Storm induced flooding presents a multifaceted threat to coastal communities across the world.With climate change and sea level rise this danger is expected to increase. As coastal communities become exposed to more frequent and more severe flooding, the need for protective measures will increase. To know how to optimally protect against coastal flooding requires an understanding of future flood risk, storms, and storm surge. These are challenging to estimate due to many sources of uncertainty.
In this thesis I present a methodology to forecast this future flood risk. I combine multiple computational, physics and statistical models to accurately describe the fluid dynamics of flooding, the cyclones that drive surge, and how climate change will influence these different components in the future. These computational models must be fast so that they can be embedded into an optimization framework that makes many evaluations. To find an optimal protective measure I employ stochastic and derivative free optimization methods. A complete study is conducted on New York City and optimal protective strategies are found for minimizing the total cost from storm surge subject to different budget constraints.
| Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/gxrc-f397 |
| Date | January 2023 |
| Creators | Dinenis, Philip Constantine Andreas |
| Source Sets | Columbia University |
| Language | English |
| Detected Language | English |
| Type | Theses |
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