Triggering Mechanism Of Landslides Research Articles

Balancing Submarine Landslides and the Marine Economy for Sustainable Development: A Review and Future Prospects

To proactively respond to the national fourteenth Five-Year Plan policy, we will adhere to a comprehensive land and sea planning approach, working together to promote marine ecological protection, optimize geological space, and integrate the marine economy. This paper provides a comprehensive review of the sustainable development of marine geological hazards (MGHs), with a particular focus on submarine landslides, the marine environment, as well as the marine economy. First, the novelty of this study lies in its review and summary of the temporal and spatial distribution, systematic classification, inducible factors, and realistic characteristics of submarine landslides to enrich the theoretical concept. Moreover, the costs, risks, and impacts on the marine environment and economy of submarine engineering activities such as oil and gas fields, as well as metal ores, were systematically discussed. Combined with the current marine policy, an analysis was conducted on the environmental pollution and economic losses caused by submarine landslides. Herein, the key finding is that China and Mexico are viable candidates for the future large-scale offshore exploitation of oil, gas, nickel, cobalt, cuprum, manganese, and other mineral resources. Compared to land-based mining, deep-sea mining offers superior economic and environmental advantages. Finally, it is suggested that physical model tests and numerical simulation techniques are effective means for investigating the triggering mechanism of submarine landslides, their evolutionary movement process, and the impact on the submarine infrastructure. In the future, the establishment of a multi-level and multi-dimensional monitoring chain for submarine landslide disasters, as well as joint risk assessment, prediction, and early warning systems, can effectively mitigate the occurrence of submarine landslide disasters and promote the sustainable development of the marine environment and economy.

The Influence of Vertical Seismic Acceleration on the Triggering of Landslides Constrained by Bedding Faults under an Inertial Frame Reference: The Case of the Daguangbao (DGB) Landslide

The Daguangbao (DGB) landslide was the largest landslide that was triggered by the 2008 Wenchuan earthquake with a magnitude of Ms8.0. The sliding surface of this landslide was constrained on a bedding fault 400 m below the ground surface. Seismic records show that the landslide suffered not only from strong horizontal but also vertical ground shaking that was almost equal to the horizontal component. In this study, to reveal the landslide triggering mechanism of the DGB landslide, this study ignores the steep dipping tension fracture section and the leading edge-locking section of the trailing edge of the DGB landslide, and the geological model of the large optical package landslide is generalized into a block model with the bottom controlled slip soft zone as the interface. Based on the improved Newmark method that considers vertical ground motion, the three-way seismic acceleration data and the shear strength parameter of the sliding surface being taken as a variable are used to calculate the cumulative permanent displacement of the slider. Then, by considering the cumulative permanent displacement ratio of vertical seismic acceleration or not and the cumulative permanent displacement ratio value considering the inertial force as the index, the response characteristics of the cumulative permanent displacement of the block-to-vertical ground motion and inertial forces were analyzed. The results show that both the horizontal inertial force and the vertical acceleration significantly increased the permanent displacement. The permanent displacement is 4.9 cm when considering the vertical acceleration, whereas it is only 2.0 cm without taking this into account. The contribution of vertical acceleration is significantly enlarged (87.8–90.7%) by the decreasing of the internal friction angle of the slide surface, while it is less influenced (5–27.4%) by the cohesion. Compared with the lower shear strength parameter of the sliding surface, the contributions of vertical acceleration and inertial force to the permanent displacement are more obvious when the shear strength parameter of the sliding surface is higher. When ϕ > 18°, the D/D* is greater than 1, and the maximum D/D* reaches 7. The fast accumulation event of permanent displacement is triggered in the concentration stage of the seismic energy release. In the DGB landslide area, 50% of the energy is released within 30–50 s, as indicated by the acceleration peaks recorded at the nearest seismic station, Qingping station. It is assumed that the DGB landslide may be triggered at 30–50 s due to half of the seismic energy being released during that time span.

A multi-scale approach for deterministic analysis of landslide triggering and mass flow mechanism at Kaliasaur (Rudraprayag)

A multi-scale approach for deterministic analysis of landslide triggering and mass flow mechanism at Kaliasaur (Rudraprayag)

Case Studies and Numerical Investigation of Landslide Triggering Mechanisms in Western Ghats, Kerala, India

Case Studies and Numerical Investigation of Landslide Triggering Mechanisms in Western Ghats, Kerala, India

Hydro–Mechanical Behaviour of a Rainfall-Induced Landslide by Instrumental Monitoring: Landslide–Rainfall Threshold of the Western Black Sea Bartin Region of Türkiye

Bartin City is located in the Western Black Sea Region of Türkiye, where rainfall-induced landslides are more frequently observed. Although it is known that many landslides are induced by rainfall, there is limited knowledge regarding how rainfall triggers these landslides in the city. To clarify the triggering mechanisms of rainfall-induced landslides, a detailed field monitoring program was performed on a chosen area to represent landslides in Bartin. The instrumentation included the measurements of site suction, volumetric water content, groundwater level, and rainfall amount over a period of two years. Various stability analyses were performed regarding pore pressures after both transient flow infiltration analysis and site-measured suction values. The rainfall intensity–duration thresholds were obtained for both dry and wet periods as a result of the numerical analyses performed by means of parameters obtained from field monitoring. The results show that the wet period conditions create more critical conditions before failure compared to the dry period conditions, so landslides occur more easily in wet periods. According to the landslide–rainfall threshold relations, landslide-risk limits are reached if the rainfall intensity is over 10 mm/h for the dry periods and lasts between 0.85 h and 17 h depending on the saturated hydraulic conductivity of the soil. When the rainfall intensities are less than 10 mm/h, longer rainfall durations are needed for a landslide to occur. For the wet periods, landslide-risk situations are encountered if the rainfall intensity over 1 mm/h continues for 0.36 h–3.67 h, depending on the saturated hydraulic conductivities.

Insight from a Physical-Based Model for the Triggering Mechanism of Loess Landslides Induced by the 2013 Tianshui Heavy Rainfall Event

Rainfall-induced landslides pose a significant threat to human life, destroy highways and railways, and cause farmland degradation in the Loess Plateau. From 19 June 2013 to 26 July 2013, continuous and heavy rainfall events occurred in the Tianshui area, Gansu Province. This strong rainfall process included four short-term serious rainfall events and long-term intermittent rainfall, triggering many shallow loess landslides. To improve our understanding of this rainfall process as the triggering mechanism of the loess landslides, we conducted the physical-based spatiotemporal prediction of rainfall-induced landslides. By utilizing precipitation data recorded every 12 h from the rain gauge stations and 51 soil samples from within a 50 km radius of the study area, we predicted 1000 physical-based model-calculated pictures of potential landslides, and the slope failure probability (Pf) of the study area was obtained by Monte Carlo simulations. The model was validated by the actual landslide data of the 2013 heavy rainfall event, and the effects of the precipitation process and the trigger mechanism on the landslides were discussed. The results showed that the fourth rainfall event had the best prediction ability, while the third event had the second-best prediction ability. There was a solid linear link between the antecedent precipitation (Pa) and the predicted landslide area (Pls) based on the fitting relationship, indicating that antecedent rainfall may play a significant role in the occurrence of landslides in the region. By comparing the distribution of the predicted results of the four heavy rainfall events with the actual landslide, we observed that the first two rainfall processes may not have been the main reason for slope failure, contributing only to prepare for the landslides in the later period. The superposition of the fourth and third rainfall events finally determined the spatial distribution characteristics of the landslide induced by the 2013 heavy rainfall event.

Landsifier v1.0: a Python library to estimate likely triggers of mapped landslides

Abstract. Landslide hazard models aim at mitigating landslide impact by providing probabilistic forecasting, and the accuracy of these models hinges on landslide databases for model training and testing. Landslide databases at times lack information on the underlying triggering mechanism, making these inventories almost unusable in hazard models. We developed a Python-based unique library, Landsifier, that contains three different machine-Learning frameworks for assessing the likely triggering mechanisms of individual landslides or entire inventories based on landslide geometry. Two of these methods only use the 2D landslide planforms, and the third utilizes the 3D shape of landslides relying on an underlying digital elevation model (DEM). The base method extracts geometric properties of landslide polygons as a feature space for the shallow learner – random forest (RF). An alternative method relies on landslide planform images as an input for the deep learning algorithm – convolutional neural network (CNN). The last framework extracts topological properties of 3D landslides through topological data analysis (TDA) and then feeds these properties as a feature space to the random forest classifier. We tested all three interchangeable methods on several inventories with known triggers spread over the Japanese archipelago. To demonstrate the effectiveness of developed methods, we used two testing configurations. The first configuration merges all the available data for the k-fold cross-validation, whereas the second configuration excludes one inventory during the training phase to use as the sole testing inventory. Our geometric-feature-based method performs satisfactorily, with classification accuracies varying between 67 % and 92 %. We have introduced a more straightforward but data-intensive CNN alternative, as it inputs only landslide images without manual feature selection. CNN eases the scripting process without losing classification accuracy. Using topological features from 3D landslides (extracted through TDA) in the RF classifier improves classification accuracy by 12 % on average. TDA also requires less training data. However, the landscape autocorrelation could easily bias TDA-based classification. Finally, we implemented the three methods on an inventory without any triggering information to showcase a real-world application.

Framework for the identification of shallow ground movement in modified slopes (an expert opinion)

This paper has discussed and analyzed some significant ways to quickly find the root course of landslides on slopes, especially on shallow artificial slopes. Many mechanisms that trigger ground movement leading to landslides in slopes are discussed here. The general idea was to study the occurrence of slips on a modified slope under certain environmental conditions for a specific duration and develop a simple framework that can help to identify landslides’ causative factors subjectively. This whole idea was to help locals and other experts easily identify the triggering mechanisms of landslides to reveal the possible time when the slides will occur and control their impact. Furthermore, a framework was developed to help us understand the critical factors leading to shallow landslides on modified slopes. Establishing the mechanism that triggers landslides in an area helps greatly identify the landslides-prone locations, especially for the locals living in high-risk areas. The research also presented significant forms of landslides with their presumed causes. Although the general causes of landslides are not limited to what was presented in this text, the environment is the main factor deciding the nature and extent of landslides in an area.

Evaluation of horizontal ground motion waveforms at Sedongpu Glacier during the 2017 M6.9 Mainling earthquake based on the equivalent Green's function

The terrain along the Tibet Railway is primarily steep mountains and valleys with complex geological structures. The occurrence of the Mainling earthquake indicates that the intensity of seismicity in the eastern structural junction area has strengthened, and the potential risk of earthquake-induced disasters such as landslides and debris flows is also increasing. The earthquake engineering community generally recognizes that the prediction of near-field strong ground motion can reduce the disasters caused by future large earthquakes and can guide earthquake prevention, disaster reduction and seismic design along the Sichuan–Tibet railway. The M6.9 Mainling earthquake affected the stability of Sedongpu Glacier near the epicentre. A glacier avalanche occurred under the coupling of multiple factors, including post-earthquake and precipitation events. The waveform and response spectra of a strong earthquake are key input parameters for investigating the seismic triggering mechanisms of landslides and glacier avalanches and accurately reproducing the dynamics of such disasters. In this paper, the concept of the equivalent Green's function is introduced, and various source parameter uncertainties are fully considered. The waveform and response spectra of the Mainling earthquake at Sedongpu Glacier are simulated, and the most likely seismic waveform is comprehensively assessed from multiple perspectives. This work can provide reliable acceleration waveform input for the analysis of ground motion damage and the study of earthquake-induced disaster mechanisms at important locations along the Sichuan–Tibet railway and provide a scientific reference for earthquake prevention and disaster reduction along the railway.

Slope with Predetermined Shear Plane Stability Predictions under Cyclic Loading with Innovative Time Series Analysis by Mechanical Learning Approach.

We propose a mechanical learning method that can be used to predict stability coefficients for slopes where slopes with predetermined shear planes are subjected to cyclic seismic loads under undrained conditions. Firstly, shear tests with cyclic loading of different parameters were simulated on designated slip zone soil specimens, in which the strain softening process leading to landslide occurrence was closely observed. At the same time, based on the limit equilibrium analysis of the Sarma method, the variation of slope stability coefficients under different cyclic loads was investigated. Finally, a Box–Jenkins’ modeling approach is used to predict the data from the time series of slope stability coefficients using a mechanical learning approach. The simulation results show that (1) reduction in coordination number can be an accurate indicator of the level of strain softening and evolutionary processes; (2) the gradual reduction of shear stress facilitates the soil strain softening process, while different cyclic loading stress amplitudes will result in rapid penetration or non-penetration of the fracture zone by means of particulate flow. Although the confining pressure of the slip zone soil can inhibit the increase of fractures, it has a limited inhibitory effect on strain softening; (3) based on field observations of the slope stability factor and stress field, two possible landslide triggering mechanisms are described. (4) Mechanical learning of time series can accurately predict the changing pattern of stability coefficients of slopes without loading. This study establishes a potential bridge between the geological investigation of landslides and the theoretical background of landslide stability coefficient prediction.

Dynamic triggering mechanism of the Pusa mining-induced landslide in Nayong County, Guizhou Province, China

Catastrophic landslides have occurred frequently in the karst areas of Southwestern China for these years, which makes it urgently necessary to reveal their triggering mechanisms. The universal distinct element code (UDEC) was used to simulate whole response of the Pusa landslide during its underlying coal-seam mining. The results are as follows. First, under the given pre-conditions, when coal seams beneath the original slope were mined from bottom to top, caving zone, fracture zone, and deformation zone overlying the goaf gradually expanded; and as the uppermost layer was mined, the deformation, which was apparently characterized by subsidence and clockwise rotation, overwhelmed the slope. Second, under action of the heavy rainfall, the deformed slope, which was affected by the goaf, behaved further progressive deformation characterized by subsidence and clockwise rotation as a whole. Third, with continuous action of near stoping blasting vibrations, the more-deformed slope, which had been influenced by the goaf and the heavy rainfall, behaved continuous progressive deformation, critical failure, shattering, ejection, debris flow, and accumulation. The deformation exhibited significant subsidence, clockwise rotation, and collapse. These responses were verified by the field reconnaissance. It is the first time to explore dynamic triggering mechanism of the landslide triggered by the vibrations.

Progressive failure analysis of slip zone soils with strain-softening behavior and implications for landslide triggering mechanisms

Progressive failure analysis of slip zone soils with strain-softening behavior and implications for landslide triggering mechanisms

Co-seismic stress changes and triggering mechanism of earthquake-induced landslides: a case of 2005 Kashmir earthquake

Co-seismic stress changes and triggering mechanism of earthquake-induced landslides: a case of 2005 Kashmir earthquake

Evaluation of failure of slopes with shaking-induced cracks in response to rainfall

Centrifuge model tests on slopes subject to shaking and rainfall have been performed to examine the response of slopes with shaking-induced cracks to subsequent rainfall and evaluate the corresponding landslide-triggering mechanisms. The failure pattern of the slope subject to shaking and then rainfall was found different from that of the slope subject to only rainfall. When shaking caused cracks on the slope shoulder and rupture line below, the mobilized soil slid along the slip surface that extended to the rupture line, the main crack became the crown of the undisturbed ground once the slope was subject to a subsequent rain event, and the progression of the landslide was related to the rainfall intensity. During the landslide caused by light rainfall, the main scarp kept exposing itself in the vertically downward direction while the ground behind the main crack in the crack-containing slope remained undisturbed. The detrimental effect of cracks on soil displacement was more evident when the slope was exposed to heavy post-shaking rainfall, resulting in a rapid and massive landslide. Additionally, the volume of displaced material of the landslide, the main scarp area on the upper edge, and the zone of accumulation were larger in the crack-containing slope subject to heavy rainfall, in comparison with those in the crack-free slope. The deformation pattern of slopes with shaking-induced cracks during rainfall was closely related to rainfall intensity and the factor of safety provided a preliminary estimation of slope stability during rainfall. Moreover, even when subjected to the same rainfall, the slopes with antecedent shaking-induced cracks displayed different levels of deformation. The slope that experienced larger shaking had greater deformation under the following rainfall, and the shaking-induced slope deformation also controlled the slip surface location. Finally, the velocity of rainfall-induced landslide could be greatly influenced by the prior shaking event alone. Despite being under light rainfall, the slope that has encountered intense previous shaking exhibited an instant landslide.

A mechanical insight into the triggering mechanism of frequently occurred landslides along the contact between loess and red clay

The triggering mechanism and movement evolution of loess-red clay landslides, which occurred frequently along the contact between the loess and red clay on the Loess Plateau, are closely related to the mechanical properties of the contact surface. This work presents an experimental investigation on loess, clay and loess-red clay interlaminar (LRCI) samples obtained from a typical loess-red clay landslide in northern part of Shaanxi province of China, using a series of ring shear tests, microscopic observation and scanning electron microscopy tests, in an attempt to explore the mechanical behavior of loess, clay and LRCI samples with variation in moisture content, normal stress and shear rate. The results revealed that for all specimens, both the peak shear strength tau_{p} and the residual shear strength tau_{r} decreased with increasing moisture content, among which, moisture content has the greatest influence on the tau_{p} and tau_{r} of red clay, followed by the LRCI specimen, and the loess specimen is least affected by moisture content. Meanwhile, exponential functions describing the correlations between shear strength and moisture content of LRCI, red clay and loess specimens were proposed. Furthermore, the macroscopic morphological characteristics and the microstructure of shear surface obtained from the LRCI specimens showed that a localized water accumulation was built up within the shear surface as the water content increases to some extent, and a high degree of liquefaction developed within shear surface when the moisture content reached to the saturate degree. The microstructural observation on LRCI specimen suggested that the shear surface became smoother and the larger percentage of small-sized pores was observed with moisture content. Accordingly, the built-up excess pore water pressure during shearing is difficult to be dissipated due to a close structure of small-sized pores. Due to the low permeability, high pore-water pressure built up within the shear zone and the increase in the fine particle content, the LRCI soils with a high saturation degree shows the potential for the localized liquefaction within shear zone, which further provides a scientific explanation for the triggering mechanism of loess-red clay landslides with high-speed and long- run out.

Regional-scale simulation of flowslide triggering in stratified deposits

Capturing the failure mechanisms responsible for static liquefaction is a challenging task for the zoning of landslide susceptibility. While geomechanical models accounting for solid-fluid coupling can identify locations prone to flowslides, their performance in regional settings is impacted by the lack of procedures to replicate accurately stratigraphic heterogeneities. To mitigate this inconvenience, this paper discusses the performance of a spatially-distributed model aimed at capturing distinct landslide triggering mechanisms in layered deposits. The model relies on the simultaneous computation of multiple factors of safety associated with the triggering of frictional slips and liquefaction-induced flowslides. In addition, the spatiotemporal variation of such indices is retrieved from a vectorized finite element platform solving pore pressure transients in stratified unsaturated soils. Such features enable the model to take into account the vertical heterogeneity of individual slope units, while dramatically reducing the computational cost of regional-scale analyses. For illustrative purposes, the model is used to analyze a series of documented shallow landslides that occurred in Campania (Italy) following heavy rainstorms. A comparison of model predictions with and without stratigraphic heterogeneity is provided, showing that the incorporation of site heterogeneity leads to a substantial improvement of the model's spatiotemporal performance, as well as of its ability to identify different modes of failure. Furthermore, the model is applied to four municipalities across the region of interest, each characterized by different representative stratigraphic settings. Despite some mismatches, often linked to the scarcity of site-specific information, the numerical results obtained on the basis of the available dataset shows that the proposed methodology is a robust and effective tool for landslide susceptibility mapping in stratified deposits.

Landslide Geometry Reveals its Trigger

AbstractElectronic databases of landslides seldom include the triggering mechanisms, rendering these inventories unusable for landslide hazard modeling. We present a method for classifying the triggering mechanisms of landslides in existing inventories, thus, allowing these inventories to aid in landslide hazard modeling corresponding to the correct event chain. Our method uses various geometric characteristics of landslides as the feature space for the machine‐learning classifier random forest, resulting in accurate and robust classifications of landslide triggers. We applied the method to six landslide inventories spread over the Japanese archipelago in several different tests and training configurations to demonstrate the effectiveness of our approach. We achieved mean accuracy ranging from 67% to 92%. We also provide an illustrative example of a real‐world usage scenario for our method using an additional inventory with unknown ground truth. Furthermore, our feature importance analysis indicates that landslides having identical trigger mechanisms exhibit similar geometric properties.

Triggering mechanism and possible evolution process of the ancient Qingshi landslide in the Three Gorges Reservoir

The Qingshi landslide in the Three Gorges Reservoir was selected as a case study of ancient landslides. The detailed on-site surveys and long-term monitoring data were analysed to classify the triggering mechanism and possible evolution process of the Qingshi landslide. The results show that the ancient Qingshi landslide was triggered by the water storage in 2010. The leading edge slipped first, and the trailing edge underwent large-scale deformation after losing the resistance provided by the leading edge. In early 2011, the compaction of the leading edge of the landslide provided a certain resisting force, which controlled the overall downward movement of the landslide. In 2014, the integrity of the landslide was strengthened by emergency treatment measures, which caused the stabilization of the landslide and further reduced the displacement rate of the landslide. The local strengthening of the leading edge may act as a locking segment that could provide direct support to the sections in the middle and upper parts of the landslide. However, abnormal water-level regulation and heavy rainfall may cause the landslide to collapse again. The entire evolution process of the Qingshi landslide can provide an important reference for ancient landslides located on reservoir banks.

Analysis of the triggering mechanism of landslide in the village Podi, Montenegro

Frequent landslides in the flysch zones along the Adriatic coast commonly develop on the contact between the sound flysch and Quaternary sediments. The reason for this is most often the increased pore pressure and degradation of material due to inadequately regulated surface and groundwater. A case of one such landslide in the south-western part of Montenegro is presented in this paper. The disposal of construction waste materials above the location of the village Podi was followed by the occurrence of a landslide which affected 3.5 ha of slope and damaged 27 houses in the village. In the course of legal proceedings initiated against the contractor, a question arose of whether the deposited material could have triggered the landslide. Response to this complex question required a multidisciplinary approach, including also a numerical parametric analysis. The results of such analysis indicated that the improper depositing of material above the village induced the landslide activation for two reasons: an increase in shear stress and a change in the natural groundwater regime, which in turn affected elevation in the pore water pressure. Numerical analyses indicated that with a moderate water table rising, the factor of safety decreased by some 20%, which in case of an already conditionally stable slope is sufficient to initiate the terrain movement and formation of a landslide on a wider area.

LANDSLIDE-GENERATED TSUNAMIS: A NUMERICAL ANALYSIS OF THE NEAR-FIELD

There are coastal areas which are particularly prone to landslide-generated tsunami risk. The destructive effects caused by the impulsive waves, generated by landslide sources, can be strongly magnified by the characteristics of the so-called "confined geometries" (e.g. bays, reservoirs, lakes, volcanic islands, fjords, etc.). Complicated physical phenomena (e.g. trapping mechanisms, edge waves, wave runup, etc.) take place as a consequence of the interaction between the generated waves and the local bathymetry and control the tsunami propagation and interaction with the coast, often causing devastating consequences. Many past events of landslide-generated tsunamis testify this reality (e.g. Lituya Bay, Alaska, Fritz et al., 2009; Stromboli Island, Italy, Tinti et al., 2005; Anak Krakatau, Indonesia, Grilli et al., 2019). To reduce and mitigate the tsunami risk a proper comprehension, and modelling, of such complicated phenomena is crucial. Landslide-generated tsunamis have been largely studied by exploiting experimental, analytical and numerical modelling. Experimental tests are often time and money consuming, especially if 3D models are considered. Large facilities, as well as complicated experimental configurations and sophisticated measurement systems (e.g. Romano et al. 2016), are often needed. Furthermore, not always it is possible to explore in detail the influence of all the involved parameters, in particular those related to the landslide triggering mechanisms and rheology, that have a considerable influence on the wave characteristics in the so-called "near-field". To this end, numerical modelling can provide a valuable assistance. The new tools offered by the Computational Fluid Dynamics (CFD) methods represent a valuable means for shedding light on the unresolved aspects. In particular, the 3D CFD modelling techniques appear to be crucial as far as the tsunami characteristics in the near-field, induced by landslide sources, are concerned. Indeed, the accurate reproduction of the energy transfer between the landslide and the water is essential to model the tsunami generation and propagation mechanisms, allowing to explore a large variety of landslide triggering mechanisms and rheology. In this paper we present a numerical study of the landslide-generated tsunamis in the near-field.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/liUdiV2qXPg