Flood susceptibility mapping in Debre Berhan Regio-Politan City, Central Ethiopia, using geospatial technologies and analytical hierarchy process

Flooding is a major natural hazard with escalating global impacts, necessitating robust susceptibility assessments for effective disaster risk reduction, particularly in rapidly growing urban areas. This study applied a GIS-based Analytical Hierarchy Process (AHP) approach to map and evaluate flood susceptibility (FS) in the rapidly developing Debre Berhan Regio-Politan city. The study generated a city-scale flood susceptibility map for Debre Berhan under conditions of increasing climate variability and intensifying extreme rainfall. In a rapidly growing urban environment with limited drainage infrastructure, the regular characterization of flood-prone areas is essential for anticipating risk, guiding land-use planning, and supporting more effective flood control and resilience measures. It also captures the unique interplay between Debre Berhan’s steep topography and its recent rapid industrial growth by integrating AHP-weighted GIS with field-based verification. A total of 13 flood-control factors were identified from the literature and refined through field reconnaissance, satellite imagery, and expert judgment informed by field surveys. The susceptibility map was generated using a multi-criterion decision-making AHP framework and validated through the Receiver Operating Characteristic (ROC) curve method. The resulting FS map categorized the region into five classes, revealing that 40.62% of the total area falls under High (31.09%) and Very High (9.55%) susceptibility levels, which primarily concentrated in the central and southwestern low-lying regions and along river networks. An additional 32.15% of the area was classified as Moderate susceptibility, indicating a widespread potential flood risk. The consistency ratio (CR) value of 0.04 indicates highly consistent weight comparisons using AHP. Model validation using the ROC curve yielded an Area Under the Curve (AUC) of 0.86, indicating very good predictive accuracy. Among the considered factors, the Topographic Wetness Index (24.8%), slope (18.6%), Land Use/Land Cover (14.3%), and Normalized Difference Vegetation Index (10.8%) emerged as the most influential contributors to flood generation. These findings highlight a significant and spatially extensive flood risk, further intensified by ongoing urban expansion. The study provides critical insights for urban planners and decision-makers, emphasizing the integration of flood susceptibility into land-use planning, the prioritization of targeted mitigation strategies, the enhancement of early warning systems, and the promotion of sustainable urban development to strengthen regional resilience against future flood events.