Flood Risk Management and the U.S. Army Corps of Engineers Actions for Change

1. Flood Risk Management and the U.S. Army Corps of Engineers Actions for Change 4th International Symposium on Flood Defence: Managing Flood Risk, Reliability and Vulnerability Toronto, Canada May 6-8, 2008 David Moser1, Martin Schultz2, Todd Bridges2 and Brian Harper1 US Army Corps of Engineers 1. Institute for Water Resources, Alexandria, VA 2. Engineer Research and Development Center, Vicksburg, MS Relevant, Ready, Responsive, Reliable

2. Outline • Twelve Actions for Change • Risk-informed decision framework (RIDF) for Louisiana Coastal Protection and Restoration (LaCPR) Project. • Illustrative example: • How risks, costs, and other tradeoffs are evaluated. • How risk and uncertainty is incorporated into the decision process. • How stakeholder preferences are considered. • How RIDF serves the Actions for Change Relevant, Ready, Responsive, Reliable

3. Actions for Change (1-8): Systems and Risk-Based Approaches • Employ an integrated, systems-based approach • Employ risk-based concepts in planning and design • Continuously reassess and update policy • Employ dynamic independent review • Employ adaptive planning and engineering systems • Focus on sustainability • Review and inspect completed works • Assess and modify organizational behavior Relevant, Ready, Responsive, Reliable

4. Actions for Change (9-12): Communication and Professionalism Communication: • Effectively communicate risk • Involve the public in developing risk reduction strategies Professionalism: • Manage and enhance technical expertise and professionalism • Invest in research Relevant, Ready, Responsive, Reliable

5. Louisiana Coastal Protection and Restoration Project (LaCPR) “…develop and present a full range of flood, coastal, and hurricane protection measures exclusive of normal policy considerations for south Louisiana.” Factors not restricted to of national economic benefits and costs. Consider full range of risks to people, cultural heritage, environment, property, and economy as well as project costs. Charge: Five Planning Units in So. Louisiana Relevant, Ready, Responsive, Reliable

6. Risk-Informed Decision Framework • Multi-Criteria Decision Analysis (MCDA) • Identify plan that maximizes utility and optimizes the level of risk reduction given preferences • Provides a means to: • Make tradeoffs between risks, costs, and other decision outcomes • Enhance transparency • Account for aleatory and epistemic uncertainty • Address stakeholder preferences and values Relevant, Ready, Responsive, Reliable

7. Steps of Multi-Criteria Decision Analysis (MCDA) • Identify decision alternatives • Develop an objectives hierarchy and choose performance metrics • Assess preferences over objectives • Model performance of decision alternatives • Evaluate multi-attribute utility scores • Choose alternative that maximizes expected utility • Sensitivity analysis Relevant, Ready, Responsive, Reliable

8. Illustrative Example • Nine (9) flood risk-reduction alternatives and a no-action alternative • Five (5) decision objectives and eight (8) performance metrics • Three (3) uncertain planning assumptions • Stage frequency curve (ADCIRC Model) • Development pattern (employment growth rate and population distribution) • Rate of relative sea-level rise Relevant, Ready, Responsive, Reliable

9. Objectives Hierarchy and Metrics Relevant, Ready, Responsive, Reliable

10. Preferences and Consequences • Assess stakeholder and decision maker’s preferences over objectives • Conduct interviews using an elicitation instrument to assess relative importance. • Obtain relative preference weight on the sub-objective • Model decision outcomes for each alternative in terms of performance metrics Relevant, Ready, Responsive, Reliable

11. Multi-Attribute Utility • Utility: An aggregate measure of relative satisfaction with modeled decision outcomes given objectives • Transform metrics to a 0 (worst) to 1 (best) • Weight transformed metrics by relative importance • Compensatory • Six Planning Scenarios Relevant, Ready, Responsive, Reliable

12. Relative Sea-level Rise Uncertainty In stage frequency Development Pattern Performance Outcome (Utility score) Decision Alternatives High & compact Alternative 1 High Alt 2 BAU & dispersed Moderate Alt 3 None Alt n Alt N Multi-Criteria Decision Analysis Maximize Expected Utility: Relevant, Ready, Responsive, Reliable

13. Sensitivity of the Decision • Choose alternative that maximizes expected utility • Optimal level of risk reduction is the level associated with the chosen alternative given the decision maker’s preferences. • How sensitive is the decision? • to stakeholder and decision maker’s preferences? • to the distribution of probability over sea-level rise scenarios? • to the pattern of development? Relevant, Ready, Responsive, Reliable

14. Sensitivity to Preference Patterns BAU employment Dispersed population High employment Compact population Relevant, Ready, Responsive, Reliable

15. How sensitive is the decision to sea-level rise assumptions? BAU Employment Growth Rate and Dispersed Population Relevant, Ready, Responsive, Reliable

16. Changing the Development Scenario alters the Landscape High Employment Growth Rate and Compact Population Relevant, Ready, Responsive, Reliable

17. Risk-Informed Planning and the USACE Actions for Change • An integrated, systems-based approach to problem solving • Uses risk-based concepts in planning and decision making • Suitable for adaptive planning and engineering systems • Helps planners effectively communicate risks • Involves stakeholders in developing risk reduction strategies and decision making Relevant, Ready, Responsive, Reliable

18. Back-up Slides Relevant, Ready, Responsive, Reliable

19. Relevant, Ready, Responsive, Reliable

20. Aleatory and Epistemic Uncertainty • Aleatory uncertainty: • Natural variability that cannot be reduced • Example is the variability in storm surge • Epistemic uncertainty: • Lack of knowledge, can in principle be reduced • Examples used in modeling performance outcomes for LaCPR: • Characterization of the stage frequency curve for storm surge • Projections of the future rate of sea-level rise • Population and employment growth rate projections Relevant, Ready, Responsive, Reliable

21. Model Performance of Alternatives in Terms of Risk Metrics • Calculate risk metrics under each plan • Integrate stage frequency curve w/ the damage function • Characterize parameter uncertainty in the risk metrics • Integrate realizations of the stage frequency curve w/ damage function Relevant, Ready, Responsive, Reliable

22. Multi-attribute Utility (U ) Value Function Averse Neutral 1 U Multi-attribute utility score w Preference weight on objective V(mi) Risk-neutral value score M Metric for the objective i Index on objectives Value V(mi) Seeking 0 Worst Best Metric (m) Relevant, Ready, Responsive, Reliable

23. Six Planning Scenarios Relevant, Ready, Responsive, Reliable

24. Assess Preferences over Objectives Stakeholder and Decision Maker’s Relevant, Ready, Responsive, Reliable