Storm surges induced by tropical cyclones have been ravaging coastal communities worldwide, where a growing number of people reside. Tremendous life and economic losses are caused by tropical cyclones, contributing to more than half of the damages induced by natural hazards. To improve the resilience of coastal communities to surge hazards, it is of great importance to provide reliable and efficient real time forecasts of the spatiotemporal evolution of storm surge, as well as reliable predictions of the probabilistic surge hazards under future conditions. Three specific goals are addressed in this work. Studies on characterization and prediction of surge before a hurricane landfall show that a dimensionless relationship between intensity scaled surge magnitude and wind-duration scaled surge timing may effectively be used for rapid and reliable forerunner surge forecasting. Investigation of how probabilistic surge hazard changes with sea level rise (SLR) shows that the probabilistic surge with SLR can be 1.0 m larger, while different individual storm's surge with the same magnitude can be 1.5 m larger or 0.1 m smaller, indicating the importance of not relying on results from a limited number of storm surge events to assess the probabilistic surge hazard change to SLR. Finally, studying the temporal evolution of coastal flooding changes with SLR shows forerunner surge responds differently to SLR than peak surge, and that storm forward speed is a key factor determining the forerunner-SLR response. / Ph. D. / Flooding induced by tropical cyclones have been ravaging coastal communities worldwide, where a growing number of people reside. Tremendous life and economic losses are caused by tropical cyclones, contributing to more than half of the damages induced by natural hazards. To improve the resilience of coastal communities to flood hazards, it is of great importance to provide reliable and efficient real time forecasts of the flooding time series, as well as reliable predictions of the statistical flood elevation under future conditions. Three specific goals are addressed in this work. Studies on forecasting early coastal flooding show that a dimensionless relationship between storm characteristics and flood elevation may effectively be used for rapid and reliable early flood forecasting. Investigation of how statistical flood elevation changes with sea level rise show the importance of modeling the physical processes and of the storm sample size to address this issue. Finally, studying the coastal flooding time series with sea level rise shows early flooding responds differently to sea level rise, compared to maximum flooding, and that storm’s moving speed is a key factor determining flooding response to sea level rise.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/96547 |
| Date | 31 July 2018 |
| Creators | Liu, Yi |
| Contributors | Civil and Environmental Engineering, Irish, Jennifer L., Stark, Nina, Murray-Tuite, Pamela Marie, Weiss, Robert |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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