Relative contributions of water-level components to extreme water levels along the US Southeast Atlantic Coast from a regional-scale water-level hindcast

Kai Parker (), Li Erikson (), Jennifer Thomas (), Kees Nederhoff (), Patrick Barnard () and Sanne Muis ()
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Kai Parker: USGS, Pacific Coastal and Marine Science Center
Li Erikson: USGS, Pacific Coastal and Marine Science Center
Jennifer Thomas: USGS, Pacific Coastal and Marine Science Center
Kees Nederhoff: Deltares USA
Patrick Barnard: USGS, Pacific Coastal and Marine Science Center
Sanne Muis: Deltares

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2023, vol. 117, issue 3, No 5, 2219-2248

Abstract: Abstract A 38-year hindcast water-level product is developed for the US Southeast Atlantic coastline from the entrance of Chesapeake Bay to the southeast tip of Florida. The water-level modeling framework utilized in this study combines a global-scale hydrodynamic model (Global Tide and Surge Model, GTSM-ERA5), a novel ensemble-based tide model, a parameterized wave setup model, and statistical corrections applied to improve modeled water-level components. Corrected water-level data are found to be skillful, with an RMSE of 13 cm, when compared to observed water-level measurement at tide gauge locations. The largest errors in the hindcast are location-based and typically found in the tidal component of the model. Extreme water levels across the region are driven by compound events, in this case referring to combined surge, tide, and wave forcing. However, the relative importance of water-level components varies spatially, such that tides are found to be more important in the center of the study region, non-tidal residual water levels to the north, and wave setup in the north and south. Hurricanes drive the most extreme water-level events within the study area, but non-hurricane events define the low to mid-level recurrence interval water-level events. This study presents a robust analysis of the complex oceanographic factors that drive coastal flood events. This dataset will support a variety of critical coastal research goals including research related to coastal hazards, landscape change, and community risk assessments.

Keywords: Extreme sea levels; Coastal flooding; Regional hindcast; Wave setup; Water levels; Extreme events; Compound events (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11069-023-05939-6

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