FLOOD VULNERABILITY

Flooding remains one of the most devastating environmental hazards in Nigeria, with severe impacts on lives, livelihoods, and infrastructure. Etsako West Local Government Area (LGA) of Edo State is particularly vulnerable due to its low-lying terrain, proximity to rivers, and recurring seasonal rainfall. This study applied Geospatial Information System (GIS) and the Analytical Hierarchy Process(AHP) to assess and map flood vulnerability across the LGA. Key geospatial and socioenvironmental indicators including elevation, slope, land use/land cover, distance to rivers,soil type, and population density, were integrated and weighted to generate a composite Flood Vulnerability Index. The resulting map classified the area into four risk categories: very high, high, moderate, and low. Findings revealed that very high-risk zones, occupying about 22% of the land area, are concentrated in riverine communities such as Anegbette, Udaba, and Osomegbe, while high-risk areas (33%) extend across Aviele and Iyakpi. Moderate- and low-risk zones accounted for 27% and 18% respectively, with upland towns like Auchi and Jattu benefiting from higher elevation and better drainage. Notably, nearly two-thirds of the population reside within high or very high vulnerability zones, underscoring the human dimension of flood risk. The study demonstrates the effectiveness of GIS-based multi-criteria analysis for local-scale flood assessment and provides an evidence-based tool to support disaster preparedness, land-use planning, and sustainable development in Etsako West and similar flood-prone regions of Nigeria

Flooding brought on by excessive rainfall is one of the frequently occurring and widely reported disasters affecting human existence. The purpose of this study is to create flood risk maps of Ikpoba Okha which can be used for predicting the level of vulnerability due to rapid urban development taking place in recent times. The procedure to achieve this involved using the method of Analytical Hierarchy Process (AHP) in a Geographic Information System (GIS) environment. Among the fundamental datasets requirements for the project were: cloud-free high-resolution satellite images, SRTM DEM data, FAO soil data, rainfall data, etc. Maps of flood-enhancing elements, such as
flood risk vulnerability mapping, were created in Geographic Information Systems using the same scale of 1: 200,000 and geographic coordinate system (WGS 1984 UTM zone 31N). This multiparametric technique includes rainfall distribution, elevation and slope, drainage network and density, land use/land cover, and soil type, among other flood determinants. All the output raster maps
were first ranked using the "Weighted Linear Combination" method with a grid cell size of 0.0028 mm before being sent for Multi-Criteria Analysis (MCA). The computation of the consistency ratio at an acceptable level of 0.055 further confirmed the model's validity. Additionally, the research found topography and rainfall as the most significant factors contributing to floods in Benin City.