4.7 Article

HySwash: A hybrid model for nearshore wave processes

Journal

OCEAN ENGINEERING
Volume 291, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.oceaneng.2023.116419

Keywords

Hybrid model; Coral reefs; Principal component analysis; Wave hydrodynamics; Spectral transformation

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This research presents a site-specific metamodel based on the SWASH numerical model simulations, which can predict coastal hydrodynamic variables in a fast and efficient manner. The metamodel uses downscaled and dimensionality reduced synthetic database to accurately reproduce wave setup, wave heights associated with different frequency bands, and wave runup. This method has great potential in coastal risk assessments, early warning systems, and climate change projections.
Climate change-induced sea level rise and increasing storm severity are significant stressors that threaten the livability of coastal areas worldwide. This research presents a sitespecific metamodel based on SWASH (Simulating WAves till SHore) numerical model simulations that aim at simplifying in a fast and efficient manner the prediction of hydrodynamic variables along cross-shore profiles. To accomplish this, a large synthetic database of offshore wave and sea level conditions is created and downscaled using numerical modeling together with sampling, selection, and interpolation techniques. All these mathematical methods permit to replace the computationally intensive cost of classical dynamical downscaling. In addition, the metamodel uses dimensionality reduction techniques that allow to account for a comprehensive analysis of the primary patterns governing the coastal hydrodynamic behavior. The proposed tool has been numerically validated in three different idealized coral reef profiles, showing good skill at reproducing the spatial evolution of wave setup, wave heights associated with different frequency bands, and wave runup. The flexibility and robustness of the method make it very convenient for being used in coastal risk assessments, early warning systems, or climate change projections.

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