Climate change impacts on magnitude and frequency of urban floods under scenario and model uncertainties.

Many studies have confirmed that climate change leads to frequent urban flooding, which can lead to significant socioeconomic repercussions. However, most existing studies have not evaluated the impacts of climate change on urban flood from both event-scale and annual-scale dimensions. In addition, there are only few studies that simultaneously consider scenario and model uncertainties of climate change, and combine flood risk assessment and uncertainty analysis results to provide practical suggestions for urban drainage system management. This study uses the statistical downscaling method to calculate the design rainfall under ten rainfall return periods of four climate models and three climate change scenarios in 2040s, 2060s, and 2080s in various prefecture-level cities in China. The four climate models are HadGEM2- ES, MPI-ESM-MR, NorESM1-M and FGOALS-g2 models and the three climate change scenarios are constructed by different representative concentration pathways (RCP), namely RCP2.6, RCP4.5 and RCP8.5. On this basis, relying on the generated drainage systems using geographical information and other data, event-scale and annual-scale precipitation are combined to calculate the change ratio of annual flood volume expectation in prefecture-level cities in each future year compared with the current situation. Furthermore, the study evaluates scenario and model uncertainties of climate change, and then comprehensively integrates the flood risk and its uncertainties to provides suggestions for urban drainage system management.