Geohazards such as slope failures and retaining wall collapses have been observed during thawing season, typically in early spring. These geohazards are often attributed to changes in the engineering properties of soil through changes in soil phase with moisture condition. This study investigates the impact of freezing and thawing on soil stiffness by addressing shear wave velocity (Vs) and compressional wave velocity (Vp). An experimental testing program with a temperature control system for freezing and thawing was prepared, and a series of bender and piezo disk element tests were conducted. The changes in Vs and Vp were evaluated across different phases: unfrozen to frozen; frozen to thawed; and unfrozen to thawed. Results indicated different patterns of changes in Vs and Vp during these transitions. Vs showed an 8% to 19% decrease for fully saturated soil after thawing, suggesting higher vulnerability to shear failure-related geohazards in thawing condition. Vp showed no notable change after thawing compared to initial unfrozen condition. Based on the test results in this study, correlation models for Vs and Vp with changes in soil phase of unfrozen, frozen, and thawed conditions were established. From computed tomography (CT) image analysis, it was shown that the decrease in Vs was attributed to changes in bulk volume and microscopic soil structure.

Different slope geohazards have different causal mechanisms. This study aims to propose a method to investigate the decision-making mechanisms for the susceptibility of different slope geohazards. The study includes a geospatial dataset consisting of 1203 historical slope geohazard units, including slope creeps, shallow slides, rockfalls and debris flows, and 584 non-geohazard units, and 22 initial condition factors. Following a 7:3 ratio, the data were randomly divided into a test set and a training set, and an ensemble SMOTE-RF-SHAP model was constructed. The performance and generalization ability of the model were evaluated by confusion matrix and the receiver operating characteristic (ROC) for the four types of geohazards. The decision-making mechanism of different geohazards was then identified and investigated using the Shapley additive explanations (SHAP) model. The results show that the hybrid optimization improves the overall accuracy of the model from 0.486 to 0.831, with significant improvements in the prediction accuracy for all four types of slope geohazards, as well as reductions in misclassification and omission rates. Furthermore, this study reveals that the main influencing factors and spatiotemporal distribution of different slope geohazards exhibit high similarity, while the impacts of individual factors and different factor values on different slope geohazards demonstrate significant differences. For example, prolonged continuous rainfall can erode rock masses and lead to slope creep, increased rainfall may trigger shallow mountain landslides, and sudden surface runoff can even cause debris flows. These findings have important practical implications for slope geohazards risk management. (c) 2025 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/).

Hydrologically-induced landslides are ubiquitous natural hazards in the Himalayas, posing severe threat to human life and infrastructure. Yet, landslide assessment in the Himalayas is extremely challenging partly due to complex and drastically changing climate conditions. Here we establish a mechanistic hydromechanical landslide modeling framework that incorporates the impacts of key water fluxes and stocks on landslide triggering and risk evolution in mountain systems, accounting for potential climate change conditions for the period 1991-2100. In the drainage basin of the largest river in the northern Himalayas- the Yarlung Zangbo River Basin (YZRB), we estimate that rainfall, glacier/snow melt and permafrost thaw contribute similar to 38.4%, 28.8%, and 32.8% to landslides, respectively, for the period 1991-2019. Future climate change will likely exacerbate landslide triggering primarily due to increasing rainfall, whereas the contribution of glacier/snow melt decreases owing to deglaciation and snow cover loss. The total Gross Domestic Productivity risk is projected to increase continuously throughout the 21st century, while the risk to population shows a general declining trend. The results yield novel insights into the climatic controls on landslide evolution and provide useful guidance for disaster risk management and resilience building under future climate change in the Himalayas.

Forecasting landslide deformation is challenging due to influence of various internal and external factors on the occurrence of systemic and localized heterogeneities. Despite the potential to improve landslide predictability, deep learning has yet to be sufficiently explored for complex deformation patterns associated with landslides and is inherently opaque. Herein, we developed a holistic landslide deformation forecasting method that considers spatiotemporal correlations of landslide deformation by integrating domain knowledge into interpretable deep learning. By spatially capturing the interconnections between multiple deformations from different observation points, our method contributes to the understanding and forecasting of landslide systematic behavior. By integrating specific domain knowledge relevant to each observation point and merging internal properties with external variables, the local heterogeneity is considered in our method, identifying deformation temporal patterns in different landslide zones. Case studies involving reservoir-induced landslides and creeping landslides demonstrated that our approach (1) enhances the accuracy of landslide deformation forecasting, (2) identifies significant contributing factors and their influence on spatiotemporal deformation characteristics, and (3) demonstrates how identifying these factors and patterns facilitates landslide forecasting. Our research offers a promising and pragmatic pathway toward a deeper understanding and forecasting of complex landslide behaviors. (c) 2025 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/).

Disintegration fragments the loess body, causing erosion and the emergence of significant geohazards. The impact of vibrations on soil disintegration has been slightly documented; however, the contribution and mechanism of train vibration frequency in the disintegration of undisturbed loess remain unclear. In this study, train vibrations were monitored in situ, and the resulting vibrational parameters were used in loess disintegration tests using a customised vibration-disintegration apparatus. The changes in the meso-parameters of the disintegrated loess and aqueous solutions were quantified, and the microstructural differences in the residual loess after disintegration were compared under non-vibrating and vibrating conditions. The results revealed that train vibrations in the loess progressively diminished with increasing distance from the track, with dominant vibration frequencies ranging from 17 to 49 Hz. Increasing the vibration frequency accelerated loess disintegration and enhanced the dispersion of the disintegrated fragments. Notably, the acceleration effect of disintegration was particularly pronounced in the early stages of increasing vibration frequency, and it tended to plateau above 15 Hz. The relationship between the vibration frequency and disintegration velocity (DV) of loess influenced by the initial water content can be expressed as a power function with variables. Vibrations accelerate loess disintegration primarily attributed to repetitive particle displacement and the vibrations of free water in the pores which lead to frictional damage to the weakly cemented structure and pore expansion. Higher vibration frequencies generate greater inertial forces and facilitate more frequent particle jumps, allowing the loess to reach the disintegration threshold conditions more readily than at lower frequencies. These findings provide theoretical value for the prevention and mitigation of water-induced loess geohazards and land degradation in vibrating environments.

Purpose. This paper aims to establish a robust soil treatment plan designed to enhance the geotechnical engineering properties of tailings. The study evaluates the efficacy of various soil additives, including both traditional and non-traditional types, in reinforcing tailings dam materials. Methods. A comprehensive experimental program was conducted, where polymeric resin and a combination of recycled gypsum (B), cement kiln dust (CKD), and ordinary cement (OC) were added to tailings in a controlled laboratory setting. The assessment methodology included unconfined compressive strength (UCS) tests to determine the optimal treatment percentage, Oedometer tests to evaluate stiffness and consolidation properties, and direct shear strength tests to assess the material's response to shearing. Findings. The study provides valuable insights into the performance of the CKD:B compound, revealing a critical OC percentage that must be maintained to prevent sample dissolution in water due to anhydrate presence. The tailings treated exhibit improved mechanical properties, contributing essential data that can support numerical modeling for assessing the stability of tailings dams. Originality. This research offers novel data on tailings treatment, particularly regarding the combination of CKD and B with OC. The study's findings advance understanding in the field by identifying the optimal conditions for enhancing tailings dam stability, which has not been extensively explored in previous literature. Practical implications. The results of this study contribute to improved tailings storage facility management and environmental best practices. By optimizing soil treatment strategies, the research supports more effective utilization of natural resources and enhances the safety and sustainability of tailings dam structures.

Due to favorable natural conditions and human impact, the territory of North Macedonia is very susceptible to natural hazards. Steep hillslopes combined with soft rocks (schists on the mountains; sands and sandstones in depressions), erodible soils, semiarid continental climate, and sparse vegetation cover give a high potential for soil erosion and landslides. For this reason, this study presents a multi-hazard approach to geohazard modeling on the national extent in the example of North Macedonia. Utilizing Geographic Information Systems, relevant data about the entire research area were employed to analyze and assess soil erosion and susceptibility to landslides and identify areas prone to both hazards. Using the Gavrilovi & cacute; Erosion Potential Method (EPM), an average value of 0.36 was obtained for the erosion coefficient Z, indicating low to moderate susceptibility to erosion. However, a significant area of the country (9.6%) is susceptible to high and excess erosion rates. For the landslide susceptibility assessment (LSA), the Analytical hierarchy process approach is combined with the statistical method (frequency ratio), showing that 29.3% of the territory belongs to the zone of high and very high landslide susceptibility. Then, the accuracy assessment is performed for both procedures (EPM and LSA), showing acceptable reliability. By overlapping both models, a multi-hazard map is prepared, indicating that 22.3% of North Macedonia territory is highly susceptible to erosion and landslides. The primary objective of multi-hazard modeling is to identify and delineate hazardous areas, thereby aiding in activities to reduce the hazards and mitigate future damage. This becomes particularly significant when considering the impact of climate change, which is associated with increased landslide and erosion susceptibility. The approach based on a national level presented in this work can provide valuable information for regional planning and decision-making processes.

Mountains are highly diverse in areal extent, geological and climatic context, ecosystems and human activity. As such, mountain environments worldwide are particularly sensitive to the effects of anthropogenic climate change (global warming) as a result of their unique heat balance properties and the presence of climatically-sensitive snow, ice, permafrost and ecosystems. Consequently, mountain systems-in particular cryospheric ones-are currently undergoing unprecedented changes in the Anthropocene. This study identifies and discusses four of the major properties of mountains upon which anthropogenic climate change can impact, and indeed is already doing so. These properties are: the changing mountain cryosphere of glaciers and permafrost; mountain hazards and risk; mountain ecosystems and their services; and mountain communities and infrastructure. It is notable that changes in these different mountain properties do not follow a predictable trajectory of evolution in response to anthropogenic climate change. This demonstrates that different elements of mountain systems exhibit different sensitivities to forcing. The interconnections between these different properties highlight that mountains should be considered as integrated biophysical systems, of which human activity is part. Interrelationships between these mountain properties are discussed through a model of mountain socio-biophysical systems, which provides a framework for examining climate impacts and vulnerabilities. Managing the risks associated with ongoing climate change in mountains requires an integrated approach to climate change impacts monitoring and management.

Climate change increases the risk of severe alterations to essential wildlife habitats. The Arctic fox (Vulpes lagopus (Linnaeus, 1758)) uses dens as shelters against cold temperatures and predators. These dens, needed for successful reproduction, are generally dug into the active layer on top of permafrost and reused across multiple generations. We assessed the vulnerability of Arctic fox dens to the increasing frequency of geohazards (thaw settlement, mass movements, and thermal erosion) that is arising from climate change. On Bylot Island (Nunavut, Canada) we developed, and calculated from field observations, a qualitative vulnerability index to geohazards for Arctic fox dens. Of the 106 dens studied, 14% were classified as highly vulnerable, whereas 17% and 69% had a moderate and low vulnerability, respectively. Vulnerability was not related to the probability of use for repro- duction. Although climate change will likely impact Arctic fox reproductive dens, such impact is not a major threat to foxes of Bylot Island. Our research provides the first insights into the climate-related geohazards potentially affecting Arctic fox ecology in the next decades. The developed method is flexible and could be applied to other locations or other species that complete their life cycle in permafrost regions.

The subsurface structure of permafrost is of high significance to forecast landscape dynamics and the engineering stability of infrastructure under human impacts and climate warming, which is a modern challenge for Arctic communities. Application of the non-destructive method of geo-penetrating radar (GPR) survey is a promising way to study it. The study program, which could be used for planning and monitoring of measures of adaptation of Arctic communities to environmental changes is provided in this paper. The main principle was to use etalons of coupled radargrams and archive geological data to interpret changes in the permafrost structure from a grid of 5-10 m deep GPR transects. Here, we show the application of GPR to reconstruct and predict hazards of activation of cryogenic processes from the spatial variability in the structure of permafrost. The cumulative effects of the village and climate change on permafrost were manifested in changes in the active layer thickness from 0.5-1.0 m to up to 3.5 m. Despite that the permafrost degradation has declined due to the improved maintenance of infrastructure and the effects of ground filling application, the hazards of heaving and thermokarst remain for the built-up area in Lorino.