4 Risk Management - Background In UK 5 million people in 2 million homes live in flood risk areasOver 120,000 residential and commercial properties at erosion riskSignificant geographic variationWidespread flooding experienced in 1998 and 2000“Lessons Learned” led to an enhanced emphasis on flood risk managementUK Government Flood & Erosion Risk Management Objective:In order to ensure the best use of public money, target spending in those areas of greatest flood risk, whilst seeking to maximise the return on investment in terms of reduction of flood risk.Erosion figures shown are from Defra’s National Appraisal of Assets at Risk Study (2002) which suggested that £7.7b of capital assets were at risk from coastal erosion. That figure was low compared to flood, but nevertheless a substantial financial risk to our nation.
5 Risk Assessment for Strategic Planning (RASP) Structured approach to the analysis and management of the flooding systemFocus on risk, explicitly recognising that defences and flood plains perform as ‘systems’(HR Wallingford, 2001)
6 Performance of flood risk structures represented as ‘fragility curves’ Analysis PhilosophyFigure 1:Halcrow have been involved in two studies related to improving the prediction of the flood pathway within the risk based framework.The pathway is defined by fragility curves. A fragility curve is used to define the relationship in the framework between the ‘source’ or ‘loading’ and the probability of failure. Where probability of failure is related to the failure to perform a flood risk role ie., breach or overtopping.Fragility curves are developed for the five key condition grades ranging from very good to very poorPerformance of flood risk structures represented as ‘fragility curves’Relates loading on an asset to the conditional probability of failure of that asset given that loading.
7 Predicting to flooding pathway True Fragility CurveRASPFigure 2:Fragility curves illustrate the relationship between the loading on an asset and the conditional probability of failure of the asset given that loading.Based on: field inspections, empirical models, limit state equations, expert judgementDeveloped for approx. 60 generic asset types
8 Asset Condition Grades Fragility curves are developed for the five key condition grades ranging from very good to very poorFive condition gradesBased on asset performance, not just traditional condition.
9 Receptor The Analytical Approach Pathway Source Pathway LoadProbabilitySourceDamageReceptorDepthProbability of failureLoadPathway
10 Performance-based Asset Management System (PAMS) PAMS project:Developing performance-based approach to identifying and prioritizing management of flood defencesOngoing studies, including:Improved failure mode analysis to determine key performance features, and hence condition gradeLocal applications to determine site specific fragility curvesFragility curves are developed for the five key condition grades ranging from very good to very poor
13 Application of RASP Set-up within GIS National Assessments: 2002, 05, 06 & 082004 Foresight Future FloodingUsed to inform policy and decision makingProvide consistent national flood risk mapping (public access)Local scale assessments:Project developmentAssist in the planning maintenance and replacement of assets
15 Asset Management System (AMS) Based on existing GIS data platform (SANDS)Import, visualize and manipulate asset dataBasis for consistent data captureRecord asset types and condition, hence fragilityIdentify asset systemsLink assets to risk areas and receptorsUse cost models to optimise investment strategies
16 Key Components of System Base mappingAsset inventoryRelationship between loading and asset condition (fragility curve)Cost models for upgrading from different condition grades (hence improving performance) for a given asset typeFlood extent and receptor data
23 Ongoing DevelopmentUse of optimization engine to automate decision-makingTool to provide user with top ten outcomes (against multi-criteria objectives), to enable considered selection of preferred optionPossible development for use at higher, regional & national level to inform policy makers and budget setters
24 Conclusions Benefits of Risk-based Asset Management: provides for systematic and co-ordinated approach to asset managementrequires comprehensive asset information (facilitates collection)focus on asset function and reduction of riskavoid surprises (physical or financial)evidence-based decision-makingAMS benefits:built on established database platformconsistent data storage and analysisfacilitates improved decision-makingmaximize risk management benefits from finite budgets