Flood vulnerability and risk mapping in Arba minch city using remote sensing, GIS and AHP

Abstract

Flooding is a major threat to urban areas, especially in developing countries facing rapid urbanization and weak infrastructure. This study addresses the limited flood risk assessment for Arba Minch City, Ethiopia, a fast-growing city in a flood-prone region. The research used an integrated approach of Remote Sensing, Geographic Information Systems (GIS), and the Analytical Hierarchy Process (AHP) to map flood hazard and risk zones. Biophysical and socio-environmental factors were weighted using AHP, which identified slope (26.3%) and elevation (23.7%) as the most significant contributors to flood risk. The model's reliability was confirmed with a Consistency Ratio (CR) of 0.042. The resulting flood hazard map shows that, out of the total 32.15 km² area of the city, 63.51% falls within the high and very high hazard categories (41.11% high and 22.40% very high), particularly in low-lying and urbanized areas. A comprehensive risk map was created by combining these hazard zones with socio-economic data. This revealed that, out of the total 32.15 km² area, 40.50% is at high and very high risk (32.16% high and 8.33% very high). The model’s accuracy was validated using historical flood data from 1985-2003 and 26 flood points, yielding an Area Under the Curve (AUC) score of 0.847. The flood risk map highlights the critical interplay between urban expansion, socio-economic vulnerability, and hydrometeorological dynamics, underscoring the need for integrated flood management strategies. These findings provide valuable support for urban planners and disaster managers in developing targeted mitigation strategies to enhance resilience and protect vulnerable communities.