Population growth and escalating water demands in arid regions have led to a surge in deep well water extraction, adversely affecting water quality. The Water Quality Index (WQI) emerges as a crucial tool for systematically assessing and monitoring the impact of these trends. By integrating various physicochemical parameters, the WQI provides a concise and comprehensive measure to evaluate the overall health and sustainability of water resources in the region. This study employed the Water Quality Index (WQI) to assess the water quality status of 37 wells in the Abarkuh Plain in Yazd province, Iran. Spatial distribution maps for 10 key water quality parameters were generated using the Inverse Distance Weighted interpolation method (IDW) in the ArcGIS tool. A Pearson’s test was conducted to examine the correlations among the different variables. The major findings of this study indicated that, among anions and cations, chloride ion (Cl-) and sodium ion (Na+) were the most prevalent. Water Quality Index (WQI) classified 70% of samples as good, 11% as poor, 14% as very poor, and 5% as unsafe. In this research, a new index named IWQI is introduced which is enhanced through the application of the entropy method. The entropy method utilizes data dispersion for parameter weighting, assigning a singular rank to each parameter.. After applying this method, the revised classification showed 68% as good, 5% as poor, 8% as very poor, and 19% as unsafe. Aligned with the Piper diagram, the facies of the water in terms of the dominant anions are sulfate and chloride, and also the facies of the water in terms of the dominant cations are calcium, and magnesium. Therefore, this diagram showed that the composition of groundwater in the Abarkuh plain was affected by the interaction of water and rock. This research underscores the value of spatial distribution maps of hydrochemical parameters and IWQI for effective decision-making in water resources management by local and international authorities.

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