Loess Landslide Research Articles

Quantitative spatial distribution model of site-specific loess landslides on the Heifangtai terrace, China

Landslide disasters are associated with severe losses on the Loess Plateau of China. Although early warning systems and susceptibility mapping have mitigated this issue to some extent, most methods are qualitative or semi-quantitative in the site-specific range. In this paper, a quantitative spatial distribution model is presented for site-specific loess landslide hazard assessment. Coupled with multi-temporal remote sensing images and high-precision UAV cloud point data, a total of 98 loess landslides that have occurred since 2004 on the Heifangtai terrace were collected to establish a landslide volume-date and retreating distance database. Eleven loess landslides are selected to construct a numerical model for parameter back analysis, and the accuracy of the simulation results is quantitatively evaluated by the centroid distance and overlapping area. Different volumes and receding distance rates of landslides are fitted to determine the relationship between cracks and potential volume, and different volumes and parameters are combined to simulate the spatial distribution of potential loess landslides. The results of this study reveal that landslide volumes mainly range between 1 × 103 and 5 × 105 m3, and the historical occurrence probability reaches 0.551. The optimal parameters are estimated by the maximum likelihood method to obtain a uniform distribution parameter value probability model, and the results show that the error of the estimated length within a range of 0.05 from the optimal parameter does not exceed 15%. In the selected slope slide case, farmland near the toe of the slope primarily includes exposed hazards with probabilities greater than 0.7. This work provides a useful reference for local disaster reduction and a theoretical methodology for hazard assessments.

Probabilistic evaluation of loess landslide impact using multivariate model

The Loess Plateau is the largest loess accumulation area around the world, onto which loess landslides have been occurring frequently each year, thus bringing significant threats to communities there. To mitigate or manage the risk brought by loess landslides, many methods have been developed to gain insights into mechanisms that trigger loess landslides, or to identify regions that are susceptible to landslides through landslide susceptibility mapping. However, none of these methods can be used to quantitatively evaluate possible impact of potentially unstable slopes, which offers important information for risk management, especially for regions with high susceptibility to landslides. This study aims to fill this gap by constructing a loess landslide database first from field investigation. Then, a multivariate model for loess landslide data, including its height, width, area, and length, is developed considering correlation among these parameters. Subsequently, the multivariate model is used to predict statistically and quantitatively impact of a potentially unstable loess slope, in terms of slide width, length, and area, given height of the potentially unstable loess slope. The proposed method is applied to loess landslides occurred in Baoji City for illustration. Results show that the proposed method works reasonably well. In addition, some key equations are provided using results from the multivariate model. With these equations, geotechnical engineers or decision-makers can evaluate possible impact of a potentially unstable loess slope with minimal effort.

Improvement of Physical-Chemical and Rheological Properties of Ghardaïa Loess (Southern Algeria) Using Bentonite Clay and Lime

AbstractLoess is a collapsible soil; when it collapses, it can cause significant damage to structures built on it. Improvement in the stability and strength performance of loess is necessary to meet engineering needs. In the present study, the effects on the physical-chemical and rheological characteristics of Ghardaïa loess of adding bentonite and lime (southern Algeria) were examined. Rheological characterization of suspensions was implemented to assess the mechanical sensitivity of the bonds and the structural inter-particle resistance to both the chemical effect and mechanical impact. By analyzing the viscosity results and the evolution of the rheological parameters, the improvements needed in terms of the resistance characteristics of the loess-bentonite and loess-lime mixtures were evaluated and confirmed. The loess physical sensitivity was examined through grain-size distribution and plasticity properties. The pH and electrical conductivity of the mixtures were also used to explore structural modifications. Physical test results showed that introduction of the additives changed the loess texture and improved the plasticity of mixtures. Chemical examination (via change in pH and electrical conductivity) revealed the structural changes in the mixtures studied. Rheological test results showed that increasing concentrations of bentonite and lime improves the mechanical strength and increased the yield stress, consistency, and viscosity of the suspensions. The creation of cement interactions between mixture particles explained the increase in those parameters. Hydration, agglomeration, and inter-particle flocculation induced by the additives promoted these interactions. The experimental results led to the conclusion that bentonite and lime may represent an effective means to improve the performance in terms of preventing loess collapse and to increase its resistance to mechanical impact. The results presented in the present study may provide a geotechnical and rheological working database for the control and treatment of loess collapse and landslides in the region under study. Technical data related to loess may, therefore, be beneficial in terms of civil engineering, public works, hydraulics, and the manufacture of construction materials.

Groundwater Response of Loess Tableland in Northwest China under Irrigation Conditions

Water induced loess landslides are closely related to the rise of the groundwater level. Therefore, research on the response of the groundwater level to irrigation water holds promise for revealing the mechanism of water-induced loess landslide. Taking Heitai, Gansu Province, as the research area, a coupling model o unsaturated-saturated water movement is established using the HYDRUS-MODFLOW software. The parameters of the model are calibrated and verified by the Bayesian parameter inversion method combined with field observations of the groundwater level. Finally, the change in the groundwater level under different irrigation amounts is predicted using the optimized model. It is found that a reasonable reduction of the irrigation amount can effectively slow the rise of the groundwater level. This research provides a scientific reference for the development of reasonable irrigation measures.

Integrating principal component analysis with statistically-based models for analysis of causal factors and landslide susceptibility mapping: A comparative study from the loess plateau area in Shanxi (China)

Landslide susceptibility assessment is an important task in urban planning and risk management. For mountainous areas where multiple types of landslides occur, the differences between landslide types should be considered when mapping landslide susceptibility. The main objective of the present study is to compare the prediction performances of three statistically-based models, namely, information value (IV), logistic regression (LR), and weight of evidence (WOE) models, in susceptibility assessments of different landslide types and to optimize the combination of causal factors. The Loess Plateau area in Shanxi Province, China, was selected as the study area. We prepared a landslide inventory by mapping the detailed spatial distribution of 234 loess landslides and 232 rockfalls in the area. Subsequently, 11 causal factors were considered in the construction of an initial index system for the susceptibility assessments, and corresponding thematic layers were generated in a GIS environment. Principal component analysis was utilized to obtain the relative importance of these layers in causing loess landslides and rockfalls, and nine factors with relatively high weights were selected as the final landslide influencing parameters. The relationships between these parameters and landslide distribution were analyzed using the three aforementioned methods and training samples (75% of landslides). The outcomes were extended to the entire study area to determine landslide susceptibility, and the testing samples (25% of landslides) were used to verify the predictive ability of the models. The results illustrated that rainfall and land use were essential in predicting both loess landslide and rockfall occurrences. The WOE and LR models showed the best performance in rockfall and loess landslide susceptibility assessments, respectively. Both models had an accuracy of more than 80%. If both landslide types were considered as an entire group or if all 11 factors were included in the model, the accuracy decreased.

Formation mechanism analysis of irrigation-induced retrogressive loess landslides

The Loess Plateau covers about 6.6% of the total land area of China. Landslides are serious concerns in Loess Plateau of China, and the south Jingyang tableland on the Loess Plateau of China has received significant attention because of frequent occurrence of gradual retrogressive loess landslides (GRLL) there. However, the characteristics and mechanism of GRLL are largely unknown. In this study, three typical landslide groups, namely, Miaodian-zaitou landslide group, Jiangliu landslide group and Dabuzi landslide group are chosen as examples to analyze the characteristics of GRLL by performing a field survey and undrained triaxial shear tests. Loess fissures are found to play a key role in controlling the evolution of landslides. On the one hand, the mechanical properties of loess surrounding fissures rapidly weaken due to water infiltration into loess fissures. On the other hand, the self-weight of the overlying loess increases since water infiltrates into fissures. The undrained triaxial shear tests results indicate that loess specimen shows either strain-hardening or strain-softening behavior, depending on its initial moisture content. Furthermore, reduction in the shear strength of loess samples is observed as moisture content increases. Three factors associated with the characteristics and mechanism of GRLL group, including strata lithology, slope shape, irrigation and rainfall are discussed. Finally, the formation mechanism and evolution of GRLL are summarized into three stages, namely, a creep-tensional stage, a localized liquefaction stage and a sliding stage. This study provides important insights on gradual retrogressive characteristics of loess landslides and facilitates appropriate safeguards to reduce the risk of such landslide hazards.

Landslides of the 1920 Haiyuan earthquake, northern China

The great M ~ 8 1920 Haiyuan earthquake (HYEQ) was one of the largest and most deadly earthquakes in China in the last century, with ~ 234,000 deaths. The earthquake occurred within the Loess Plateau of northern China, where Quaternary loess deposits form a distinctive blanket across the landscape. Large regions of this loess cover experienced co-seismic landslides. Based on an analysis of the original disaster reports, field surveys, and satellite image interpretation, we have compiled the shaking effects of the earthquake, including the distribution of landslides, fatalities, and structural damage. Landslides triggered by the HYEQ (n > 7,000) are concentrated south of the Haiyuan fault, in a region that has both thick loess cover and long-term relief generated by the drainage network. This distribution is spatially separated from landslides triggered by other earthquakes. We find that in contrast to previous studies, the most important factor in the severe death toll of the HYEQ was the collapse of housing by ground shaking, including collapse of loess house-caves. Landslides were a secondary factor; although up to 32,000 deaths occurred in areas with intense landsliding. Based on the revised distribution pattern of landslides and damage (e.g., house collapses), we suggest that the isoseismal intensity IX line extends south of previous locations. We have also identified 126 dammed lakes created by co-seismic landslides, which form major modifications of this semi-arid landscape. The research methods in this paper, combining historical review, satellite image interpretation, and field validation of landslides, can be used as a reference for studies of other areas affected by historical earthquakes and co-seismic landslides, elsewhere in the Loess Plateau and beyond.

The impermeability effect of soil air on the ponding infiltration experiment of soil column

The agricultural flood irrigation in Jingyang South Platform, Shaanxi Province caused the rise of groundwater level, which induced a large number of loess landslides. The study of water movement in unsaturated loess under irrigation is the premise of revealing the mechanism of loess landslide. In this paper, the changes of matric suction, volume moisture content and air pressure with time at different depths of unsaturated undisturbed loess are measured by indoor soil column water infiltration test. Air pressure at each point of the soil rises to about 98 Pa in a short time after the test beginning, and keeps small fluctuation up and down during the test. At the end of the experiment, the air pressure at each point of the soil returns to zero in a short time after the upper water accumulation is eliminated. During the test, the change of infiltration rate has a significant corresponding relationship with the exhaust phenomenon at the top of the soil column, and the air resistance significantly reduces the infiltration rate of water.

Successful implementations of a real-time and intelligent early warning system for loess landslides on the Heifangtai terrace, China

Real-time monitoring and intelligent early warning system are crucial and significant to take mitigation measures and reduce casualties and property losses related to landslides. It is difficult to obtain entire monitoring data in the accelerated deformation phase in a landslide event, and hard to issue early warning information using a traditional monitoring approach with fixed and low sampling frequency. Displacement increments of loess landslides induced by agriculture irrigation on the Heifangtai terrace could be sudden and extremely rapid. Typical landslide types include loess flowslides and loess falls. It is of practical significance to develop a self-adaptive data acquisition monitoring technique and establish a real-time landslide early warning system (LEWS) to meet the needs for risk mitigation of rapid sliding slopes on the Heifangtai terrace. The monitoring technique can wirelessly transmit displacement data and the LEWS was devised using the new artificial intelligence. The LEWS could automatically release the warning information in advance of the event once the early warning parameters exceed default thresholds. In this study, the early warning procedures, real-time monitoring approach, intelligent LEWS, a multiple criteria warning model, warning release and emergency mitigation measures, and performance are introduced in detail. Six loess landslides at Heifangtai and eight landslides in other regions of China have been successfully warned since its implementation in 2012. This study proposed an effective and practical solution for the early warning of loess landslides at Heifangtai. Two typical loess landslides that had successful early warnings at Heifangtai were presented. The successful implementation could serve as a reference for global rapid slope failure cases, considering the complex nature of landslide behaviors and failure mechanisms.

Static Liquefaction Capacity of Saturated Undisturbed Loess in South Jingyang Platform

According to a previous geological investigation, high-speed and long-distance loess landslides in the South Jingyang platform in Shaanxi Province are closely related to the static liquefaction of loess. Considering the typical loess landslides in this area, isotropic consolidated undrained (ICU) triaxial tests and scanning electron microscopy analyses were conducted in this study. The main conclusions are as follows: (1) The stress-strain curves indicate strong strain softening under different confining pressures. The pore water pressure increases significantly and then remains at a high level; (2) The liquefaction potential index (LPI) shows an increasing trend followed by stabilization; the larger the LPI is, the smaller the state parameter (Ψ) is. The steady-state points of the loess are in the instability region; however, the steady-state strength is not zero; (3) Based on the ICU test results, the average pore diameter decreases; the shape ratio remains essentially unchanged; and the fractal dimension and roundness show different trends. The proportions of the macropore and mesopore decrease; that of the small pore increases slightly; and that of the micropore increases significantly; (4) The compression deformation of the highly spaced pores causes rapid strain hardening. A rapid strain softening results from the pore throat blockage at the beginning of particle rearrangement and reorganization. A stable strain softening is related to the agglomeration blocking of the reconstructed pore throat in the gradually stable stage of particle rearrangement and reorganization.

UAV survey and numerical modeling of loess landslides: an example from Zaoling, southern Shanxi Province, China

This work attempted to reveal the geometric and kinematic characteristics of a loess landslide that occurred at Zaoling, southern Shanxi Province, China, on March 15, 2019. Based on the high-resolution unmanned aerial vehicle survey and DEM data acquired after this event, the topography of the study area was reconstructed to estimate the volumes of the source area and the deposit area of the landslide. Coupled with the high-resolution three-dimensional topographic data, three-dimensional particle flow code was used to simulate the motion process and depositing characteristics of the landslide. Results show that the Zaoling landslide is a deep-seated loess landslide with a projection area of 9844 m2 and the attitude of the sliding surface 355°∠37° (trending and dip). The total volumes of the source zone and accumulation zone are 77,000 and 82,000 m3, respectively. The simulation results show that the whole sliding process lasts about 17 s. The maximum average velocity of the sliding body is 5.12 m/s and the average sliding displacement is 33.3 m. Comparing the depositing thickness obtained from the simulation with the reality shows that the accumulation thickness of the deposit area decreases gradually from the center to both sides. The accumulation characteristics from the simulation are roughly consistent with those of the actual landslide. According to the latest landslide classification system for loess slopes, the Zaoling landslide is a typical rotational slide. It is a typical case for loess landslide studies, in particular, its special failure mechanism and kinematic features.

Time-series analysis of the evolution of large-scale loess landslides using InSAR and UAV photogrammetry techniques: a case study in Hongheyan, Gansu Province, Northwest China

Loess landslides are a severe engineering geological problem on the Loess Plateau of China. This study relies on interferometric synthetic aperture radar (InSAR) and unmanned aerial vehicle (UAV) photogrammetry techniques to characterise a large-scale loess landslide deformation process in Northwest China. First, a total of 85 Sentinel-1 SAR images acquired from March 2015 to March 2019 were used to detect the spatial displacement and characterise the pattern of deformation from presliding to postsliding. Second, three UAV flight surveys were conducted to reconstruct landslide morphology, identify scarps, cracks and fissures; and generate elevation differences. By comparing these two technologies, we found that InSAR has more advantages in the retrieval of creeping deformation, while UAV data is valuable for detecting large sudden slides. Dynamic deformation zonation maps were generated based on comprehensive analysis, and the deformation pattern of the large loess landslide was deduced. The Hongheyan landslide was induced by heavy rainfall and then gradually became suspended owing to the topography effect. Recently, the western part of the slope showed a clear accelerating trend. This evolution provides comprehensive kinematic information for local governments to make further intensive observations or take effective precautions.

Experimental Study on Humidity Structure and p-value of Undisturbed Loess in High-risk Slope

A long-term dry-wet cycle will cause changes in the internal structure of the loess, which will affect its permeability coefficient and slope properties. In this paper, through the dry-wet cycle test, the changes of permeability coefficient P value, porosity and dry density of undisturbed loess and remodelled loess under the action of dry-wet cycle are studied. Under the condition of dry-wet cycle, the permeability coefficient of undisturbed loess in high-risk slope decreases, and the permeability coefficient of remoulded loess increases. Remoulding the original loess of high-risk slopes due to soil erosion is more likely to cause gullies and internal erosion, accelerating the occurrence of original loess landslides and collapse of high-risk slopes.

Inclination effect of coal mine strata on the stability of loess land slope under the condition of underground mining

The coal seam mining-induced characteristics of overlying strata fracture and surface subsidence are tested and numerically analyzed using the similar materials. Two mining models were conducted in a laboratory with two different rock orientations and slopes to simulate the stability conditions and driving conditions of the loess land slope of under the guides of the V-shaped law. Given a 30° dip angle of coal seam in the Model 1, the results show that the loess landslide on top of inclined rock layers is in the state of critical instability when working face advances to 100 m. Whereas, given a 30° dip angle of coal seam in the Model 2, the loess landslide on top of anti-inclined rock layers is in the state of critical instability when working face advances to 120 m. Numerical analysis using a discrete element method was performed to compare the analysis results with laboratory findings. Based on the test and numerical analysis results both indicate that the land sliding along loess land slope are most likely be triggered on inclined rock layers than anti-inclined rock layers when an underground mining activity begins to excavate.

Multitemporal UAV-based photogrammetry for landslide detection and monitoring in a large area: a case study in the Heifangtai terrace in the Loess Plateau of China

With high spatial resolution, on-demand-flying ability, and the capacity for obtaining three-dimensional measurements, unmanned aerial vehicle (UAV) photogrammetry is widely used for detailed investigations of single landslides, but its effectiveness for landslide detection and monitoring in a large area needs to be investigated. The Heifangtai terrace in the Loess Plateau of China is a loess terrace that is extremely susceptible to irrigation-induced loess landslides. This paper used UAV-based photogrammetry for a series of highresolution images spanning over 30 months for landslide detection and monitoring of the terrace with an area of 32 km2. Dense and evenly distributed ground control points were established and measured to ensure the high accuracy of the photogrammetry results. The structure-from-motion (SfM) technique was used to convert overlapping images into orthographic images, 3D point clouds, digital surface models (DSMs) and mesh models. Using multitemporal differential mesh models, landslide vertical movements and potential landslides were detected and monitored. The results indicate that a combination of UAV-based orthophotos and differential mesh models can be used for flexible and accurate detection and monitoring of potential loess landslides in a large area.

Interdisciplinary asperity theory to analyze nonlinear motion of loess landslides with weak sliding interface

While research into landslide disasters is relatively extensive and in-depth, the false alarm rate is still high. Previous research has indicated similar mechanical problems between the seismic faults and the sliding interface of landslides. Here, we introduce asperity theory from seismology to improve the prediction level of landslide damage. We designed a soil landslide model sized at 2.0 m × 0.6 m × 1.5 m where the upper layer is loess and the lower layer is mudstone. Four pore water pressure sensors and four soil pressure sensors are equally spaced at the loess-mudstone interface. The monitoring results show that the sliding interface has the characteristics of asperity, while the landslide failure is a nonlinear movement process. Although it is difficult to directly measure asperities, we can infer their position at the sliding interface by measuring the velocity or displacement of the landslide surface. We install monitoring sensors at the surface region corresponding to the asperity. Once there is a large deformation in the region, there is a significant probability that the entire landslide will be destroyed. Thus, asperity theory was applied for an early warning system of landslide disasters, which will greatly improve the monitoring and prediction of future landslides.

Rainfall-induced landslide in loess area, Northwest China: a case study of the Changhe landslide on September 14, 2019, in Gansu Province

A large-scale loess landslide occurred in Xiaozhuang Village, Changjiahe Town, Tongwei County, Gansu, at approximately 11:00 am on September 14, 2019. A volume of 774 × 104 m3 of a historical sliding mass was reactivated by rainfall and slipped down along a weak interface. The sliding mass accumulated in the valley of the Kushui River, blocking the channel for a distance of ~ 1000 m and destroying several roads and the Yangpo Bridge. This landslide is a typical case of rainfall-induced revival of a historical seismic landslide in the loess region of Northwest China. On the basis of site investigation, Google satellite image, unmanned aerial vehicle photography, and numerical simulation, the deformation and failure characteristics of this landslide are described in detail, and the possible inducing factors and failure mechanism are preliminarily assessed. The Tongwei earthquake in 1718 and the Haiyuan earthquake in 1920 caused the slope to slide multiple times in history. Due to continuous rainfall, the existing softened layer (previous sliding surface) was highly saturated due to the perched water on the top of the relatively impervious mudstone and formed the critical weak zone. Therefore, previous sliding mass in the lower and middle slope was reactivated along the softened layer on September 14, 2019. We suggest that the perched water mainly came from the dominant seepage channels such as sinkholes and underground rivers. In addition, sinkholes on the previous sliding body are the key factors controlling the boundary of the landslide. The movement of the landslide lasted for 12 h, and the main landslide lasted for only 60 s, with a runout distance of 60 m and an average velocity of 5 m/h. Study of the formation conditions and failure mechanism of the Changhe landslide is of great significance for the early identification and risk prevention of this kind of landslide in the loess region of Northwest China.

Study on the creep behaviours and the improved Burgers model of a loess landslide considering matric suction

Loess landslides frequently occur in the northwest area of China, leading to serious damage to the society and economy. Under the effects of rainfall and groundwater seepage, the stress–strain behaviours of Malan loess landslides are closely related to the saturated–unsaturated state of slide mass. Hence, it is of great significance to study the creep behaviours of Malan loess considering matric suction. First, the sliding-zone soil of a typical Malan loess landslide is collected to carry out tri-axial creep tests with a confining pressure of 100 kPa and diffident matric suction values of 20, 50 and 80 kPa. Then, a stress–suction–strain–time model (an improved Burgers model) is established by connecting a nonlinear dashpot element in series with the Burgers model and combining this with the functional relationship between the viscoelastic modulus and matric suction. The results show that (1) the Malan loess has obvious creep behaviours with viscoelastic and viscoplastic creep properties, (2) the long-term shear strength of Malan loess increases along with the increase in its matric suction, and (3) the improved Burgers model can more accurately describe the unsaturated creep behaviours of Malan loess with matric suction compared to the traditional Burgers model.

Regional Recognition and Classification of Active Loess Landslides Using Two-Dimensional Deformation Derived from Sentinel-1 Interferometric Radar Data

Identification and classification of landslides is a preliminary and crucial work for landslide risk assessment and hazard mitigation. The exploitation of surface deformation velocity derived from satellite synthetic aperture radar interferometry (InSAR) is a consolidated and suitable procedure for the recognition of active landslides over wide areas. However, the calculated displacement velocity from InSAR is one-dimensional motion along the satellite line of sight (LOS), representing a major hurdle for landslide type and failure mechanism classification. In this paper, different velocity datasets derived from both ascending and descending Sentinel-1 data are employed to analyze the surface ground movement of the Huangshui region (Northwestern China). With global warming, precipitation in the Huangshui region, geologically belonging to the loess basin in the eastern edge of Qing-Tibet Plateau, has been increasing, often triggering a large number of landslides, posing a potential threat to local citizens and natural and anthropic environments. After processing both SAR data geometries, the surface motion was decomposed to obtain the two-dimensional displacements (vertical and horizontal E–W). Thus, a classification criterion of the loess landslide types and failure mode is proposed, according to the analysis of deformation direction, velocities, texture, and topographic characteristics. With the support of high-resolution images acquired by remote sensing and unmanned aerial vehicle (UAV), 14 translational slides, seven rotational slides, and 10 loess flows were recognized in the study area. The derived results may provide solid support for stakeholders to comprehend the hazard of unstable slopes and to undertake specific precautions for moderate and slow slope movements.

Study of shaking table test of seismic subsidence loess landslides induced by the coupling effect of earthquakes and rainfall

Light rain or moderate rain is the most common meteorological event in the rainy season in the loess area of China, so the probability of landslide hazards induced by the coupling effect of earthquakes and rainfall under the condition of light rain or moderate rain is relatively higher than that under heavy rain. To study the dynamic response characteristics and instability mechanism of loess slopes by the coupling effect of earthquakes and rainfall under the conditions of moderate rain and light rain, a low-angle slope model test of a large-scale shaking table after 10 mm of rainfall was carried out. By gradually increasing the dynamic loading, the evolution of the macroscopic deformation and the instability failure mode of the slope model are observed; the temporal and spatial trends of the amplification effect, acceleration spectrum, pore pressure and soil pressure are analyzed; and the failure mechanism of the slope is determined. The results showed that the amplification effect increased along the slope surface upward, and a strong amplification effect appeared at the front of the top of the slope. Because of the stronger dynamic stress action on the upper part of the slope, the immersed soil in the upper part of the slope experienced seismic subsidence deformation, the saturation in the seismic subsidence soil increased, and the water content temporarily increased locally. With the further increase in the loading intensity, a large number of tension cracks were generated in the seismic subsidence area, and water infiltrated down along the cracks and the wetting range expanded under dynamic action. The range of seismic subsidence and cracks further extended to the deep part of the slope. Under the reciprocating action of the subsequent ground motion, the swing amplitude of the soil mass in the seismic subsidence area, which is divided by a large number of cracks in the upper part of the slope, increased further, resulting in the further reduction in the residual strength of the seismic subsidence soil mass located at the crack tip due to the pull and shear action. Finally, under the combined action of gravity and dynamic force, the upper soil mass in the seismic subsidence area dragged the lower soil mass in the seismic subsidence area downward because the sliding force is greater than the residual strength of the soil mass, which induced a seismic subsidence-type loess landslide. Under the coupling effect of earthquakes and rainfall, the instability mode and mechanism of this landslide are significantly different from those of liquefaction-type landslides.