The United States experienced record-breaking losses from natural disasters in 2017. Damages from floods were particularly costly, largely because of the high exposure and value of capital at risk. Without targeted mitigation strategies, flood losses are expected to escalate due to urbanization and the projected changes to the frequency of extreme weather events. This dissertation provides and evaluates engineering methods for flood risk mitigation in an era of global change. The body of work contains three research articles: two provide and critique methodology for incorporating changing environmental conditions in the design of flood control infrastructure along rivers and coasts, and the third contributes guidance for improving the clarity and utility of commonly produced flood hazard maps. The results demonstrate that attempting to forecast the impact of changing environmental conditions on extreme floods substantially increases predictive uncertainty relative to traditional methods. Thus, so-called ``non-stationary" methods have limited utility for decision making and are difficult to use as the basis for infrastructure design or mitigation planning. Our inability to meaningfully forecast changes in extremes over long time periods has important implications for engineering, but the first step is to acknowledge the unknown. Additional factors of safety, adaptable decision making, and better communication of what we actually do know are the keys to successfully reducing losses.
|Advisor:||Sanders, Brett F.|
|Commitee:||AghaKouchak, Amir, Vrugt, Jasper A.|
|School:||University of California, Irvine|
|School Location:||United States -- California|
|Source:||DAI-B 80/01(E), Dissertation Abstracts International|
|Subjects:||Hydraulic engineering, Hydrologic sciences, Statistics, Civil engineering|
|Keywords:||Bayesian statistics, Climate change, Extreme value analysis, Flood frequency analysis, Risk communication, Sea level rise|
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