The constitutive model is essential for predicting the deformation and stability of rock-soil mass. The estimation of constitutive model parameters is a necessary and important task for the reliable characterization of mechanical behaviors. However, constitutive model parameters cannot be evaluated accurately with a limited amount of test data, resulting in uncertainty in the prediction of stress-strain curves. This paper proposes a Bayesian analysis framework to address this issue. It combines the Bayesian updating with the structural reliability and adaptive conditional sampling methods to assess the equation parameter of constitutive models. Based on the triaxial and ring shear tests on shear zone soils from the Huangtupo landslide, a statistical damage constitutive model and a critical state hypoplastic constitutive model were used to demonstrate the effectiveness of the proposed framework. Moreover, the parameter uncertainty effects of the damage constitutive model on landslide stability were investigated. Results show that reasonable assessments of the constitutive model parameter can be well realized. The variability of stress-strain curves is strongly related to the model prediction performance. The estimation uncertainty of constitutive model parameters should not be ignored for the landslide stability calculation. Our study provides a reference for uncertainty analysis and parameter assessment of the constitutive model.

This study conducted an in-depth analysis of the landslide problem in the loess hill and gully area in northern Shaanxi Province, selecting the loess landslide site in Quchaigou, Ganquan County, Yan'an City, as the object to assess the stability of loess slopes under the conditions of different plant root densities and soil moisture contents through field investigation, physical mechanics experiments and numerical simulation of the GeoStudio model. Periploca sepium, a dominant species in the plant community, was selected to simulate the stability of loess slope soils under different root densities and soil water contents. The analysis showed that the stability coefficient of Periploca sepium natural soil root density was 1.263, which was a stable condition, but the stability of the stabilized slopes decreased with the increase in soil root density. Under the condition of 10% soil moisture content, the stability coefficient of the slope body is 1.136, which is a basic stable state, but with the increase in soil moisture content, the stability of the stable slope body decreases clearly. The results show that rainfall and human activities are the main triggering factors for loess landslides, and the vegetation root system has a dual role in landslide stability: on the one hand, it increases the soil shear strength, and on the other hand, it may promote water infiltration and reduce the shear strength. In addition, the high water-holding capacity and permeability anisotropy of loess may lead to a rapid increase in soil deadweight under rainfall conditions, increasing the risk of landslides. The results of this study are of great significance for disaster prevention and mitigation and regional planning and construction, and they also provide a reference for landslide studies in similar geological environments.

The stability of loess landslides affects the production and livelihood of the people in its vicinity. The stability of loess landslides is influenced by various factors, including internal structure, collapsibility, water content, and shear strength. The landslide stability of loesses can be analyzed by several geophysical methods, such as seismic refraction tomography (SRT), electrical resistivity tomography (ERT), micro-seismic technology, and ground penetrating radar (GPR). Geotechnical tests (compression and shear tests) and remote sensing techniques (Global Navigation Satellite System (GNSS), Interferometric Synthetic Aperture Radar (InSAR) and airborne 3D laser technology) are used for studying the landslide stability of loesses as well. Some of the methods above can measure parameters (e.g., fractures, water content, shear strength, creep) which influence the stability of loess landslides, while other methods qualitatively indicate the influencing factors. Integrating parameters measured by different methods, minimizing disturbances to landslides, and assessing landslide stability are important steps in studying landslide hazards. This paper comprehensively introduces the methods used in recent studies on the landslide stability of loesses and summarizes the factors which affect the landslide stability. Furthermore, the relationships between different parameters and methods are examined. This paper enhances comprehension of the underlying mechanisms of the stability of loess landslides to diminish disastrous consequences.

It is beneficial for disaster prevention and mitigation to use a numerical model to evaluate landslide stability. The Sifangbei landslide, located in the Three Gorges Reservoir Area (TGRA), is sliding slowly under the action of reservoir water. Due to the lack of early technology and funds, the depiction of the longitudinal profile and stability analysis of the landslide are very limited. In this study, the longitudinal profile of the main sliding direction was corrected from the original version of the ground model using field investigation, drilling, in situ monitoring, and geophysical observation. Then, through the establishment of numerical models, the landslide model based on the original profile is used as a reference to re-study its deformation characteristics and stability analysis. The results are as follows: The displacement response of the new model is closer to the real deformation record of the landslide. The deformation of the landslide body in the rear and front edge is significant, even during periods of low rainfall in the reservoir storage season. According to the hydraulic mechanism, the stability changes of the two models under the influence of RWL show that there is a stronger buoyancy force of the soil mass in the front resisting after the profile of the model is modified. The above conclusions indicate that the Sifangbei landslide is not a typical seepage-driven landslide, and its prevention and control should be updated in time. This study also provides a case for the same type of landslide and the relationship between the landslide deformation and the sliding surface shape.

Landslides are one of the most common geological natural hazards worldwide. This study considered a landslide that occurred on August 13, 2022 at Baotou General Industrial Park, Inner Mongolia. Through dynamic penetration and laboratory tests, the physical and mechanical properties of the landslide area were obtained. Asperity theory can be applied to this matter as we deal mostly with an interfacial landslide. In the process of analyzing the mechanism of landslide, we focus on the distribution of asperity in the sliding interface. Through the analysis of routine laboratory test data, it was found that the physico-mechanical properties present small variations between the sampling sites on the sliding interface, and the positions of asperities could not be determined. The dynamic penetration test revealed that the penetration times at different sites on the sliding interface were different, indicating that different parts of the asperity had different strengths. The general range of asperities in the sliding interface was determined by this means. According to the test data and field conditions, a three-dimensional landslide was obtained. F-s = Sigma(i)(1)tau piSaiKai/tau(g)-(tau) over bar S-gamma. The formula considers an asperity with different strengths contained in the landslide interface and explains that the process of progressive sliding of the slope occurs through the sequential destruction of many asperities. In this study, asperity theory and engineering applications were combined through the use of a dynamic penetration test, enabling the key positions where engineering protection and monitoring were required to be preliminarily identified.