A GIS-based aquifer vulnerability assessment in the basement complex terrain of southwestern Nigeria

Abstract

Aquifer contamination risk is a major challenge confronting the sustainability of groundwater resources in the basement environment of sub-Saharan Africa. This study adopted a GIS-based fuzzy logic model to assess the vulnerability of basement aquifers across a basin in southwestern Nigeria. Hydro-environmental setting of the studied basin was represented by twelve parameters, viz: pro-aquifer medium, water table depth, drainage density, lineament density, topsoil, aquifer depth, aquifer HC, lithology, landuse, vegetation index, slope and aquifer LUC. Sensitivity analyses were undertaken to determine the significance and individual contributions of the model parameters to aquifer vulnerability. In addition, the study demonstrated scientific methods of constructing independent model parameters. The studied basin is characterized by patches of very high aquifer vulnerability in the west owing to low protective capacity and high anthropogenic imprints. The eastern part is dominated by moderate aquifer vulnerability, while the elevated central part portrays low aquifer vulnerability due to low anthropogenic imprints. Highest aquifer vulnerability is attributed to slope, while vegetation index, aquifer LUC and pro-aquifer medium also pose high impact on aquifer vulnerability. Vulnerability index is highly sensitive to the combined removal of pro-aquifer medium and water table depth, while the least sensitivity is attributed to the removal of lineament density layer. Pro-aquifer medium, water table depth, drainage density, lineament density, topsoil, aquifer depth and aquifer HC constitute a set of parameters that can explain aquifer vulnerability in the basement environment. However, pro-aquifer medium and water table depth are the most important environmental variables that determine aquifer vulnerability across the study area. The adoption of geophysical techniques has provided scientific means of constructing the model parameters. The employed GIS procedure paved way for a more objective intrinsic aquifer vulnerability analysis.