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Optimisation of flood risk management strategies - Developments in FRMRC

Optimisation of flood risk management strategies - Developments in FRMRC. Michelle Woodward 1,2 , Ben Gouldby 1 and Zoran Kapelan 2. 1 HR Wallingford 2 University of Exeter. International workshop on the science of asset management 9 th December 2011. Presentation Overview.

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Optimisation of flood risk management strategies - Developments in FRMRC

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  1. Optimisation of flood risk management strategies- Developments in FRMRC Michelle Woodward1,2, Ben Gouldby1 and Zoran Kapelan2 1 HR Wallingford 2 University of Exeter International workshop on the science of asset management 9th December 2011

  2. Presentation Overview • Decision Support system overview • Description of each component • Flood risk management intervention strategies • Risk analysis model • Cost Model • Optimisation Algorithm • Decision support • Case study on the Thames Estuary Page 2

  3. Decision Support System Page 3

  4. Decision Support System INPUT • Intervention 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 …) Page 4

  5. Decision Support System Page 5

  6. Flood risk model Utilises a structured definition of the flood system (For a more detailed description see Hall et al 2003., and Gouldby et al 2008.) Page 6

  7. Intervention measures implemented in risk model SOURCE Climate Change Scenarios Defence maintenance Widen base of defences Raise crest level of defence PATHWAY Set back defences Flood warnings RECEPTOR Socio Economic Scenarios Flood proof properties Page 7

  8. Simplified risk model • Model approximation – replaced Monte-Carlo simulation with an average volume approach • Number of inundation simulations from: • >20,000 goes to 5 • Ok For optimisation? 97.97% Page 8

  9. Decision Support System Page 9

  10. Cost Model Page 10

  11. Cont… Page 11

  12. Decision Support System Page 12

  13. Optimisation Algorithms • Optimisation 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 Page 13

  14. Evolutionary Algorithms • Powerful Search Process • Based on Darwin’s Theory of Natural Selection and survival of the fittest • Methods include: • Genetic Algorithms • Shuffled Complex Evolution • Ant Colony Optimisation • Multi-Objective Genetic Algorithm Page 14

  15. Genetic Algorithm Single Objective Optimisation: Maximise NPV or Maximise BCR Multiobjective optimisation: Maximise Benefits and Minimise Costs START Are optimisation criteria met? Generate initial population Evaluate objective function Best individual Generate new population RESULT Mutation Crossover Selection Page 15

  16. Decision Support System Page 16

  17. Decision Support OUTPUT • Single Objective Optimisation: • - Single Optimal Intervention strategy • - Optimised according to chosen objective • Multi Objective Optimisation: • - A trade off curve (Pareto Front) of the conflicting criteria • - A set of optimal intervention strategies to support decision makers Page 17

  18. The Pareto Front Page 18

  19. The Pareto Front Page 19

  20. The Pareto Front Page 20

  21. Legend Tidal flood risk area Tidal flood defences Case Study on the Thames Estuary River Roding River Lee Westminster Purfleet Tilbury Greenwich Richmond Gravesend Page 21

  22. Flood Defence Examples 2. 1. 3. 1. Concrete vertical wall 2. Embankment 3. Sheet-pile vertical wall Page 22

  23. Results Page 23

  24. 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. Page 24

  25. Dissemination of work • Woodward, 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) Page 25

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