91探花

A research paper from Dr. Xander Wang proposes a new mathematical model to provide real-time prediction of urban flooding caused by heavy rainfall in a changing climate. The paper is published in the latest issue of . Dr. Wang is an assistant professor in the 91探花 School of Climate Change and Adaptation.

 

鈥淚ncreasing our cities鈥� resilience to floods under climate change has become one of the major challenges for decision makers, urban planners, and engineering practitioners around the world,鈥� said Dr. Wang. 鈥淎ccurate prediction of urban floods under heavy precipitation is critically important to address such a challenge. This new model is capable of simulating the rapid generation of surface runoff and the reverse-flow phenomenon during urban floods. The model accounts for typical characteristics of urban areas, such as large-scale impermeable surfaces and urban drainage systems, in order to simulate urban floods more realistically.鈥�

Dr. Wang used the model to reproduce the 2016 flood in Lafayette Parish, Louisiana and it performed very well in simulating both the flood extent and depth. The model can be used not only for real-time flooding prediction and early-warning, which require as much lead time as possible for evacuation preparation, but also for long-term urban resilience development, which relies on a better understanding of urban flooding risks under future climate scenarios. 

鈥淭his new model is completely different from traditional flood inundation models, and it allows us to precisely predict both flood extent and depth for every corner of a city,鈥� said Dr. Wang. 鈥淚t will be a very powerful tool for assessing the flood resilience of our cities under future climate change.鈥�