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.

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.