Abstract

Hydrogeophysical methods have been used in conjunction with new numerical models (statistical and other) in recent years within intricate alluvial aquifers. Understanding aquifer distribution and improving groundwater quality knowledge in the context of huge databases is made feasible by the numerous descriptive statistics approaches (such as Principal Component Analysis (PCA), clustering, and moment calculations) and regression modeling. The study area database includes physicochemical data collected throughout multiple periods and over 2600 vertical electrical sounding (VES). Numerous studies have revealed that the water table is dropping and the quality of the water is declining in this area. To illustrate the spread of mineralization, we used a four-phase technique. The occurrence of four geoelectrical levels, as demonstrated by our results, suggests that the deep deposits are rather homogeneous when compared to the shallow surface data. Additionally, there may be a statistical relationship between the hydrochemical data and the two upper geoelectrical levels. It was, as a consequence, feasible to forecast a distribution map for the mineralization that was consistent with the geological information from earlier work by developing a regression relation between apparent resistivity and electrical conductivity. The acquired results provide new opportunities for understanding large-scale database exploitation, enhancing our understanding of intricate aquifers, and integrating hydrogeophysical and hydrochemical data in predictive modeling.

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