Xun Zhou

To address the challenges of identifying mine water inrush sources and the low efficiency of risk control under complex karst hydrogeological conditions in the Beiya Gold Mine, Yunnan, this study proposes an intelligent identification model integrating nonlinear feature extraction and intelligent parameter optimization. Utilizing 42 sets of measured water samples (comprising karst springs, surface water, and solution caves), a coupling identification model was constructed based on 11-dimensional features including hydrochemical indices and hydrogen–oxygen isotopes. The model employs Kernel Principal Component Analysis (KPCA) to extract discriminative low-dimensional features from nonlinear data, while the critical parameters of the Support Vector Machine (SVM) are optimized via an Improved Sparrow Search Algorithm (ISSA) to enhance generalization performance. The results demonstrate that the following: (1) the proposed model achieves an identification accuracy of 91.7% on the independent test set, significantly outperforming benchmark models such as RF and standard SVM; (2) three sets of comparative experiments indicate that the fusion of multi-source features yields superior identification performance compared to single-source inputs; and (3) SHAP (shapley additive explanation) interpretability analysis reveals that HCO₃⁻, Mg²⁺, Ca²⁺, and F⁻ are the core discriminative factors, with their contribution patterns aligning closely with the hydrogeochemical evolution mechanisms of the mining area. This model achieves a synergy between high-precision identification and mechanical interpretability, providing reliable technical support for water disaster prevention in karst mining areas.

Hydrogeochemical characteristics and temperature variations in fault-controlled, deep-circulation thermal springs elucidate water–rock interaction dynamics and hydrothermal circulation depths, providing critical insights into fault permeability and stress accumulation. To investigate the coexistence of high-temperature and medium-low-temperature thermal springs on small-scale faults and their distinct circulation mechanisms, hydrochemical and isotopic analyses were conducted on 13 water samples (9 proximal on the Xiangbaihe Fault) in western Yunnan. The hot springs along the Xiangbaihe Fault are predominantly classified as the Na-HCO₃ type, derived from carbonate and aluminosilicate hydrolysis. δ²H and δ¹⁸O confirmed a meteoric origin, with recharge elevations spanning 2465–3286 m (Gaoligong Mountain). Inverse hydrochemical modeling demonstrated progressive mineral transfer and water–rock interactions along the fault’s east–west axis. Conservative elements (Cl, Li) suggested a shared geothermal fluid source or reservoir affiliation. BLZ reservoir temperatures (194–221 °C) were classified as a high-temperature system, whereas others (58–150 °C) represented medium-low-temperature systems. Although each thermal spring represents a distinct geothermal system, reservoir interconnectivity is inferred. Notably, despite uniform lithology, variations in spring temperature and elemental composition are attributed to a subsurface magma chamber beneath BLZ, heterogeneous fault geometries, differential reservoir temperatures, and variable cold-water mixing ratios. This study establishes a framework for understanding groundwater circulation in small-scale fault-associated geothermal systems, with implications for tectonic activity monitoring and geothermal resource assessment.

Thermal groundwater in the Lower and Middle Triassic carbonates in Chongqing, China, is mainly concentrated in anticlines. Hot springs (32.9 to 57 °C) with SO₄-Ca type waters and Total Dissolved Solids (TDS) of 1620 to 2929 mg/L emerge in the middle and the plunging ends of the structures. Multivariate methods are used to analyze the hydrochemical characteristics of the waters, and identify the sources of the main dissolved components, providing an insight into the evolution of the environment in which they formed. Hierarchical cluster analysis of compositional data differentiates samples in the study area into three categories: high TDS-high Ca²⁺ and SO₄²⁻ water; medium TDS-high Na⁺ and Cl⁻ water; and low TDS-high HCO₃⁻ water. Factor analysis and ion ratio relationships show that Ca²⁺ and SO₄²⁻ are mainly derived from the dissolution of gypsum and anhydrite within the geothermal reservoir, with some addition of SO₄²⁻ from coal-bearing cap rocks. The main source of HCO₃⁻, is in the dissolution of dolomite and CO₂ that also promotes the incongruent dissolution of albite and K-feldspar, adding Na⁺ and K⁺ to the groundwater. Reverse modelling of the transfers of each phase shows, in three models, that the minerals dissolved decrease progressively—with the exception of halite and albite. Combined with the hydrochemical characteristics of hot water in the same reservoir in the adjacent area (Cl-Na type, TDS of 13.37 g/L), a process of desalination of the hot water can be confirmed, which has not yet reached the ‘freshwater’ stage dominated by HCO₃⁻.