- MRI Research Associates, Inc. (MRA), Tokyo, Japan (hideaki_kitauchi@mri-ra.co.jp)
For local governments, it is essential to quickly and accurately understand the extent of flooding damage caused by typhoons, linear rainbands, or other heavy rainfall events in order to make critical decisions such as broadcasting evacuation notices or requesting emergency assistance to national government. In recent years, various systems have been developed to quickly predict and assess flood damage, but high implementation costs, computational demands, or operational complexity have become barriers to widespread adoption. Here, we develop a flood depth estimation system that keeps implementation as well as computational costs down while meeting practical needs of disaster management applications.
Using actual flood measurements obtained by low-cost water level sensors and digital elevation model (DEM), the system estimates flooded areas and depths in near real-time based on the sum of the measured flood depth and the ground elevation at each sensor location and visualize them quickly on the system. The system also includes features designed for convenience during imminent disasters, such as alerting every evacuation warning level, regularly saving and exporting flood depth maps and logs.
Additionally, estimating flood areas from past heavy rainfall events and validating these estimates, we assess the system accuracy. By involving disaster management personnels in using the system, we build a solution that is easy to operate even in the field during emergencies.
Figure 1. A schematic diagram of the system.
REFERENCES
- Idehara, A. and K. Hirano, 2020: Quick Estimation Method of Flood Inundation Mapping using Single Point Information, Report of the National Research Institute for Earth Science and Disaster Prevention (NIED), 85
(https://dil-opac.bosai.go.jp/publication/nied_report/PDF/85/85-1idehara.pdf, 2026.1.12). - NIED: https://midoplat.bosai.go.jp/web/shinsui/index.html (2026.1.12).
- ArcGIS Online: https://www.esri.com/en-us/arcgis/products/arcgis-online/overview (2026.1.12).
How to cite: Kitauchi, H., Nagao, A., Nakamura, M., and Igari, T.: A near real-time flood depth estimation system for practical disaster management applications, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15958, https://doi.org/10.5194/egusphere-egu26-15958, 2026.
