Application of GIS-based data-driven models for groundwater potential mapping in Kuhdasht region of Iran

Water shortage and population growth in Iran rapidly diminish groundwater supplies. Thus, finding the techniques such as GIS that can be used as powerful tools in groundwater management, and predicting groundwater potential is required. The main objective of this study is to evaluate the efficiency of the statistical index (SI), frequency ratio (FR) weights of evidence (WoE) and evidential belief function (EBF) models for groundwater potential mapping at Kuhdasht region, Lorestan province, Iran. For this purpose, 12 groundwater influencing factors were considered in this investigation. From 171 available wells in the study area, 114 wells (67%) and 57 wells (33%) were used based on random selection in SI, FR, WoE and EBF models as training and validation data-sets, respectively. The area under the ROC curve (AUC) for SI, FR, WoE and EBF models was calculated as 91.8, 91, 93.6 and 93.3%, respectively. These curve values indicated that all four models have reasonably good accuracy in spatially predicting groundwater potential in this area.