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The goal of the present research is to evaluate three bivariate models of the frequency ratio, Shannon entropy (SE) and evidential belief function in the spatial prediction of groundwater at the Sero plain located in west Azerbaijan, Iran. In the first phase, well locations with groundwater yields >11 m 3 /hr were identified (75 well locations). Ten groundwater conditioning factors affecting the occurrence of groundwater, namely, altitude, slope degree, curvature, slope aspect, rainfall, soil, land-use, geology and distance from the fault and the river, were selected for modelling. Finally, the groundwater potential map results were drawn from three implemented models and they were validated using testing data by area under the receiver operating characteristic curve (AUC). The AUCs of these models were 0.84, 81 and 85%, respectively. The results of the current study demonstrated that these models could be successfully employed for spatial prediction modelling. Moreover, the results of the SE model demonstrated that the most and the least important factors in groundwater occurrences in the area under study were altitude, curvature and rainfall, respectively. The results of this study are helpful for the Regional Water Authority of Urmia and the decision makers to comprehensively assess the groundwater exploration development and environmental management in future planning.