GIS-based groundwater spring potential assessment and mapping in the Birjand Township, southern Khorasan Province, IranEvaluation de la potentialité des sources d’eau souterraine à partir d’un SIG et cartographie dans le district de Birjand, Sud de la province de Khorasan, IranEvaluación del potencial de manantiales de agua subterránea basado en GIS y mapeo en el Birjand Township, sur de la provincia de Khorasan, Irán伊朗Khorasan省南部Birjand镇基于GIS的地下水泉潜力评价和编图Avaliação e mapeamento do potencial em nascentes de água subterrânea com base em SIG no município de Birjand, sul da Província de Khorasan, Irão

Three statistical models—frequency ratio (FR), weights-of-evidence (WofE) and logistic regression (LR)—produced groundwater-spring potential maps for the Birjand Township, southern Khorasan Province, Iran. In total, 304 springs were identified in a field survey and mapped in a geographic information system (GIS), out of which 212 spring locations were randomly selected to be modeled and the remaining 92 were used for the model evaluation. The effective factors—slope angle, slope aspect, elevation, topographic wetness index (TWI), stream power index (SPI), slope length (LS), plan curvature, lithology, land use, and distance to river, road, fault—were derived from the spatial database. Using these effective factors, groundwater spring potential was calculated using the three models, and the results were plotted in ArcGIS. The receiver operating characteristic (ROC) curves were drawn for spring potential maps and the area under the curve (AUC) was computed. The final results indicated that the FR model (AUC = 79.38 %) performed better than the WofE (AUC = 75.69 %) and LR (AUC = 63.71 %) models. Sensitivity and factor analyses concluded that the bivariate statistical index model (i.e. FR) can be used as a simple tool in the assessment of groundwater spring potential when a sufficient number of data are obtained.