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Robustness of Risk-Based Optimization Methodology for Flood Protection Decisions

Author(s): Balqis Mohamed Rehan

Linked Author(s): Balqis Mohamed Rehan

Keywords: Risk-based decision making, flood risk management, optimization, decision making

Abstract: Historically, flood events have caused disastrous impacts to human life. Severe damages to properties and infrastructures, environmental damage and even loss of lives have been experienced in many countries due to the natural disaster. Recognizing the importance of protecting vulnerable society from the adverse consequences of extreme flood events and managing long-term flood risk has become a salient adaptation response. Engineered structural flood protection is one of the many measures that significantly reduce the impacts of flooding. In deciding upon an optimal flood protection design of a structural protection, there is now a shift from the traditional standard fixed return period to a more holistic approach of risk-based decision making. A risk-based optimization methodology is one of the decision tools in flood risk management that prioritize public expenditure whilst providing protection against disastrous flood impacts. This study aims to investigate the robustness of the methodology against uncertainty caused by the natural variability. A modeling approach comprises simulations of annual maxima flow series and of decision makers� behavior in applying the risk-based optimization methodology is adopted. 128 Annual maxima flow discharges from Thames at Kingston gauging records in London were processed and used for a realistic representation of an extreme distribution. The performance of decisions from the risk-based optimization methodology is captured in economic terms. It is found that the risk-based optimization methodology is robust to uncertainty caused by the natural variability and that decisions are performing well economically for a service period of 100 years. These findings provide evidence that the methodology is suitable to be adopted in deciding upon the optimal flood protection designs of structural measures


Year: 2017

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