Factor Affecting and Damage Mapping of Flood Inundation in Japan: A Case Study of Hitoyoshi City, Kumamoto Prefecture, Japan

Abstract

One of the most water-related disasters is flooding induced by heavy rain. According to several model experiments and an analysis of historical data, such natural disasters will become more common in the future. In recent years, torrential rain and flooding have caused significant damage to agricultural land, homes, and human life in numerous Japanese towns. We used the Hitoyoshi City in Kumamoto Prefecture, Japan, as a case study for the area’s flood event in July 2020. This study uses machine learning to study spatial analysis of the city of Hitoyoshi after the 2020 flood disaster. Assessments such as flood hazards, exposure, and susceptibility are critical components of total flood risk assessment. In addition, this study also uses several driving factors for mapping the scenario to the evacuation center, how the impact of flooding on the residential environment, and changes to land use in the Hitoyoshi area. For land-use planners, estimating the quickly flooded region using distinct land use profiles is quite important. It aids in the analysis of flood losses and the allocation of resources for recovery and restoration.