Geo-spatial integration of Dar-Zarrouk geoelectrical parameters and land surface dynamics for aquifer characterization in Ohafia, Southeastern Nigeria

Sustainable groundwater management requires a deep understanding of subsurface aquifer characteristics and their interaction with surface environmental features. In southeastern Nigeria, where increasing population and land use changes threaten groundwater resources, such assessments are vital. This study aimed to evaluate the protective capacity and productivity of aquifers in Ohafia, Ohafia, southeastern Nigeria, using integrated geophysical and spatial analysis. A total of seven vertical electrical sounding (VES) points were investigated across Ohafia using a Schlumberger array to derive aquifer resistivity, thickness, and depth. Dar-Zarrouk parameters, including longitudinal conductance and transverse resistance, were computed. These subsurface metrics were integrated with drainage density, digital elevation models (DEM), and 2024 land use/land cover (LULC) data using GIS tools to analyze their spatial relationships and influence on groundwater potential. Aquifer resistivity values varied widely (99.4–1360 Ω·m), while longitudinal conductance ranged from 0.02 to 0.63 1/Ω. The highest transmissivity (40.40 m²/day) was recorded in rangeland-dominated Achị, suggesting productive aquifer conditions. Areas dominated by tree cover and rangelands demonstrated better aquifer protection and recharge potential than built-up regions like Elu and Abiriba. Drainage density and LULC patterns significantly influenced recharge dynamics. High drainage density zones correlated with poor recharge potential, except where offset by favorable subsurface lithology. Vegetated areas promoted infiltration, while impervious surfaces hindered it. This study demonstrates that combining Dar-Zarrouk parameters with surface geospatial data provides a robust framework for aquifer characterization. The novelty lies in the integrated assessment of geomorphological, anthropogenic, and geoelectrical indicators to prioritize groundwater development zones in a data-scarce tropical region.