Delineation of Groundwater Potential Zone in Hard Rock Terrain, using Remote Sensing, GIS, and Analytical Hierarchy Process (AHP): A Case of Suleja Local Government Area, North-Central Nigeria

Groundwater exploration using integrated approaches such as remote sensing data, geographic information system (GIS), and Multi-criteria decision-making techniques has recently become a breakthrough in groundwater exploration. Suleja, a suburb underlain by Basement complex rocks, has in recent times recorded a reasonable number of abortive boreholes, largely due to poor exploration techniques and lateral discontinuity of the hard rock lithologies. This research aims to delineate possible groundwater potential zones (GPZ) by integrating remote sensing, GIS, and electrical resistivity data. Geophysical data were obtained using the electrical resistivity method through vertical electrical sounding (VES), and the interpreted data were used to produce the study area map. Thematic layers such as geology, depth to bedrock, drainage density, elevation, land use/land cover, and the lineament density were generatedfrom conventional maps, remote sensing data, and geophysical investigation. The data were processed into readable maps in the GIS environment using IDW interpolation techniques. The generated maps were subjected to weighted overlay analysis to obtain the groundwater potential zones. The weights for the various layers were generated using the multi-criteria decision-making technique called the analytical hierarchy process (AHP), which allows the pairwise comparison of criteria influencing the Groundwater potential zone. Using the overlay analysis technique, the thematic maps were integrated to produce the GPZ map of the study area. The map displays five groundwater potential zones, namely very high, high, moderate, low, and very low potential zones. The results of the study revealed that the very high potential zone occupies 0.01% (0.006 km2 ), high 10.04% (11.92 km2 ), moderate 61.46 % (72.98 km2), low 28.34% (33.66 km2), and very low 0.15% (0.1 km2), of the study area respectively. The map generated from this research agrees  easonably with field conditions.