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Inicio  /  Hydrology  /  Vol: 10 Par: 5 (2023)  /  Artículo
ARTÍCULO
TITULO

CoastFLOOD: A High-Resolution Model for the Simulation of Coastal Inundation Due to Storm Surges

Christos Makris    
Zisis Mallios    
Yannis Androulidakis and Yannis Krestenitis    

Resumen

Storm surges due to severe weather events threaten low-land littoral areas by increasing the risk of seawater inundation of coastal floodplains. In this paper, we present recent developments of a numerical modelling system for coastal inundation induced by sea level elevation due to storm surges enhanced by astronomical tides. The proposed numerical code (CoastFLOOD) performs high-resolution (5 m × 5 m) raster-based, storage-cell modelling of coastal inundation by Manning-type equations in decoupled 2-D formulation at local-scale (20 km × 20 km) lowland littoral floodplains. It is fed either by outputs of either regional-scale storm surge simulations or satellite altimetry data for the sea level anomaly. The presented case studies refer to model applications at 10 selected coastal sites of the Ionian Sea (east-central Mediterranean Sea). The implemented regular Cartesian grids (up to 5 m) are based on Digital Elevation/Surface Models (DEM/DSM) of the Hellenic Cadastre. New updated features of the model are discussed herein concerning the detailed surveying of terrain roughness and bottom friction, the expansion of Dirichlet boundary conditions for coastal currents (besides sea level), and the enhancement of wet/dry cell techniques for flood front propagation over steep water slopes. Verification of the model is performed by comparisons against satellite ocean color observations (Sentinel-2 images) and estimated flooded areas by the Normalized Difference Water Index (NDWI). The qualitative comparisons are acceptable, i.e., the modelled flooded areas contain all wet area estimations by NDWI. CoastFLOOD results are also compared to a simplified, static level, ?bathtub? inundation approach with hydraulic connectivity revealing very good agreement (goodness-of-fit > 0.95). Furthermore, we show that proper treatment of bottom roughness referring to realistic Land Cover datasets provides more realistic estimations of the maximum flood extent timeframe.

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