A porosity-based flood inundation modelling approach for enabling faster large scale simulations. (April 2022) - Ayoub, Vita; Delenne, Carole; Chini, Marco; Finaud-Guyot, Pascal; Mason, David; Matgen, Patrick; Maria-Pelich, Ramona; Hostache, Renaud
Abstract: Floods are among the most devastating natural hazards in the world. With climate change and growing urbanisation, floods are expected to become more frequent and severe in the future. Hydrodynamic models are powerful tools for flood hazard assessment but face numerous challenges, especially when operating at a large scale. The downside of discretising an area using a fine mesh yielding more accurate results, is the expensive computational cost of simulations. Moreover, critical input information such as bathymetry (i.e, riverbed geometry) are required but cannot be easily collected by field measurements or remote sensing observations. During the past few years, the development of sub grid models has gained a growing interest as these enable faster simulations by using coarser cells and, at the same time, preserve small-scale topography variations within the cell. In this study, we propose and evaluate a modelling framework based on the shallow water 2D model with depth-dependent porosity enabling to represent floodplain and riverbed topography through porosity functions. To enable a careful and meaningful evaluation of the model, we set up a 2D classical model and use it as a benchmark. We also exploit ground truth data and remote sensing derived flood inundation maps to evaluate the proposed modelling framework and use as test cases the 2007 and 2012 flood events of the river Severn. Our empirical results demonstrate a high performance and low computational cost of the proposed model for fast flood simulations at a large scale. Highlights: A porosity-based modelling approach is proposed to simulate flood inundations fast. The method uses large grid cells, saves CPU times and preserves high-resolution topographic data. The approach allows for representing riverbed geometry via porosity. The method paves the way for applications in large areas where bathymetric data are not available.