With the onset of global warming, the environment has profoundly changed. The melting of ice and slope instability were widely observed in the permafrost regions of the Qinghai–Tibet Plateau, which has destroyed infrastructure and threatened people’s safety. For this study, we conducted a direct shear test, monitored field temperature, and performed a numerical simulation to explore the mechanism of slope instability in the permafrost regions of the Qinghai. The results show that the shear strength of the permafrost soil decreased with the increases in water content and thawing condition. Moreover, the thawing depth of the slopes increased with the rising temperature. From the temperature monitoring data and field observations, cracks and slope instability phenomena were observed in the Qinghai and occurred with the thawing of the permafrost soil. The safety of slopes in the permafrost regions decreased with increases in the temperature, slope gradient, and pore water pressure and with decreases in the shear strength parameters. In addition, the sliding interface had a direct correlation with the freeze–thaw interface, which is a migrated interface of water in liquid form. Therefore, the thawing of the permafrost soil causes the shear strength to decrease and pore water pressure to increase, which leads to slope instability in the permafrost regions of the Qinghai.

The geological structure of the upper reaches of the Yellow River is complex, especially in the Sigouxia-Laganxia section. It has always been a high-incidence area of landslide disasters, which poses a threat to the safe operation of the upper reaches of the Yellow River. In this study, based on the high-precision remote sensing image data, the spatial distribution of each landslide was obtained by superimposing the remote sensing image and the 1:50,000 digital elevation model (DEM). Some typical landslides were selected for detailed field investigation and field verification. The results show that the remote sensing image characteristics of landslides in the upper reaches of the Yellow River are obvious. Through remote sensing interpretation and field investigation, a total of 508 landslides of various types were found, including 24 giant landslides. The spatial spreading patterns of landslides mainly include six types: dumb-bell shape, rectangle, saddle type, long arc shape, triangle, and side-by-side shape. The length and width of the landslide deposit are mainly concentrated at 550–1500 m and 600–1500 m, and the average elevation of the sliding body is mainly concentrated between 2000 and 2800 m. The average slope of the landslide is mainly distributed between 15–20°. Giant landslides are mainly distributed in the Jianzha basin area, surrounded by the Jishishan fault and the Lajishan fault in the West Qinling Mountains. The spatial distribution characteristics of giant landslides have obvious regional differences due to different factors such as lithologic differences and riverside erosion. The research results are of great significance for the early identification, prevention, and mitigation of landslide disasters in the upper reaches of the Yellow River.

Slope instability may cause severe casualties, property losses, and ecological damage. To accurately evaluate slope stability grades and mitigate geological hazards, a dynamic stability assessment method based on variable weight theory and trapezoidal cloud model is proposed. First, an evaluation index system for slope stability is established following the principles of uniqueness, purposefulness, and scientific validity. Then, to improve the accuracy of subjective constant weights, the intuitionistic fuzzy analytic hierarchy process (IFAHP) is employed to calculate subjective constant weights. Considering the contrast intensity and conflict among indicators, an improved CRITIC method is applied to determine objective constant weights. To balance subjective and objective factors and avoid constant weight imbalance, the optimal comprehensive constant weights are computed based on game theory, effectively reducing bias caused by single weighting methods. Furthermore, to fully account for the influence of indicator state values on their weights, variable weight theory is introduced to dynamically adjust the comprehensive constant weights. Finally, based on the variable weights of evaluation indicators, a trapezoidal cloud model is utilized to construct the slope stability evaluation model, which is validated through an engineering case study. The results indicate that the stability grade of Stage 1 is assessed as basically stable, while Stages 2 and 3 are evaluated as stable. Numerical simulations show the safety factors of the three stages are 1.36, 1.83, and 2.36, respectively, verifying the correctness of the proposed model. The proposed model demonstrates practical engineering value in slope stability assessment and can be referenced for slope reinforcement and hazard prevention in later stages.

In recent years, large-scale linear infrastructure developments have been developed across hundreds of kilometers of permafrost regions on the Qinghai–Tibet Plateau. The implementation of major engineering projects, including the Qinghai–Tibet Highway, oil pipelines, communication cables, and the Qinghai–Tibet Railway, has spurred intensified research into permafrost dynamics. Climate warming has accelerated permafrost degradation, leading to a range of geological hazards, most notably widespread thermokarst landslides. This study investigates the spatiotemporal distribution patterns and influencing factors of thermokarst landslides in Qinghai Province through an integrated approach combining field surveys, remote sensing interpretation, and statistical analysis. The study utilized multi-source datasets, including Landsat-8 imagery, Google Earth, GF-1, and ZY-3 satellite data, supplemented by meteorological records and geospatial information. The remote sensing interpretation identified 1208 cryogenic hazards in Qinghai’s permafrost regions, comprising 273 coarse-grained soil landslides, 346 fine-grained soil landslides, 146 thermokarst slope failures, 440 gelifluction flows, and 3 frost mounds. Spatial analysis revealed clusters of hazards in Zhiduo, Qilian, and Qumalai counties, with the Yangtze River Basin and Qilian Mountains showing the highest hazard density. Most hazards occur in seasonally frozen ground areas (3500–3900 m and 4300–4900 m elevation ranges), predominantly on north and northwest-facing slopes with gradients of 10–20°. Notably, hazard frequency decreases with increasing permafrost stability. These findings provide critical insights for the sustainable development of cold-region infrastructure, environmental protection, and hazard mitigation strategies in alpine engineering projects.

Debris flow in the upper Yellow River is very developed and is generally characterized by wide distribution with large numbers and a high frequency of occurrence. This paper analyses the distribution characteristics, material composition, and formation causes of the Erlian debris flow fan in the eastern part of the Guide Basin and discusses the relationship between debris flow fan and river evolution. Results show that: (1) At least 66 debris flow gullies and 20 large debris flow accumulation fans have been developed on both sides of the Yellow River in the eastern Guide Basin. (2) In the Erlian Village area, the Yellow River channel has experienced the accumulation, erosion, destruction, and accumulation process of debris flow fans in 16 kaB.P., 16 ka B.P.–8 ka B.P., and 8 kaB.P., respectively, the late-accumulation fan has been continuously extruding the Yellow River channel since 8 kaB.P., and the Yellow River channel has been shifted to the south by at least 1.25 km during the period of 8 ka. (3) Five accumulation periods for the Late Mudslide Fan were identified by classifying the 16 kaB.P. and 8 kaB.P. early and late mudslide fans. This study can provide theoretical and technical support for preventing debris flow disasters in the upper reaches of the Yellow River and has certain reference and reference values.