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.

The construction of subways exacerbates the non-uniformity of surface deformation, which in turn poses a potential threat to the safe construction and stable operation of urban rail transit systems. Beijing, the city with the most extensive subway network in China, has long been affected by land subsidence. Utilizing data from Envisat ASAR, Radarsat-2, and Sentinel-1 satellites, this study employs PS-InSAR technology to monitor and analyze land subsidence within a 2 km buffer zone along Beijing Metro Line 22 over a span of 20 years (from January 2004 to November 2024). The results indicate that land subsidence at Guanzhuang Station and Yanjiao Station along Metro Line 22 is particularly pronounced, forming two distinct subsidence zones. After 2016, the overall rate of subsidence along the subway line began to stabilize, with noticeable ground rebound emerging around 2020. This study further reveals a strong correlation between land subsidence and confined groundwater levels, while geological structures and building construction also exert a significant influence on subsidence development. These findings provide a crucial scientific foundation for the formulation of effective prevention and mitigation strategies for land subsidence along urban rail transit lines.

Beijing is a city on the North China Plain with severe land subsidence. In recent years, Beijing has implemented effective measures to control land subsidence. Since this implementation, the development of time-series land subsidence in Beijing has slowed and has shown nonlinearity. Most previous studies have focused on the linear evolution of land subsidence; the nonlinear evolutionary patterns of land subsidence require further discussion. Therefore, we aimed to identify the evolution of land subsidence in Beijing, based on Envisat ASAR and Radarsat-2 images from 2003 to 2020, using permanent scatterer interferometric synthetic aperture radar (PS-InSAR) and cubic curve polynomial fitting methods. The dates of the extreme and inflection points were identified from the polynomial coefficients. From 2003 to 2020, the subsidence rate reached 138.55 mm/year, and the area with a subsidence rate > 15 mm/year reached 1688.81 km². The cubic polynomials fit the time-series deformation well, with R² ranging from 0.86 to 0.99 and the RMSE ranging from 1.97 to 60.28 mm. Furthermore, the subsidence rate at 96.64% of permanent scatterer (PS) points first increased and then decreased. The subsidence rate at 86.58% of the PS points began to decrease from 2010 to 2015; whereas the subsidence rate at 30.51% of the PS point reached a maximum between 2015 and 2019 and then decreased. The cumulative settlement continued to increase at 69.49% of the PS points. These findings imply that groundwater levels are highly correlated with the temporal evolution of subsidence in areas with pattern D (Vs+-, S+), with increasing and then decelerating rates and increasing amounts. In regions with a thickness of compressible clay layer over 210 m, subsidence follows pattern E (Vs+, S+), with increasing rates and amounts. Fractures such as the Gaoliying and Sunhe fractures significantly influence the spatial distribution of subsidence patterns, showing distinct differences on either side. Near the Global Resort Station, pattern E (Vs+, S+) intensifies in subsidence, potentially due to factors like land use changes and construction activities.

Using an iterative numerical approach, we have obtained the self-consistent thermal expansion, heat capacity, and Grüneisen parameters of diopside (MgCaSi₂O₆) over wide pressure and temperature ranges based on experimental data from the literature. Our results agree well with the published experimental and theoretical data. The determined thermodynamic parameters exhibit nonlinear dependences with increasing pressure. Compared with other minerals in the upper mantle, we found that the adiabatic temperature gradient obtained using the thermodynamic data of diopside is larger than that of garnet while lower than that of olivine, when ignoring the Fe incorporation. Combining our results with thermodynamic parameters of garnet obtained in previous studies, we have estimated the adiabatic temperature gradient and geotherm of an eclogitic upper mantle in a depth range of 200–450 km. The results show that the estimated adiabatic temperature gradient of the eclogite model is ~16% and ~3% lower than that of the pyrolite model at a depth of 200 km and 410 km, respectively. However, the high mantle potential temperature of the eclogite model leads to a similar temperature as the pyrolite model in a depth range of 200–410 km.