Probabilistic flood susceptibility assessment using a GIS-based Certainty Factor approach in the Arakawa River basin, Japan

Abstract

Flooding is one of the most frequent and destructive natural disasters in Japan, particularly in river basins with high population density and urbanization. This study aimed to use a GIS-based probabilistic Certainty Factor (CF) model to evaluate flood susceptibility in the Arakawa River basin, Japan. Nineteen flood conditioning factors were incorporated: soil, land use/land cover (LULC), normalized difference built-up index (NDBI), normalized difference water index (NDWI), normalized difference vegetation index (NDVI), curvature, elevation, precipitation, slope, topographic position index (TPI), sediment transport index (STI), stream power index (SPI), topographic wetness index (TWI), drainage density (Dd), distance to streams, distance to roads, flow accumulation, population, and aspect were included to assess their impact on flood frequency. A flood susceptibility map (FSM) was generated by applying the Certainty Factor model. A total of 230 flood locations within the study area were examined and geostatistically processed in ArcGIS for model validation. The resulting FSM was categorized into five susceptibility classes: very low, low, moderate, high, and very high. The spatial distribution of these classes showed that 22.5% of the area falls under moderate susceptibility, 37.1% under high, and 22.6% under very high susceptibility. The model's performance was evaluated using the area under the receiver operating characteristic curve (AUC), yielding an accuracy of approximately 71%. The results indicate that the most influential factors affecting flood susceptibility in the basin are elevation, stream power index (SPI), sediment transport index (STI), flow accumulation, and distance to roads. The suggested framework offers useful spatial insights that can assist in supporting decision-makers to reduce both economic losses and risks to human life.