Machine learning for post-storm profile predictions: Using XBeach and convolutional neural network structure U-Net to predict 1D dune erosion profile shapes at the Holland Coast

To reduce computational efforts, surrogate models have been developed for dune erosion prediction. Current surrogate models can describe the relationship between the XBeach input and output (Athanasiou, 2022) and provides a prediction of a morphological indicator based on a parameterized input (profile shape parameters and hydrodynamics). In...

The determination of the feasibility of a 'Sand Breakwater' on the Nigerian coastline at Badagry

The coastal waters of Nigeria are a difficult environment to build structures to control the local morphology and hydrodynamic conditions to ones desire. This difficulty is a consequence of the persistent high-energy swell wave climate and Longshore Sediment Transport (LST) in the order of one million cubic metres per<br/>year. Besides these...