Types Of Landslides Research Articles

Multi-scale analysis of the susceptibility of different landslide types and identification of the main controlling factors

Multi-scale analysis of the susceptibility of different landslide types and identification of the main controlling factors

Numerical Modeling of Tsunamis Generated by Subaerial, Partially Submerged, and Submarine Landslides

Using the existing two-dimensional experimental data and Open-source Fields Operation and Manipulation (OpenFOAM) software, this study performs a comprehensive comparative analysis of three types of landslide-generated tsunamis (subaerial, partially submerged, and submarine). The primary objective was to assess whether numerical simulations can accurately reproduce the experimental results of each type and to compare the predictive equations of the tsunami amplitudes derived from experimental and simulated data. The mesh size and dynamic viscosity parameters were initially optimized for a specific partially submerged landslide tsunami scenario and then applied across a broader range of experimental scenarios. Most of the simulated wave amplitudes remained within the 50% error margin, although significant discrepancies were observed between landslide types. When focusing on the crest amplitude of the first wave, the simulations of subaerial landslides least deviated from the experimental data, with a mean absolute percentage error of approximately 20%, versus approximately 40% for the partially submerged and submarine landslides. The predictive equations derived from the simulations closely matched those from the experimental data, confirming that OpenFOAM can effectively capture complex landslide–tsunami dynamics. Nonetheless, variations in the coefficients related to slope angles highlight the need for further calibration to enhance the simulation fidelity.

Utilizing deep learning approach to develop landslide susceptibility mapping considering landslide types

Utilizing deep learning approach to develop landslide susceptibility mapping considering landslide types

Rainfall characteristics and magnitude control the volume of shallow and deep-seated landslides: Inferences from analyses using a simple runoff model

Landslide volume plays a pivotal role in controlling landslide movement and potential damage. Although rainfall is widely recognized as one of the most important factors underlying landslide occurrence worldwide, its impact on landslide volume has been investigated only for individual landslide types. In this study, we show that rainfall characteristics and magnitude control the volume produced by both shallow and deep-seated landslides. A total of ten shallow and deep-seated landslides in Japan were compiled with volume, occurrence time, and rainfall data. Rainfall characteristics that triggered landslides were identified using the Soil Water Index and the three-layer tank model, which is a simple runoff model, and magnitude was quantified based on lag time. A strong positive correlation was found between lag time and landslide volume, indicating that landslide volume increases with increasing magnitude of rainfall to induce landslides. This study is the first attempt to suggest a relationship between rainfall magnitude and the volume produced by shallow and deep-seated landslides systematically and will promote the development of landslide risk management strategies.

The Influence of Claystone Type on Landslide Hazard: A Case Study

The landslide is more common in locations with steep slopes and is unstable. Developing an early warning system is the aim of this study, which focuses on Nanggulan, Yogyakarta Special Region-Indonesia. The Nanggulan has a wavy shape with a minor slope and is made up of Eocene sedimentary rocks. The landslide indicators, such as curved walls, cracked roads, fractured building walls, subsided building floors, sinkholes, and the creation of crown scarps, were discovered at various sites. X-Ray Diffraction (XRD) analysis and soil index properties of rock and soil samples, were used in the research. The XRD examination revealed the presence of smectite-group clay minerals (monmorillonite and saponite). Calculating the soil index parameters yielded that the soil has a specific gravity of 2.173–2.62, water content of 18.207–47.653%, liquid limit of 45–77%, plastic limit of 21–43%, plasticity index of 18–42%, cohesiveness of 1–91 kPa, and a friction angle of 10°–54°. The direction of the slope is more than 20°, so there is little possibility of planar failure, and the Nanggulan is stable. However, from the smectite-group clay minerals, the plasticity index and the liquid limit value indicate that the rock is cohesive and easy to move when it is wet. This form of landslide typically occurs on gently sloping terrain, is controlled by expansive lithology, has a relatively slow movement rate, and indicates that the landslide type was creep.

Spatio-temporal deformation characteristics and triggering factors of Wangjiashan landslide

Hydrodynamic-induced landslide is a type of landslide whose stability can be reduced by rainfall, groundwater or reservoir water level fluctuations (RWLF). Based on the monitoring data of Wangjiashan landslide located in the reservoir area of Baihetan Hydropower Station, this article illustrates the deformation characteristics of Wangjiashan landslide on time and space distribution. Spearman correlation coefficients are used to make analysis of the relationship between surface deformation and different dynamic factors such as RWLF, seismic activity, and rainfall. The results indicate that RWLF is a dominant dynamic factor of Wangjiashan landslide. Besides, two variables of deformation factors are presented to find differences during various deformation periods. The results show that the displacement and its rate are both strongly correlated with the RWLF, especially during the acceleration period and the deceleration stage. It is indicated that Wangjiashan landslide is a typical hydrodynamically induced landslide. This study provides a useful reference for understanding the instability mechanism of the landslide.

The influence of erosion on the dynamic process of landslide in Xinmo Village, Maoxian

A large-scale, high-speed, long-runout landslide occurred in Xinmo Village, Maoxian, Sichuan Province, China, on June 24, 2017. It was characterized by fast sliding speed, rapid volume growth, and large impact area. The dynamic process of such landslides and the influence of erosion on the dynamic process are studied by field investigation, numerical inversion and simulation. The results showed that entrainment erosion was a major factor of landslide volumetric change and a salient feature of the landslide process. An exponential equation relating the erosion rate and the deposition volume was established. Moreover, the study found that a slight change of the erosion rate (1e-4) also had a significant impact on the lateral spreading, longitudinal runout, and vertical erosion. As the erosion rate increased, the lateral spreading, longitudinal runout, and vertical erosion of this type of landslide became more obvious. By using the coefficient of variation method, it was obtained that the erosion rate had a greater influence on the vertical erosion than on the lateral spreading and longitudinal runout. In the study of the velocity of the rock avalanche under different erosion conditions, it was found that the erosion amount and the landslide velocity were not strictly linearly related. This study has important significance for understanding the dynamic process and erosion effect of rock avalanche, and provides useful references and insights for future research in related fields.

Multitemporal analysis of cliffs evolution along an Atlantic African coast (Safi Region, Morocco)

Unstable coastal cliffs represent a major threat to coastal infrastructure, housing, and economic activities, which depend on coastal stability. Understanding recession rates and the factors influencing them is therefore essential for enhancing risk prediction and management. Here, we investigated the evolution of coastal cliffs in a crucial sector of the Atlantic African coast in Morocco, stretching from Cap Beddouza in the north to Jorf Lihoudi in the south, covering an area of around 48 km and including the large city of Safi. The instability of these cliffs constitutes the main coastal geological hazard of the area, which has its geomorphological expression in different types of landslides punctuating the coastal cliff. We employed multidecadal aerial imagery along with GIS technique to calculate the rate of change of the cliff over 66 years. Our results indicate that most of the Safi Region coastal zone has undergone recession with rates of change generally variable from 0.04 to 0.08 m/yr ± 0.01 m. The central part of the study area, conversely, experienced the highest retreat rate, exceeding 0.10 m/yr. The spatial variability of recession rates is explained through geological and morphological factors such as the nature of low-strength clay rock formations, favoring large-scale gravity movements. These data are crucial to better define the current level of coastal hazard in this densely populated portion of the Moroccan coast, given that cliff recession have considerable effects on the economic, social and environmental risk of the area. Moreover, this study represents one of the first applications of the Digital Shoreline Analysis System (DSAS) method to an African coastline segment, specifically from Cape Beddouza to the Lihoudi cliffs. More generally, it is among the few studies focused on cliff recession rates in Africa. While a similar application has been conducted for the cliff base in the northern part of the same study area (Raja et al., 2023), that study primarily addresses coastal cliff failure hazards along the Safi coastline in Morocco. In contrast, the present study is focused on determining long-term cliff recession rates and understanding the distribution of these rates and modes of retreat in relation to the physical processes affecting the study area.

Monitoring and Evaluation of Debris Flow Disaster in the Loess Plateau Area of China: A Case Study

The Loess Plateau area, with complex geomorphological features and geological structure, is highly prone to geologic disasters such as landslides and debris flow, which cause great losses. To investigate the initiation mechanism of landslide and debris flow disasters and their spreading patterns, historical satellite images in the Laolang gully were collected and digitized to generate three-dimensional topographic and geomorphological maps. Typical landslides were selected for landslide thickness measurement using a standard penetrometer and high-density electrical method. Numerical models were established to simulate the occurrence and development of landslides under different working conditions and to evaluate the spreading range based on the propagation algorithm and friction law. The results show that the 10 m resolution DEM data are well matched with the potential hazard events observed in the field site. The smaller the critical slope threshold, the greater the extent and distance of landslide spreading. The larger the angle of arrival, the greater the energy loss, and therefore the smaller the landslide movement distance. The results can provide scientific theoretical guidance for the prevention and control of rainfall-induced landslide and debris flow disasters in the Loess Plateau area.

Research on the Pile–Soil Interaction Mechanism of Micropile Groups in Transparent Soil Model Experiments

Micropile groups (MPGs) are typical landslide resistant structures. To investigate the effects of these two factors on the micropile–soil interaction mechanism, seven sets of transparent soil model experiments were conducted on miniature cluster piles. The soil was scanned and photographed, and the particle image velocimetry (PIV) technique was used to obtain the deformation characteristics of the pile and soil during lateral loading. The spatial distribution information of the soil behind the pile was obtained by a 3D reconstruction program. The results showed that a sufficient roughness of the pile surface was a necessary condition for the formation of a soil arch. If the surface of the pile was smooth, stable arch foundation formation was difficult. When the roughness of the pile surface increases, the soil arch range behind the pile and the load-sharing ratio of the pile and soil will increase. After the roughness reaches a certain level, the above indicators hardly change. Pile spacing within the range of 5–7 d (pile diameters) was suitable. The support effect was poor when the pile spacing was too large. No stable soil arch can be formed, and the soil slips out from between the piles.

Rainfall and water level fluctuations dominated the landslide deformation at Baihetan Reservoir, China

Understanding the deformation patterns of different types of landslides around reservoirs is crucial for precise prevention and control of related hazards. However, under the complex coupling effect of extreme rainfall and reservoir level fluctuations, the response between various types of landslides and triggering factors is still unclear. Our study employed the Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) method and wavelet analysis to undertake an early identification and quantitative analysis of deformation patterns of unstable slopes in the Baihetan Reservoir region, China, and explored the responses of different types of landslide deformation to rainfall and reservoir water level fluctuations. The findings reveal distinct differences in the deformation characteristics of unstable slopes around the reservoir. The quantitative analysis of normalized displacement indicated that the convergent-type landslide exhibits an initial rapid movement that gradually tends to be stable, following an exponential function. The steady-type landslide moves at a consistent speed along a linear trendline. The exponential-type landslide starts slowly and then progressively accelerates. The periodic-type landslide displays periodic fluctuations in displacement, which conforms to the Fourier periodic function. Furthermore, comparisons with antecedent rainfall and reservoir water levels reveal that the convergent-type landslide is significantly influenced by water level fluctuations, and both steady-type and exponential-type landslides are subject to the dual impact of rainfall and water level fluctuations, while the periodic-type landslide exhibits a notable response to rainfall. Therefore, this research aims to provide a scientific basis for the prevention and mitigation of geohazards in reservoir areas.

Investigation of planar sliding deformation and analysis of the damage mechanism of a rocky landslide in Yaoping triggered by highway excavation in Hubei, China

During projects to build roads in China's mountainous areas, which are often characterized by the poor stability of rocky slopes, cases of deformation damage occur frequently. Because of the wide distribution of rocky landslides in the smooth layer, the unavoidable perturbation caused by engineering construction and the seriousness of landslide disasters, the destruction of this type of landslide and the research into prevention of the mechanism cannot be ignored. On 6 February 2023, a rock slide occurred in Yaoping village, Hubei Province, China. Using field investigations, Google satellite images, unmanned aerial vehicle photography, indoor testing and numerical simulations, we analysed the geological situation, deformation characteristics, damage process and triggering mechanism. The results show that the Yaoping landslide is a typical downward plane-sliding rock slide induced by the excavation of a highway. When strain softening occurs, the shear strength and friction coefficient of the slip zone soil are significantly reduced. Excavation caused the factor of safety of the slope to decrease substantially, with a maximum decrease rate of 60.7%. Excavation is considered to be the extrinsic factor that triggered the occurrence of the Yaoping landslide, while the reduction of landslide resistance caused by strain softening of the soil in the slip zone is the intrinsic direct factor that led to the occurrence of this type of landslide. The Yaoping landslide has obvious traction landslide characteristics. The landslide from deformation to destruction has four stages: creep at the leading edge of the landslide; traction deformation in the middle and back of the landslide; slip belt softening; and integral sliding. The prevention and control of this type of landslide requires a larger scope and depth of investigation, in order to identify in advance the possible soft surface in the rock layer, to speculate on the possible formation of landslide destruction mode, and to determine the support scheme and scope according to the geological conditions of the slopes on both sides of the highway. The slip zone soil of the Yaoping landslide was used to obtain the strength index of slip zone soil, which provides data support for the overall deformation characterization of the landslide. The results can provide a reference for the risk management and prevention of rock slides caused by human engineering activities during the excavation of roads.

Experimental Study on Shear Creep Characteristics of Residual Soil with Different Stone Content

The residual soil on a slope can slowly move downward under the influence of gravity, forming a creep landslide. These types of landslides are known for their extensive coverage, significant magnitude, and prolonged duration of hazard. A systematic study of the creep properties of creep landslide geotechnical bodies is essential for the analysis of the deformation process and long-term safety evaluation of landslides. This paper focuses on studying a creep landslide involving residual soil in western Henan Province. The creep characteristics of residual soil with different stone content are investigated through direct shear creep experiments. The findings reveal that stone content has a profound impact on the creep behavior of residual soil. As the stone content of the soil increased, the structure of the test soil changed significantly, resulting in a gradual decrease in its shear creep. The Burgers model can effectively fit the deceleration creep and steady-state creep stages of the residual soil. With the increase in stone content, the four parameters of the Burgers model show a significant increase, with the instantaneous elasticity coefficient G1 and the viscosity coefficient η1 experiencing more noticeable changes. The average long-term strength of specimens with different stone content is only 54% of their instantaneous strength. Additionally, as the stone content increases, the ratio of long-term strength to instantaneous strength also increases. Notably, the long-term strength of specimens with 10–30% stone content is significantly lower than that of specimens with 50–70% stone content.

Identification of Landslide Precursors for Early Warning of Hazards with Remote Sensing

Landslides are a widely recognized phenomenon, causing huge economic and human losses worldwide. The detection of spatial and temporal landslide deformation, together with the acquisition of precursor information, is crucial for hazard prediction and landslide risk management. Advanced landslide monitoring systems based on remote sensing techniques (RSTs) play a crucial role in risk management and provide important support for early warning systems (EWSs) at local and regional scales. The purpose of this article is to present a review of the current state of knowledge in the development of RSTs used for identifying landslide precursors, as well as detecting, monitoring, and predicting landslides. Almost 200 articles from 2010 to 2024 were analyzed, in which the authors utilized RSTs to detect potential precursors for early warning of hazards. The applications, challenges, and trends of RSTs, largely dependent on the type of landslide, deformation pattern, hazards posed by the landslide, and the size of the area of interest, were also discussed. Although the article indicates some limitations of the RSTs used so far, integrating different techniques and technological developments offers the opportunity to create reliable EWSs and improve existing ones.

Landslide Distribution and Development Characteristics in the Beiluo River Basin

The Beiluo River Basin, situated in the central region of the Loess Plateau, frequently experiences landslide geological disasters, posing a severe threat to local lives and property. Thus, establishing a detailed database of historical landslides and analyzing and revealing their development characteristics are of paramount importance for providing a foundation for geological hazard risk assessment. First, in this study, landslides in the Beiluo River Basin are interpreted using Google Earth and ZY-3 high-resolution satellite imagery. Combined with a historical landslide inventory and field investigations, a landslide database for the Beiluo River Basin is compiled, containing a total of 1781 landslides. Based on this, the geometric and spatial characteristics of the landslides are analyzed, and the relationships between the different types of landslides and landslide scale, stream order, and geomorphological types are further explored. The results show that 50.05% of the landslides have a slope aspect between 225° and 360°, 68.78% have a slope gradient of 16–25°, and 38.97% are primarily linear in profile morphology. Areas with a high landslide density within a 10 km radius are mainly concentrated in the loess ridge and hillock landform region between Wuqi and Zhidan Counties and in the loess tableland region between Fu and Luochuan Counties, with a significant clustering effect observed in the Fu County area. Loess–bedrock interface landslides are relatively numerous in the northern loess ridge and hillock landform region due to riverbed incision and the smaller thickness of loess in this area. Intra-loess landslides are primarily found in the southern loess tableland region due to headward erosion and the greater thickness of loess in this area. Loess–clay interface landslides, influenced by riverbed incision and the limited exposure of red clay, are mainly distributed in the northern part of the southern loess tableland region and on both sides of the Beiluo River Valley in Ganquan County. These results will aid in further understanding the development and spatial distribution of landslides in the Beiluo River Basin and provide crucial support for subsequent landslide susceptibility mapping and geological hazard assessment in the region.

Study on Temporal and Spatial Distribution of Landslides in the Upper Reaches of the Yellow River

The geological structure of the upper reaches of the Yellow River is complex, especially in the Sigouxia-Laganxia section. It has always been a high-incidence area of landslide disasters, which poses a threat to the safe operation of the upper reaches of the Yellow River. In this study, based on the high-precision remote sensing image data, the spatial distribution of each landslide was obtained by superimposing the remote sensing image and the 1:50,000 digital elevation model (DEM). Some typical landslides were selected for detailed field investigation and field verification. The results show that the remote sensing image characteristics of landslides in the upper reaches of the Yellow River are obvious. Through remote sensing interpretation and field investigation, a total of 508 landslides of various types were found, including 24 giant landslides. The spatial spreading patterns of landslides mainly include six types: dumb-bell shape, rectangle, saddle type, long arc shape, triangle, and side-by-side shape. The length and width of the landslide deposit are mainly concentrated at 550–1500 m and 600–1500 m, and the average elevation of the sliding body is mainly concentrated between 2000 and 2800 m. The average slope of the landslide is mainly distributed between 15–20°. Giant landslides are mainly distributed in the Jianzha basin area, surrounded by the Jishishan fault and the Lajishan fault in the West Qinling Mountains. The spatial distribution characteristics of giant landslides have obvious regional differences due to different factors such as lithologic differences and riverside erosion. The research results are of great significance for the early identification, prevention, and mitigation of landslide disasters in the upper reaches of the Yellow River.

Landslide type inference based on statistical analysis of a high-resolution digital elevation model in Gorce National Park, Poland

High-resolution digital elevation models are commonly utilized for detecting and classifying landslides. In this study, we aim to refine landslide detection and classification by analyzing the geometry of landslides using slope and aspect, coupled with descriptive statistics up to the fourth central moment (kurtosis). Employing the Monte Carlo method for creating terrain topography probability distributions and ANOVA tests for statistical validation, we analyzed 364 landslides in Gorce National Park, Poland, revealing significant kurtosis differences across landslide types and lithologies. This methodology offers a novel approach to landslide classification based on surface geometry, with implications for enhancing scientific research and improving landslide risk management strategies.

Hazard assessment of seismic-collapsed loess landslides on the Loess Plateau as exemplified by the M6.2 earthquake in Jishishan County, China

The Loess Plateau is marked by intense neotectonic activity and frequent earthquakes. Its unique physico-mechanical properties, combined with the granular overhead pore structure of loess, render it prone to seismic landslides triggered by strong earthquakes. Different types of loess seismic landslides have distinct formation mechanisms, disaster-causing characteristics, and risk assessment programs. In this study, the risk of seismic-collapsed loess landslides as one of the types of loess seismic landslides was evaluated on the Loess Plateau. A risk zoning map for seismic-collapsed loess landslides on the Loess Plateau, considering various exceedance probabilities, was compiled by assessing eight factors. These factors include peak ground acceleration, microstructure of loess, and were evaluated using both the minimum disaster-causing seismic peak ground acceleration zoning method and the analytic hierarchy process. The following conclusions were obtained: (1) Earthquakes are the primary inducing factor for seismic-collapsed loess landslides, with other factors serving as influencers, among which the microstructure of loess carries the highest weight; (2) Across various exceedance probabilities, the likelihood of seismic-collapsed loess landslides occurring at 63% of the 50-year exceedance probability is low. Moreover, as the minimum hazard-causing seismic peak ground acceleration increases, the risk of occurrence of seismic-collapsed loess landslides rises, leading to a gradual expansion of the area share in moderate and high-risk zones; (3) Hazard evaluation results align well with existing data on seismic-collapsed loess landslides and findings from field investigations. The case of seismic-collapsed loess landslides induced by the M6.2 magnitude earthquake in Jishishan County, China, is presented as an illustration. The combined use of the minimum hazard-causing seismic peak ground acceleration zoning method and the analytic hierarchy process method offers a reference for geohazard hazard assessment, with earthquakes as the primary inducing factor and other factors as influencers.

Landslide susceptibility assessment using different rainfall event-based landslide inventories: advantages and limitations

AbstractThe present work aims to evaluate potential sources of uncertainty associated with rainfall-triggered event-based landslide inventories within the framework of landslide susceptibility assessment. Therefore, this study addresses the following questions: (i) How representative is an event-based landslide inventory map of the total landslide activity and distribution in a study area?; (ii) How reliable is an event-based landslide susceptibility map?; (iii) How appropriate is an event-based landslide inventory map for independently validating a landslide susceptibility map? To address these questions, two independent and contrasting rainfall event-based landslide inventories were used, together with a historical landslide inventory, to assess landslide susceptibility for different types of landslides in a study area located north of Lisbon, Portugal. The results revealed the following findings: (i) contrasting rainfall critical conditions for failure can trigger similar landslide types, although they may vary in size and be spatially constrained by different predisposing conditions, particularly lithology and soil type; (ii) landslide susceptibility models using event-based landslide inventories are not reliable in the study area, regardless of the landslide inventory map used for training and validation; and (iii) complementary sources of uncertainty results from using incomplete historical landslide inventories to assess landslide susceptibility and non-totally independent landslide inventories for modeling validation. The present study enhances the understanding of regional landslide susceptibility patterns based on contrasting rainfall-trigger conditions, providing valuable information to minimize exposure; to design regional landslide early warning systems for specific rainfall-trigger landslide events; and to improve the response and preparedness of civil protection services.

The Diverse Mountainous Landslide Dataset (DMLD): A High-Resolution Remote Sensing Landslide Dataset in Diverse Mountainous Regions

The frequent occurrence of landslides poses a serious threat to people’s lives and property. In order to evaluate disaster hazards based on remote sensing images via machine learning means, it is essential to establish an image database with manually labeled boundaries of landslides. However, the existing datasets do not cover diverse types of mountainous landslides. To address this issue, we propose a high-resolution (1 m) diverse mountainous landslide remote sensing dataset (DMLD), including 990 landslide instances across different terrain in southwestern China. To evaluate the performance of the DMLD, seven state-of-the-art deep learning models with different loss functions were implemented on it. The experiment results demonstrate not only that all of these deep learning methods with different characteristics can adapt well to the DMLD, but also that the DMLD has potential adaptability to other geographical regions.