The utilization for water resource has been of great concern to human life. To assess the natural water system in Kangding County, the integrated methods of hydrochemical analysis, multivariate statistics and geochemical modelling were conducted on surface water, groundwater, and thermal water samples. Surface water and groundwater were dominated by Ca-HCO₃ type, while thermal water belonged to Ca-HCO₃ and Na-Cl-SO₄ types. The analyzing results concluded the driving factors that affect hydrochemical components. Following the results of the combined assessments, hydrochemical process was controlled by the dissolution of carbonate and silicate minerals with slight influence from anthropogenic activity. The mixing model of groundwater and thermal water was calculated using silica-enthalpy method, yielding cold-water fraction of 0.56–0.79 and an estimated reservoir temperature of 130–199 °C, respectively. δD and δ¹⁸O isotopes suggested that surface water, groundwater and thermal springs were of meteoric origin. Thermal water should have deep circulation through the Xianshuihe fault zone, while groundwater flows through secondary fractures where it recharges with thermal water. Those analytical results were used to construct a hydrological conceptual model, providing a better understanding of the natural water system in Kangding County.

Detection of subsurface hydrodynamic anomalies plays a significant role in groundwater resource management and environmental monitoring. In this paper, based on data from the groundwater level, atmospheric pressure, and precipitation in the Chengdu area of China, a method for detecting outliers considering the factors affecting groundwater levels is proposed. By analyzing the factors affecting groundwater levels in the monitoring site and eliminating them, simplified groundwater data is obtained. Applying sl-Pauta (self-learning-based Pauta), iForest (Isolated Forest), OCSVM (One-Class SVM), and KNN to synthetic data with known outliers, testing and evaluating the effectiveness of 4 technologies. Finally, the four methods are applied to the detection of outliers in simplified groundwater levels. The results show that in the detection of outliers in synthesized data, the OCSVM method has the best detection performance, with a precision rate of 88.89%, a recall rate of 91.43%, an F1 score of 90.14%, and an AUC value of 95.66%. In the detection of outliers in simplified groundwater levels, a qualitative analysis of the displacement data within the field of view indicates that the outlier detection performance of iForest and OCSVM is better than that of KNN. The proposed method for considering the factors affecting groundwater levels can improve the efficiency and accuracy of detecting outliers in groundwater level data.

Gypsum-bearing salt rock in the Cretaceous Guankou Formation is widely distributed in the southern suburbs of Chengdu and may undergo significant strength attenuation under water–rock interaction. Based on a 35-day immersion experiment, this study investigates the mechanical degradation, microstructural evolution, and engineering implications of gypsum rock. Laboratory mechanical tests, X-ray diffraction analysis, thin-section observations, and deterioration-index analysis were conducted to establish the relationship between time-dependent strength attenuation and microstructural damage. The results show that gypsum rock exhibits rapid strength and stiffness degradation after immersion. The uniaxial compressive strength (UCS) retention ratio decreased from 1.00 to 0.63 after 7 days and further to 0.26 after 35 days, while the elastic modulus retention ratio decreased to 0.33 after 35 days. The deterioration process can be divided into three stages: rapid softening, pore–fissure development, and structural fragmentation. Microscopically, gypsum dissolution, cement loss, pore enlargement, fissure propagation, and weakening of intercrystalline bonding progressively damage the rock fabric. Macroscopically, these processes are manifested as mass loss, surface dissolution, volume reduction, stiffness attenuation, strength reduction, and a brittle-to-plastic transition in failure mode. The results indicate that dry-state mechanical parameters may overestimate the stability of gypsum-bearing rock masses under groundwater disturbance. Water-degraded mechanical parameters, groundwater chemistry monitoring, drainage control, waterproofing, grouting reinforcement, and anti-corrosion measures should be considered in engineering construction in gypsum-bearing red-bed areas.

Subalpine meadow soil is widespread in the steep valleys of the eastern Tibetan Plateau. Owing to its unique structure and climatic conditions, rainfall can trigger extensive ecohydrological disaster, characterized by soil disintegration and shallow landsliding. This phenomenon leads to significant soil erosion and degradation of meadow ecosystems, highlighting the ecological vulnerability of the region. Field investigations have identified porewater pressure from infiltrated rainwater and gravitational pressure on saturated meadow soil as the primary drivers of the landsliding. Building on this understanding, efforts were made to assess the risk of subalpine meadow soil erosion induced by extreme rainfall near Xinduqiao County using the TRIGRS model and the coupled TRIGRS-TOPMODEL (TOP-TRIGRS). Validation of the simulated results against observed erosion events revealed that TOP-TRIGRS tends to predict unstable areas more accurately, particularly in the lower to mid-sections of slopes with gentler gradients, in line with theoretical models of shallow landslide. Specifically, while TRIGRS identified 50.31% of actual shallow landslides, TOP-TRIGRS reached 80.35%. Moreover, the AUC values for TRIGRS and TOP-TRIGRS were 0.787 and 0.896, respectively, indicating the superior predictive performance of TOP-TRIGRS. Accurate prediction of shallow landslides in subalpine meadow soil is vital for informing ecological management regulations and advancing soil and water conservation efforts in the eastern Tibetan Plateau.