Sediments and Subgrid: A Great Combination

Long term morphodynamic simulations are used for predicting the impact of climate change and human interventions in our estuarine and coastal regions. The accuracy of this type of simulations suffers generally from low resolution grids. Eventhough high resolution bathymetry data is increasingly more available thanks to new measurement techniques. However, the computational effort for such high resolution simulations is high. Even with increasing computer power and by using the various available techniques for speeding up simulations [Roelvink (2006) ], the computational effort remains high. By introducing a subgrid based method for morphodynamics, we aim at increasing theaccuracy of coarse grid based morphodynamic simulations, without significantly increasing the computational effort. Over the last years, we have gained experience in hydrodynamic modelling using subgrid based methods [i.e. Defina(2003), Casulli (2009), Volp et al (2013) ]. These methods combine coarse computational grids with high resolution information. In Volp et al (2013 ) we presented a subgrid based, two-dimensional, depth averaged hydrodynamic model, that is inspired by the method presented by Casulli (2009 ). The model makes use of two grids: a (coarse) computational grid and a high resolution subgrid, see Figure 1. The system of equations is solved at the coarse grid, but high resolution information is taken into account. The water level is assumed to be uniform within a computational cell, but the bed and the roughness are allowed to vary within a cell. Therefore, high resolution effects can be taken into account for the computation of cross-sectional areas, cell volumes, advection and friction. This also implies that cells can be wet, partly wet or dry. The solution based on a coarse computational grid improved significantly, when high resolution effects are taken into account. This result is obtained without a significant increase in computational cost.Environmental Fluid Mechanic