Search Results (262)

Increasing frequency and intensity of extreme precipitation events, together with altered soil saturation dynamics, have significantly increased the occurrence of shallow landslides. These processes are closely linked to climate change and increasingly affect mountainous and hilly regions worldwide, where rainfall-induced pore pressure variations and transient infiltration govern slope instability. Despite growing recognition of climate-driven slope failures, most conventional geomechanical analyses still rely on static assumptions and simplified boundary conditions, which are insufficient to capture the pronounced temporal variability of hydro-climatic forcing. To address this gap, this study introduces a conceptual and methodological framework for a proactive landslide cadaster, developed within the Climate Adaptive Resilience Evaluation (CARE) framework. Rather than serving as a static inventory of past events, the proposed cadaster functions as a structured, updatable repository of climate–geomechanical parameters that directly support advanced landslide analyses. The core innovation lies in the formalization of the climate–geomechanical interface, which enables the transformation of climatic and hydrological variables into parameters directly applicable in geomechanical modeling. These parameters encompass climatic, hydrological, geomechanical, and thermo-hydraulic processes and are assigned to spatially referenced locations, complemented by documented landslide occurrences. Their spatial distribution forms a network of reference points that allows interpolation, continuous updating, and reuse across multiple analyses. In this way, the cadaster becomes a proactive, process-based data infrastructure, serving as the foundational input for scenario-based landslide susceptibility, hazard, and risk assessments within the CARE analytical workflow. The conceptual framework is illustrated through an example from Slovenia, focusing on the Visole area near Maribor, where selected data types and workflow steps are presented for demonstration purposes. Full article

The Bayan Obo Mining District, recognized as the largest rare-earth resource base worldwide, has experienced significant surface instability due to intensive mining and large-scale dumping activities. To address the challenges posed by complex geological conditions and mining-induced disturbances, this study employs dual-ascending Sentinel-1A C-band Synthetic Aperture Radar (SAR) datasets (Path 11 and Path 113) and applies the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique to retrieve time-series deformation along the line-of-sight (LOS) direction for each track. Through temporal normalization and spatial matching, paired LOS observations from the two tracks were established. Based on the SAR observation geometry and under the assumption that the north–south component is negligible, a LOS projection model was constructed and a geometric decomposition was performed to derive the east–west and vertical two-dimensional deformation fields. The results indicate that the study area is generally stable, while significant subsidence occurs in the northern pit and adjacent waste-dump zones, with local maximum rates approaching 50 mm/year, predominantly controlled by the vertical component. The two-dimensional deformation analysis reveals that vertical displacement dominates surface motion, whereas east–west movement shows smaller amplitudes but clear directional concentration. In particular, the east–west slopes exhibit slightly higher velocities, suggesting a lateral adjustment tendency along this direction, likely related to the overall east–west geometric configuration of the open-pit and waste-dump areas. Time-series observations further reveal that precipitation-related surface deformation occurs with an approximate two-month delay, reflecting the hydrological–mechanical coupling processes of rainfall infiltration, pore-water pressure propagation, and dump-material consolidation. Overall, this study reveals the multi-dimensional deformation characteristics and precipitation-driven stage-wise response of the mining area, demonstrating the effectiveness of the dual-ascending SBAS-InSAR for two-dimensional deformation monitoring in highly disturbed environments, and providing a scientific basis for surface stability assessment and geohazard prevention. Full article

The Hulukou-Xiangbiling section of the Jinsha River is located in a typical high-mountain gorge area characterized by a complex geological environment, rendering it highly susceptible to landslide disasters. To reveal the deformation mechanisms of typical landslides in this region under hydrological effects, this study employed the Small Baseline Subset InSAR (SBAS-InSAR) technique to process multi-track Sentinel-1 SAR images acquired between 2021 and 2024. Long-term deformation time series were extracted for the Xiaxiaomidi and Chenjiatian landslides. On this basis, a systematic multi-scale coupling analysis of the deformation characteristics was conducted using trend-cycle decomposition, Continuous Wavelet Transform (CWT), Cross Wavelet Transform (XWT), and Wavelet Coherence (WTC). The results indicate that although the two landslides are located in the same river section, their deformation mechanisms and hydrological response patterns differ significantly. The deformation of the Xiaomidi landslide is mainly concentrated in the lower part of the slope, exhibiting a characteristic of continuous acceleration. The analysis demonstrates that the evolution of this landslide is primarily controlled by hydrodynamic processes such as toe unloading, water body erosion, and water level fluctuations. In contrast, the Chenjiatian landslide displays a distinct dominant cycle of 365 days, manifesting as a composite mode of long-term creep superimposed with seasonal acceleration. Its deformation shows a high correlation with rainfall (correlation coefficient > 0.9), with a lag effect of approximately 1 to 2 months. This reflects the dominant role of rainfall infiltration and pore pressure transfer in the landslide dynamics. Full article

Rainfall is recognised as one of the major external factors affecting the stability of retaining walls. The magnitude of rainfall directly influences the overall stability of retaining walls, while rainfall patterns alter the infiltration process and the saturation state of the soil, thereby affecting soil shear strength and retaining wall stability. In order to investigate the effects of rainfall pattern and intensity on the stability of reinforced soil gabion retaining walls, numerical simulations were carried out to examine wall stability under two typical rainfall patterns (uniform and intermittent) and three rainfall intensities (20 mm/d, 50 mm/d, and 80 mm/d). The results indicate that: (1) under uniform rainfall conditions, the extent of the soil pore water pressure response zone is greater than that under intermittent rainfall of the same intensity, and as the uniform rainfall intensity increases from 20 mm/d to 80 mm/d, the pore water pressure response zone expands by approximately four times; (2) the rainfall pattern exerts a certain influence on the distribution characteristics of the time-history curves of lateral displacement of the retaining wall, with the horizontal displacement under intermittent rainfall exhibiting a non-uniform growth pattern associated with the rainfall pattern; (3) uniform heavy rainfall has a more pronounced effect on the horizontal displacement of reinforced soil gabion retaining walls, with the maximum absolute horizontal displacement reaching approximately 12.89 mm; and (4) rainfall pattern affects the evolution of the slope stability coefficient, which gradually decreases and eventually stabilises under uniform rainfall, whereas under intermittent rainfall it shows a continuous decreasing trend characterised by alternating rates of reduction, with a greater reduction observed under uniform rainfall conditions. These findings elucidate the influence of different rainfall patterns and intensities on the displacement behaviour and stability of reinforced soil gabion retaining walls, and provide a reference for risk assessment of reinforced soil gabion retaining walls. Full article

Soil tillage practices play a key role in controlling soil’s physical properties, water infiltration, and runoff generation, particularly in erosion-prone cropping systems such as maize monocultures. The cultivation of wide-row crops is restricted on erosion-prone land; however, these crops constitute a fundamental basis for livestock feed and represent a key input raw material for biogas plants. This 4-year study evaluated the effects of three tillage practices—conventional ploughing, shallow tillage, and no tillage—on selected soil’s physical and chemical properties and on water infiltration processes in a maize (Zea mays L.) monoculture. Experimental maize stands were established in a field with a silty clay Luvic Chernozem. Field measurements were performed over multiple years and included soil bulk density, macroporosity, cone index, soil organic carbon, soil pH, soil aggregate stability, and water infiltration. Infiltration processes were assessed using a combination of double-ring infiltrometers, rainfall simulation, and dye tracer experiments to characterize water flow patterns under controlled conditions. The results demonstrated that soil tillage significantly influenced the vertical distribution of soil organic carbon and pH, soil aggregate stability, soil compaction, and pore characteristics, with the most pronounced differences observed in the upper soil layers. Soil aggregate stability in the 0–0.10 m layer showed a clear numerical trend, with the highest mean value under ST (0.42) compared with PL (0.28) and no tillage (NT) (0.26). Topsoil Cox was the highest under ST (3.591%) compared with PL (2.838%) and NT (2.634%). Differences among tillage practices were particularly evident during simulated rainfall events, affecting infiltration rates, runoff initiation, and preferential flow patterns. Ring infiltrometer measurements indicated higher infiltration in PL (e.g., 21.1 mm min⁻¹ at minute 1 in PL vs. 11.1/11.9 mm min⁻¹ in ST/NT; 10.9 mm min⁻¹ at minute 10 in PL vs. 5.3/7.6 mm min⁻¹ in ST/NT). However, rainfall simulation showed the highest runoff in PL, including the earliest runoff onset (4.5 min). Despite the soil’s high infiltration capacity due to low bulk density and higher porosity, the decisive factor promoting water infiltration into the soil is the condition of the soil surface, which is influenced by the stability of soil aggregates; this stability was enhanced by the input of organic matter from plant residues. The findings confirm that long-term soil tillage management substantially modifies soil hydraulic behaviour and highlight the importance of tillage system selection for improving soil water infiltration and reducing runoff risk in maize monoculture systems. Full article

Climate-driven extremes in temperature and precipitation are increasingly threatening the stability and serviceability of slopes, embankments, levees, transportation corridors, and other earthen infrastructures founded on expansive and problematic soils. Conventional stabilization strategies, which often treat reinforcement and drainage as separate design elements, struggle to cope with cyclic wetting-drying, freeze-thaw, and prolonged rainfall events that drive desiccation cracking, loss of matric suction, elevated pore-water pressures, and progressive strength degradation. This paper presents a state-of-the-art review of geosynthetic-reinforced slopes with particular emphasis on geogrid geotextile composite systems and their performance under high-temperature, high-rainfall, and low-temperature environments. We first summarize the fundamentals of geosynthetic types, functions, and material properties, then examine how thermal and hydrological processes such as creep, oxidation, frost heave, infiltration, suction loss, and pore-pressure build-up govern the performance of geosynthetic-reinforced soil (GRS) systems. Next, we synthesize recent advances in composite geosynthetics that integrate reinforcement, filtration, separation, and drainage, highlighting laboratory studies, centrifuge modeling, numerical analyses, and field case histories for mechanically stabilized earth walls, pavements, railway embankments, levee systems, and rainfall-induced and expansive soil slopes. Across these applications, geogrid geotextile composites consistently improve hydraulic control, maintain effective stress, and enhance factors of safety under extreme climatic loading. The review concludes by identifying critical research gaps, including coupled thermo-hydro-mechanical characterization, performance-based design approaches, and climate-resilient guidelines for geosynthetic selection and detailing. These findings underscore the potential of composite geosynthetics to enable more sustainable and resilient slope and earthwork infrastructure in a changing climate. Full article

Mexico City (CDMX) is located in an endorheic basin historically prone to flooding and waterlogging, the recurrence and magnitude of which have intensified in recent decades. However, flood risk assessment tends to focus primarily on the occurrence of intense rainfall to explain this phenomenon. The main objective of this study is to demonstrate that the risk of flooding in Mexico City (CDMX) depends not only on intense rainfall, but also on changes in hydrological vulnerability resulting from the loss of natural vegetation cover. The curve number (CN) method is used to determine hydrological vulnerability and flood risk in CDMX, integrating environmental information and precipitation values. Changes in surface runoff are also determined for 10 watersheds located west of Mexico City, considering urbanization in 1992 and 2021, as well as a non-urbanized scenario. The results indicate that hydrological vulnerability and flood risk increased from acceptable levels to “high” and “very high” levels, mainly in regions where urbanization increased and natural vegetation decreased. It was also identified that, under different levels of precipitation, agricultural and urban land cover have considerably lower infiltration capacities compared to natural land cover, such as forests, which infiltrate more than half of the precipitation. Finally, the increase in surface runoff in the watersheds located west of the city is closely related to the urbanization process and the physical characteristics of the territory. It was also observed that a degraded watershed can generate approximately 90% more runoff than a non-urbanized watershed. Full article

Understanding the crack development and rainfall infiltration in loess under wetting–drying cycles is crucial for assessing slope stability and promoting sustainable land management in ecologically vulnerable regions. This study employed a three-dimensional column model (Φ₂₄ × 50 cm) with 64 buried electrodes to simulate short-term heavy rainfall by changing the light duration (10 h/d and 5 h/d) and using 100 mm rainfall water. Results indicate that dry–wet cycles cause cumulative damage, significantly altering soil infiltration properties. After four cycles, the rainfall infiltration recharge coefficient increased from an initial 0.44% to 45.58%, a more than 100-fold rise. Resistivity imaging revealed a shift in water transport mode: from uniform matrix flow initially to preferential flow dominated by crack networks as cracks developed. During drying, crack zones exhibited high resistivity (ρ > 150 Ω·m), while water-filled cracks during infiltration showed low resistivity (ρ < 50 Ω·m). Resistivity is an excellent comprehensive index to quantify multi-field coupling damage, and its change (ρ∝ 1/w^1.86 × 1/(1 + 0.032 width)) synchronously responds to water content, crack development and dry–wet process. Low water content (w < 15%) and medium crack width (4–6 mm) are the most sensitive states. Longer illumination (10 h/d) promoted greater crack development and higher infiltration capacity compared to shorter cycles (5 h/d). The developed resistivity–moisture relationship provides a non-destructive monitoring tool for slope moisture dynamics, supporting not only geotechnical stability assessment but also optimized irrigation scheduling and adaptive land-use planning. These insights contribute directly to the sustainable management of soil and water resources in loess landscapes, aligning with sustainability goals in fragile ecosystems. Full article

Frequent extreme rainfall events in northwestern China have made loess–mudstone composite slopes highly susceptible to progressive failure, posing serious threats to infrastructure and public safety. This study investigates the deformation–failure mechanisms and evolutionary characteristics of such slopes under rainfall infiltration by integrating indoor physical model tests with long-term SBAS-InSAR time-series deformation monitoring. The physical model experiments reveal pronounced hydro-mechanical heterogeneity within the composite slope: surface fissures act as preferential flow paths, the mudstone interface exerts a significant water-blocking effect, and hydrological responses differ markedly between shallow and deep layers. The wetting front exhibits a distinct dual-layer migration pattern, characterized by rapid lateral expansion in the shallow layer and delayed advancement in the deep layer. Rainfall infiltration induces a progressive failure process, evolving from toe infiltration softening and mid-slope local erosion to differential crest erosion and ultimately overall sliding, forming a typical failure pattern of frontal creeping, central shearing, and rear tensile deformation. SBAS-InSAR results indicate that the natural landslide experienced a similar long-term progressive evolution, developing from shallow, localized deformation to deep-seated and slope-wide acceleration under multi-year rainfall. Despite differences in spatial deformation patterns influenced by natural microtopography, the failure stages and dominant deformation zones identified by both approaches show strong consistency. The combined results demonstrate that rainfall-induced suction decay, interface softening, pore water pressure accumulation, and stress redistribution jointly control the progressive instability of loess–mudstone slopes. This study highlights the effectiveness of integrating physical modeling and InSAR monitoring for elucidating rainfall-induced landslide mechanisms and provides scientific insights for hazard assessment and mitigation in composite-structure slopes. Full article

Instability in dump slopes frequently induces landslides, a process governed by complex factors. To investigate the impact of gradation composition on dump slope stability, four distinct gradations were designed, and large-scale laboratory triaxial tests were conducted to characterize their strength and deformation behaviors under varying confining pressures. Concurrently, numerical models of dump slopes with these four gradations were established using Particle Flow Code (PFC) to simulate rainfall infiltration processes. Through a comparative analysis of particle contact force chains, pore water pressure evolution, particle displacement under varying rainfall durations, and safety factors under natural and rainfall conditions, the mechanisms governing the influence of gradation composition on slope stability were elucidated from both macroscopic and microscopic perspectives. Results indicate the following: (1) Gradation composition significantly affects the strength and deformation characteristics of dump materials. Sample group 3 (with a fine-to-coarse particle ratio of 4:6) exhibited the highest strength among the four test samples, with peak deviatoric stresses of 610 kPa, 1075 kPa, and 1539 kPa under confining pressures of 200 kPa, 400 kPa, and 600 kPa, respectively. Its corresponding shear strength parameters were a cohesion of 38.45 kPa and an internal friction angle of 32.55°. In contrast, sample group 4 (fine-to-coarse ratio of 6:4) showed the lowest strength, with peak deviatoric stresses of 489 kPa, 840 kPa, and 1290 kPa under the same confining pressures, and shear strength parameters of c = 25.35 kPa and φ = 30.02°. (2) Gradation modulates contact forces and failure modes via a “skeleton-filling” mechanism. (3) Gradation plays a critical role in controlling pore water pressure evolution and the seepage characteristics of the dump slope model. Among the four designed gradations and their corresponding numerical models, Model 3 was characterized by the highest contact forces and the lowest pore water pressure. It exhibited the highest stability under both natural and rainfall conditions, with safety factors of 1.70 and 1.22, respectively. Conversely, Model 4 showed weak particle contact forces and high pore pressure, demonstrating the poorest stability. It yielded safety factors of only 1.25 and 1.02 under natural and rainfall-saturated conditions, indicating that it represents the least favorable gradation composition. These findings provide valuable references for the optimization of dumping processes and stability control in similar engineering projects. Full article

Rainfall infiltration is one of the main factors inducing slope instability, while the spatial heterogeneity and uncertainty of soil parameters have profound impacts on slope response characteristics and stability evolution. Traditional deterministic analysis methods struggle to reveal the dynamic risk evolution process of the system under heavy rainfall. Therefore, this paper proposes an uncertainty analysis framework combining Karhunen–Loève Expansion (KLE) random field theory, Polynomial Chaos Kriging (PCK) surrogate modeling, and Monte Carlo simulation to efficiently quantify the probabilistic characteristics and spatial risks of rainfall-induced slope instability. First, for key strength parameters such as cohesion and internal friction angle, a two-dimensional random field with spatial correlation is constructed to realistically depict the regional variability of soil mechanical properties. Second, a PCK surrogate model optimized by the LARS algorithm is developed to achieve high-precision replacement of finite element calculation results. Then, large-scale Monte Carlo simulations are conducted based on the surrogate model to obtain the probability distribution characteristics of slope safety factors and potential instability areas at different times. The research results show that the slope enters the most unstable stage during the middle of rainfall (36–54 h), with severe system response fluctuations and highly concentrated instability risks. Deterministic analysis generally overestimates slope safety and ignores extreme responses in tail samples. The proposed method can effectively identify the multi-source uncertainty effects of slope systems, providing theoretical support and technical pathways for risk early warning, zoning design, and protection optimization of slope engineering during rainfall periods. Full article

This study investigates rainstorm-induced highway subgrade slope collapses in the coastal areas of Southeast China. By integrating the seepage–stress coupled finite element method with the strength reduction method, we simulate the entire process of seepage, deformation, and slope collapse under rainstorm conditions, analyzing the variation in the stability factor. The key findings are as follows: (1) During rainstorms, water infiltration increases soil saturation and pore water pressure, while reducing matrix suction and soil shear strength, leading to soil softening. (2) The toe of the subgrade slope first undergoes plastic deformation under rainstorms, which develops upward, and finally the plastic zone connects completely, causing collapse. The simulated landslide surface is consistent with the actual one, revealing the collapse mechanism of the subgrade slope. Additionally, the simulated displacement at the slope toe when the plastic zone connects provides valuable insights for setting warning thresholds in landslide monitoring. (3) The stability factor of the subgrade slope in the case study decreased from 1.24 before the rainstorm to 0.985 after the rainstorm, indicating a transition from a stable state to an unstable state. (4) Parameter analysis shows that heavy downpour or downpour will cause the case subgrade slope to enter an unstable state. The longer the rainfall duration, the lower the stability factor. Analysis of soil parameters indicates that strength parameters, internal friction angle, and effective cohesion exert a significant influence on slope stability, whereas deformation parameters, elastic modulus, and Poisson’s ratio have a negligible effect. Slope collapse can be timely forecasted by predicting the stability factor. Full article

The finite element method (FEM) and discrete element method (DEM) have been widely applied to analyze the deformation and failure processes of embankment slopes. Although both methods can produce promising results, the choice between them has long remained unresolved. In this study, a failure case of a granite residual soil (GRS) embankment was analyzed. FEM and DEM models were established to simulate the instability process of this embankment slope, and the applicability of both methods to GRS embankments was then evaluated. The main conclusions are as follows: (1) Geotechnical parameters of GRS were determined through laboratory testing, and FEM and DEM models were developed to reproduce the deformation and failure behavior of the embankment slope subjected to rainfall and vehicle loading. (2) Similar rainfall infiltration patterns were obtained from both FEM and DEM simulations; however, significant differences in deformation were observed. The FEM-predicted deformation was 0.075 m after rainfall, indicating that the embankment remained stable. In contrast, the DEM-predicted deformation reached 1.4 m, indicating that the embankment slope had already become unstable. (3) The DEM simulation closely reproduced the failure of the GRS embankment slope observed in the field. It realistically captures the process of particle disintegration in GRS caused by rainfall infiltration, as well as the subsequent slope collapse. Therefore, DEM can be regarded as the most appropriate approach for modeling the instability of GRS embankment slopes. Full article

Rain-on-snow (ROS) events significantly impact hydrological processes in snowy regions, yet their seasonal drivers remain poorly understood, particularly in low-elevation and low-gradient catchments. This study uses an XGBoost-SHAP explainable artificial intelligence (XAI) model to analyze meteorological and watershed controls on ROS runoff in the Laurentian Great Lakes region. We used daily discharge, precipitation, temperature, and snow depth data from 2000 to 2023, available from HYSETS, to identify ROS runoff. The XGBoost model’s performance for predicting ROS runoff was higher in winter (R² = 0.65, Nash–Sutcliffe = 0.59) than in spring (R² = 0.56, Nash–Sutcliffe = 0.49), indicating greater predictability in colder months. The results reveal that rainfall and temperature dominated ROS runoff generation, jointly explaining more than 60% of total model importance, while snow depth accounted for 8–12% depending on season. Winter runoff is predominantly governed by climatic factors—rainfall, air temperature, and their interactions—with soil permeability and slope orientation playing secondary roles. In contrast, spring runoff shows increased sensitivity to land cover characteristics, particularly agricultural and shrub cover, as vegetation-driven processes become more influential. Snow depth effects shift from predominantly negative in winter, where snow acts as storage, to positive contributions in spring at shallow to moderate depths. ROS runoff responded positively to air temperatures exceeding approximately 2.5 °C in both winter and spring. Land cover influences on ROS runoff differ by vegetation type and season. Agricultural areas consistently increase runoff in both seasons, likely due to limited infiltration, whereas shrub-dominated regions exhibit stronger runoff enhancement in spring. The seasonal shift in dominant controls underscores the importance of accounting for land–climate interactions in predicting ROS runoff under future climate scenarios. These insights are essential for improving flood forecasting, managing water resources, and developing adaptive strategies. Full article

Managing overland flow (OF) is essential in steep high-rainfall regions. A key strategy is to increase ground cover either naturally or through management. In Japanese cypress plantations, low ground cover increases OF and flood risks during intense rainfall. We analyzed OF and soil water content (SWC) in three plots of a Japanese cypress plantation under clear-cutting, 40% thinning, and control conditions over one year (2022–2023). The SWC remained consistently higher in the clear-cut plot than in the thinned and control plots. In contrast, the OF rate was greatest in the control plot (1.97%), intermediate in the thinned plot (1.03%), and lowest in the clear-cut plot (0.58%) with 5, 5, and 35% ground cover, respectively. Event-based analyses showed that in the clear-cut plot, OF was correlated with total rainfall (r = 0.597, p = 0.003), suggesting a tendency toward subsurface flow. Conversely, in the control plot, OF was correlated with 60 min of maximum rainfall (r = 0.90, p < 0.001), indicating Hortonian flow. No significant relationships were observed in the thinned plot, likely because of response variability. Our findings imply that ground cover dynamics following management regulate OF, emphasizing the importance of continued monitoring. Full article