Search Results (57)

Min County experiences intense debris flow activity due to extreme weather and geological events. This study analyzes debris flow activity in Min County using GIS spatial analysis, time-series statistics, correlation analysis, periodic fitting, and field investigations across four event-based key periods (2002, 2012, 2013, and 2020). Long-term meteorological records (1951–2020) are introduced to support climatic trend analysis. Results indicate that stratigraphic lithology and fault tectonics control about 85–90% of the spatial distribution of debris flows, while extreme short-duration rainstorms trigger large-scale outbreaks and strong earthquakes further intensify activity. The high-occurrence cycle of debris flows (7–8 years) does not fully align with the annual wetness cycle (12 years). On a short time scale (years to decades), extreme earthquakes and rainstorms exert more significant impacts than normal precipitation patterns. This study preliminarily infers potential future peak periods of debris flows in Min County, with uncertainty from climate fluctuations and uncertain seismic events considered. The coupled mechanism of seismic weakening and rainfall triggering, together with lag-time characteristics, is revealed to support disaster prevention and mitigation. Full article

Under dynamic loading (e.g., earthquakes, extreme rainfall), multi-stage slope slumps occur as downstream slopes lose anti-sliding stability, triggering intensive lateral sediment supply that governs mountainous channel evolution. This study uses a coupled CFD-DEM model to simulate how water–sediment conditions regulate sediment transport and riverbed deformation. Results show that during the first sediment supply event, particle motion is initially slower under wet than dry conditions but accelerates due to buoyancy, with the peak average particle velocity along the gully axis decreasing by 11.5% and exhibiting negligible flow rate dependence. In the channel, higher flow rates raise particle velocity and downstream sediment flux, while a prolonged supply interval elevates peak velocity and delays its occurrence. For subsequent events, peak gully axis and vertical velocities increase with sediment supply mass, with weak dependence on flow rate or interval. Post-peak particle motion accelerates with these three factors, enhancing sediment entrainment effects. Increasing flow rate from 1.7 to 2.2 L/s, supply mass from 0.75 to 1.50 kg, and interval from 4 to 6 s significantly strengthens substrate dynamic response, with the peak average velocity rising by 78.3%, 33.3%, 67.0% and maximum displacement by 80.7%, 51.2%, 67.6%, respectively. Channel particle velocity is more sensitive to flow rate but suppressed by greater sediment mass and shorter intervals. The deposited riverbed has three zones: first-supply-dominated, mixed, and subsequent-supply-dominated. Higher flow rates restrict depositional area expansion but increase thickness, whereas greater subsequent sediment expands its dominant zone while reducing thickness, with minimal influence from supply intervals. This study offers theoretical insights for preventing water–sediment disasters in mountainous areas. Full article

Rapid and accurate acquisition of landslide inventories is essential for effective disaster relief. Deep learning-based pixel-wise semantic segmentation of remote sensing imagery has greatly advanced in landslide mapping. However, the heavy dependance on extensive annotated labels and sensitivity to domain shifts severely constrain the model performance in unseen domains, leading to poor generalization. To address these limitations, we propose LandsDANet, an innovative unsupervised domain adaptation framework for cross-domain landslide identification. Firstly, adversarial learning is employed to reduce the data distribution discrepancies between the source and target domains, thereby achieving output space alignment. The improved SegFormer serves as the segmentation network, incorporating hierarchical Transformer blocks and an attention mechanism to enhance feature representation capabilities. Secondly, to alleviate inter-domain radiometric discrepancies and attain image-level alignment, a Wallis filter is utilized to perform image style transformation. Considering the class imbalance present in the landslide dataset, a Rare Class Sampling strategy is introduced to mitigate bias towards common classes and strengthen the learning of the rare landslide class. Finally, a contrastive loss is adopted to further optimize and enhance the model’s ability to delineate fine-grained class boundaries. The proposed model is validated on the Potsdam and Vaihingen benchmark datasets, followed by validation in two landslide scenarios induced by earthquakes and rainfall to evaluate its adaptability across different disaster domains. Compared to the source-only model, LandsDANet achieved improvements in IoU of 27.04% and 35.73% in two cross-domain landslide disaster recognition tasks, respectively. This performance not only showcases its outstanding capabilities but also underscores its robust potential to meet the demands for rapid response. Full article

In many mountainous areas of China, frequent geological disasters pose a serious threat to human life and property. The Luding “9.5” earthquake triggered a large number of landslide disasters, causing serious loss of life and property. Therefore, it is extremely urgent to carry out research on the stability analysis and treatment methods of landslides in the Luding area. In this paper, the Caiyangba landslide in Yanzigou Town, Luding County, is taken as the research object. The slope model is constructed by Midas to study the stability development law of Caiyangba landslide under different rainfall conditions and seismic conditions, and to explore the feasibility of the “anchor lattice treatment method”. The results show that the “anchor lattice treatment method” can effectively improve the stability of the slope under rainfall conditions. The improvement effect of slope stability decreases with the increase in rainfall duration and rainfall. The development law of the slope stability coefficient with rainfall duration in WMG (the working condition of not adopting the “anchor lattice treatment method” is referred to as WMG) and MG (the working condition of adopting the “anchor lattice treatment method” is referred to as MG) conditions conform to the development law of exponential function, and the expression of instantaneous change rate of slope stability coefficient is derived. The above function can also well explain the development law of X-direction displacement and Y-direction displacement of SP (school: monitoring point) and RP (road: monitoring point); the development law of the instantaneous change rate of displacement. Under the influence of ground motion, the improvement effect of the “anchor lattice treatment method” on the slope stability coefficient is limited, but the improvement effect of slope stability increases with the increase in seismic intensity. The slope stability coefficient and the displacement of SP and RP show obvious fluctuation with time, and the fluctuation law is similar to that of ground motion records. It is recommended to add a gravity-retaining wall at the foot of the slope. The teaching building reduces the number of floors and increases the number of pile foundations. Roads should restrict the passage of heavy vehicles, such as cars and strictly stacked items. The above results can provide a theoretical reference for the sustainable treatment and sustainable development of landslides in the Luding area. Full article

Yongshan County in northeastern Yunnan Province is a frequent geological hazard zone. Based on previous detailed geological hazard surveys, the county contains 455 landslide hazard sites, primarily distributed in the western and northern regions. Influenced by multiple factors including rainfall, earthquakes, human activities, and reservoir water storage, it is challenging to evaluate their development using a single indicator. Therefore, there is an urgent need to conduct landslide susceptibility assessments that integrate deformation rate characteristics. However, existing studies in this region have only considered static spatial factors such as slope aspect, elevation, and lithology. Traditional landslide susceptibility assessments often struggle to balance zoning accuracy with timeliness, leading to biased results and limited update efficiency. This study employs SBAS-InSAR technology to capture surface deformation rates and utilizes machine learning models to partition landslide susceptibility distribution maps. It innovatively introduces an RFE-RF-XGBoost model to reduce partitioning errors and enhance the accuracy of landslide susceptibility mapping. Experiments utilized 147 Sentinel-1A and 14 LT-1 scenes. Through five-fold cross-validation, 13 influencing factors were selected. The RFE-RF-XGBoost model was trained via hyperparameter optimization and compared against four conventional models (CatBoost, LightGBM, XGBoost, RF). After validating the predictive performance of different models via ROC curves, the prediction results at each level were analyzed using Accuracy, Precision, Recall, and F1 metrics. Results indicate that all five machine learning models demonstrate effective zoning capabilities. Among them, the RFE-RF-XGBoost model achieves optimal mapping performance. Compared to the other four models, it reduces the proportion of low-risk zones by 2–4% while increasing the proportion of extremely high-risk zones by approximately 2–12%, with an AUC value reaching around 0.95. Field investigations further validated that this approach enhances landslide interpretation accuracy by integrating SBAS-InSAR technology with remote sensing techniques. Full article

This article examines the effects of climate change on the 32 million inhabitants of the Megalopolis of Central Mexico (MCM), which is threatened by chaotic urbanization, land-use changes, the deforestation of the Forest of Water by organized crime, unsustainable agriculture, and biodiversity loss. Expensive hydraulic management extracting water from deep aquifers, long pipes exploiting water from neighboring states, and sewage discharged outside the endorheic basin result in expensive pumping costs and air pollution. This mismanagement has increased water scarcity. The overexploitation of aquifers and the pollution by toxic industrial and domestic sewage mixed with rainfall has increased the ground subsidence, damaging urban infrastructure and flooding marginal neighborhoods with toxic sewage. A system approach, satellite data, and participative research methodology were used to explore potential water scarcity and weakened water security for 32 million inhabitants. An alternative nature-based approach involves recovering the Forest of Water (FW) with IWRM, including the management of Natural Protected Areas, the rainfall recharge of aquifers, and cleaning domestic sewage inside the valley where the MCM is found. This involves recovering groundwater, reducing the overexploitation of aquifers, and limiting floods. Citizen participation in treating domestic wastewater with eco-techniques, rainfall collection, and purification filters improves water availability, while the greening of urban areas limits the risk of climate disasters. The government is repairing the broken drinking water supply and drainage systems affected by multiple earthquakes. Adaptation to water scarcity and climate risks requires the recognition of unpaid female domestic activities and the role of indigenous people in protecting the Forest of Water with the involvement of three state authorities. A digital platform for water security, urban planning, citizen audits against water authority corruption, and aquifer recharge through nature-based solutions provided by the System of Natural Protected Areas, Biological and Hydrological Corridors [SAMBA] are improving livelihoods for the MCM’s inhabitants and marginal neighborhoods, with greater equity and safety. Full article

This study explores the impact of the 2022 Mw 6.8 Luding Earthquake on various geo-hazards and their corresponding rainfall thresholds. Focusing on the seismic intensity VI zone in Sichuan Province, China, we analyzed 1979 geo-hazard records and hourly precipitation data from 475 stations between 2010 and 2024. Empirical ID (intensity–duration) and AC (accumulated rainfall–continuous rainfall duration) rainfall threshold models are established based on these datasets. By comparing pre- and post-earthquake data, this study assesses changes in the spatial distribution and triggering rainfall thresholds of landslides, rockfalls, and debris flows. The results indicate a significant increase in geo-hazard risks post-earthquake, particularly near the Xianshuihe Fault, with rockfall risks exhibiting the most pronounced rise. Statistical analysis reveals that the rainfall thresholds required to trigger geo-hazards decreased notably after the earthquake: ID models indicate a decrease of approximately 20%, while AC models show a reduction of about 20% in the western zone and 10% in the eastern zone. A four-level early warning system is developed using empirical rainfall threshold models, offering tailored hazard alerts for different regions and geo-hazard types. The variation in threshold values between the east and west zones highlights the influence of differing topographic and climatic conditions. These findings provide critical insights for post-seismic hazard assessment and inform more effective, sustainable early warnings, thereby supporting more reliable and sustainable disaster risk management in earthquake-affected regions. Full article

The seismic bearing capacity of water-saturated composite foundations adjacent to slopes is critical for engineering safety, yet it is significantly influenced by complex factors such as earthquakes and heavy rainfall. This paper establishes a failure mechanism model that involves both reinforced and non-reinforced zones, comprehensively considering the synergistic effects of seismic force, pore water pressure and group pile replacement rate, and thus addressing the issue that existing models struggle to account for the coupling effects of multiple factors. Based on the principle of virtual work, a general solution for ultimate bearing capacity is derived, and the optimal solution is obtained using the MATLAB R2023a exhaustive method. Findings reveal that pile group support substantially enhances bearing capacity: the improvement becomes more pronounced with higher soil strength parameters (φ, c) and replacement ratios. When the seismic acceleration coefficient increases from 0 to 0.3, the bearing capacity of the unreinforced foundation decreases by approximately 61.6% (from 134.71 kPa to 51.83 kPa), while group pile support can increase the bearing capacity by 433.2%. Notably, when soil strength is inherently high, the marginal benefit of pile group reinforcement diminishes. A case study in Fuzhou validates through numerical simulation that pile groups improve foundation stability by altering energy dissipation distribution, with the discrepancy between theoretical calculations and simulation results within 10%. The research results can directly guide the design of saturated composite foundations near slopes in earthquake-prone areas (such as Fujian and Guangdong) and enhance the seismic safety reserve by optimizing the replacement rate of group piles (recommended to be 0.2~0.3). Full article

It is an urgent issue for preventing slope failure caused by increasingly severe earthquakes and heavy rain. As a conventional construction method, reinforcing bar insertion work uses the tensile force of the core bar to integrate multiple core bars and pressure plates. Meanwhile, landslide deterrence piles are a construction method in which steel or concrete piles are constructed below the slope, and the rigidity of the piles is used to resist slope failure. In this study, these methods are combined to propose a reinforcing bar insertion work that uses pipes as a construction method. The pipes are not embedded in the immovable layer and are not connected to the reinforcing bar insertion work; therefore, the construction is expected to be simple. Two series of model experiments—a lift-up experiment and a water sprinkling experiment—were performed. Through the lift-up experiment, the effectiveness of the proposed method against static load was confirmed, and the evaluation formula of the load applied to the core bar was proposed. Through the water sprinkling experiment, the effectiveness against rainfall was confirmed, that is, the time until slope failure was extended by the proposed method. Full article

This study investigates the stability of high-rise wind turbine tower foundations in collapsible loess regions through finite element analysis. The mechanisms by which wind load, extreme rainfall load, and seismic load interact during the dynamic response of a pile foundation under single-action and intercoupling conditions are analyzed. A comprehensive multi-parameter analytical model is developed to evaluate pile foundation stability, incorporating key indicators including pile skin friction, average axial stress of pile groups, horizontal displacement at pile tops, and pile inclination. The results show that, among single-load conditions, seismic loading has the most pronounced impact on foundation stability. The peak horizontal displacement at the pile top induced by seismic loads reaches 10.07 mm, substantially exceeding the effects of wind and rainfall loads, posing a direct threat to wind turbine tower safety. Under coupled loading conditions, notable nonlinear interaction effects emerge. Wind–earthquake coupled loading amplifies horizontal displacement by 1.85 times compared to single seismic loading. Rainfall–earthquake coupled loading reduces the peak of positive skin friction by 20.17%. Notably, all seismic-involved loading combinations significantly compromise the pile foundation safety margin. The seismic load is the dominant influencing factor in various loading conditions, and its coupling with other loads induces nonlinear superposition effects. These findings provide critical insights for wind turbine foundation design in collapsible loess areas and strongly support the need for enhanced seismic considerations in engineering practice. Full article

Debris flows are rapid, destructive landslides that pose significant risks in mountainous regions. This study presents a novel algorithm to simulate debris flow dynamics, focusing on sediment transport from 0-order basins to depositional zones. The algorithm integrates the D8 flow direction method with an adjustable friction coefficient to enhance the accuracy of debris flow trajectory and deposition modeling. Its performance was evaluated on three real-world cases in the Otoishi River basin, affected by rainfall-induced debris flows in July 2017, and the Aso Bridge landslide triggered by the 2016 Kumamoto Earthquake. By utilizing diverse friction coefficients, the study effectively captured variations in debris flow behavior, transitioning from fluid-like to more viscous states. Simulation results demonstrated a precision of 88.9% in predicting debris flow paths and deposition areas, emphasizing the pivotal role of the friction coefficient in regulating mass movement dynamics. Additionally, Monte Carlo (MC) simulations enhanced the identification of critical slip surfaces within 0-order basins, increasing the accuracy of debris flow source detection. This research offers valuable insights into debris flow hazards and risk mitigation strategies. The algorithm’s proven effectiveness in simulating real-world scenarios highlights its potential for integration into disaster risk assessment and prevention frameworks. By providing a reliable tool for hazard identification and prediction, this study supports proactive disaster management and aligns with the goals of sustainable development in regions prone to debris flow disasters. Full article

Taiwan is located at a junction of tectonic plates, which results in frequent earthquakes. Its terrain is mostly hilly, and its rainfall ranks among the highest in the world. Each of these elements affects the stability of slopes in various regions of Taiwan. Several slopes along Taiwan’s Freeway 1 and 5 have experienced landslides and rockfalls. It is imperative that the slope stability of these national freeways be analyzed to avoid future slope collapses brought on by precipitation or other outside factors. Thus, three sites on Taiwan’s Freeway 1 and 5 were chosen for numerical slope stability analysis in this study. PLAXIS 2D CE (Version: 24.02.00.1144) finite element software was used in this study to simulate and analyze the safety of freeway slope protection projects. Displacements induced by normal and high groundwater levels were discussed. Moreover, a pseudo-static study of slope displacements under seismic conditions was performed. According to the results of the numerical study, the force operating on the slope was centered on the sliding surface when the groundwater level was normal, and it extended to the top when the groundwater level was high. By comparison, under seismic conditions, the force acting on the slope extended to the whole slope. Furthermore, the slope safety factor of Site 1 was greater than the design specification value in three different scenarios. This confirms that the slope protection project at Site 1 is effective. Full article

Major earthquakes and rainfall may occur at the same time, necessitating further investigation into the dynamic characteristics and responses of reinforced soil retaining walls subjected to the combined forces of rainfall and seismic activity. Three sets of shaking table tests on model retaining walls were designed, a modular reinforced earth retaining wall was utilized as the subject of this study, and a custom-made device was made to simulate rainfall conditions of varying intensities. These tests monitored the rainwater infiltration pattern, macroscopic phenomena, panel displacement, tension behavior, dynamic characteristics, and acceleration response of the modular reinforced earth retaining wall during vibration under different rainfall intensities. The results indicated the following. (1) Rainwater infiltration can be categorized into three stages: rapid rise, rapid decline, and slow decline to stability. The duration for infiltration to reach stability increases with greater rainfall. (2) An increase in rainfall intensity enhances the seismic stability of the retaining wall panel, as higher rainfall intensity results in reduced sand leakage from the panel, thereby diminishing panel deformation during vibration. (3) Increased rainfall intensity decreases the shear strength of the soil, leading to a greater load on the reinforcement. (4) The natural vibration frequencies of the three groups of retaining walls decreased by 0.21%, 0.54%, and 2.326%, respectively, indicating some internal damage within the retaining walls, although the degree of damage was not severe. Additionally, the peak displacement of the panel increased by 0.91 mm, 0.63 mm, and 0.61 mm, respectively. (5) The amplification effect of rainfall on internal soil acceleration is diminished, with this weakening effect becoming more pronounced as rainfall intensity increases. These research findings can provide a valuable reference for multi-disaster risk assessments of modular reinforced soil retaining walls. Full article

In 2013, a Ms 6.6 earthquake occurred at the boundary of Min County and Zhang County, triggering numerous landslides. Notably, two landslides with significantly different sliding characteristics emerged less than 100 m apart in Yongguang Village, Min County. The eastern landslide was characterized by instability induced by seismic inertial forces, whereas the western landslide exhibited flow slides triggered by liquefaction in loess. To further analyze the causes of these landslides, this study employed a 1 m depth ground temperature survey to probe the shallow groundwater in the area, aiming to understand the distribution of shallow groundwater. Based on the results from the 1 m depth ground temperature survey, a random forest model was applied to regressively predict the initial groundwater levels. The TRIGRS model was utilized to evaluate the influence of pre-earthquake rainfall conditions on landslide stability, and the pore water pressure outputs from TRIGRS were integrated with the Scoops3D model to analyze landslide stability under seismic effects. The results indicate that the combination of the 1 m depth ground temperature survey with high-density electrical methods and random forest approaches effectively captures the initial groundwater levels across the region. Notably, the heavy rainfall occurring one day prior to the earthquake did not significantly reduce the stability of the landslide in Yongguang Village. Instead, the abundant groundwater in the source area of the western landslide, combined with several months of pre-earthquake rainfall, resulted in elevated groundwater levels that created favorable conditions for its occurrence. While the primary triggering factor for both landslides in Yongguang Village was the earthquake, the distinct topographic and groundwater conditions led to significantly different sliding characteristics under seismic influence at the same slope. Full article

Rainfall-triggered landslides generally pose a high risk due to their sudden initiation, massive impact force, and energy. It is, therefore, necessary to perform accurate and timely hazard prediction for these landslides. Most studies have focused on the hazard assessment and verification of landslides that have occurred, which were essentially back-analyses rather than predictions. To overcome this drawback, a framework aimed at forecasting landslide hazards by combining UAV remote sensing and numerical simulation was proposed in this study. A slow-moving landslide identified by SBAS-InSAR in Tianjin city of northern China was taken as a case study to clarify its application. A UAV with laser scanning techniques was utilized to obtain high-resolution topography data. Then, extreme rainfall with a given return period was determined based on the Gumbel distribution. The Particle Flow Code (PFC), a discrete element model, was also applied to simulate the runout process after slope failure under rainfall and earthquake scenarios. The results showed that the extreme rainfall for three continuous days in the study area was 151.5 mm (P = 5%), 184.6 mm (P = 2%), and 209.3 mm (P = 1%), respectively. Both extreme rainfall and earthquake scenarios could induce slope failure, and the failure probabilities revealed by a seepage–mechanic interaction simulation in Geostudio reached 82.9% (earthquake scenario) and 92.5% (extreme rainfall). The landslide hazard under a given scenario was assessed by kinetic indicators during the PFC simulation. The landslide runout analysis indicated that the landslide had a velocity of max 23.4 m/s under rainfall scenarios, whereas this reached 19.8 m/s under earthquake scenarios. In addition, a comparison regarding particle displacement also showed that the landslide hazard under rainfall scenarios was worse than that under earthquake scenarios. The modeling strategy incorporated spatial and temporal probabilities and runout hazard analyses, even though landslide hazard mapping was not actually achieved. The present framework can predict the areas threatened by landslides under specific scenarios, and holds substantial scientific reference value for effective landslide prevention and control strategies. Full article