Flood vulnerability assessment in Kogi State (Nigeria), using weighted linear combination of multi-criteria factors

Abstract

Floods and flood events are major natural disasters in Nigeria and around the world, their severity and impact result in numerous troubling consequences for human development and the displacement of people. This study used geographic information systems (GIS) and remote sensing techniques to produce maps of Kogi State, Nigeria's flood risk and vulnerable areas. This research used the AHP and MIF models. Data were sourced from multiple sources and analyzed using ArcGIS 10.8 software, generating nine thematic maps showing different factors that influence flooding, including the topographic wetness index, slope, elevation, rainfall, drainage density, land use, and land cover (LULC), soil type, distance from the river and distance from the road. Thematic layers were assigned weights according to their influence on flooding in the area. The weighted overlay tool in ArcGIS 10.8 combined each thematic map with their respective assigned weights, producing the ultimate flood vulnerability map for both the Analytic Hierarchy Process (AHP) and Multi-Influence Factor (MIF) models. Flood zones were classified into four distinct classifications: low, moderate, high, and very high, according to the data analyzed that cover a significant part of the study area. According to the AHP and MIF  model results, 0.66% and 2.18% of the area were classified as very high-risk zones, while 27.69% and 28.17% of the total land area were classified as high flood-vulnerable regions. The flood zones classified as moderate and low vulnerability covered 68.56% and 3.09% (according to the AHP), 59.91%, and 9.75% (according to the MIF), respectively. The results of this study will provide a framework for decision-making that can result in effective planning, allocation of resources, and creation of policies.