To assess and predict the Nansi Lake soil pollution risk, we evaluate the soil environmental quality in the Nansi Lake region using machine learning techniques, combined with the SHapley Additive exPlanations (SHAP) model for interpretability. The primary objective was to predict the level of soil pollution caused by heavy metals, incorporating the traditional Pollution Load Index (PLI) and Potential Ecological Risk Index (PERI) methods. Through the integration of statistical characteristics, PLI, and PERI evaluations, a new assessment method was created, categorizing soil pollution into “Class0—no risk”, “Class1—low risk”, and “Class2—high risk”. Various machine learning models, including Support Vector Machine (SVM), Decision Tree Classifier (DT), Random Forest (RF), and XGBoost, were employed to predict the soil quality based on these indices. XGBoost demonstrated the highest accuracy, achieving a prediction accuracy of 93%. SHAP analysis was further applied to explain the machine learning model and determined that the accumulation of key pollutants such as cadmium (Cd) and mercury (Hg) may significantly produce soil pollution risk, and targeted management needs to be developed for these pollution features.

This study analyzed the sources of total metal elements using the positive matrix factorization (PMF) model and conducted human health risk assessment for adults and children using the health risk assessment model recommended by the United States Environmental Protection Agency (USEPA). According to the health risk assessment, As is the main contributor to the non-carcinogenic risk of groundwater in Tengzhou, with drinking water as the main exposure route. Regarding carcinogenic risks (CR), the values of As and Cr for adults and children were higher than 1 × 10⁻⁴, with drinking water as the main exposure route. Therefore, As is the largest contributor to the CR of groundwater for adults and children and drinking water is the main exposure route in the study area. The primary exposure pathways are oral intake and dermal contact, with oral intake presenting a significant risk. The carcinogenic risks according to principal component analysis (PCA) and PMF analysis showed that the main sources of heavy metals in shallow groundwater in Tengzhou City are agricultural, industrial, natural, and industrial deposition sources, with contribution rates of 21.7%, 27.2%, 31.0%, and 20.1%, respectively. In particular, natural sources are the largest contributor to the accumulation of heavy metals.

Groundwater shortage and pollution are critical issues of global concern. In Wulian County, a typical hilly area, groundwater is the main source of water supply. This study investigates the current situation of groundwater pollution in Wulian City through the analysis of groundwater water chemistry characteristics, water quality evaluation, and health risk evaluation. After the analysis of the controlling factors of chemical components in groundwater and the analysis of ion sources, the main ion sources in groundwater were determined. The results showed that the major cations in groundwater were Ca²⁺ and Na⁺ and the major anions were HCO₃⁻ and SO₄²⁻. Nevertheless, NO₃⁻ exceeded the standard to different degrees in pore water (PW), fissure pore water (FPW), and fissure water (FW). The minimum NO₃⁻ concentration exceeded the standard in FW. Under the influence of rock weathering and salt rock dissolution, the main hydrochemical types of groundwater were the HCO₃-Ca, HCO₃-Ca·Mg, and SO₄·Cl-Ca·Mg types. According to the water quality evaluation and health risk assessment, the FW area in the south had the highest water quality, where Class I water appeared and potable water was more widely distributed. The PW and FPW areas in the north had lower water quality, with higher health risks. Category V water gradually appeared in the FPW area, which is not suitable as a water supply source. Factor analysis and ion ratio analysis showed that the study area is strongly affected by anthropogenic factors. These research methods have important reference value to the research of groundwater pollution status.

In order to understand the pollution degree and source of potentially toxic elements (PTEs) in groundwater around the accident site and evaluate their harm to human health, 22 groundwater samples were collected around the accident well, and the contents of As, Cd, Cr, Cu, Hg, Ni, Pb, Zn, CH₂Cl₂ and C₂H₄Cl₂ were determined. On the basis of water quality evaluation, the source apportionment method combining qualitative and quantitative analysis was used to determine the main sources of PTEs in the region, and the health risk assessment model was used to evaluate the health risk of PTEs to the human body. The results show that pH, TDS, Th and COD all exceed the standard to varying degrees, among which TH is the index with the largest number exceeding the standard. The quality of the groundwater environment in the study area is at a very poor level, and the F value is between 7.25 and 8.49. The exposure results model showed that there was no non-carcinogenic risk of PTEs in the study area, and the health risk of oral intake in the exposed population was greater than that of skin contact. Compared with adults, children were more vulnerable to the health risk stress of PTEs in groundwater. The total carcinogenic risk is higher than the total non-carcinogenic risk. As, Cd and Cr are the primary factors causing carcinogenic health risks in this area. Principal component analysis (PCA) was used to analyze the sources of PTEs in groundwater, and three principal components were extracted. It was preliminarily determined that PTE pollution was mainly related to agricultural sources, anthropogenic industrial sources and industrial sedimentation sources. The results of positive definite factor matrix analysis (PMF) were basically similar to those of PCA, but PMF further clarified the contribution rate of three pollution sources, among which agricultural sources contributed the most to the accumulation of PTEs.

Groundwater in the Nansi Lake Basin, a key reservoir of the South-to-North Water Diversion Project, supports domestic, agricultural, and ecological needs but faces pressure from overexploitation and pollution. This study clarifies the hydrochemical characteristics, controlling processes, environmental quality, and source contributions of shallow groundwater in the basin. Hydrochemical data from 67 wells were interpreted using Piper and Schukalev diagrams, Gibbs and ion-ratio plots, the entropy-weight water quality index (EWQI), and an absolute principal component scores–multiple linear regression (APCS-MLR) model. Groundwater shows high mineralization and hardness, with 35.82% and 55.22% of samples exceeding standard limits for total dissolved solids and total hardness, respectively. The dominant facies are HCO₃-Ca, HCO₃-Ca·Mg, and HCO₃·Cl-Na·Ca, indicating dissolution and ion exchange involving carbonate and silicate rocks. Gibbs and ion-ratio analyses demonstrate that rock–water interaction is the main control, with secondary influence from evaporation. EWQI results indicate generally good groundwater quality (68.66% Class I, 20.90% Class II). APCS-MLR identifies natural, agricultural, ion-exchange, and anthropogenic sources, contributing 53.34%, 22.71%, 4.79% and 19.14%, respectively. These findings show that protection should focus on pollution control in northern agricultural and mining zones while conserving high-quality groundwater elsewhere in the basin.