Earthquake-induced Landslides Research Articles

The influence of frequency and duration of seismic ground motion on the size of triggered landslides—A regional view

Observation, theory, and intuition all suggest that larger earthquakes should trigger larger landslides. Many factors could contribute to this, including depth-dependent shear strength or non-linearity of ground motion in soils and rock, but we hypothesize that the key characteristics of large earthquakes causing this phenomenon are (in addition to magnitude) the frequency and duration of the strong ground motion. Because of the paucity of site-specific data for detailed analysis, we take a regional approach to this question by analyzing strong-motion records and earthquake-induced landslide (EQIL) inventories from six well-documented earthquakes. Ground motion is characterized using earthquake magnitude and the median durations and frequencies (mean periods) of subsets of strong-motion records relevant to landslide triggering. EQIL inventories are characterized using the median landslide area of the entire inventory as well as the median areas of the largest 1% of the landslides and the largest 10 landslides. We then compare ground-motion characteristics with landslide size statistics to determine possible correlations. Comparisons of all earthquake- and landslide-size statistics show strong positive correlations between landslide size and (1) magnitude, (2) ground-motion duration, and (3) mean period. Although all the ground-motion measures yield highly correlated regressions, mean period appears to be the best overall predictor of landslide size. Landslide modeling using Newmark's sliding-block method also shows that longer mean periods and durations and larger magnitudes correlate strongly with increases in modeled displacements. These results support our hypothesis that increasing period and duration of seismic ground motion are the physical factors driving increased landslide sizes for larger earthquakes. Additional studies including data from a much larger set of earthquakes is needed to confirm the results of this initial study.

Spatial and temporal evolution of co-seismic landslides after the 2005 Kashmir earthquake

Large earthquakes in mountainous regions often trigger widespread landslides, some of which remain active for years to decades. This study has evaluated the spatial and temporal evolution of the 2005 Kashmir earthquake-induced landslides using pre-earthquake and post-earthquake landslide inventories. Temporal landslide inventories were developed from the SPOT satellite images, using the visual image interpretation supported with field validation. It is observed that after the earthquake, the landslide area and number showed a surge, however, decays in the subsequent years. The rate of decline in the landslide area was relatively slower until 2010, however, it dropped considerably during 2010–2018. The spatial variation of the landslides was traced and analyzed to classify them based on the activity. The temporal evolution of the landslides was compared with the geology, earthquake triggering fault and topographic attributes of slope, aspect, and elevation, to evaluate their influence on the distribution of landslides. The landslide inventories were related to the major triggering factors including rainfall and earthquakes, to determine their impact on the temporal dynamics of the landslides. Regeneration of vegetation is analyzed using the temporal NDVI images as one of the drivers for the decline in the landslide area. The knowledge of temporal dynamics of landslides and their major contributing factors shall assist to understand their triggering mechanism and effective mitigation measures.

Solid-like and liquid-like granular flows on inclined surfaces under vibration – Implications for earthquake-induced landslides

Earthquake-induced landslides can result in serious property damage and significant casualties. Although extensive research has been conducted to investigate their extraordinarily long runout, the underlying mechanism remains a very challenging open problem. In this paper, we explore the effect of vibration on landslide runout through simulations of simplified granular chute flows using the discrete element method with a focus on surface-normal vibration. We show that the mobility of the flows is enhanced by low-frequency vibration for inclination angles of both 19° and 24°. The flows are, however, strikingly different – solid-like for the former and liquid-like for the latter, as revealed by their microstructure and stress states. The vibration enhances the mobility through reduction in the normal load and in the solid volume fraction for the 19° and the 24° flows respectively. This work reveals complexities in the rheological states and the dynamic responses of inclined-surface granular flows under vibration, serving as an initial step to unravelling the full dynamic mechanisms of the long runout of earthquake-induced landslides.

Dynamic properties of Tianshui saturated remolded loess: A laboratory study

Tianshui City is located in an earthquake-prone area of China that has experienced many earthquake-induced loess landslides. The formation of such landslides is closely related to the dynamic properties and residual deformation characteristics of the loess when seismically loaded. However, the loess dynamics under earthquakes in the Tianshui area have been little studied. Therefore, to understand the dynamic properties of loess during the earthquake, consolidated-drained triaxial tests were conducted on saturated remolded loess specimens in GCTS cyclic triaxial test system. The results indicate that (1) The dynamic properties of saturated remolded loess are closely related to the consolidation confining pressure, initial stress state, dynamic stress amplitude and N. The dynamic strength of loess specimens increases with increasing confining pressure but decreases as Nf and the consolidation stress ratio increase. (2) Isotropically consolidated specimens undergo tensile deformation and shear dilation, and the consolidation confining pressure has a significant influence on the accumulated residual strain. However, anisotropically consolidated specimens undergo compressive deformation and shear shrinkage, and the consolidation confining pressure has limited impact on the accumulated residual strain. (3) The dynamic elastic modulus of saturated remolded loess decreases with increasing strain and cycle number, and increases with increasing confining pressure. The damping ratio increases nonlinearly with increasing dynamic strain and decreases with increasing confining pressure. (4) There is a significant critical effect on the growth of residual deformation. After a certain critical N or dynamic stress, the accumulated residual deformation increases rapidly. Under isotropic consolidation, the specimens undergo shear shrinkage in the initial stage of cyclic loading, which gradually changes to shear dilation as the number of cycles increase. Under anisotropic consolidation, the specimens are basically in a state of shear shrinkage under cyclic loading. The results form an important reference for loess material, and are significant in terms of stability analysis of loess slopes and for improving the dynamic constitutive relationships in loess.

A global dataset and model of earthquake-induced landslide fatalities

In this study, we present a newly developed, comprehensive dataset of 196 historical earthquakes, including 127 events with known landslide fatality counts, which we use to examine the impact of earthquake-induced landslides. Using this dataset, we assess the potential impact of seismically induced landslides on affected populations, based on the exposure of population to expected landslide occurrence. We calculate predicted landslide probabilities out of a global statistical landslide model in the area surrounding each earthquake using USGS’s ShakeMap model of strong ground motion. We identify estimated population exposure by comparing the predicted probability grid with a time-corrected global population dataset to determine a predicted landslide exposure index. We compare these values to the number of actual fatalities for 91 training events and use these comparisons, together with the United Nations Human Development Index as a vulnerability proxy, to develop a multiple regression model that can potentially be used to provide order-of-magnitude estimates of human impact of earthquake-induced landslides. We observe a significant positive correlation between predicted and observed fatalities, but with very high variability in fatality rates for similar exposure levels, suggesting that other factors (e.g., landslide type and density, the effect of urbanization on population exposure) should be used to improve this estimate. We also demonstrate that these estimates of landslide impacts can be used in a deterministic mode, in collaboration with use of scenario earthquakes, to assess the potential impacts of anticipated future events. With further development, these landslide scenarios can be used by vulnerable communities to improve land use planning, structural design, and emergency response in landslide-prone areas.

An integrated SEM-Newmark model for physics-based regional coseismic landslide assessment

Earthquake-induced landslides are one of the most catastrophic effects of earthquakes, as evidenced by many historic events over the past decades, such as the 1994 Northridge earthquake in California and the 2008 Wenchuan earthquake in China. Realistic prediction of coseismic landslides is crucial for the design of key infrastructure and to protect human lives in seismically active regions. To date, analytical methods for estimating coseismic landslides have been based on highly simplified models. In this study, an integrated Spectral Element Method (SEM)-Newmark model is developed to directly simulate three-dimensional wave field in complex topography on a regional scale, while the associated landslide is indicated by the Newmark sliding displacement analysis considering key model factors. Topographic amplification, soil response, near-field characteristics of earthquake shaking and hydrogeological conditions can be simulated, and their effects on coseismic landslides are studied. In this paper, two regional-scale case studies were conducted using the developed SEM-Newmark model, including landslide hazard assessment for natural terrain in the western part of Hong Kong island, and the massive landslides occurred during the 2014 M6.5 Ludian earthquake in China. These case studies demonstrated that the proposed integrated model can be effectively used for regional-scale coseismic landslide hazard assessment under various earthquake scenarios and hydrogeological conditions.

GIS-based pre- and post-earthquake landslide susceptibility zonation with reference to 1999 Chamoli earthquake

Landslides induced due to monsoon rainfall and earthquakes are very common phenomena in Uttarakhand Himalayas of India. For example, many such landslides got induced and reactivated by the 1999 Chamoli earthquake. In view of above, authors have made an attempt to prepare pre- and post-earthquake landslide susceptibility zonation (LSZ) maps for a part of Chamoli district, Uttarakhand, India. The novelty of this work lies in producing an LSZ map considering peak ground acceleration (PGA) as one of the controlling factors for earthquake-induced landslide occurrences and validating the LSZ map with the post-earthquake landslide inventory. For this purpose, a spatial database of seven controlling factors, i.e., slope angle, slope aspect, slope curvature, geology, distance to drainage, normalized difference vegetation index (NDVI) and peak ground acceleration (PGA) was prepared in Geographic Information System (GIS). Then, relative frequency ratio (RFR) method was adopted for the LSZ maps. The landslide inventory of 276 landslides (220 pre-earthquake and 56 post-earthquake landslides) was prepared for the study area. Firstly, an LSZ map was generated using six controlling factors excluding PGA and the pre-earthquake landslide inventory (Case I). In another attempt, the LSZ map is prepared using seven controlling factors including PGA and pre-earthquake landslide inventory to examine the influence of seismic parameter (PGA) in landslide susceptibility assessment (Case II). Subsequently, pre- and post-earthquake landslide inventory along with seven controlling factors were used to construct another LSZ map (Case III). Finally, these three LSZ maps were validated and compared with the training and testing data. In this study, a spatial predictive model for earthquake-induced landslide is developed.

Comparison of three statistical methods for earthquake-induced landslides susceptibility in Lushan region China

This paper adopts three models including the logistic regression (LR), support vector machine (SVM), and random forest (RF) to study the susceptibility distribution rule of susceptibility distribution of earthquakes induced landslides. The Area Under the Receiver Operating Characteristic (ROC) curve (AUC) and Ratio were used for evaluating the model’s accuracy and mapping availability susceptibility assessment. The result shows that RF has the best performance in the susceptibility assessment of earthquake-induced landslides in the Lushan region of China.

Proposal of probabilistic prediction method of travel distance in an earthquake-induced landslide

Proposal of probabilistic prediction method of travel distance in an earthquake-induced landslide

Application of an Incomplete Landslide Inventory and One Class Classifier to Earthquake-Induced Landslide Susceptibility Mapping

Rapid and effective evaluation of landslide susceptibility after earthquakes is critical for various applications, such as emergency rescue, land planning, and disaster prevention. Current research suffers from the lack of a complete landslide inventory and sample selection uncertainty issues. To solve these problems, this study presents a landslide susceptibility mapping model that integrates one-class support vector machine (OCSVM) and an incomplete landslide inventory, which was established with the aid of change detection from bi-temporal Landsat images. Wenchuan County is selected as the study area to test the performance of the proposed method. The proposed method is also compared with standard two-class SVM that selects a sample randomly. Experimental results show that OCSVM can achieve better performance than SVM when only an incomplete landslide inventory is available. The findings of this study can be applied to determine regional landslide susceptibility after earthquakes and provide an essential reference for emergency response.

Distance Prediction of Slope-Foot Landslide in Southwest of China Based on GA-BP Neural Network

Landslide is a typical geological hazard in southwest China. In order to reasonably assess the disaster-causing range of earthquake-induced landslides in southwest China, the prediction of landslide movement distance is very important. By making principal component analysis of the factors affecting the distance of landslide movement and combining with the mechanism of landslide movement, the three principal components are named as kinetic energy factor, slope factor and resistance factor, which are used as input neurons of BP neural network. The initial weights and thresholds of BP neural network are optimized by using the global search ability of genetic algorithm, and the prediction models of maximum vertical motion distance (H) and maximum horizontal motion distance (L) of landslide are constructed based on the optimized network. At the same time, on the basis of principal component analysis, a multivariate regression prediction model is constructed, and the results of network model prediction are compared with those of multivariate regression prediction. The optimization effect of genetic algorithm for BP neural network is obvious. The BP neural network model after optimization is accurate and stable in predicting the motion distance of slope foot landslide. The prediction errors of maximum horizontal and vertical motion distances below 10% accounted for 86.67% and 93.33% respectively, which is superior to the original BP neural network and multiple regression prediction model.

Probabilistic seismic landslide hazard assessment: a case study in Tianshui, Northwest China

Probabilistic analysis in the field of seismic landslide hazard assessment is often based on an estimate of uncertainties of geological, geotechnical, geomorphological and seismological parameters. However, real situations are very complex and thus uncertainties of some parameters such as water content conditions and critical displacement are difficult to describe with accurate mathematical models. In this study, we present a probabilistic methodology based on the probabilistic seismic hazard analysis method and the Newmark’s displacement model. The Tianshui seismic zone (105°00′–106°00′ E, 34°20′–34°40′ N) in the northeastern Tibetan Plateau were used as an example. Arias intensity with three standard probabilities of exceedance (63%, 10%, and 2% in 50 years) in accordance with building design provisions were used to compute Newmark displacements by incorporating the effects of topographic amplification. Probable scenarios of water content condition were considered and three water content conditions (dry, wet and saturated) were adopted to simulate the effect of pore-water on slope. The influence of 5 cm and 10 cm critical displacements were investigated in order to analyze the sensitivity of critical displacement to the probabilities of earthquake-induced landslide occurrence. The results show that water content in particular, have a great influence on the distribution of high seismic landslide hazard areas. Generally, the dry coverage analysis represents a lower bound for susceptibility and hazard assessment, and the saturated coverage analysis represents an upper bound to some extent. Moreover, high seismic landslide hazard areas are also influenced by the critical displacements. The slope failure probabilities during future earthquakes with critical displacements of 5 cm can increase by a factor of 1.2 to 2.3 as compared to that of 10 cm. It suggests that more efforts are required in order to obtain reasonable threshold values for slope failure. Considering the probable scenarios of water content condition which is varied with seasons, seismic landslide hazard assessments are carried out for frequent, occasional and rare earthquake occurrences in the Tianshui region, which can provide a valuable reference for landslide hazard management and infrastructure design in mountainous seismic zones.

Relationship between earthquake-induced excess pore water pressure and strong ground motion observed in a monitored fill slope

The generation of excess pore water pressures during ground shaking can be an important earthquake-induced landslide trigger. We measured pore water pressures and seismic ground motion in filled slopes and examined their relationships obtained from 29 observed earthquakes. We characterized pore water pressure and seismic waveforms by calculating several parameters that described their magnitudes and durations. We demonstrate that whilst the instantaneous magnitude of strong ground motion is responsible for the generation of excess pore water pressure, the magnitude of excess pore water pressure generated is related to the peak ground acceleration (PGA) and Arias Intensity (AI) in the observed PGA range of 0.12–1.9 m/s2. The magnitude of peak ground velocity (PGV) also produced a strong correlation although a few exceptional events where long period component (>1 s) of seismic waves is dominant were observed. Lastly, the time-span over which excess pore water pressure continues to rise is affected by the duration of seismic ground motion. Our study shows how excess pore water pressures can be generated in fill-slopes during seismic events. This new knowledge could be used to improve future earthquake-induced landslide hazard assessment.

Earthquake-Induced Shallow Landslide Susceptibility Assessment of Gorkha District

Nepal is very seriously affected by landslides every year causing loss of life and property. Large scale earthquakes that occurred in different time periods such as on 15th January, 1934 or that on 25th April 2015 have proved Nepal as seismically vulnerable -place. Nepal has witnessed several landslides during and after the earthquake events making some areas of land quite vulnerable for settlement and other usages. Therefore in order to minimize the impacts of landslides caused due to earthquakes, highly susceptible locations should be identified and spatial planning is made accordingly. Considering topographic effects in amplification of earthquake ground motion, Uchida et al. (2004) have developed a topographical parameter based empirical description of landslide susceptibility during an earthquake. In this research, the method proposed by Uchida et al. (2004) is utilized in raster GIS and landslide susceptibility analysis is performed in the study area of SulikotGaupalika of Gorkha district, Nepal which was severely hit by several landslides due to “Gorkha Earthquake 2015". The landslide inventory map of SulikotGaupalika due to “Gorkha Earthquake 2015" is obtained and is correlated with landslide susceptibility values as obtained by using Uchida et al. (2004). The analysis shows that the method proposed by Uchida et al. (2004) is more than 68.9% accurate in delineating the probable locations of earthquake induced landslides. By calibrating landslide data and landslide susceptibility values in a small site (i.e. SulikotGaupalika) within the study area, a final landslide susceptibility map is prepared for the whole study area of Gorkha district. The resultant susceptibility map is very useful for planning settlements, development activities and reconstruction planning.

Spatial probability assessment of landslide considering increases in pore-water pressure during rainfall and earthquakes: Case studies at Atsuma and Mt. Umyeon

Increased pore-water pressure due to rainfall infiltration and cyclic loading is a major cause of slope instability. Many studies have been carried out to assess rainfall-induced landslide spatial probability based on physical models, combining hydrological models to analyze changes in pore-water pressure on slopes due to rainfall. However, the generation of pore-water pressure due to seismic loading is often disregarded during assessments of earthquake-induced landslide susceptibility. Hence, in this paper, we propose a model to assess landslide spatial probability that takes into account increased pore-water pressure during both rainfall and earthquakes. The procedure for the proposed method includes two main steps. In step 1, we analyze the change in the groundwater table due to rainfall infiltration and subsurface flow during rainfall. In step 2, the slope safety factor is calculated using an infinite slope model, considering the generation of excess pore-water pressure under cyclic loading during earthquakes. Landslide spatial probability is established based on the slope factor of safety. We validated the proposed model by analyzing rainfall-earthquake-induced landslide events occurring on September 6, 2018 in Atsuma town, Japan. According to our results, the area under the receiver operating characteristic curve of the Atsuma landslide data is 82.4% and the true-positive rate of unstable slope classification is 98.1%. The proposed model was then applied to Mt. Umyeon, Korea, to assess the spatial probability of rainfall-earthquake-induced landslide. Our model classifies the likelihood of landslide occurrence according to four susceptibility levels: high, moderate, low and very low. We also compared our results to those of previous models and show that the proposed approach may provide reasonably accurate predictions of landslide spatial probability during rainfall and earthquake events.

Hydrological changes after the 2016 Kumamoto earthquake, Japan

The 2016 Kumamoto earthquake, whose main shock was an M7.3 event on April 16, 2016, 28 h after a foreshock of M6.5, caused severe damage in and around Kumamoto Prefecture, Japan. It also caused postseismic hydrological changes in Kumamoto Prefecture. In this study, we analyzed daily streamflow data collected by eight observation stations from 2001 to 2017 in regions that experienced strong ground motion during the 2016 Kumamoto earthquake. We also surveyed 11 water springs in the region several times after the main shock. Streamflow had no or slight change immediately after the earthquake; however, large increases were recorded at some of the eight stations following a heavy rainfall that occurred 2 months after the earthquake. A decrease in the water-holding capacity of the catchment caused by earthquake-induced landslides can explain this delayed streamflow increase. Conversely, earthquake-related changes to the spring flow rate were not so clear. Water temperature and chemical composition of spring waters were also hardly changed. Only the concentration of NO3−, which is usually considered to be supplied from the surface, changed slightly just after the earthquake. These results show that the postseismic hydrological changes were caused mainly by earthquake-induced surface phenomena and that there was little contribution from hydrothermal fluid.

SPH Simulation of High-Volume Rapid Landslides Triggered by Earthquakes Based on a Unified Constitutive Model. Part I: Initiation Process and Slope Failure

Landslides triggered by seismic loading pose a great threat to human lives, property, and infrastructure. This paper embeds a unified constitutive model in the smoothed particle hydrodynamics (SPH) method and analyzes the initiation process of landslides. A seismic wave is applied to bottom boundary particles by imposing velocities calculated using the seismic wave. The bottom boundary is set as a no-slip boundary and the free field boundary is chosen to reduce seismic wave reflection. The reliability of the developed SPH method is first validated by the simulation of a benchmark problem of thin plate oscillation and stability analysis of a homogenous slope. Initiation of the earthquake-induced Tangjiashan landslide is then simulated as a case study. Formation of a shear zone under the action of seismic loading is followed by the formation of a continuous slip surface at about 15[Formula: see text]s. The sliding surface formed in the SPH simulation agrees well with the speculative sliding surface based on field observations. The velocities of monitored points during the initiation process are also captured by the SPH method.

SPH Simulation of High-Volume Rapid Landslides Triggered by Earthquakes Based on a Unified Constitutive Model. Part II: Solid–Liquid-Like Phase Transition and Flow-Like Landslides

High-volume fast-moving landslides undergo a solid–liquid-like phase transition. In this study we apply the smoothed particle hydrodynamics (SPH) method to simulate the solid–liquid-like phase transition in earthquake-induced landslides based on a unified constitutive model. The feasibility analysis is carried out from two aspects: the governing equations in SPH and the unified constitutive model. A sand-collapse experiment simulating the fluidization motion is performed to verify the SPH model. Strong similarities between the SPH results and the experimental results are observed, confirming that the motion of geo-materials in different states can be simulated by the unified constitutive model. The entire process of the Tangjiashan landslide is reproduced. The SPH simulation shows that during the initiation process, the sliding-mass velocity was low as the geo-materials were in solid state. As shown in Part I of this study, a continuous slip surface formed at about 15[Formula: see text]s. The sliding body gains speed as it enters the fluid state. About 50[Formula: see text]s later, the mass gradually stops moving, reaches a steady state and returns to a solid phase. Besides, the SPH simulation based on elastic–plastic model clearly shows the advantage of the proposed model.

Quantification of human vulnerability to earthquake-induced landslides using Bayesian network

Devastating landslides were frequently triggered by earthquakes and caused severe damage and human losses. More than 25,000 people were killed by the Wenchuan earthquake-induced landslides. A proper model for estimating loss of lives is important in quantifying the human risks posed by earthquake-induced landslides. This paper presents a new model for quantitatively estimating the human vulnerability to earthquake-induced landslides using Bayesian networks. A database incorporating information of fatal landslides induced by the Wenchuan earthquake is established. A Bayesian network is constructed according to a logic structure of loss-of-life mechanisms by considering four types of key factors, i.e., deposit thickness, building damage, evacuation, and resistance capacity. The probabilities of the nodes (factors) and the arcs (inter-relationships) of the network are quantified according to statistical data, judgment based on experiences, and existing physical or empirical models. The human vulnerability to earthquake-induced landslides is quantitatively estimated through constructing a systematic structure considering the uncertainties of the control factors and their inter-relationships. Comparison between the recorded fatality rate and predicted fatality is conducted to verify the proposed model. Finally, sensitivity analysis is conducted to identify the most important parameters that lead to loss of lives.

The September 19, 2017 Mw 7.1 Puebla-Mexico City earthquake: Observed rockfall and landslide activity

This note documents key observations of slope instability and rockfall activity made by the UNAM-GEER reconnaissance team after the Mw 7.1 Puebla-Mexico City earthquake of September 19, 2017. The investigated sites were located in Mexico City and the states of Morelos, Puebla and Mexico. Sites were studied using a combination of ground surveys, UAV imagery, and terrestrial LiDAR imaging. The field reconnaissance efforts were supplemented by analysis of pre- and post-event satellite images to define the boundary of the region affected by earthquake-induced landslides. Most slope failures occurred in remote areas or areas that had a prior history of instability. Overall, the consequences of slope instabilities caused by the 2017 Puebla-Mexico City earthquake were relatively minor compared with the reported structural damage. More than 360 deaths were attributed to this earthquake of which one death was attributed to landslide activities. The size of the area affected by landslides and the intensity of shaking in these areas was consistent with relationships developed in previous studies. The lack of major effects from earthquake-induced landslides is consistent with previous earthquakes in central and southern Mexico and stands in sharp contrast to many parts of Central America where earthquake-induced landslides pose a significant hazard.