Traditional materials such as fly ash and lime are generally used to improve soils but can severely pollute the environment. Eco-friendly protocols, such as the application of xanthan gum, are therefore essential for soil treatment. In this study, a series of microscopic tests, water retention characteristics tests, and shear tests were carried out on silt, which are known to have poor engineering properties, to explore the effect and mechanism of xanthan gum treatment on the water retention and shear strength characteristics of silt during the wetting process. The results show that the water retention capacity of the treated silt increases with increasing xanthan gum content, and a hysteresis effect is clearly observed. The cohesion and internal friction angle of the silt strongly decrease with increasing water content, and the strength significantly weakens. However, the strength of the silt treated with xanthan gum is consistently higher than that of the untreated silt. The microscopic tests show that soil pores are gradually filled by xanthan gum with good water-retaining properties, thus significantly enhancing the water retention capacity. Furthermore, the hydrogel that cements the soil particles forms by the bonding effects between xanthan gum and soil particles, which greatly improves the silt strength.

The dynamics parameters cause sudden change during the damage of the structural plane of landslide perilous rocks, and these can be easily accessed. Therefore the changes in dynamics parameters can effectively achieve early identification, stability evaluation, and monitoring and pre-alarming of the perilous rocks. Seven kinds of dynamic indexes, such as pulse indicator, margin index, the center of gravity frequency, root mean square frequency, impact energy, relative energy of the first frequency band, and damping ratio, are introduced and the early identification of landslide perilous rock is achieved based on the support vector machines (SVM) model, improved by particle swarm optimization algorithm. A laser vibrometer collected seven dynamic indexes of two rock masses on the reservoir bank slope in Baihebao Reservoir, China. Based on the particle group optimization algorithm optimization support vector (PSO–SVM) perilous rocks recognition model, and seven dynamic indicators, the stability of two rock masses was recognized with high efficiency and accuracy. The identification results were consistent with the landslide perilous rock identification results based on natural vibration frequency, and the results verify the accuracy of the PSO–SVM perilous rocks identification model. The results show that the sensitivity order of each identification index is: root mean square frequency > margin index > relative energy of the first frequency band > center of gravity frequency > impact energy > pulse indicator > damping ratio. The accuracy of the multi-dynamics parameters landslide perilous rock mass identification model can be improved by selecting appropriate dynamic indexes with good sensitivity. The research results have high theoretical significance and application value for early identification of landslide perilous rocks, stability evaluation, and safety monitoring, and early warning.

This study addresses the key scientific problem of urban safety in complex, hazard-inducing geological environments by focusing on representative towns in the Three Gorges Reservoir area. Through the integrated use of field investigations, numerical simulations, and multivariate statistical analysis, we developed a comprehensive model for assessing geological safety risk in reservoir-area towns. A four-tier deep safety evaluation system was constructed for two types of hazard-inducing geological environments, and a classification scheme for shallow susceptibility was proposed. On this basis, a five-tier integrated urban geological safety risk evaluation model was established that combines deep safety level, engineering sensitivity, shallow susceptibility, and prevention difficulty. The model exhibited strong performance (pseudo R² ≥ 0.914, p < 0.001) and indicates that risk is predominantly moderate (Grade III), with 85.7% of the 21 representative areas in Wushan, Fengjie, and other “2 + 4” towns falling into this category. Overall, the results provide an operational tool to support disaster risk reduction, risk-informed land-use governance, and resilient infrastructure planning, thereby contributing to sustainable urban development in reservoir-side mountainous regions.

Loess landslides represent a severe geohazard in the Loess Plateau, posing significant challenges to sustainable development and regional safety. This study analyzed 111 landslides (1976–2018) and 529 marginal fissures in the South Jingyang Tableland (SJT) to reveal the distribution and failure modes of the landslide cluster. Preparation factors, including stratigraphic lithology, geomorphic features, and discontinuity systems (vertical/tectonic joints, unloading fissures, weak layers, and marginal fissures), were evaluated alongside triggering factors such as precipitation, irrigation, and river erosion. The main takeaways of this study are as follows. (1) A comprehensive database of 111 loess landslides (1976–2018) and 529 marginal fissures was constructed for the SJT, representing the longest and most complete chronological record available for this region. (2) Landslide activity within the Jiangliu landslide cluster (LC) exhibits an approximately decadal clustering pattern, with a temporal spacing of 9.6 ± 2.8 years between successive active periods, providing a basis for medium-term hazard forecasting in comparable settings. (3) The evolution of marginal fissures is controlled by the margin’s geometry and their interaction with slope failure processes, and the strong correlation between fissure development and landslide initiation enables the use of fissure monitoring as an early warning indicator. (4) The evolutionary mechanism follows a sequence of initial tectonic activity → rising groundwater → formation of the critical slide structure → water accumulation in fissures → single landslide → subsequent clustering. This process, termed a “water-induced loess catastrophe” (WILC), provides a conceptual framework for understanding landslide clustering on loess tablelands. (5) The database construction methodology, the decadal clustering analysis, and the WILC model collectively offer transferable tools for medium-term hazard forecasting, fissure-based early warning, and sustainable land-use planning on loess tablelands, not only in the SJT, but also in other loess regions with similar geological and hydrological settings.

To investigate the characteristics of the in-situ stress field in the lower rock mass of underground gas storage caverns at the Zhumadian compressed air energy storage (CAES) power station, and to predict the risk level of rockburst in the caverns for ensuring geological safety, a series of studies were conducted. Firstly, hydraulic fracturing in-situ stress tests were carried out in the lower rock mass of the CAES power station to obtain the basic data of the in-situ stress field in the storage cavern area. Subsequently, indoor rock mechanics tests were conducted on the core samples from the corresponding test sections of the stress measurement boreholes to determine the saturated uniaxial compressive strength of the rocks. Finally, the rockburst risk level in the caverns was predicted using the rock strength-to-stress ratio. The results indicate the following: (1) The measured in-situ stress in the underground gas storage caverns is at a low-to-medium level, with the maximum horizontal principal stress (S_H) ranging from 4.48 to 9.61 MPa and the minimum horizontal principal stress (S_h) from 3.15 to 5.79 MPa. Within the measured depth range, both the maximum and minimum principal stresses exhibit a linear relationship with burial depth, increasing as the depth increases. (2) The orientation of the measured maximum horizontal principal stress is NE-SW (N43.3° E), which is generally consistent with the regional principal stress direction. The coefficient of the maximum horizontal principal stress in the rock mass of the underground storage caverns ranges from 1.12 to 1.62, while that of the minimum horizontal principal stress ranges from 0.79 to 0.97. The horizontal stress coefficient within the measured depth ranges from 1.29 to 1.68, indicating a strike-slip faulting stress regime. (3) The tensile strength (T) of the rocks obtained from hydraulic fracturing tests ranges from 1.72 to 11.97 MPa, with an average value of 4.71 MPa. The overall tensile strength of the rocks is relatively high, which is generally consistent with the values obtained from the indoor rock mechanics tests. (4) Through a point-by-point analysis of rockburst risk during tunnel excavation, the surrounding rock at a burial depth (H) of 187.20 m is classified as having a slight rockburst susceptibility, while no rockburst is expected at other test points. (5) These research findings provide a scientific basis for the design and construction of the underground energy storage caverns at this CAES power station, and also fill the gap in the measured in-situ stress data for this region.