DescriptionCo-authored with Ian Shennan, Richard Hardy, and Laura Turnbull-Lloyd
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 spatial discretisation 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 a managed sandy shoreline in the Long Beach Barrier Island, New York. We use a coastal elevation model from the National Center for Environmental Information to produce computational grids with varying nearshore discretisations, referenced to mean high water. These provide the basis for a two-dimensional coupled wave, flow, and sediment transport model to simulate shoreline change at the site using the MIKE 21 Coupled Model. We quantify the impacts of varying nearshore discretisations on predicted shoreline changes and net littoral drift. From these, we identify an optimal nearshore spatial resolution for modelling shoreline change to refine CNMs and improve their applicability to guide coastal management in data-poor countries.
|15 May 2019
|15th UK Young Coastal Scientists and Engineers Conference
|Glasgow, United Kingdom