Integrating GIS and AHP for a multi-criteria flood vulnerability assessment in the Benue River Basin, Nigeria

Life and infrastructure are becoming increasingly vulnerable to flooding and flood-related risks along the Benue River, particularly in Adamawa catchment, with inadequate knowledge about physical factors affecting vulnerability and flood-prone zones. Controlling flood vulnerability involves addressing vulnerabilities to communities and infrastructure whilst reducing flood risks and enhancing resilience. This study employed geospatial analysis and the Analytical Hierarchy Process (AHP) method to model and analyse seven flood vulnerability factors: elevation, drainage, soil type, precipitation, bedrock, slope of the surface, and land use/cover. Remote sensing data was utilised to create thematic map layers for the factor criterion. A pairwise comparison matrix was created and normalised to ensure uniformity. Weights were derived by averaging all of the row’s components and calculating the percentage weight. The estimated weights were applied to the theme layers in a weighted sum analysis with the highest weight (33.66%) assigned to drainage density while the least (2.68%) was assigned to land cover. The aggregation of information from the layers in ArcGIS software using the weighted sum analysis method produced a flood vulnerability map depicting the following vulnerability levels - low (19.89%), moderate (31.44%), high (31.80%), and extremely high (16.85%). Field investigation showed that the majority of the indicated flood-prone zones corresponded to field-based studies. The technique and findings were validated using a consistency ratio of 0.0944, which was discovered to be within the permissible range for satisfactory consistency of the criteria applied. A coherence value of 7.748 was obtained signifying severe rainfall causes floods in the area, with the River Benue and its tributaries being particularly prone to flooding occurrences. This result presents a platform for policy formulation by the relevant agencies to ensure resilience to flooding and vulnerability in the study area.