Delineation of groundwater potential zones using remote sensing and GIS-based data-driven models

The rapid increase in human population has increased the groundwater resources demand for drinking, agricultural and industrial purposes. The main purpose of this study is to produce groundwater potential map (GPM) using weights-of-evidence (WOE) and evidential belief function (EBF) models based on geographic information system in the Azna Plain, Lorestan Province, Iran. A total number of 370 groundwater wells with discharge more than 10m(3)s(-1)were considered and out of them, 256 (70%) were randomly selected for training purpose, while the remaining114 (30%) were used for validating the model. In next step, the effective factors on the groundwater potential such as altitude, slope aspect, slope angle, curvature, distance from rivers, drainage density, topographic wetness index, fault distance, fault density, lithology and land use were derived from the spatial geodatabases. Subsequently, the GPM was produced using WOE and EBF models. Finally, the validation of the GPMs was carried out using areas under the ROC curve (AUC). Results showed that the GPM prepared using WOE model has the success rate of 73.62%. Similarly, the AUC plot showed 76.21% prediction accuracy for the EBF model which means both the models performed fairly good predication accuracy. The GPMs are useful sources for planners and engineers in water resource management, land use planning and hazard mitigation purpose.