Flooding is of particular concern in low-lying coastal zones that are prone to impacts from multiple flooding drivers, such as coastal (storm surge and waves), fluvial (excessive river discharge), and pluvial (excessive surface runoff). Failure to account for dependence (and its changes over time) between flood drivers, when dependence exists between them, may lead to underestimation of flood risk and under-design of flood defense measures. Characterizing the dependence between compound flooding drivers in space and across seasons (tropical and extra-tropical), and how this dependence changed over time is essential in this context.
In this dissertation, compound flooding potential from all relevant flooding drivers is assessed at 35 locations along the contiguous United States (CONUS) coastline. Different dependence measures are derived and analyzed using observations and state-of-the-art re-analysis data sets. In addition, temporal changes in the extremal dependence are assessed, using a sliding time window approach and possible associations with large-scale climate indices are explored. The effects of changes in dependence and marginal distributions over time between coastal and fluvial flooding drivers are investigated in more detail for a selected case study location.
To overcome the computational expense of numerical modeling for flood mapping of large sets of events, a framework is introduced based on hybrid statistical modeling and one-dimensional hydraulic modeling combined with a flood inundation tool capable of propagating spatially variable along-river water surface elevations inland. The framework to delineate the flood transition zone is implemented for the Potomac River and different flood scenarios are analyzed to assess how different combinations of coastal water levels and river discharge modulate the flood hazard (specifically flood depth and extent).
Overall, the findings provide new insights into characterizing compound flooding potential, its changes in space and time and how incorporating flood driver dependencies affects flood hazard.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2023-1308 |
| Date | 01 January 2024 |
| Creators | Nasr, Ahmed A. |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Thesis and Dissertation 2023-2024 |
| Rights | In copyright |
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