Spatial analysis of groundwater potential using weights-of-evidence and evidential belief function models and remote sensing

As demands for groundwater in the arid and semiarid areas increase, delineation of groundwater potential zone becomes an increasingly valuable technique for implementing a successful groundwater potential analysis. The capability of using weights-of-evidence (WOE) and evidential belief function (EBF) models for groundwater potential mapping is tested and compared in the Ilam Plain, Iran. In the present study, multiple geo-env iron menta l factors including lithology, land use, distance from river, soil texture, drainage density, altitude, curvature, topographic wetness index (TWI), slope percent, lineament density, and rainfall were used as inputs for both models. Subsequently, a well inventory map was produced using documentary sources of Iranian Water Resources Department (IWRD) and extensive field surveys. About 145 groundwater productivity data (with high potential yield values of >= 11 m(3)/h) were separated from well locations. Out of these. 101 (70 %) cases were randomly selected for groundwater potential modeling, and the remaining 44 (30 %) cases were applied for the validation purpose. In the next step, groundwater potential maps were produced using WOE and EBF models in GIS environment. The receiver operating characteristic (ROC) curves for the produced maps were drawn and the areas under the curves (AUC) were determined. From the analysis, predictive performance of EBF model (AUC=83.7 0) was better than of WOE model (AUC=78.2 %). The results also show the capability of EBF model in managing uncertainty associated in groundwater potential mapping. Therefore, WOE and EBF models are shown to he an effective prediction models for groundwater potential mapping. The groundwater potential map can he helpful for planners in groundwater management and land use planning.