Rapid urban growth and climate change have put substantial stress on the current urban stormwater management system that has always been a concerning issue for local governments and residents. Nowadays, many cities face two challenges in stormwater management. First, what is the stormwater facilities’ current capacity, including rainwater pipes, storage tanks, pumps, and so forth? That is also to say to what extent of stormwater can the facilities handle. Second, as the global climate change, stormwater happens more frequently than before, do the facilities need to be upgraded and upgraded to what extent in the next 50 or 100 years? Therefore, this research addresses these two questions focusing on the damages to the urban land surface and the alerts to the water bodies within urban areas with modeling and algorism. In such a way, four significant issues were tackled. First, quantifying the damages and the alerts by combining SWMM and GIS. Second, an auto-calibration technique of the SWMM model will be explored. Third, an effective multi-objective optimization will be achieved to reduce the damages and alerts under various stormwater circumstances. The maximum capacity of current facilities could be obtained. This answers challenge 1. Fourth, considering the stormwater trend in 50 or 100 years, optimize the stormwater facilities in order to achieve a better balance between stormwater and urban development. With the optimization scheme, insufficient or excessive facilities investment could be avoided to a certain extent. This answers challenge 2. This research will be evidence-based, oriented on quantitative data, containing rainfall data, urban rainfall pipe networks, pump stations, DEM, and so forth. Selected Chinese or Dutch city will be the research object. The research result will be disseminated to potential end-users like municipalities, urban planners, and water engineers.