Flood disasters have become one of the most threatening natural disasters in the world, in which waterlogging is the most common form in the context of highly urbanized megacities. The formation of flood disaster is related to many factors and involves information from multiple sources, making it difficult be predicted. This paper integrates multi-source information data, classifies the study area into different categories according to hydrological analysis results, and combines hydrodynamic theory and ArcGIS to get the quantitative prediction of the range and depth of waterlogging under different rainfall inputs. The evaluation results provide the government with accurate and timely information of waterlogging risks and locations in order to improve promptness of emergency management such as evacuation and managing traffics.