Improvements to the Characterization of Hurricane Flooding with Advanced Statistical and Numerical Modeling
| dc.contributor.advisor | Bedient, Philip | en_US |
| dc.contributor.committeeMember | Griffin, Robert | en_US |
| dc.creator | Bass, Benjamin | en_US |
| dc.date.accessioned | 2019-05-17T13:20:39Z | en_US |
| dc.date.available | 2019-05-17T13:20:39Z | en_US |
| dc.date.created | 2017-12 | en_US |
| dc.date.issued | 2017-12-19 | en_US |
| dc.date.submitted | December 2017 | en_US |
| dc.date.updated | 2019-05-17T13:20:39Z | en_US |
| dc.description.abstract | Hurricanes have historically and continue to result in some of the most devastating natural disasters. Despite a wealth of research efforts since the active 2005 hurricane season (i.e. Katrina, Rita, Wilma), key questions related to hurricane flood characterization, mitigation, forecasts, and frequency remain under-explored. This dissertation addresses such research topics by combining several numerical models with hindcast, deterministic, and probabilistic methodologies to represent multiple hurricane flood hazards, including storm surge, rainfall-runoff, and interactions between these two sources of flooding (combined flooding). This thesis begins with the first numerical analysis of the performance and sensitivity of different hurricane storm surge indices, or simple parametric descriptors of hurricane characteristics, and their ability to represent a hurricane’s storm surge response. After Katrina (2005) several surge indices were proposed to replace the category-based Saffir-Simpson index, but these surge indices were either not evaluated or their performance relative to one another was determined inconclusive due to limited observational data. For this, and other projects in this thesis, the storm surge response of hurricanes was evaluated using the tightly coupled ADvanced CIRCulation (ADCIRC) and Simulating WAves Nearshore (SWAN) model (ADCIRC+SWAN). Findings from this research demonstrate the performance and sensitivity of different surge indices and can help guide the replacement of Saffir-Simpson categories with an improved hurricane storm surge index. In the second study of this thesis, storm surge dynamics are characterized in a complex bay environment to understand how variations in storm and environmental factors, including sea level rise and the potential erosion of barrier islands, influence flow dynamics across the various tidal inlets and barrier islands that make up Galveston Bay’s (the Bay’s) coastline. This research provides useful insight regarding the regional flood vulnerability of the Houston-Galveston region and how this flood vulnerability can effectively be reduced by focusing surge mitigation along specific sections of the Bay’s coastline. The third study in this thesis demonstrates that while a coastal barrier can prevent flood impacts from oceanic storm surge, significant storm surge can still develop within Galveston Bay itself, suggesting the additional need for multiple lines of defense strategies. This study proceeds to evaluate the hydrodynamic performance of several regional surge mitigation strategies, including designs that protect from oceanic storm surge as well as local surge that can develop within Galveston Bay itself. Analyses in this study goes beyond the typical 100-yr rule of thumb design by evaluating the performance of different strategies for several return period events under current as well as future sea level conditions. The final study of this thesis evaluates combined flooding in coastal watersheds due to rainfall-runoff associated with hurricanes and its interactions with storm surge. Such analysis is crucial given that rainfall associated flooding is still not represented in probabilistic forecasting and frequency (i.e. 100-yr floodplain) products despite causing ~27% of human fatalities during hurricane events. To fill this information gap, a rapid hurricane flood prediction system was developed to represent the combined flood response from hurricanes. The utility of this combined flood prediction system was then demonstrated by improving upon probabilistic hurricane flood forecasting and frequency products. In this thesis, numerical flood analysis was performed in coastal watersheds, a bay, and the open coast. By characterizing, forecasting, and evaluating different strategies to protect against hurricanes, the author hopes to not only advance the current state of hurricane science, but to additionally provide practical insight and tools to increase coastal resiliency. | en_US |
| dc.format.mimetype | application/pdf | en_US |
| dc.identifier.citation | Bass, Benjamin. "Improvements to the Characterization of Hurricane Flooding with Advanced Statistical and Numerical Modeling." (2017) Diss., Rice University. <a href="https://hdl.handle.net/1911/105583">https://hdl.handle.net/1911/105583</a>. | en_US |
| dc.identifier.uri | https://hdl.handle.net/1911/105583 | en_US |
| dc.language.iso | eng | en_US |
| dc.rights | Copyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder. | en_US |
| dc.subject | Hurricanes | en_US |
| dc.subject | Floods | en_US |
| dc.subject | Surge | en_US |
| dc.subject | Hydrology | en_US |
| dc.title | Improvements to the Characterization of Hurricane Flooding with Advanced Statistical and Numerical Modeling | en_US |
| dc.type | Thesis | en_US |
| dc.type.material | Text | en_US |
| thesis.degree.department | Civil and Environmental Engineering | en_US |
| thesis.degree.discipline | Engineering | en_US |
| thesis.degree.grantor | Rice University | en_US |
| thesis.degree.level | Doctoral | en_US |
| thesis.degree.name | Doctor of Philosophy | en_US |
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