A Numerical Investigation of Hurricane Florence-Induced Compound Flooding in the Cape Fear Estuary Using a Dynamically Coupled Hydrological-Ocean Model
Virginia Institute of Marine Science
Journal of Advances in Modeling Earth Systems
Hurricane-induced compound flooding is a combined result of multiple processes, including overland runoff, precipitation, and storm surge. This study presents a dynamical coupling method applied at the boundary of a processes-based hydrological model (the hydrological modeling extension package of the Weather Research and Forecasting model) and the two-dimensional Regional Ocean Modeling System on the platform of the Coupled-Ocean-Atmosphere-Wave-Sediment Transport Modeling System. The coupled model was adapted to the Cape Fear River Basin and adjacent coastal ocean in North Carolina, United States, which suffered severe losses due to the compound flood induced by Hurricane Florence in 2018. The model's robustness was evaluated via comparison against observed water levels in the watershed, estuary, and along the coast. With a series of sensitivity experiments, the contributions from different processes to the water level variations in the estuary were untangled and quantified. Based on the temporal evolution of wind, water flux, water level, and water-level gradient, compound flooding in the estuary was categorized into four stages: (I) swelling, (II) local-wind-dominated, (III) transition, and (IV) overland-runoff-dominated. A nonlinear effect was identified between overland runoff and water level in the estuary, which indicated the estuary could serve as a buffer for surges from the ocean side by reducing the maximum surge height. Water budget analysis indicated that water in the estuary was flushed 10 times by overland runoff within 23 days after Florence's landfall.
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Bao, Daoyang; Xue, Z. George; Warner, John C.; Moulton, Melissa; Yin, Dongxiao; and et al, A Numerical Investigation of Hurricane Florence-Induced Compound Flooding in the Cape Fear Estuary Using a Dynamically Coupled Hydrological-Ocean Model (2022). Journal of Advances in Modeling Earth Systems, 14(11), e2022MS003131.