Landslide Volume Research Articles

Experimental and Statistical Study on the Formation Characteristics and Discrimination Criteria of River Blockages Caused by Landslides

The discrimination of river blockages is very important for the risk assessment of landslide disasters and secondary hazards. Experimental studies and statistical analyses were carried out to explore the formation process and discriminant criteria of river blockages caused by landslides. An adjustable slide chute was designed and built to conduct forty-five landslide experiments. According to the experimental results, river blockage was identified as having six types based on the differences between the water depth and the height of the landslide dam, and the degree of river blockage increased from 70% to 100% as the chute angle, particle size, and landslide volume increased. It is also found that landslide volume controls the landslide dam height and degree of blockage, and particle size and slide angle control both the landslide velocity as it enters the river and the cross-section shape of the landslide dam. To investigate more influence factors, a statistical investigation of 60 real landslide cases was carried out, and it revealed that some geometric attributes related to landslide volume have the highest correlation with river blockage, especially landslide thickness. Finally, an improved probability model was proposed to assess the possibility of complete blockage, and it has overall accuracies of 91.1% and 83.3% when applied to predict experimental landslide cases and real landslide cases, respectively.

Simulation of landslide tsunami in the Russian Far East based on 3D Navier–Stokes equations

The paper presents the results of modeling landslide tsunamis near the Kamchatka Peninsula in part of the Pacific Ocean. The paper describes the model based on the three-dimensional (3D) Navier–Stokes equations. The model is supplemented with the rheological relation based on the Bingham model to account for the rheology of landslide masses. The paper proposes a modification of the classical Bingham model with a non-zero yield strength, which implies that the medium is at rest or it moves as a solid (body) in the absence of a tension in the medium exceeding this limit. The application of the classical model is impossible within the framework of the used equation system. The paper proposes its modification, which consists in the possibility of changing the yield strength to zero value by adding a linear function to a given shear rate, until which the fluid flows as Newtonian and after reaching it, the flow conditions of the substance obeys Bingham’s law. An original algorithm is used to simulate waves in real water areas, it implements open boundary conditions. The algorithm is based on the use of a damping boundary layer that absorbs the kinetic energy of the incoming wave, which is taken into account using an additional source in the angular momentum equation. A method is proposed for determining the resistance coefficient, the value of which determines the intensity of absorption of the kinetic energy of the wave. The used mathematical model makes it possible to model in a single way the occurrence, propagation and rolling on shore of tsunami waves of landslide origin. The results of modeling of an underwater landslide in the waters of the Kamchatka Bay near the city of Ust-Kamchatsk are presented, taking into account bathymetric date. The paper includes the analysis of dependence of wave heights on the volume of landslide in the zone of its initial position and at several points of the coast, as well as sections of the coast (in particular on Bering Island), which may be most severely affected by the occurrence of landslide tsunamis in this water area.

Three-Dimensional Modeling of Tsunami Waves Triggered by Submarine Landslides Based on the Smoothed Particle Hydrodynamics Method

Submarine landslides are a global geohazard that can displace huge volumes of loose submarine sediment, thereby triggering enormous tsunami waves and causing a serious threat to coastal cities. To investigate the generation of submarine landslide tsunamis, a three-dimensional numerical model based on the smoothed particle hydrodynamics (SPH) method is presented in this work. The model is first validated through the simulation of two underwater landslide model tests, and is then applied to simulate the movement of the Baiyun landslide in the South China Sea (SCS). The kinetics features of the submarine landslide, including the sliding velocity and runout distance, are obtained from the SPH simulation. The tsunami waves generated by the Baiyun landslide are predicted. In addition, sensitivity analyses are conducted to investigate the impact of landslide volume and water depth on the amplitude of the tsunami waves. The results indicate that the amplitude of tsunami waves triggered by submarine landslides increases with the landslide volume and decreases with the water depth of the landslide.

Forecast volume of potential landslides in alpine-canyon terrain using time-series InSAR technology: a case study in the Bailong River basin, China

Forecast volume of potential landslides in alpine-canyon terrain using time-series InSAR technology: a case study in the Bailong River basin, China

Submarine landslide-induced tsunami generation in Makassar strait, Indonesia using Non-hydrostatic wave model

Tsunami modelling of potential landslide-induced tsunami in Makassar Strait is carried out to quantify possible damage to the nearby cities. The numerical model is used to represent the wave generation by using NHWAVE model. The simulations consist of a series of scenarios based on distinct size of the landslide volume. Four landslides with volume 5, 8, 70, and 200 km3 are used as tsunami sources in the initiation stage. The sources are evenly distributed in the strait addressing different landslide location. Maximum wave heights of 1.5 m are found in the area between Palu and Bangkir from case 1 and around Talok from case 2 simulations. The empirical run-up calculation of 7.5 m is estimated at the land for the presented wave height. The value significantly elevates the case 3 and 4 proportional to the volume values. The waves impact more than half of coastline with maximum value found in the Sulawesi side. Interestingly, wide and narrow shelf next to Kalimantan Island plays an important role in reducing the tsunami hazard level.

Analysis on the volume expansion effect and influencing factors on loess landslides: a case study of the Heifangtai tableland in the Chinese Loess Plateau

ABSTRACT Landslide scale measurement and hazard risk assessment are crucial, especially since landslide deposits often have an expansion effect, and can lead to more serious secondary hazard events. In this study, we obtained substantial high-resolution terrain and orthophoto data through multiple UAV photography and field surveys. Based on GIS spatial analysis and landslide geometric models, sliding and deposit data for 42 loess landslides in the Heifangtai tableland were calculated. The results show that sliding volume and sliding area have the highest correlation with the power-law distribution ( V e = 1.204 A 1.1360 ). The ratio of H max / L max increases with the increase of sliding volume and deposit volume of the landslides, with an average value of 0.306. The ratio of H/L has a higher correlation with deposit volume, and the fitting expression is H max / L max = 0.187 V D − 0.123 . The VEC of 42 loess landslides ranged from 1.05 to 2.53, while the AVEC was about 1.503. The correlation analysis show that the VEC is positively correlated with AEC, Hmov , Hmov/Lmax and Lmov/Lmax but negatively correlated with Dave . The essence of the volume expansion effect is that landslide fluidity increases, resulting in looser deposit distribution, larger pore scale in the deposit and lower overall compaction. Loess collapse in the Heifangtai tableland lack protection from the liquefaction of the sliding mass basement, resulting in large VEC values. The semi-ellipsoid model is a valuable approach for landslide volume assessment in the Chinese Loess Plateau, yielding an average error rate of restoring the sliding volume of landslides of 13.55%. This study provides a useful reference for accurate evaluations at the landslide scale.

The influence of seismic displacement models on spatial prediction of regional earthquake-induced landslides

Regional landslide prediction is a critical step towards achieving community resilience against landslides during earthquakes. We present a predictive methodology for regional earthquake-induced landslides that uses a pseudo-three-dimensional (pseudo-3D) procedure implemented on a digital elevation model (DEM). The methodology calculates a seismic displacement for every grid cell in the DEM as the basis for predicting the location and the size of landslide that is determined using a three-dimensional (3D) geometric projection based on topography. This “pseudo-3D” methodology for predicting landslides outperforms cell-based approaches. It has the advantage of deriving landslide number and size characteristics of individual landslides. We quantify the influence of seven commonly used seismic displacement models: four rigid, two decoupled flexible, and one fully coupled flexible. Seismic displacement model performance is evaluated by implementing a prediction for the 2015 Mw6.5 Lefkada earthquake event in Greece for which precise location and high-resolution landslide volume data are available for model validation and ground motion intensity measures are well constrained by nearby ground motion recordings. The 3D landslide inventory was created by topographically differencing pre-existing DEMs from post-event digital surface models derived from satellite and unmanned aerial vehicle (UAV) imagery. The inventory contains over 700 landslides, primarily shallow disrupted slides and rock slides, along with occasional occurrences of deep-seated, rotational failures. Qualitative comparisons between predicted and mapped landslides show that all seismic displacement models predict landslides that broadly overlap geospatially with most mapped landslides and the regions of high mapped landslide densities are predicted. A variety of metrics are used to quantify the prediction results: these include metrics such as landslide number and area density, as well as correctly predicted ratio, overlapped ratio, centroid distance, ground failure capture, and efficiency. The results show that the Rathje and Antonakos (kmax, k-velmax) model and the Saygili and Rathje (PGA, PGV) model correctly predict the most mapped landslides and obtain the highest prediction efficiency, but at the cost of the highest overprediction. The Bray and Macedo model achieves the best performance in predicting landslide number, area density, and location accuracy, but the correct prediction of the mapped landslides and the prediction efficiency are worse than other seismic displacement models. The results highlight the role of seismic displacement models in the prediction of regional earthquake-induced landslides and guide selection of the seismic displacement model depending on the objective of the prediction. Strength parameters also affect landslide prediction, and we demonstrate that all evaluation metrics vary widely due to variation of cohesion and friction angle, except for the correctly predicted ratio. More importantly, variation in prediction results due to the selection of seismic displacement models is found to be comparable to variation in results associated with strength parameter uncertainty. A critical slope parameter is proposed and defined as the flattest slope at which landslide triggering may occur for a given predictive model. As such, seismic displacement models that have lower critical slopes predict more landslides and differences in critical slopes for each seismic displacement model provide a parsimonious explanation for the different performances of the seismic displacement models in the regional earthquake-induced landslide prediction.

Distribution and formation of soil balls under heavy rainstorm conditions in the northern Loess Plateau

The occurrence of a peculiar phenomenon called “soil balls” was observed in Dingbian County, northern Loess Plateau, due to an extremely heavy rainstorm on July 10, 2022. Determining the distribution characteristics and formation of these soil balls is crucial for enriching the knowledge and the precise prevention and control of soil erosion on the Loess Plateau. This research is particularly significant in studying the off-site effects of soil erosion caused by rainstorm and flooding disasters. This study conducted a comprehensive analysis through field investigation and drone aerial photography in the three dam-controlled watersheds selected. The results showed that the soil balls originated from the soil clods generated by landslides and collapses that occurred within the watersheds during heavy rainstorms. Under the action of hyperconcentrated flows, the soil clods were transported downstream. The size of the soil balls is mainly in the range of 20–60 cm in diameter, accounting for 81% of the total soil balls in the dam lands, with significant differences in the morphology at different locations within a dam land region. The average area density and volume density of soil balls in the dam lands of the watersheds are 0.13–0.25 m2 m−2 and 0.05–0.11 m3 m−2, respectively. In each watershed, the area density and volume density of the soil balls exhibit the following order: one-third of the dam land nearest from the dam wall > the middle one-third of the dam land > one-third of the dam land furthest the dam wall. The total erosion intensity of landslides and collapses in the three watersheds was 18,730, 5,213, and 9,879 m3 km−2, respectively. The sediment transport ratio of landslides and collapses expressed by the soil balls in the dam land is at least 4–10%. The study also indicated that the volume of landslides and collapses, the shape coefficient of the watershed, the density of the confluence paths, and the peak discharge had a significant impact on the volume density distribution of the soil balls in the dam lands. We recommend implementing certain measures in similar watersheds, including converting steep slopes into terraced fields or grasslands, constructing water storage and drainage facilities, building energy dissipation measures in channels, and reinforcing check dams, to reduce the risk of soil ball events occurring under heavy rainstorm conditions, and protect the ecological environment on the Loess Plateau.

THE CASE OF SEDIMENT OUTFLOW FROM MOUNTAIN TO THE COAST DUE TO SMALL AND MEDIUM-SIZE FLOODS

Smaller rivers in Japan can be characterized as having short distances from the mountainous areas of the source of sediment production to the estuary and steep slopes. Therefore, sediment produced from the mountains and river channels at the time of flooding immediately contributes significantly to the sediment dynamics at the estuary and coast in a short period of time. On the other hand, there have been few observations or studies that have measured the volume of landslides and riverbed fluctuations in the mountains in the entire basin before and after the occurrence of flooding, and quantitatively linked them to the amount of landslide movement and shoreline changes in the entire basin. This paper discusses the Chitose River basin (basin area A: 30km2, river channel distance L: 0.179km, stream gradient I: 1/14) and the Niizaki River basin (A: 16km2, L: 0.213km, I:1/17), which have an estuary on the Yugawara coast in Kanagawa Prefecture. The effect of sediment production from mountains and riverbeds at the time of flooding on coastal sediment dynamics on July 3rd, 2021.

Forest management history influences eight decades of shallow landsliding in the northwest Cascade Mountains, USA

AbstractForest management‐driven increases in landsliding may impact aquatic habitat and water quality, yet it is difficult to disentangle the effects of hydroclimate from evolving land‐use practices when interpreting landslide rate fluctuations over decadal timescales. We compiled shallow landslide inventories starting in the 1940s from nine small watersheds in the northwest Cascade Mountains, USA, and updated the mapping through 2019. We stratified the landscape by management regime (industrial/state and federally managed forests and forests with no history of management) and compared landslide volume generation rates against timeseries representing regional climate, precipitation and river discharge, timber harvest rate, and instability ratings from the topographic model SHALSTAB. Results demonstrate a bell‐shaped temporal trend in composite landsliding that peaked in the 1970s and 1980s and is unlikely to have arisen from random variation alone. The signal from unmanaged forests correlates with regionally warm/wet climatic conditions at decadal scales, but we found mixed quantitative support for storm hydrology in explaining the landslide trends. Landsliding in federal managed forests was greatly reduced following cessation of clearcut logging in the mid‐1990s in most basins. In contrast, topographic and stand age modelling suggest the private industrial and state forest trend is consistent with reduced landsliding resulting from regulations requiring hazard avoidance in logging unit design—not changes to logging rate—demonstrated by a decline in probability of recent clearcuts on highly unstable terrain relative to more stable terrain following the 1980s in most basins. The analysed covariates could not explain all trends in all watersheds, suggesting the presence of methodological or data‐based limitations in the analyses. Late 20th century landslide sediment delivery acutely impacted tributaries but likely became muted downstream due to lag effects and mixing with other sources; our results suggest that proximal sediment supply impacts may be greatly reduced.

Study on the volume of landslides in lunar impact craters

The lunar exploration project is of great significance, among which the statistics and measurement of lunar landslide are an important part of lunar exploration. With the help of Google Earth software, lunar image data were obtained, and the volume calculation and analysis of landslides in 14 meteorite impact craters on the Moon were performed using the Alfred S. McEwen formula. It is found by calculation and observation that the diameter of the crater is proportional to the volume of the landslide in most of the meteorite impact craters on the moon.

Simulate landslide activities during flood season 2020 - 2021 in Phong Nha - Ke Bang National Park

Research highlights in study area, there are various small-scale landslide points occurred and located surround from major landslide point with already 42 field-investigated points. The core zone of study area has the gravity displacement coefficient (Kg) by 0.0006, the buffer zone has Kg by 0.0033, all of them are weak and relative stable. The core zone of the National Park has more than 60 landslide points with total area of 81.19 hectares, and total landslide soil volume is over 2.6 mil m3. The largest landslide volume in study area is about 2.4 mil m3, with added 14 large-scale lanslide volume from 1,000 to 65,000 m3. In particular, a number of slopes occurred consecutively during flood seasons in years of 2020 - 2021. Landslide activities strongly affecting the integrity and aesthetic value of Phong Nha – Ke Bang (PNKB) National Park with calculation results, for the largest landside point during rainny season in October, 2020, show that the sliding soil blocks have displaced more than 130 m, with low factor of safety (FS) by 0.32 and the total sliding soil volume is 2.1 million m3, also consistent with field monitoring data and analysis of remote sensing images (2.4 mil m3).

Assessing loess landslide volume using high-precision UAV-derived DEM: A case study of the 15 March 2019 landslide in Zaoling Township, Xiangning County in North China

Landslides pose significant hazards on China's Loess Plateau, potentially resulting in catastrophic consequences for human life and property. A prompt assessment of landslide disasters is crucial in providing scientific decision support for post-disaster relief efforts and serves as a fundamental basis for risk assessment of secondary disasters such as debris flow. On March 15, 2019, a loess landslide occurred in Zaoling Town, Xiangning County, Shanxi Province. This event led to the collapse of three buildings, resulting in 20 fatalities and 13 injuries. Subsequently, high-resolution orthophotos and an unmanned aerial vehicle-derived digital elevation model (UAV-DEM) of the landslide area were obtained through photogrammetry. By analyzing the shape of the exposed main scarp of the landslide in the 0.2 ​m UAV-DEM and the softened layer, this study successfully identified an unexposed underground sliding surface. Through further analysis of the shape of the exposed main scarp of the landslide in the 0.2 ​m UAV-DEM and the softened layer, this study accurately reconstructed the unexposed underground sliding surface. To reconstruct the pre-landslide digital elevation model (DEM), Google Earth images depicting the pre-landslide terrain features were utilized. The volume of each component of the landslide was then calculated using the pre-, post- DEM, and the sliding surface. The calculation results reveal that volume of the landslide is about 54,000 ​m3, the expansion rate was determined to be 13.9%.

Investigation of motion characteristics of catastrophic landslide using material point method and gene expression programming

This study presents two approaches (i.e., the material point method (MPM) and gene expression programming (GEP)) for prediction of landslide runout. The MPM was modified based on a strain-softening constitutive model. A collapse test and physical model test were conducted to verify the suitability of the modified MPM. The sensitivity analysis was performed to investigate the importance of the softening parameters on the motion characteristics and final accumulation state. In addition, a predictive equation for prediction of the maximum horizontal distance was proposed based on GEP, with the coefficient of determination of 0.8825. The effects of the maximum vertical distance, landslide volume and landslide posture on the maximum horizontal distance were quantitatively analyzed. Moreover, the GEP model was verified by comparison with other machine learning approaches. Finally, taking the Jiweishan landslide as an example, the simulation and prediction results obtained from the MPM and GEP approaches were compared. The results show that the two are both within a reasonable range, with the errors of 14.1% and 10.6%, respectively.

Mesh-free simulation of height and energy transfer of landslide-induced tsunami waves

The landslide-induced tsunami wave poses a threat to human society and the living environment by causing disasters such as run-up of water surfaces and overtopping of dams. In this paper, we systematically investigated the relationship between landslide properties and induced tsunami wave characteristics as well as the energy transfer between the landslide and waves. A meshless smoothed particle hydrodynamics (SPH) framework was presented and validated with four experiments of different landslide types. The validations indicate that the SPH model is capable of reproducing the complex processes of tsunami wave generation induced by both rigid and deformable landslides. Then we perform numerical simulations of 162 landslide-induced waves scenarios with varying landslide deformability, relative initial positions, densities, landslide size, and downstream water depths using the validated SPH model. The results show that the effect of density and initial water depth on the maximum wave height can be disregarded, while the effective landslide volume has a significant effect. The analysis of the kinetic and potential energy of the induced waves reveals that energy transfer occurs rapidly, which mainly increases the potential energy of the water downstream. We also find an exponential relationship between landslide potential energy reduction and maximum wave height. These findings provide valuable insights into the landslide-induced tsunami waves and enhance risk assessment and mitigation efforts.

Numerical Simulation of the Large‐Scale Huangtian (China) Landslide‐Generated Impulse Waves by a GPU‐Accelerated Three‐Dimensional Soil‒Water Coupled SPH Model

AbstractThis work presents an improved soil‒water coupling model to simulate landslide‐generated impulse waves (LGIWs) in a unified smoothed particle hydrodynamics (SPH) framework, where both water flow and landslide motions are modeled by SPH using an interface coupling technique. Graphics processing unit technology based on an open‐source platform DualSPHysics is chosen to employ the landslide dynamics and soil‒water interface coupling to achieve the capability of large‐scale simulation and high‐resolution modeling for three‐dimensional LGIW problems. A subaerial landslide‐generated water waves, is simulated to demonstrate the accuracy and ability of this model. The Huangtian LGIW is then simulated to reproduce the entire disaster chain, including landslide dynamics, fluid‒solid interaction, and surge wave generation. Particle resolution dependence is examined, giving a particle distance of 5.0 m, which can provide a converged landslide deposit and surge wave. The simulation shows that in the Huangtian LGIW, the landslide deposit volume was approximately 41.6 million m3 (600 m width, 768 m length, and 400 m above the still water level), with an immersed landslide volume of 11.3 million m3; for the surge wave, the maximum wave and run‐up heights were 34.3 and 48 m, respectively. These results are within the estimated ranges of both the landslide and surge wave according to limited field survey data. The case study of the Huangtian LGIW provides a typical reference of how to reproduce a reliable whole process of large scale multi‐physical and multiscale LGIW, including full information of landslide dynamics, interface coupling behavior, and surge wave characteristics.

Earthquake-induced soil landslides: volume estimates and uncertainties with the existing scaling exponents

Quantifying landslide volumes in earthquake affected areas is critical to understand the orogenic processes and their surface effects at different spatio-temporal scales. Here, we build an accurate scaling relationship to estimate the volume of shallow soil landslides based on 1 m pre- and post-event LiDAR elevation models. On compiling an inventory of 1719 landslides for 2018 Mw 6.6 Hokkaido-Iburi earthquake epicentral region, we find that the volume of soil landslides can be estimated by γ = 1.15. The total volume of eroded debris from Hokkaido-Iburi catchments based on this new scaling relationship is estimated as 64–72 million m3. Based on the GNSS data approximation, we noticed that the co-seismic uplift volume is smaller than the eroded volume, suggesting that frequent large earthquakes (and rainfall extremes) may be counterbalancing the topographic uplift through erosion by landslides, especially in humid landscapes such as Japan, where soil properties are rather weak.

Inferring slip-surface geometry and volume of creeping landslides based on InSAR: A case study in Jinsha River basin

The slip-surface geometry and volume of landslides are fundamental for landslide modeling and mechanism interpretation. The movement of a landslide, which is generally controlled by the slip-surface geometry, can be obtained from interferometric synthetic aperture radar (InSAR) measurements. However, there is a lack of a general approach for inferring the slip-surface geometry and volume of landslides through the InSAR-derived deformation field. Here we developed a geometry-based method to determine the landslide slip-surface geometry and volume using InSAR measurements and applied it to the Jinsha River Basin, a landslide-prone area that poses a significant threat to residents and infrastructure. Through the InSAR-derived displacement, topography, and Google Earth images, 50 creeping landslides were identified in the study area. Based on the displacement field, the landslide slip-surface slope was inverted under the assumption that the landslide displacement was parallel to the slip-surface. Then the two-dimensional slip-surface depths and volumes of selected landslides were inferred using the slip-surface slope. Comparisons with the in-situ data suggest that the results obtained in this study are reliable. The mapped landslides in the study area have depths of approximately 16–160 m along the central axis and volumes ranging from 483,412 to 135,789,944 m3. The derived volume–area relationship and 2D slip-surface depth suggest that deep-seated landslide is a major landslide type in the study area. We conclude that our method can infer the slip-surface geometry of creeping landslides based on InSAR observation and our results have improved the understanding of the landslide mechanisms in the Jinsha River Basin, China.

A Physically Based Model for the Sequential Evolution Analysis of Rainfall‐Induced Shallow Landslides in a Catchment

AbstractPredicting the occurrence time, volume, distribution and run‐out length of shallow landslides is critical for assessing the volume of debris flow in a catchment. Recent studies suggest that the landslides hydro‐mechanical triggering (LHT) model based on threshold‐based mechanical interactions can adequately predict rainfall‐induced landslides. However, this model assumes that the soil‐rock interface is the only sliding surface and cannot dynamically determine a sliding surface above the soil‐rock interface. Therefore, by calculating the wetting front depth in the shallow soil layer and using the limit analysis method, the most likely sliding surface can be dynamically calculated to improve the model. Through linking the Soil and Water Assessment Tool (SWAT, USDA) model and the depth‐resolved LHT model (D‐LHT), a framework for predicting shallow landslides in a catchment was proposed in this work. This framework considers the effects of antecedent rainfall, the mechanical reinforcement of roots, and the spatial distribution of soil properties on slopes. The D‐LHT model was applied to the Jiangjia gully in Yunnan, China, to adequately predicted the occurrence time, scale and spatial distribution of shallow landslides. In addition, the present and antecedent rainfall effects on the shallow landslide volume were analyzed. The results showed that the average soil moisture content threshold was determined by antecedent and same‐day rainfall, which affect the timing and volume of the shallow landslides. This study provides a new method for predicting shallow landslides. The stability and simplicity of the model make it suitable for early warning systems.

Prediction of Landslide Deformation Region Based on the Improved S-Growth Curve Model

Quantitative research on and the prediction of a landslide deformation area is an important point to accurately and comprehensively understand the failure mechanism of landslides and the degree of slope failure. This study uses image processing techniques to quantitatively identify the area and volume of deformation regions during rainfall-type landslide destabilization under multifactor conditions. The findings revealed that (1) an increase in rainfall intensity and slope angle, as well as the existence of slope crest, will accelerate the process of slope instability. In our study, when the rainfall intensity was 140 mm/h and the landslide volume reached 35.68%, the landslide failure was the most serious. (2) Slopes with high compaction of subsoil as well as those without perimeter pressure are relatively more damaged. (3) The higher the density of vegetation cover, the stronger the protection ability of the slope, and the higher the wind speed, the greater the failure to the slope. Furthermore, an improved S-growth curve model was proposed to predict landslide volumes in 16 sets of experiments. In detail, the proposed S-growth curve model predicted landslide volumes with an average absolute percentage error of 4.34–16.77%. Compared with the time series analysis moving-average method (average absolute percentage error of 6.39–68.89%), the S-growth curve model not only has higher prediction accuracy but also can describe the three stages of deformation region development from a physical perspective and can be applied to the volume during landslide change prediction.