A Hybrid Spatial–Analytical Network Process Model for Groundwater Inventory in a Semi-Arid Hard Rock Aquifer System—A Case Study

Abstract

Growing agricultural, industrial, and residential needs have increased the demand for groundwater resources. Targeting groundwater has become a challenging endeavour because of the complex interplay between varying climatic, geological, hydrological, and physiographic elements. This study proposes a hybrid RS, GIS, and ANP method to delineate groundwater zones. The resource was evaluated using seven surface hydrological and six subsurface aquifer parameters. The analytic network process model was used to determine the global priority vectors of each subclass. Surface and subsurface groundwater potential maps were created by assigning the resulting weights and spatially integrating them. Later, an integrated potential map was created by combining them. The validation of the obtained results using water level data demonstrates that the integrated map accurately predicted the zones. The area under study has 172.94 km2 of good groundwater potential. An area of 393.01 km2 is classified as having a moderate potential, and an area of 410 km2 is classified as having low potential. These findings will be beneficial to regional policymaking and long-term groundwater management. The results show that an integrated approach using ANP can better determine the groundwater potential zones in semi-arid zones.