Deterministic, dynamic model forecasts of storm-driven coastal erosion

Jessica F. Gorski (), J. C. Dietrich (), Davina L. Passeri (), R. C. Mickey () and R. A. Luettich ()
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Jessica F. Gorski: U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center
J. C. Dietrich: North Carolina State University
Davina L. Passeri: U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center
R. C. Mickey: U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center
R. A. Luettich: University of North Carolina at Chapel Hill

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2025, vol. 121, issue 5, No 45, 6257-6283

Abstract: Abstract The U.S. Atlantic and Gulf of Mexico coasts are vulnerable to storms, which can cause significant erosion of beaches and dunes that protect coastal communities. Real-time forecasts of storm-driven erosion are useful for decision support, but they are limited due to demands for computational resources and uncertainties in dynamic coastal systems and storm forcings. Current methods for coastal change forecasts are based on empirical calculations for wave run-up and conceptual models for erosion, which do not represent sediment transport and morphological change during the storm. However, with continued advancements in high-resolution geospatial data and computational efficiencies, there is an opportunity to apply morphodynamic models for forecasts of beach and dune erosion as a storm approaches the coast. In this study, we implement a forecast system based on a deterministic, dynamic model. The morphodynamic model is initialized with digital elevation models of the most up-to-date conditions and forced with hydrodynamics from wave and circulation model forecasts, and its predictions are categorized based on impact to the primary dune, defined in this study as the first ridge of sand landward of the beach. Results are compared spatially to the observed post-storm topography using changes to dune crest elevations and volumes, and temporally to the predicted total water level at the forecasted moment of dune impact.

Keywords: Forecasting; Morphology; Erosion; Hazards (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11069-024-07012-2

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