Comparing 2D capabilities of HEC-RAS and LISFLOOD-FP on complex topography

This study evaluates and compares two-dimensional (2D) numerical models of different complexities by testing them on a floodplain inundation event that occurred on the Secchia River (Italy). We test 2D capabilities of LISFLOOD-FP and HEC-RAS (5.0.3), implemented using various grid sizes (25\u2013100 m) based on 1-m DEM resolution. As expected, the best results were shown by the higher-resolution grids (25 m) for both models, which is justified by the complex terrain of the area. However, the coarser resolution simulations (50 and 100 m) performed virtually identically compared to the high-resolution simulations. Nevertheless, the spatial distribution of flood characteristics varies: the 50 and 100 m results of LISFLOOD-FP and HEC-RAS misestimated flood extent and water depth in selected control areas (built-up zones). We suggest that the specific terrain of the area can cause ambiguities in large-scale modelling, while providing plausible results in terms of the overall model performance

Comparison of two modelling strategies for 2D large-scale flood simulations

In this paper, two emerging strategies for the reduction of the computational time of 2D large-scale flood simulations are compared, with the aim of evaluating their strengths and limitations and of suggesting guidelines for their effective application. The analysis is based on two state-of-the-art raster flood models with different governing equations and parallelization strategies: PARFLOOD, a GPU-accelerated code that solves the fully dynamic shallow water equations, and LISFLOOD-FP, which combines a parallel implementation for CPU with simplified equations (local-inertial approximation). The results of two case studies (a river flood propagation, and a lowland inundation) suggest that, at coarse grid resolutions, the parallelized simplified model LISFLOOD-FP can represent a good alternative to fully dynamic models in terms of accuracy and runtime, while the GPU-parallel code PARFLOOD is more efficient in case of high-resolution simulations with millions of cells, despite the greater complexity of the numerical scheme

A New Automated Method for Improved Flood Defense Representation in Large-Scale Hydraulic Models

The execution of hydraulic models at large spatial scales has yielded a step change in our understanding of flood risk. Yet their necessary simplification through the use of coarsened terrain data results in an artificially smooth digital elevation model with diminished representation of flood defense structures. Current approaches in dealing with this, if anything is done at all, involve either employing incomplete inventories of flood defense information or making largely unsubstantiated assumptions about defense locations and standards based on socioeconomic data. Here, we introduce a novel solution for application at scale. The geomorphometric characteristics of defense structures are sampled, and these are fed into a probabilistic algorithm to identify hydraulically relevant features in the source digital elevation model. The elevation of these features is then preserved during the grid coarsening process. The method was shown to compare favorably to surveyed U.S. levee crest heights. When incorporated into a continental-scale hydrodynamic model based on LISFLOOD-FP and compared to local flood models in Iowa (USA), median correspondence was 69% for high-frequency floods and 80% for low-frequency floods, approaching the error inherent in quantifying extreme flows. However, improvements versus a model with no defenses were muted, and risk-based deviations between the local and continental models were large. When simulating an event on the Po River (Italy), built and tested with higher quality data, the method outperformed both undefended and even engineering-grade models. As such, particularly when employed alongside model components of commensurate quality, the method here generates improved-accuracy simulations of flood inundation