The integrated fuzzy AHP and fuzzy logic techniques for mapping and prioritizing groundwater potential zone based on water quality.

Groundwater, which is utilized to supply water demand in various sectors such as domestic water consumption, agriculture, and industry, could be achieved by delineating a groundwater potential zone. Although mapping groundwater potential zones has been done through different approaches in recent studies, conjunctive use of fuzzy analytic hierarchy process (AHP) and fuzzy logic equations for ranking according to water quality has not been done. So, the aim of this study was to map and prioritize groundwater potential lands by combining the utilization of fuzzy AHP and fuzzy logic equations while considering water quality parameters in the central part of Iran. For this study, six thematic layers, viz., soil texture, rainfall, lineament density, land use, lithology, and slope, were considered as effective factors, while the weight for each parameter was calculated by a fuzzy AHP model. The verification of the model through 21 piezometric and 18 pumping wells resulted in overall accuracy values of 76.19% and 72.22%, which approved the reliability of the fuzzy AHP approach for groundwater potential (GWP) prediction in this region. Also, the scatter plot between the well's yield values and the groundwater potential index presented coefficient of determination (R) values equal to 0.5682, which was a reasonable correlation. Therefore, spatial distribution maps and fuzzy layers of electrical conductivity (EC) and sodium absorption ratio (SAR) parameters were prepared to assess agricultural water quality, and these layers were also provided for total dissolve salts (T.D.S), total hardness (TH), some anions, and cations to evaluate water quality for the drinking consumption. So, the integration of the GWP layer with the water quality layers led to the ranking of the GWP map. The findings showed that the north and parts of the center of the watershed were ranked 1, 2, and 3 in terms of groundwater storage potential with a more desirable quality for irrigation, while the rank 3 covered the maximum part (31.59%). Also, by considering the drinking water quality, it highlighted that 29.61% of the region were ranked 1, 2, and 3, whose total areas were less than areas of the rank 4 (31.65%). This study emphasized that the GWP ranking according to water quality will help allocate land for agriculture and residential usage based on supplying desirable water demand. Finally, it can be concluded that the outcomes of this research will be useful for decision makers to ensure the availability and sustainability of favorable groundwater and also, plan for artificial recharge in places with inadequate or undesirable groundwater.