Impacts of nearshore mesh resolution on modelling shoreline change

Coastal Numerical Models (CNMs) provide predictions of shoreline change across different timescales, which can guide coastal management. Shoreline evolution studies in data-poor countries may be limited to globally available... [ view full abstract ]

Coastal Numerical Models (CNMs) provide predictions of shoreline change across different timescales, which can guide coastal management. Shoreline evolution studies in data-poor countries may be limited to globally available data, such as the ETOPO1 Global Relief Model (1 arc-minute). The usefulness of coarse datasets in modelling shoreline change, particularly where the outputs inform coastal management, is under-researched. This paper examines how nearshore mesh resolution influences the accuracy and precision of shoreline change predictions.

To simulate the interactions between hard structures, coastal processes, sediment redistribution, and coastal morphological changes, CNMs require a good representation of the nearshore in the computational mesh. An inaccurate solution of nearshore morphodynamics will compromise a model prediction of shoreline change. Input data and their resolution influence the accuracy and precision of model predictions. We consider two locations, both managed sandy shorelines, in New York and Southern California. We use coastal elevation models from the National Centers for Environmental Information to produce computational grids with varying nearshore resolution, referenced to mean high water. These provide the basis, at each site, for a two-dimensional coupled wave, flow, and sediment transport model to simulate shoreline change using the MIKE 21 Coupled Model. We calibrate and verify the models against observations of currents and shoreline morphology, and quantify the impacts of varying nearshore mesh resolution on predicted sediment transport rates and bed level changes. From these, we identify an optimal nearshore resolution for modelling shoreline change to refine CNMs and improve their applicability to guide coastal management in data-poor countries.