This study develops an integrated framework for groundwater pollution source identification by coupling Principal Component Analysis (PCA), Positive Matrix Factorization (PMF), and the Mantel test, with the Qujiang River Basin as a case study. The framework enables a full-process assessment, encompassing qualitative identification, quantitative apportionment, and spatial validation of pollution drivers. Results indicate that groundwater chemistry is primarily influenced by three categories of sources: natural rock weathering, agricultural and domestic activities, and industrial wastewater discharge. Anthropogenic sources account for 73.7% of the total contribution, with mixed agricultural and domestic inputs dominating (38.5%), followed by industrial effluents (35.2%), while natural weathering contributes 26.3%. Mantel test analysis further shows that agricultural and domestic pollution correlates strongly with intensive farmland distribution in the midstream area, natural sources correspond to carbonate outcrops and higher elevations in the upstream, and industrial contributions cluster in downstream industrial zones. By integrating PCA, PMF, and Mantel analysis, this study offers a robust and transferable framework that improves both the accuracy and spatial interpretability of groundwater pollution source identification. The proposed approach provides scientific support for regionalized groundwater pollution prevention and control under complex hydrogeological settings.

The Qujiang River Basin is a significant water system located in Zhejiang Province, China, that serves as a primary water source for Quzhou City. For this research, we collected and examined water samples from the Qujiang River Basin. In this study, we collected and analyzed water samples from the Qujiang River Basin and employed a combination of methods, including water balance analysis; Piper trilinear diagram; Gibbs diagram; and environmental tracer techniques, such as hydrochemical and isotopic analysis. These techniques helped us to analyze the spatial distribution patterns and evolutionary trends of surface water and groundwater hydrochemistry, along with the stable isotopes of hydrogen and oxygen, as well as to determine the sources of surface water and groundwater by calculating the conversion ratio between surface water and groundwater. (1) The findings of our study indicate that the primary hydrochemical types in the study area are Ca-HCO₃ and Ca-HCO₃·Cl, with the ion composition of water primarily influenced by rock weathering and precipitation. (2) Similar spatial variations in hydrochemical indicators were observed between surface water and groundwater in the study area, with frequent transitions between the two. (3) The hydrogen and oxygen isotope content increases downstream, signifying that both groundwater and surface water in the study area are replenished by atmospheric precipitation, as supported by the relationship between hydrogen and oxygen isotopes and the meteoric water line. (4) We determined that groundwater predominantly replenishes surface water in the upstream area. The average contribution rate of groundwater to surface water is 19.67%, with an annual average recharge volume of 1.23 × 10⁶ m³. Midstream and downstream, surface water mainly recharges groundwater, with an average contribution rate of 22.77% and an annual average recharge volume of 1.59 × 10⁶ m³.

This study investigated the hydrochemical characteristics, solute sources, and controlling factors of the Qujiang River, a vital tributary of the Qiantangjiang River, on the basis of 61 surface water samples collected from July to September 2019. A multi-method framework integrating ArcGIS spatial analysis, a Piper trilinear diagram, a Gibbs diagram, ion ratio analysis, and principal component analysis (PCA) was systematically applied. The results demonstrate significant spatial heterogeneity in pH values (6.39–7.15 in the upper reaches, 6.31–8.83 in the middle reaches, and 6.85–8.1 in the lower reaches), with hydrochemical facies dominated by Ca-HCO₃ types (87% frequency) in the upper–middle reaches, transitioning to SO₄·Cl-Na and SO₄·Cl-Na·Ca mixed types downstream. Source apportionment indicates that carbonate weathering and atmospheric precipitation are the primary controls on hydrochemistry in the upper and middle reaches, whereas industrial effluents, evidenced by a 2.3-fold increase in SO₄²⁻ concentration, and domestic sewage, with Cl⁻ levels reaching 16.07 mg/L, are the dominant influences in the lower reaches. This study’s innovation lies in the quantitative separation of natural weathering (68% contribution) and anthropogenic activities (32%) through an integrated methodological approach, offering a basin-scale understanding of longitudinal hydrochemical evolution. These results provide valuable insights for the management and ecological conservation of medium- to small-sized basins.

Groundwater pollution in chemical industrial parks is typically concealed, delayed in onset, and difficult to remediate. Moreover, the long-term migration of typical pollutants in aquifers may threaten the safety of surrounding water sources and river water environments. In this study, a numerical subsurface flow model was constructed for a chemical industrial park in a mining area of Inner Mongolia by generalizing the Quaternary loose-rock pore aquifer system, based on hydrogeological surveys and groundwater monitoring data, using MODFLOW. A solute transport model was then established through coupling with MT3DMS to predict the spatiotemporal evolution of ammonia nitrogen and 1,2-dichloroethane in the absence of new pollution sources, and the influence of subsurface flow velocity on pollutant diffusion was further analyzed. The results show that the contaminant plume area gradually increases over the simulation period: the ammonia nitrogen plume expands from 1.84 km² to 3.98 km², and the 1,2-dichloroethane plume expands from 1.47 km² to 3.05 km². Contaminant concentrations in individual wells generally exhibit a downward trend; nonetheless, long-term exceedance risks persist at specific sites. These findings provide a scientific basis for groundwater pollution risk management, water source protection, and subsequent remediation decisions for chemical industrial parks in arid and semi-arid regions.