A New Economic Loss Assessment System for Urban Severe Rainfall and Flooding Disasters Based on Big Data Fusion

Background and Purpose: Increasingly frequent meteorological disasters have brought severe challenges that should be urgently handled in the sustainable development. However, meteorological data, loss data, social economic data and so forth relating to meteorological disasters rarely be effectively fused, failing to generate, rapidly and efficiently, economic losses and thus hindering the emergency management of disasters. Methods: A new economic losses evaluation information system has been developed for monitoring severe rainfall and flooding disasters in cities. The data mining method, econometric regression model and input–output model are implemented in the system, on the basis of multi-source data including hourly rainfall, geographical conditions, historical and real-time disaster information, socioeconomic data, and defense countermeasure. Results: Combined with the weather forecast information, this system can has the capability for reporting the real-time direct and indirect economic losses incurred by urban heavy rainfall and flooding disasters, automatically generating defense countermeasure reports for typical rainstorm and flooding points, and providing the spatial distribution of disasters. Conclusions: Finally, the system is conducive to improving the ability to manage disaster emergencies and eventually reducing the economic losses from the disaster.