Physical complexity to model rainfall-driven urban surface water flooding

Abstract

In the context of climate change, the probability for extreme rainfall events increases, leading to severe flooding in urban surface area with more casualties and property loss. Numerical simulation is essential for better understanding the formation and development of urban surface water flooding. In recent years, many numerical models have been developed, while modelers are faced with the decision of whether it is appropriate to spend computational resource on detailed simulation or simplified simulation is plenty considering a variety of uncertain input factors. This study applies a full dynamic model for rainfall-driven surface water flooding to implement parameters sensitivity analysis of urban inundation prediction at a city scale. A set of scenarios are undertaken with different values of hydraulic parameters (e.g. hydraulic conductivity) and hydraulic parameters (e.g. Manning’s friction coefficient). The 28th June 2012 event occurred in Leicester, UK is used as a baseline simulation, for which a good range of flood sites data across the city is available. The results allow us to explore physical complexities to reliably predict urban surface water flooding at city-scale. By analyzing the importance of uncertain input factors, some useful insight into the urban surface water flood prediction will be provided.