Identification of Groundwater Potential Zones in Hard Rock Terrain of Osun State, Nigeria: Insights from Knowledge-Based (AHP) and Data-Driven (FR) Models
Abstract
The uncertainties associated with groundwater prospecting in the hard rock terrains can be daunting due to erratic nature of aquifers. However, the exploration time and cost can be reduced drastically by narrowing down search areas for geophysical exploration through implementation of a preliminary GIS-based groundwater productivity mapping. This is the focus of the current study across the hard rock terrain of Osun State, Nigeria, with a view to providing a groundwater potential map for land use planning and groundwater resource development. Knowledge-based (AHP) and data-driven (FR) techniques were adopted for allocating weightages to ten applicable groundwater conditioning factors which form the thematic layers. The themes are lithology, rainfall, soil, slope, lineament density, land use, altitude, topographic wetness index, drainage density, and drainage proximity. The weighted linear combination approach was used to aggregate the themes by an overlay analysis in GIS environment. The receiver operating system (ROC) curve was used to validate the groundwater potential maps produced, using borehole yield data. The AHP model results show the order of influence of the conditioning factors as, lithology (37.4%), rainfall (11%), altitude (9.8%), soil (9.6%), lineament density (9.0%), land use (6.4%), drainage density (6.4%), and proximity to drainage (4.7%), slope (3.9%), and topographic wetness index (1.9%). The area under curve (AUC) values of 0.731 and 0.717 were obtained and they translate to prediction accuracies of 73.1% and 71.7% for AHP and FR models respectively. The groundwater potential maps can aid sustainable groundwater resources development in the study area.
Keywords
Analytic hierarchy processRemote sensingFrequency ratioWater securityGIS
References
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