Electrical resistivity tomography is a non-destructive and efficient geophysical exploration method that can effectively reveal the geological structure and sliding surface characteristics inside landslide bodies. This is crucial for analyzing the stability of landslides and managing associated risks. This study focuses on the Lijiazu landslide in Zhuzhou City, Hunan Province, employing the electrical resistivity tomography method to detect effectively the surrounding area of the landslide. The resistivity data of the deep strata were obtained, and the corresponding geophysical characteristics are inverted. At the same time, combined with the existing drilling data, the electrical structure of the landslide body is discussed in detail. The inversion results reveal significant vertical variations in the landslide body’s resistivity, reflecting changes in rock and soil physical properties. Combined with geological data analysis, it can be concluded that the sliding surface is located in the sandy shale formation. Meanwhile, by integrating various geological data, we can conclude that the landslide is currently in a creeping stage. During the rainy season, with rainfall infiltration, the landslide will further develop, posing a risk of instability. It should be promptly addressed through appropriate remediation measures. Finally, based on the results of two-dimensional inversion, this article constructs a three-dimensional surface morphology of the landslide body, which can more intuitively compare and observe the internal structure and material composition of the landslide body. This also serves as a foundation for the subsequent management and stability assessment of landslides, while also paving the way for exploring new perspectives on the formation mechanisms and theories of landslides.

The settlement and deformation of abandoned mining tunnels can lead to cracking, deformation, or even the collapse of surface structures. Recently, a dual-direction, four-lane expressway, designed a speed of 100 km/h, is planned to be constructed between Yuanling County and Chenxi County. This expressway will pass through a long-abandoned refractory clay mining area in Chenxi County. This study focuses on this abandoned mining area and employs the Electrical Resistivity Tomography (ERT) method to investigate the underground conditions, aiming to determine the location and scale of the subterranean goaf. A total of five survey lines were deployed for the investigation. The inversion results indicate the presence of five low-resistivity anomalies in the underground structure (with six low-resistivity anomalies identified along line L1). These low-resistivity anomalies are preliminarily interpreted as subsurface cavities. Subsequent borehole verification revealed that the five low-resistivity anomalies correspond to a total of eight water-filled cavities, including six abandoned mining tunnels and two karst caves. At the location K33+260~K33+350, a large low-resistivity anomaly was identified which actually consisted of three closely spaced water-filled abandoned mining tunnels. Additionally, the surrounding strata primarily consisted of fractured mudstone, which has a high water content and thus exhibits low resistivity. These two factors combined resulted in the three water-filled abandoned mining tunnels appearing as a single large low-resistivity anomaly in the inversion profile. Meanwhile, at K33+50~K33+110, two water-filled abandoned mining tunnels were found. These tunnels are far apart along line L1 but are relatively close to each other on the other four survey lines. Consequently, in the inversion results, line L1 displays these as two separate low-resistivity anomalies, while the other four survey lines show them as a single large low-resistivity anomaly. Based on the 2D inversion results, a 3D model of the study area was constructed. This model provides a more intuitive visualization of the underground cavity structures in the study area. The findings not only serve as a reference for the subsequent remediation of the goaf area but also offer new insights into the detection of abandoned mining tunnels.

Hidden disaster-causing factor investigation is a fundamental task for safety production in mines. Water hazards in karst metal underground mines are characterized by complex disaster-forming mechanisms, strong suddenness, and high risk, while traditional assessment methods are prone to expert subjective bias and cannot meet the demand for precise prevention and control. This study proposes an improved fuzzy comprehensive evaluation model by integrating the analytic hierarchy process (AHP) and normal distribution-based expert confidence weighting. A three-level assessment index system consisting of 3 first-level indicators and 11 s-level indicators is established for karst metal mine water hazard risk. The normal distribution function is used to quantify expert confidence weights so as to reduce subjective deviation. A three-level fuzzy comprehensive evaluation is performed to achieve quantitative risk grading, and the model robustness is verified through sensitivity analysis. Furthermore, three-dimensional geological modeling and seepage–stress coupling numerical simulation are conducted using COMSOL 6.0 software to validate the reliability of assessment results. The Mao’erling Gold Mine in Hunan Province is taken as a case study. The evaluation yields a comprehensive membership vector of (0.103, 0.130, 0.184, 0.351, 0.232), which is strongly consistent with numerical simulation results and field water inrush records. The results demonstrate that the improved model features strong objectivity and favorable robustness, and can provide a scientific basis for water hazard investigation, risk assessment, and prevention engineering in karst metal underground mines.

Coral sand dissolution may weaken particle strength and compromise the foundation stability of reclaimed reef islands. However, its dissolution mechanisms and associated effects under saline–freshwater conditions remain poorly quantified. This study combined dissolution experiments, inverse hydrogeochemical modeling, statistical analysis, machine learning, and multiscale characterization to identify dominant mechanisms, quantify their contributions, determine key factors, and evaluate alterations in reef island groundwater. Results demonstrated that the dissolution capacity of coral sand (q) ranged from 0.04 to 0.24 mg, increasing with salinity but decreasing with pH and particle size. Coral sand dissolution was mainly controlled by carbonic-acid-mediated dissolution and Ca-Na cation exchange. The cation exchange contribution (p) reached 63–95% under alkaline conditions and increased with pH, salinity, and particle size. Random Forest accurately predicted q and p, with R² values of 0.875 and 0.980, respectively. SHAP analysis identified salinity and pH as the dominant predictors of q and p, respectively. With increasing q, the relative aragonite content decreased, whereas calcite content increased; particle surfaces became rougher, BET specific surface area and porosity increased by 5–28% and 2–10.5%, respectively, and single-particle compressive strength decreased by 70–87%. These findings provide a theoretical basis for assessing stability and reinforcing coral sand foundations on artificial islands.

The Mufushan area, located at the junction of Hunan, Hubei, and Jiangxi provinces, hosts seven identified geothermal anomaly zones, indicating significant potential for geothermal resource development. However, the genetic mechanism of geothermal formation in this region remains insufficiently understood, limiting further exploration and sustainable utilization. By integrating multi-source datasets including geothermal field measurements, geophysical surveys, drilling data, hydrogeochemical analyses, and isotope tracing, this study investigates the formation conditions and genetic mechanism of geothermal resources in the Changtan area of the western Mufushan. The results demonstrate that the spatial distributions of subsurface temperature and geothermal gradient are significantly controlled by fault structures, while vertical variations in temperature indicate that geothermal anomalies are mainly governed by thermal convection. The granitic rock mass is classified as a medium- to high-heat-producing rock, providing a stable basal heat source for geothermal development in the region. The V-shaped structural zone is characterized by well-developed fractures, high porosity, and strong permeability, offering favorable conditions for groundwater storage and hydrothermal exchange. Hydrogeochemical and isotopic evidence indicates that geothermal water has undergone deep circulation and is mainly recharged by atmospheric precipitation from high-elevation areas of Mufushan. Based on these findings, a genetic model is proposed: under the control of major faults (F1 and F2), meteoric water infiltrates through weathered fractures, converges and migrates downward along the fault zones. It is subsequently heated by deep convective circulation and radioactive heat, then ascends through highly permeable structural zones to form confined geothermal water reservoirs. This study provides valuable insights into geothermal geological research of the Mufushan area and offers guidance for future exploration and development.