An approach for real-time monitoring of hydrological risk hotspots during extreme rainfall events - Shakti P. C.; Kohin Hirano; Satoshi Iizuka (Geomatics, Natural Hazards & Risk)
Real-time monitoring of hydrological risk hotspots during extreme rainfall events is limited by certain challenges. Here, we introduce a new approach for tracking such hotspots across large areas in real time. We focused on the Kyushu region of Japan, utilizing rainfall data and physiographic features for the months of July 2020 and September 2022, integrating key elements such as radar rainfall data (1989–2019), curve number (CN), topographic wetness index (TWI), and land use (LU). These factors were combined within a geographic information system (GIS) using the analytical hierarchy process (AHP) to effectively identify the hydrological risk hotspots. Various risk levels were assigned to different areas of the region, with some regions exhibiting extremely high risks during flood events. Comparison between the data on flooded areas and the AHP results revealed a good correlation between the high-risk zones identified in the present study and the actual flood disaster reports of the extreme rainfall event that occurred in the study area in July 2020. The approach, designed for real-time tracking, is potentially applicable in other regions worldwide. It offers an effective tool for local governments and communities to enhance disaster preparedness, improve resilience, and support flood mitigation strategies during extreme rainfall events.