Disasters caused by the climate change have been becoming a major threat to coastal cities in Pearl River Delta. Climate change has led to the temperature and sea level slowly rising in the region and altered weather patterns including more unexpected cloudburst. Two consecutive Typhoons hit the Delta in 2017 and 2018, caused severe damages in Hong Kong, Macau, Zhuhai and Shenzhen. To combat the negative impact of climate change, the adequate emergency response, infrastructure upgrade, and urban planning are necessary, but all depending on the quantitative assessment of the frequency and severity of extreme weather events at the operational level. Current methods of assessing disaster damages are often adapted to historical records and at a very coarse level. When disasters caused by climate change outside of the historical records the current methods will lead to inadequate decisions and the damage may become increasingly catastrophic. This study aims to develop a decision support platform that coupling global and regional climate and weather forecast models with hydrology and hydraulic models at operational scale. Four Global Climate Models (GCMs) covering a range of climate sensitivity of the region are selected for dynamic downscaling using Weather Research and Forecast Model (WFR) at 4 km x 4 km grid. The downscaled model was calibrated and validated using historical extreme events first. Then weather data was generated at different time scales. These data are used as input for hydrology and hydraulic models to simulate peak flows, flood plain and potential flood hot points. To demonstrate the platform, Zhuhai City is chosen as an example. Hourly and 5-minutes rainfall data were generated from the calibrated model as the input for hydrology and hydraulic models at sub-catchment level. The flood risk from 2020 – 2035 are evaluated.
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