Subgrid corrections for the linear inertial equations of a compound flood model - a case study using SFINCS 2.1.1 Dollerup release

Abstract

Accurate flood risk assessments and early warning systems are needed to protect and prepare people in coastal areas from storms. In order to provide this information efficiently and on time, computational costs in flood models need to be kept as low as possible. One way to achieve this goal is to apply subgrid corrections to relatively coarse computational grids. Previously, these have been used in full-physics circulation models. In this paper, for the first time, we developed subgrid corrections for the linear inertial equations (LIEs) that account for bed level and friction variations. They were implemented in the Super-Fast INundation of CoastS (SFINCS) model version 2.1.1 Dollerup release. Pre-processed lookup tables that correlate water levels with hydrodynamic quantities make more precise simulations with lower computational costs possible. These subgrid corrections have undergone validation through several conceptual and real-world application scenarios, including rainfall-induced flooding during a hurricane and tidal propagation in an estuary. We demonstrate that the subgrid corrections for linear inertial equations significantly improve model accuracy while utilizing the same resolution without subgrid corrections. In terms of computational efficiency, subgrid corrections increase computational costs by 38 %-128 %. However, this yields a 35-50-time speedup since coarser model resolutions with subgrid corrections can provide the same accuracy as finer resolutions without subgrid corrections. Limitations are also discussed; for example, when grids do not adequately resolve river meanders, fluxes can be overestimated. Our findings show that subgrid corrections are a useful asset for hydrodynamic modelers striving to achieve a balance between accuracy and efficiency.