Title

Development And Uncertainty Quantification Of Hurricane Surge Response Functions For Hazard Assessment In Coastal Bays

Keywords

Coastal flooding; Hazard assessment; Hurricanes; Storm surge; Uncertainty

Abstract

Reliable and robust methods of extreme value-based hurricane surge prediction, such as the joint probability method (JPM), are critical in the coastal engineering profession. The JPM has become the preferred surge hazard assessment method in the USA; however, it has a high computational cost: One location can require hundreds of simulated storms and more than ten thousand computational hours to complete. Optimal sampling methods that use physics-based surge response functions (SRFs) can reduce the required number of simulations. This study extends the development of SRFs to bay interior locations at Panama City, Florida. Mean SRF root-mean-square errors for open coast and bay interior locations were 0.34 and 0.37 m, respectively, comparable with ADCIRC errors. Average uncertainty increases from open coast, and bay SRFs were 10 and 12 %, respectively. Long-term climate trends, such as rising sea levels, introduce nonstationarity into the simulated and historical surge datasets. A common approach to estimating total flood elevations is to take the sum of projected sea-level rise (SLR) and present day surge (static approach); however, this does not account for dynamic SLR effects on surge generation. This study demonstrates that SLR has a significant dynamic effect on surge in the Panama City area, and that total flood elevations, with respect to changes in SLR, are poorly characterized as static increases. A simple adjustment relating total flood elevation to present day conditions is proposed. Uncertainty contributions from these SLR adjustments are shown to be reasonable for surge hazard assessments.

Publication Date

6-1-2015

Publication Title

Natural Hazards

Volume

77

Issue

2

Number of Pages

1103-1123

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/s11069-015-1646-5

Socpus ID

84939986564 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84939986564

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