Urban flood analysis for Pearl River Delta cities using an equivalent drainage method upon combined rainfall-high tide-storm surge events

Abstract

Many coastal cities face growing flood risks due to interactions of multiple triggers related to the changing climate such as intense rainstorms, rising sea level, severe storm surges, etc. The complex urban morphology and infrastructural systems have profound effects on flow routing and need to be properly considered in flood modelling. In particular, the underground drainage system is a key element of urban drainage, but its fine-scale modelling is still an open challenge. This paper aims to evaluate flood hazards in coastal cities upon combined high tide, storm surge and intense rainfall by incorporating the compound weather conditions into a grid-based flood analysis model. An equivalent drainage method is proposed to improve the efficiency of large-scale urban drainage modelling, which simulates the capacity of drainage networks by enhanced infiltration. The equivalent method is calibrated with a physically based drainage model considering varying rainfall intensities and sea levels. The flood hazards in two coastal cities (Shenzhen and Hong Kong) in the Pearl River Delta of South China are evaluated. Results show that in the combination of low-intensity rainfall and high sea level, stormwater is difficult to drain into the sea, and significant backflows into the drainage outfalls can occur. The inland inundation caused by rainfall can be amplified by high sea levels due to the reduction of drainage efficiency. Moreover, flood hazards both along the coastline and in the inland areas can be exacerbated due to sea level rise and ground subsidence. The equivalent drainage method shows a good performance and provides an easy alternative in large-scale urban flood modelling. The predicted hazard scenarios under various combinations of weather conditions provide essential information for re-examining urban drainage designs and developing new flood prevention strategies.