Integrated Hydrogeochemical Characterization, Drinking Water Quality Assessment, and Spatial Analysis of Groundwater Using GIS and Multivariate Statistics: A Case Study of Fars Province, Iran

Abstract

Groundwater quality in semi-arid regions is influenced by interacting geological, climatic, and human factors. This study integrated hydrochemical analysis, ionic relationships, multivariate statistics, Water Quality Index (WQI), and GIS-based spatial analysis to evaluate groundwater quality in Fars Province, southern Iran. A total of 171 groundwater wells were sampled during each of the 2020 and 2021 monitoring campaigns. Hydrochemical diagrams and ionic relationships indicated the predominance of Na–Cl facies and showed that groundwater chemistry is mainly controlled by carbonate and silicate weathering, evaporite dissolution, cation exchange, water–rock interaction, and evaporation–crystallization. Chloro-alkaline indices indicated a mixed cation-exchange system, with positive CAI values predominating regionally and negative values occurring locally. Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) consistently identified groundwater mineralization as the dominant source of hydrochemical variability, characterized by EC, TDS, major ions, and hardness, while bicarbonate and nitrate represented a secondary source of variability reflecting both carbonate-related processes and localized nutrient inputs. Based on WQI, about 48% and 42.7% of the sampled wells were classified as excellent or good in 2020 and 2021, respectively, whereas 26% and about 30% were unsuitable for drinking. Spatial analysis revealed widespread mineralization and enrichment of Na+, Cl−, and SO42−, although interpolation results for EC and TDS should be interpreted cautiously and primarily for exploratory visualization of spatial patterns because of their lower predictive performance. In general, regional groundwater quality is governed primarily by natural hydrogeochemical evolution, while localized anthropogenic influences may contribute to nutrient variability. The results provide a basis for targeted monitoring and sustainable groundwater management in semi-arid aquifers.