Search Results (267)

Landslides cause severe damage to life and property with a wide-ranging impact. Infiltration of rainfall is one of the significant factors leading to landslides. This paper reports on a phase creep landslide caused by long-term rainfall infiltration. A detailed geological survey of the landslide was conducted, and the deformation development pattern and mechanism of the landslide were analyzed in conjunction with climatic characteristics. Furthermore, reinforcement measures specific to the landslide area were proposed. To monitor the stability of the reinforced slope, a Beidou intelligent monitoring and warning system suitable for remote mountainous areas was developed. The system utilizes LoRa Internet of Things (IoT) technology to connect various monitoring components, integrating surface displacement, deep deformation, structural internal forces, and rainfall monitoring devices into a local IoT network. A data processing unit was established on site to achieve preliminary processing and automatic handling of monitoring data. The monitoring results indicate that the reinforced slope has generally stabilized, and the improved intelligent monitoring system has been able to continuously and accurately reflect the real-time working conditions of the slope. Over the two-year monitoring period, 13 early warnings were issued, with more than 90% of the warnings accurately corresponding to actual conditions, significantly improving the accuracy of early warnings. The research findings provide valuable experience and reference for the monitoring and warning of high slopes in mountainous areas. Full article

Since the times of the Incas, farmers in the remote Andes of Peru have constructed terraces to grow crops in a landscape characterized by steep slopes, semiarid climate, and landslide geohazards. Recent investigations have concluded that terracing and irrigation techniques could enhance landslide risk due to the increase in water percolation and interception of surface flow in unstable slopes, leading to failure. In this study, we generated an inventory of 170 landslides and terraced areas to assess the spatial coherence, causative relations, and geomechanical processes linking landslide presence and Inca terraces in a 250 km² area located in the Ticsani valley, southern Peru. To assess spatial coherence, a tool was developed based on the confusion matrix approach. Performance parameters were quantified for areas close to the main rivers and communities yielding precision and recall values between 64% and 81%. On a larger scale, poor performance was obtained pointing to the existence of additional processes linked to landslide presence. To investigate the role of other natural variables in landslide prediction, a logistic regression analysis was performed. The results showed that terrace presence is a statistically relevant factor that bolsters landslide presence predictions, apart from first-order natural variables like distance to rivers, curvature, and geology. To explore potential geomechanical processes linking terraces and slope failures, FEM numerical modeling was conducted. Results suggested that both decreased permeability and increased surface irrigation, at 70% of the average annual rainfall, are capable of inducing slope failure. Overall, irrigated terraces appear to further promote slope instability due to infiltration of irrigation water in an area characterized by fluvial erosion, high relief, and poor geologic materials, exposing local communities to increased landslide risk. Full article

This study investigates the stability of fine-grained sandy soil slopes under varying rainfall intensities, durations, and geotechnical properties using a parametric analysis within GeoStudio. A total of 4416 unique parameter combinations were analyzed, incorporating variations in unit weight, cohesion, friction angle, slope inclination, slope height, rainfall intensity, and duration. Results reveal that rainfall intensity is the most influential variable on the factor of safety (FS), with higher intensities (e.g., 360 mm/h) on steeper slopes (e.g., 45°) leading to critical FS values below 1, indicating an imminent risk of failure. Under moderate conditions (e.g., 9 mm/h rainfall on slopes of 26.6°), the FS remains above 2. This dataset provides a valuable foundation for training machine learning models to predict slope stability under diverse environmental conditions, contributing to the development of early warning systems for rainfall-induced landslides. Full article

Monitoring soil water content (SWC) can improve the effectiveness of early warning systems (EWSs) designed to mitigate rainfall-induced shallow landslide risk. In extensive areas, like along linear infrastructures, the adoption of cost-effective sensors is critical for the EWS implementation. The present study aims to evaluate the reliability of different low-cost SWC sensors (frequency domain reflectometry and capacitance-based) in capturing soil moisture conditions critical for EWS, without performing soil-specific calibration. The reliability of the low-cost sensors is assessed through a comparative analysis of their measurements against those from high-cost and well-established sensors (time domain reflectometry) over a two-year period in a shallow landslide-prone area of Oltrepò Pavese, Italy. Although no landslides are observed during the monitoring period, meteorological conditions are reconstructed and statistical analysis of sensor’s responses to different rainfall events is conducted. Results indicate that, despite differences in absolute readings, low-cost sensors effectively capture relative SWC variations and demonstrate sensitivity to rainfall events across both cold and warm periods. The presented low-cost sensors can serve as reliable indicators of soil infiltration and saturation levels, highlighting their potential for real-time monitoring within extensive networks for EWS. Full article

Mining causes damage to the soil and rock mass, while rainfall has a pivotal impact on the mining slope stability, even leading to geological hazards such as landslides. Therefore, the study evaluated the mine landslide stability and determined the effectiveness of the treatment measures under the impact of pore water pressure changes caused by rainfall, taking the Kong Mountain landslide in Nanjing, Jiangsu Province, China, as the research object. The geological conditions and deformation characteristics were clarified, and the failure mechanism and influencing factors were analyzed. Also, the landslide stability was comprehensively evaluated and calculated utilizing the finite element-improved limit equilibrium method and FLAC 3D 6.0, which simulated the distribution of pore water pressure, displacement, etc., to analyze the influence of rainfall conditions and reinforcement effects. The results indicated the following: (1) Rainfall is the key influencing factor of the landslide stability, which caused the pore water pressure changes and the loosening of the soil due to the strong permeability; (2) The distribution of the pore water pressure and plastic zone showed that, during the rainfall process, a large area of transient saturation zone appeared at the leading edge, affecting the stability of the whole landslide and led to the further deformation; (3) After the application of treatment measures (anti-sliding piles and anchor cables), the landslide stability increased under both natural and rainfall conditions (from 1.02 and 0.94 to 1.38 and 1.31, respectively), along with a reduction in displacement, plastic zones, etc. The Kong Mountain landslide, with the implemented treatment measures, is in good stability, which is in line with the evaluation and calculation results. The study provides certain contributions to the stability evaluation and treatment selection of similar engineering under rainfall infiltration. Full article

In the context of global climate change, shallow landslides induced by strong typhoons and the ensuing rainstorms have increased significantly in China’s eastern coastal areas. On 27 May 2022, more than 700 liquefied landslides were induced by the rain gush in Wuping County, Longyan City, Fujian Province, SE China. In light of their widespread occurrence and the severe damage caused, detailed field investigations, UAV surveys, trench observations, in situ tests, and numerical simulation are conducted in this work. The cascading landslides are classified as channelized landslides and hillslope landslides. Long-term rainfall, the influence of vegetation roots under wind load, and differences in the strength and structure of surficial soil are the dominant controlling factors. The sliding surface is localized to be the interface at a depth of 1–1.5 m between the fully weathered granite and the strongly weathered granite. Kinetic analysis of a channelized landslide shows that it is characterized by short runout, rapid velocity, and strong impact energy. The maximum velocity, impact energy, and impact force of the Laifu landslide are 29 m/s, 4221.35 J, and 2110 kPa. Effective excavation is usually impossible in this context. This work highlights the escalating issue of shallow landslides in eastern China’s coastal areas, exacerbated by climate change and extreme weather events like typhoons. By conducting comprehensive investigations and analyses, the research identifies key factors influencing landslide occurrence, such as rainfall patterns and soil characteristics. Understanding the dynamics and impact of these landslides is vital for improving risk assessment, developing effective early warning systems, and informing land management policies in this region. Further exploration concerning hydro-meteorological hazard early warning should be encouraged in this region. 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

Under the impact of global climate change and human activities, the occurrence of compound disasters such as cascading landslides and flash floods caused by heavy rainfall is increasing. In response to these compound disaster events, it is important to simultaneously transport emergency resources from multiple emergency rescue points to the disaster sites to promptly control the cascading development of disasters and reduce the areas affected by the disasters and associated adverse impacts. This study proposes a dynamic game model for emergency resources dispatch to comprehensively consider the evolution of the compound disaster states and the timely dispatch of emergency resources from the rescue points to the disaster site. The dynamic game model is exemplarily applied to the emergency resource dispatch for a rainstorm-induced compound disaster that occurs in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). Starting with the analysis of the characteristics of emergency resource management and the attributes of a cascading of heavy rainstorms, landslides, and flash floods, the game model simulates the dynamic game process between the “disaster state” and the “emergency resource manager” in the rescue operations. A two-stage dynamic game model can support decision-making with the objectives of minimal time cost and sufficient resource dispatch for the disaster sites. Game results show that the united emergency resource dispatch in the three GBA metropolitan areas can efficiently respond to compound disasters that occur within the GBA metropolitan area. The dynamic game model could be extended for compound disaster emergency responses with more complicated compound effects and resource constraints. Full article

The stability analysis of rainfall-induced slope failures considers a number of factors including the characteristics of the rainfall, vegetation, geometry of the slope, unsaturated soil characteristics, infiltration capacity, and saturation degree variations. Amongst all these factors, this study aims to investigate the effects of the antecedent rainfall and saturation conditions. A numerical modeling study was conducted using finite difference code software on a representative slope geometry with two different soil types. Two scenarios were followed: The first involved the application of three different rainfall intensities for varying initial saturation levels between 40% and 60%, representing the antecedent saturation conditions. The second scenario involved modeling successive rainfalls for a typical initial saturation degree of 50%. The impact of antecedent rainfall was assessed by determining the time required for failure during the application of a main extreme rainfall after a preceding rainfall of varying durations. Consequently, a zone of susceptible time for failure was suggested for use as a criterion in hazard management, allowing for the tracking of rainfall and its duration through the proposed chart for potential failures. Once the anticipated critical rainfall intensities have been determined through a meteorological analysis, a risk assessment for a specific slope can be conducted using the proposed practical procedure. Accordingly, a control mechanism may be established to detect the potential for a natural hazard. Furthermore, the proposed procedure was applied to a case study, whose modeling insights were in harmony with the real conditions of the slope failure. Thus, this demonstrated the significance of the antecedent conditions in modeling landslides triggered by rainfalls. Full article

Rainfall-induced shallow slope instability is a significant global hazard, often triggered by water infiltration that affects soil stability and involves dynamic changes in the hydraulic behavior of unsaturated soils. This study employs a hydro-mechanical coupled analysis model to assess the impact of rainfall on slope stability, focusing on the dynamic hydraulic behavior of unsaturated soils. By simulating the soil water content and slope stability under four different rainfall scenarios based on observational data and historical thresholds, this study reveals that higher rainfall intensity significantly increases the soil water content, leading to reduced slope stability. The results show a strong correlation between the soil water content and slope stability, with a 20 mm/h rainfall intensity threshold emerging as a reliable predictor of potential slope instability. This study contributes to a deeper understanding of slope stability dynamics and emphasizes the importance of proactive risk management in response to changing rainfall patterns while also validating current management practices and providing essential insight for improving early warning systems to effectively mitigate landslide risk. Full article

Landslides are one of the primary geological disasters posing significant threats to life and property. Strengthening the monitoring of rainfall-induced landslides is, therefore, crucial. The Direct Resistivity (DC) method can accurately map the subsurface electrical resistivity distribution, making it an essential tool for predicting the position of the slide face. However, when conducting landslide surface DC surveys, various undulating terrains such as ridges and steep slopes often pose accessibility challenges. In such topographies, conventional regular grid measurements become very difficult. Additionally, when the terrain is highly undulating and complex, interpreting apparent resistivity data can lead to erroneous results. In this study, we propose using the DC method to monitor rainfall-induced landslides. By moving away from traditional device setups and utilizing an arbitrary dipole–dipole observation system, we aim to improve efficiency, enhance data resolution, and reduce costs. The resistivity of the slope was found to change significantly during the incubation, formation, and development of a landslide in physical model experiments. Furthermore, the feasibility of our proposed method for assessment rainfall-induced landslides was illustrated by a real case study in South China. Full article

Land cover changes in mountainous areas due to silvo-pastoral abandonment can affect soil stability, especially on steep slopes. In addition, the increase in rainfall intensity in recent decades requires re-assessing landslide susceptibility and vegetation management for soil protection. This study was carried out using the software SlideforMAP in the Mt. Nerone massif (central Italy) to assess (i) the effects of land cover changes on slope stability over the past 70 years (1954–2021) and (ii) the role of actual vegetation cover during intense rainfall events. The study area has undergone a significant change in vegetation cover over the years, with a reduction in mainly pastures (−80%) and croplands (−22%) land cover classes in favor of broadleaf forests (+64%). We simulated twelve scenarios, combining land cover conditions and rainfall intensities, and analyzed the landslide failure probability results. Vegetation cover significantly increased the slope stability, up to three to four times compared to the unvegetated areas (29%, 68%, and 89%, respectively, in the no cover, 1954, and 2021 scenarios). The current land cover provided protection against landslide susceptibility, even during extreme rainfall events, for different return periods. The 30-year return period was a critical condition for a significant stability reduction. In addition, forest species provide different mitigation effects due to their root system features. The results showed that species with deep root systems, such as oaks, provide more effective slope stability than other species, such as pines. This study helps to quantify the mitigation effects of vegetation cover and suggests that physically based probabilistic models can be used at the regional scale to detect the areas prone to failure and the triggering of rainfall-induced shallow landslides. This approach can be important in land planning and management to mitigate risks in mountainous regions. Full article

Facing global warming’s consequences is a major issue in the present times. Regarding the climate, projections say that heavy rainfalls are going to increase with high probability together with temperature rise; thus, the hazard related to rainfall-induced shallow landslides will likely increase in density over susceptible territories. Different modeling approaches exist, and many of them are forced to make simplifications in order to reproduce landslide occurrences over space and time. Process-based models can help in quantifying the consequences of heavy rainfall in terms of slope instability at a territory scale. In this study, a narrative review of physically based deterministic distributed models (PBDDMs) is presented. Models were selected based on the adoption of the infinite slope scheme (ISS), the use of a deterministic approach (i.e., input and output are treated as absolute values), and the inclusion of new approaches in modeling slope stability through the ISS. The models are presented in chronological order with the aim of drawing a timeline of the evolution of PBDDMs and providing researchers and practitioners with basic knowledge of what scholars have proposed so far. The results indicate that including vegetation’s effects on slope stability has raised in importance over time but that there is still a need to find an efficient way to include them. In recent years, the literature production seems to be more focused on probabilistic approaches. Full article

Rwanda, in eastern tropical Africa, is a small, densely populated country where climatic disasters are often the cause of considerable damage and deaths. Landslides are among the most frequent hazards, linked to the country’s peculiar configuration including high relief with steep slopes, humid tropical climate with heavy rainfall, intense deforestation over the past 60 years, and extensive use of the soil for agriculture. The Karongi region, in the west-central part of the country, was affected by an exceptional cluster of more than 700 landslides during a single night (6–7 May 2018) over an area of 100 km². We analyse the causes of this spectacular event based on field geological and geomorphology investigation and CHIRPS and ERA5-Land climate data. We demonstrate that (1) the notably steep slopes favoured soil instability; (2) the layered soil and especially the gravelly, porous C horizon allowed water storage and served as a detachment level for the landslides; (3) relatively low intensity, almost continuous rainfall over the previous two months lead to soil water-logging; and (4) acoustic waves from thunder or mechanical shaking by strong wind destabilized the water-logged soil through thixotropy triggering the landslides. This analysis should serve as a guide for forecasting landslide-triggering conditions in Rwanda. Full article

Monitoring natural slopes, embankments, and unstable slopes is crucial to reducing predisposition to mass movements, especially in areas with geotechnical instability and high rainfall. This study proposes a methodology to identify geotechnical and pluviometric triggers of mass movements in railway slopes. It involves registering slopes and embankments along the railroad, recording accumulated rainfall indices, and documenting associated accidents. The experimental program included a cadastral survey at a pilot site on the MRS company’s railway network in the Paraopeba branch, Minas Gerais, Brazil. Surface and subsurface drainage conditions, anthropic interventions, and modifications affecting slope stability were also examined. Additionally, the history of accidents involving geotechnical and regional rainfall indices were incorporated to identify potential triggering events for mass movements. The study found a good correlation between landslide records and geotechnical risk mapping but a low correlation between landslide records and rainfall isohyets. The latter result is attributed to the low density and poor distribution of rainfall data and active pluviometers in the region. Overall, understanding the geological–geotechnical characteristics of slopes and the correlation between accidents and rainfall indices provides valuable insights for predicting potential landslide occurrences. Full article