Comparative analysis of GIS and RS based models for delineation of groundwater potential zone mapping

Groundwater is a crucial natural resource that varies in quality and quantity across Khyber Pakhtunkhwa (KPK), Pakistan. Increased population urbanization place enormous demands on groundwater supplies, reducing both their quantity. This research aimed to delineate the potential zone Kohat region, Pakistan by integrating twelve thematic layers. In current research, Potential Zone (GWPZ) were created implementing Weight of Evidence (WOE), Frequency Ratio (FR), Information Value (IV) models region. this study, we used Sentinel-2 satellite data utilized generate an inventory map using machine learning algorithms Google Earth Engine (GEE). Furthermore, validation was done with field survey ground data. The divided into training (80%) testing (20%) datasets. WOE, FR, IV are applied assess relationship between factors GWPZ Finally, results Area Under Curve (AUC) technique for 88%, 91%, 89%. final can aid better future planning exploration, management, supply water