisation analysis

Multi-objective optimisation techniques can provide more information to decision makers

Multi-objective optimisation techniques are useful tools to automate the search process given a large range of potential options

Need to incorporate a greater range of consequences in risk models, loss of life (hence benefits of flood warning), environmental impacts etc.

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Dissemination of workWoodward, M., Gouldby, B., Kapelan, Z., Khu, S. T. & Townend, I. (2011) Real Options in Flood Risk Management Decision Making. Journal of Flood Risk Management, 4, 339-349.

Woodward, M., Gouldby, B., Kapelan, Z. & Hames, D. (2011) Multiobjective Optimisation for Improved Management of Flood Risk. ASCE Journal of Water Resources Planning and Management, (In Review).

Woodward, M., Kapelan, Z. & Gouldby, B. (2011) Developing Flexible and Adaptive Flood Risk Management Options Based on a Real Options Decision Tree Approach. (In progress)

Based on Source-Pathway-Receptor modelExtreme value distributions of hydraulic loadFragility curves to calculate probability of failure given loadHydraulic flood spreading model to calculate the flood depthDepth Damage curves to calculate the EAD to a the floodplain

In our project RASP is used to analyse different intervention strategies, this feeds into the optimisation process to assess the overall performance of each strategy. To evaluate intervention strategies it is possible to modify the source, pathway and receptor within RASP to represent intervention measures and future scenariosSummary of Evolutionary optimisation methods.Automated search techniquesSuitable for flood risk management because it can search through very large portfolio of possible intervention options and inform decision makers of most appropriate time and place to implement optionsMany different types of evolutionary algorithms. Genetic Algorithms (GA) most popularGAs can be used to optimise single and multi objective problemsAgain suitable for flood risk management because of the many criteria that need to be considered during the appraisal processFlow chart of the GA process and its main stagesProgression of a Pareto Front through the generations.Each point on graph represents a possible solutionOver time, the solutions evolve to further improve the objectives until the optimum set has been converged uponArea of Thames (Thamesmead area) analysed during optimisation processSummary of Evolutionary optimisation methods.Automated search techniquesSuitable for flood risk management because it can search through very large portfolio of possible intervention options and inform decision makers of most appropriate time and place to implement optionsMany different types of evolutionary algorithms. Genetic Algorithms (GA) most popularGAs can be used to optimise single and multi objective problemsAgain suitable for flood risk management because of the many criteria that need to be considered during the appraisal process

optimisation of flood risk management strategies - developments in frmrc

Documents

flood risk modelutilises

beach management etcpeople

flood proofing constraints

previous epochs constraints

bcr multi objective

yrs types

yrs number

length of time steps