Groundwater potential zone mapping using GIS and Remote Sensing based models for sustainable groundwater management

Abstract

The present research is conducted in the southern region of Khyber Pakhtunkhwa, Pakistan, to identify groundwater potential zones (GWPZ). We used three models including Weight of Evidence (WOE), Frequency Ratio (FR), and Information Value (IV) with twelve parameters (elevation, slope, aspect, curvature, drainage network, LULC, precipitation, geology, Lineament, NDVI, road, and soil texture, that have been prepared and integrated into ArcGIS 10.8. The reliability of the applied models’ results was validated using Area Under the Receiver Operating Characteristics (AUROC). The GWPZ were reclassified into five classes, i.e. very low, low, medium, high, and very high zone. The area occupied by mentioned classes using WOE are very low (10.14%), low (19.58%), medium (26.75%), high (27.10%), very high (16.40%), while using FR are very low (20.93%), low (32.38%), medium (18.92%), high (13.13%), very high (14.61%) and using IV are very low (14.41%), low (17.17%), medium (29.01%), high (25.85%), and very High (13.53%). The Success Rate Curve of WOE, FR, and IV were 0.86, 0.91, and 0.87, while the Predicted Rate Curve values were 0.89, 0.93, and 0.90, respectively. The results revealed that all applied statistical models performed very well to delineate GWPZ. However, use of the FR technique is strongly encouraged to evaluate the GWPZ, and its findings are especially useful for managing groundwater resources in urban planning. Our approaches for assessing the GWPZ mapping can be applied in any region with similar scenarios and are recommended as a helpful tool for policymakers to manage groundwater.