Groundwater holds an important role in the water supply in Linyi city, China. Investigating the hydrochemical characteristics of groundwater, and revealing the factors governing groundwater geochemistry, is a primary step for ensuring the safe and rational exploitation of groundwater resources. This study used a self-organizing map (SOM) and multivariate statistical methods to assess groundwater quality in the urban area of Linyi city. Based on the hydrochemical dataset consisting of nine parameters (i.e., pH, ${\mathrm{C}\mathrm{a}}^{2+}$, ${\mathrm{M}\mathrm{g}}^{2+}$, ${\mathrm{N}\mathrm{a}}^{+}$, ${\mathrm{K}}^{+}$, ${\mathrm{H}\mathrm{C}{\mathrm{O}}_3}^{-}$, ${\mathrm{C}\mathrm{l}}^{-}$, ${{\mathrm{S}\mathrm{O}}_4}^{2-}$, and ${{\mathrm{N}\mathrm{O}}_3}^{-}$) from 89 groundwater samples, the SOM was first applied to obtain the weight vectors of the output nodes. Hierarchical cluster analysis (HCA) was used for organizing the nodes into four clusters. The node cluster indices were then remapped to the groundwater samples according to the winner node for each sample. The hydrochemical characteristics and factors controlling the groundwater geochemistry of the four clusters were analyzed using principal component analysis (PCA) and graphical methods including Piper and Gibbs diagrams, as well as binary plots of the major ions in groundwater. Results indicated that groundwater geochemistry in this area is primarily governed by water–rock interactions, such as the dissolution of halite, calcite, and gypsum, along with the influence of municipal sewage and the degradation of organic matter. This study demonstrates that the integration of an SOM and multivariate statistical methods improves the understanding of groundwater geochemistry and hydrochemical evolution in complex groundwater flow systems impacted by utilization.

The reaction between the lixiviant and the minerals in the aquifer of In-situ uranium leaching (ISL) will result mineral dissolution and precipitation. ISL will cause changes in the chemical composition of groundwater and the porosity and permeability of aquifer, as well as groundwater pollution. Previous studies lack three-dimension numerical simulation that includes a variety of minerals and considers changes in porosity and permeability properties simultaneously. To solve these problems, a three-dimensional reactive transport model (RTM) which considered minerals, main water components and changes in porosity and permeability properties in Bayanwula mine has been established. The results revealed that: (1) Uranium elements were mainly distributed inside the mining area and had a weak trend of migration to the outside. The strong acidity liquid is mainly in the mining area, and the acidity liquid dissolved the minerals during migrating to the outside of the mining area. The concentration front of major metal cations such as K⁺, Na⁺, Ca²⁺ and Mg²⁺ is about 150m away from the boundary. (2) The main dissolved minerals include feldspar, pyrite, calcite, sodium montmorillonite and calcium montmorillonite. Calcite is the most soluble mineral and one of the sources of gypsum precipitation. Other minerals will dissolve significantly after calcite is dissolved. (3) ISL will cause changes in porosity and permeability of the mining area. Mineral dissolution raises porosity and permeability near the injection well. Mineral precipitation reduced porosity and permeability near the pumping well, which can plugging the pore throat and affect recovery efficiency negatively.

Uranium extraction through the in situ leaching method stands as a pivotal approach in uranium mining. In an effort to comprehensively assess the repercussions of in situ uranium leaching on groundwater quality, this study collected 12 representative groundwater samples within the Bayan-Uul mining area. The basic statistical characteristics of the water samples showed that the concentrations of SO₄²⁻ and total dissolved solids (TDS) were relatively high. Through the use of cluster analysis, the water samples were categorized into two distinct clusters. Seven samples from wells W-d, W-u, N01, W10-2, W08-1, W10-1, and W13-1, situated at a considerable distance from the mining area, were grouped together. Conversely, five samples from wells W08-2, W13-2, W01-1, W02-2, and the pumping well located in closer proximity to the mining area, formed a separate cluster. A decision tree-based machine learning approach was employed to discern the influence of various hydrochemical indicators in forming these clusters, with results indicating that SO₄²⁻ exerts the most substantial influence, followed by Ca²⁺. The mineral saturation indices from geochemical modeling indicated that, as the distance from the mining area increased, the trend of calcium minerals changed from dissolution to precipitation; iron minerals were in a precipitation state, and the precipitation trend was gradually weakening. In light of these findings, it is clear that in situ uranium leaching significantly impacted the groundwater in the vicinity of the mining area. The prolonged consumption of groundwater sourced near the study area, or its use for animal husbandry, poses potential health risks that demand heightened attention.

Acid in-situ leaching (ISL) is a common approach to the recovery of uranium in the subsurface. As some toxic and harmful substances might be produced by the chemical reactions among the injected sulphuric acid, the groundwater, and the porous media during leaching processes, the pollution control of the mining plan for ISL is important. In this study, a three-dimensional reactive transport modeling (3DRTM) was applied to decide the pollution control mining plan, considering the partial penetration through wellbore in confined aquifer and complex chemical reactions between main minerals. Based on the 3DRTM, different pumping ratio and non-uniform injection schemes were compared. The results show that the preferential pollution control mining plan is non-uniform injection ratio equal 0.1. By analyzing the characteristics of water table and streamline, it is concluded that the scheme has a strong hydraulic capture effect. In this scheme, the concentration of UO22+, H+, SO42- obtained by 3DRTM is lower. The inner well injection rate is 194.09 m3/d, the outer well injection rate is 158.89 m3/d, and the pumping rate is 264.00 m3/d. A reasonable suggestion is to adopt non-uniform injection mining mode in ISL.