Shallow landslides are often unpredictable and seriously threaten surrounding infrastructure and the ecological environment. Traditional landslide prediction methods are time-consuming, labor-intensive, and inaccurate. Thus, there is an urgent need to enhance predictive techniques. To accurately predict the runout distance of shallow landslides, this study focuses on a shallow soil landslide in Tongnan District, Chongqing Municipality. We employ a genetic algorithm (GA) to identify the most hazardous sliding surface through multi-iteration optimization. We discretize the landslide body into slice units using the dynamic slicing method (DSM) to estimate the runout distance. The model's effectiveness is evaluated based on the relative errors between predicted and actual values, exploring the effects of soil moisture content and slice number on the kinematic model. The results show that under saturated soil conditions, the GA-identified hazardous sliding surface closely matches the actual surface, with a stability coefficient of 0.9888. As the number of slices increases, velocity fluctuations within the slices become more evident. With 100 slices, the predicted movement time of the Tongnan landslide is 12 s, and the runout distance is 5.91 m, with a relative error of about 7.45%, indicating the model's reliability. The GA-DSM method proposed in this study improves the accuracy of landslide runout prediction. It supports the setting of appropriate safety distances and the implementation of preventive engineering measures, such as the construction of retaining walls or drainage systems, to minimize the damage caused by landslides. Moreover, the method provides a comprehensive technical framework for monitoring and early warning of similar geological hazards. It can be extended and optimized for all types of landslides under different terrain and geological conditions. It also promotes landslide prediction theory, which is of high application value and significance for practical use.

Deep excavated expansive soil slopes are influenced by multiple factors, including precipitation, groundwater, geological structure, and support measures, resulting in complex spatiotemporal heterogeneity in deformation. Using the slope of Taocha canal segment in the middle route of the South-to-North Water Diversion Project as a case study, the spatiotemporal deformation characteristics were analyzed. Data mining methods, including variational modal decomposition, weighted multiscale local outlier factor, and clustering analysis, were applied. The temporal variation of deformation was analyzed, and spatial distribution characteristics were identified. The influence mechanisms of factors such as precipitation and groundwater on the trend, periodic, and fluctuating components of deformation were explained. Deformation measuring points were clustered, and potential sliding surfaces and sliding bodies were speculated. The deformation mechanism was discussed, and reinforcement measures were proposed. The results indicate that slope deformation exhibits significant trend changes, as well as seasonal and intermittent fluctuations. Deformation in the lower part is relatively large and gradually decreases upwards. The depth of the significant deformation in the upper part is 3 m, located within the climate-influenced layer. Deformation in the central part is influenced by groundwater fluctuation and dense fissure zones, with a significant deformation depth of up to 11 m. Deformation in the lower part is limited by the retaining system and occurs only in the shallow layer. Perched water in the upper part is replenished by rainwater, causing large fluctuation depths and resulting in deep deformation in the middle and upper parts, and there is a certain degree of deformation within the depth of 16.5 m. The potential sliding surface is a polyline. Due to the influence of groundwater, densely fissure zones, and retaining system, the leading edge is approximately horizontal. Drainage wells should be installed to drain groundwater to reduce the impact of groundwater fluctuations on the swelling-shrinkage deformation of expansive soil. The research results can provide technical support for the operation management and reinforcement disposal of deep excavated expansive soil slopes.

This paper presents the findings of a series of shaking table tests conducted to investigate the seismic damage and dynamic characteristics of a tunnel crossing a sliding surface system. An evaluation methodology is introduced to assess the model's boundary effects and dynamic characteristics. In this study, we propose a model soil failure mode assessment method based on Marginal Spectral Entropy (MSE) using Hilbert-Huang Transform (HHT) and information entropy parameters. Furthermore, a damage evaluation method for tunnel lining is presented, which utilizes the Hilbert Energy Spectrum (HES) and an Empirical Mode Decomposition (EMD) energy damage index. The results of the tests reveal that the MSE accurately reflects the slope failure process and provides insights into the depth of the sliding surface. The observed behavior of the model indicates a push-back shear slip type characterized by sinking, squeezing, pulling, and shearing. The HES analysis of the model soil indicates that the energy primarily concentrates in the frequency range of 0 to 25 Hz, expanding with elevation. Notably, the tunnel crossing the hauling sliding surface exhibits a more pronounced broadband effect in the model soil compared to the main sliding surface. The peak HES of the lining occurs after that of the model soil and is found to be 18.07 s. The damage index distribution correlates with the spatial position of the lining parts. When the damage index exceeds 90 %, it indicates the presence of significant damage to the specific parts of the lining, a finding that has been validated through post-seismic analysis. Furthermore, the EMD energy damage index, in conjunction with dynamic finite element simulation, demonstrates its potential for preliminarily determining the location and extent of lining damage through abrupt changes. The research findings contribute to the theoretical understanding of extracting damage features in tunnel-landslide models.

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.

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.