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11Two dimensional flood inundation models are widely used tools for flood hazard mapping and an 12 essential component of statutory flood risk management guidelines in many countries. Yet we still 13 don't know how much physically complexity a flood inundation model needs for a given problem. 14 Here, three two dimensional explicit hydraulic models, that can be broadly defined as simulating 15 diffusive, inertial or shallow water waves, have been benchmarked using test cases from a recent 16Environment Agency for England and Wales (EA) study, where results from industry models are also 17 available. To ensure consistency the three models were written in the same code and share 18 subroutines for all but the momentum (flow) and time stepping calculations. The diffusive type 19 model required much longer simulation times that the other models, whilst the inertia model was 20 the quickest. For flows that vary gradually in time, differences in simulated velocities and depths due 21 to physical complexity were within 10% of the simulations from a range of industry models. 22Therefore, for flows that vary gradually in time it appears unnecessary to solve the full two 23 dimensional shallow water equations. As expected however, the simpler models were unable to 24 simulate supercritical flows accurately. Finally, implications of the results for future model 25 benchmarking studies are discussed in light of a number of subtle factors that were found to cause 26 significant differences in simulations relative to the choice of model. 27

Abstract:Cellular-based approaches for flood inundation modelling have been extensively calibrated and evaluated for the prediction of flood flows on rural river reaches. However, there has only been limited application of these approaches to urban environments, where the need for flood management is greatest. Practical application of two-dimensional (2D) flood inundation models is often limited by computation time and processing power on standard desktop PCs when attempting to resolve flows on the high-resolution grids necessary to replicate urban features. Consequently, it is necessary to evaluate the effectiveness of coarse grids to represent flood flows through urban environments. To examine these effects, LISFLOOD-FP, a 2D storage cell model, is applied to hypothetical flooding scenarios in Greenfields, Glasgow. Grid resampling techniques in GIS software packages are evaluated and a bilinear gridding technique appears to provide the most accurate and physically intuitive results. A gridding method maintaining sharp elevation changes at building interfaces and neighbouring land is presented and estimates of the discretization noise associated with the coarse resolution grids suggest little improvement over current gridding methods. The variation in model results from the friction sensitivity analysis suggests a non-stationary response to Manning's n with changing model resolution. Model results suggests that a coarse resolution model for urban applications is limited by the representation of urban media in coarse model grids. Furthermore, critical length scales related to building dimensions and building separation distances exist in urban areas that determine maximum possible grid resolutions for hydraulic models of urban flooding.

Quantifying flood hazard is an essential component of resilience planning, emergency response, and mitigation, including insurance. Traditionally undertaken at catchment and national scales, recently, efforts have intensified to estimate flood risk globally to better allow consistent and equitable decision making. Global flood hazard models are now a practical reality, thanks to improvements in numerical algorithms, global datasets, computing power, and coupled modelling frameworks. Outputs of these models are vital for consistent quantification of global flood risk and in projecting the impacts of climate change. However, the urgency of these tasks means that outputs are being used as soon as they are made available and before such methods have been adequately tested. To address this, we compare multi-probability flood hazard maps for Africa from six global models and show wide variation in their flood hazard, economic loss and exposed population estimates, which has serious implications for model credibility. While there is around 30%-40% agreement in flood extent, our results show that even at continental scales, there are significant differences in hazard magnitude and spatial pattern between models, notably in deltas, arid/semi-arid zones and wetlands. This study is an important step towards a better understanding of modelling global flood hazard, which is urgently required for both current risk and climate change projections.