The Mid-Gangetic Plain, a vital farmland in India, faces increasing groundwater quality deterioration due to anthropogenic activities. This study aimed to assess groundwater quality and contamination sources in the region utilizing statistical methods. A total of 78 groundwater samples were collected and analyzed using standard methods. The hydrochemistry analysis of samples revealed that several parameters such as Ca2+, Mg2+, HCO3−, NO3−, F− and PO43− surpassed the limits prescribed by the Bureau of Indian Standards (BIS). The principal component analysis yielded three significant factors, explaining 68.96% variation, highlighting geogenic and anthropogenic influences on groundwater chemistry. Hierarchical cluster analysis categorized groundwater into three clusters based on the parameters with similar trends of variation. Furthermore, discriminant analysis identified four significant variables (Mg2+, F−, Cl− and NO3−) responsible for creating the distinction among the identified clusters. Hydrogeochemical categorization and multivariate statistical analyses indicated that rock–water interaction, weathering, leaching and anthropogenic activities collectively influenced groundwater quality throughout the studied region. The Water Quality Index reveals that 59% of samples have good water quality, while 41% exhibit poor quality predominantly concentrated in the south-western, south-eastern and central regions. This study demonstrates the efficacy of statistical techniques to interpret complex datasets and grasp water quality dynamics, enhancing groundwater management.

Groundwater contamination is a rising issue worldwide, and it must be treated well as most of the world relies on it. Groundwater pollution occurs when undesirable substances in groundwater rise. Understanding, simulating, and predicting solute mobility in groundwater helps to treat polluted groundwater. MT3DMS has been used to model contaminant movement with a non-linear Freundlich sorption isotherm. MT3DMS stands for “Modular three-dimensional multispecies transport model”. MT3DMS software has several categories of solute transport solution techniques, like FDM and the higher-order finite-volume TVD method, in a unique single code. Applying the combination of these solution techniques is believed to give the best possible solution with greater precision and accuracy. In the current work, the benchmark problem (P2) of the MT3DMS package was taken, and the chemical reaction package was modified according to our problem. Multiple simulations were run with different adsorption capacities and intensities, incorporating the nonlinear Freundlich sorption isotherm. After that analysis of BTC trends, at a position 8 cm from the source, the pulse input of contamination was discharged for 160 s. The simulation lasted 1500 s. The observation output files were imported to plot BTCs for trend analysis and visualize simulation results. After comparing the various BTCs, it was found that the adsorption capability of porous medium enhances retention capacity so contaminants are sorbed and retarded by the solid phase more, slowing the contaminant movement and delaying the BTC peak. For similar adsorption capacity at a lower adsorption intensity, the solid retains more contaminant and the peak is attenuated as well as delayed; but, as the adsorption intensity increases, the relative concentration in the aqueous phase increases, and the peak is enhanced early as the solid retains less contaminant.