Earthquake-induced Landslides Research Articles

Earthquake-induced landslides coupled to fluvial incision in Andean Patagonia: Inferring their effects on landscape at geological time scales

Earthquakes can deeply shape the mountainous landscape through co-seismic landslides, generating large amounts of sediment that are then transported and distributed by rivers, controlling the landscape evolution. This influence is observed in the Liquiñe-Ofqui Fault System (LOFS), an active intra-arc fault system extending hundreds of kilometers through the Andes in Chilean Patagonia. For example, on April 21, 2007, a 6.2 Mw earthquake in the Aysén Fjord triggered over 500 landslides with volumes reaching 12–20 Mm3. Although there is a well-defined recurrence time, no study has focused on the effects of co-seismic landslides and sedimentary dynamics on the evolution of this mountainous landscape. In this research, we seek to improve the long-term understanding of the interaction between landslides and fluvial incisions in this segment of the Andes. For this reason, we implemented the HyLands landscape evolution model to simulate landslide activity coupled to fluvial incision. We consider the landslides that occurred during the 2007 earthquake as a precedent and simulate nine scenarios of ten seismic cycles over 21,000 years based on the 2100-year recurrence time documented in this region for the Holocene. We further used multiple uplift rates, sediment erodibility, drainage area, and channel slope exponent ratios (m/n) associated with the stream power law to assess the parameterization's impact on the landscape. According to our results, earthquake-induced landslides are a fundamental mechanism in the landscape's evolution in this region. Deposits from landslides can create transitory landscape forms that can intervene in fluvial dynamics. A significant part of the landslide sediment can remain on the slopes for thousands of years. We identified that parameterization considerably impacts the evolutionary response of the landscape in the evaluated time scale. Low m/n ratios can generate a different evolutionary response than other scenarios because the slopes are constantly driven towards their threshold angle, intensifying the interaction between landslides and fluvial incisions. Based on our analysis and considering the seismic history of the Aysén Fjord, we can explain a critical primary control of the LOFS on landscape erosion and sediment production. Implementing a hybrid landscape evolution model can help to infer the contribution of sediments associated with large earthquakes and improve the understanding of the role of landslides in the evolutionary history of Andean Patagonia. However, we stress that it is essential to advance in capturing erodibility and incision parameters of the stream power law in the Andes and local geomechanical information. Finally, we believe the landscape evolution models can help to deepen the knowledge of these processes in other Andean basins exposed to these geomorphic processes.

Does machine learning adequately predict earthquake induced landslides?

Machine learning (ML) has been used for landslide susceptibility analysis for a while; however, studies using real-time earthquake induced landslide data are barely used. We used the data from the 2015 Gorkha earthquake in Nepal to assess adequacy of various machine learning models and segregated the importance of various landslide conditioning factors in this study. We used five supervised machine learning (ML) algorithms, namely, Logistic Regression (LR), Random Forest (RF), Extreme Gradient Boosting (XGB), Support Vector Machine (SVM), and Extremely Randomized Trees Classifier (ET) to predict earthquake-induced landslide susceptibility. Due to the Gorkha earthquake and its aftershocks, around 25,000 landslides were triggered, among them 23,217 were located within the study area. Using landslide polygons, 23,217 landslide points, and 23,213 randomly selected non-landslide points were generated. The data was randomly divided into 70:30 ratio to create training and testing data sets for model training and evaluation. Results of the SHapely Additive exPlanations (SHAP) analysis and factor importance analysis using ET infer that the first five crucial factors governing earthquake induced landslides are topographic ruggedness index, slope, distance to fault, peak ground acceleration, and distance to rupture. We evaluated the ML models by comparing their performance using accuracy, precision, recall, F1 score, Kappa value, and Matthew's correlation coefficient (MCC). The results indicated that the accuracy varies between 86.60% for ET to 74.40% for LR. The area under the ROC curve for five machine learning algorithms occurs between 0.866 and 0.744 for actual label prediction and 0.935 to 0.819 for probabilistic prediction. Based on the comparative performance assessment, ET is designated to predict earthquake induced landslides more efficiently than the other ML algorithms. The sum of the results highlights that ensemble learning outperforms other ML based classifiers to assess earthquake induced landslide susceptibility.

An Assessment of Earthquake-Induced Landslides Distribution in Nepal Using Open-Source Applications on Sentinel-1 Tops Sar Imagery

An Assessment of Earthquake-Induced Landslides Distribution in Nepal Using Open-Source Applications on Sentinel-1 Tops Sar Imagery

Earthquake-induced landslides in Norway

Abstract. Norway is located in an intraplate setting with low-to-moderate seismicity. The mountainous landscape leads to a high level of landside activity throughout the country. Earthquake-induced landslides (EQILs) are common in seismically active areas, but there are only a few studies of EQILs in intraplate regions. We systematically analyse all earthquakes in Norway with magnitudes ≥ 4.5 in the time period 1800–2021 CE. For each event we search for reports of EQILs in the available macroseismic data and in the Norwegian landslide database. We furthermore consider precipitation data from the Norwegian Centre for Climate Services to evaluate the role of precipitation in the triggering of the identified potential EQILs. Through this approach, we identify 22 EQILs that have been triggered by eight earthquakes in the magnitude range 4.5–5.9. The events are widely distributed in northern and southern Norway. The maximum landslide distance limits and landslide-affected areas are much larger than those found in empirical studies of global datasets and are in agreement with data from other intraplate regions. For four of the earthquakes, it seems that landslide triggering was due to a combined effect of precipitation and earthquake ground shaking. Our observations confirm that intraplate earthquakes have the potential to trigger EQILs over large distances, most likely due to the low ground motion attenuation in such regions. Slope susceptibility seems to be another important factor in the triggering. Our conclusions demonstrate the importance of considering EQIL potential in earthquake risk management in intraplate regions.

Predicting Earthquake-Induced Landslides by Using a Stochastic Modeling Approach: A Case Study of the 2001 El Salvador Coseismic Landslides

In January and February 2001, El Salvador was hit by two strong earthquakes that triggered thousands of landslides, causing 1259 fatalities and extensive damage. The analysis of aerial and SPOT-4 satellite images allowed us to map 6491 coseismic landslides, mainly debris slides and flows that occurred in volcanic epiclastites and pyroclastites. Four different multivariate adaptive regression splines (MARS) models were produced using different predictors and landslide inventories which contain slope failures triggered by an extreme rainfall event in 2009 and those induced by the earthquakes of 2001. In a predictive analysis, three validation scenarios were employed: the first and the second included 25% and 95% of the landslides, respectively, while the third was based on a k-fold spatial cross-validation. The results of our analysis revealed that: (i) the MARS algorithm provides reliable predictions of coseismic landslides; (ii) a better ability to predict coseismic slope failures was observed when including susceptibility to rainfall-triggered landslides as an independent variable; (iii) the best accuracy is achieved by models trained with both preparatory and trigger variables; (iv) an incomplete inventory of coseismic slope failures built just after the earthquake event can be used to identify potential locations of yet unreported landslides.

Dynamic Process Study of Earthquake-Induced Landslides Applying an Improved Discontinuous Deformation Analysis Method Considering Site Response

Dynamic Process Study of Earthquake-Induced Landslides Applying an Improved Discontinuous Deformation Analysis Method Considering Site Response

Scenario deduction of Natech accident based on dynamic Bayesian network: A case study of landslide accident in a liquor storage tank area in Guizhou Province, China

Industrial technical accidents caused by natural disasters are defined as Natech accidents, such as earthquakes and landslides, which can cause tremendous damage to industrial storage tanks, and lead to accidental leakage and even serious fire and explosion accidents. In this study, a landslide-induced storage tank accident model under earthquake disasters was proposed, and the relationship between landslide mass impact and target impact resistance was taken into account. Also, tank failure and the formation of the pool fire were considered to be the consequences of the Natech accident. Through scenario deduction, the dynamic process of landslide Natech was transformed qualitatively into a disaster chain network diagram composed of a scenario state, a disaster-causing factor and emergency management. The Bayesian network was used to learn and deduce the parameters of the network diagram, and in this process, the prior probability and conditional probability of nodes were obtained primarily by Monte Carlo simulation, and by an improved expert scoring method based on the fuzzy set theory. Through visualization software, the sensitivity analysis of landslide Natech was achieved. Finally, a case study of a liquor storage tank area in Guizhou Province, China was carried out, and the results show that a large amount of hazardous material leakage caused by buckling is key to the formation of pool fire accidents, and several prevention measures for earthquake-induced landslide Natech was proposed according to the sensitivity analysis.

Using the Spatiotemporal Hot Spot Analysis and Multi-Annual Landslide Inventories to Analyze the Evolution and Characteristic of Rainfall-Induced Landslide at the Subwatershed Scale in Taiwan

This study used rainfall and annual landslide data for the 2003–2017 period in Taiwan to determine the long-term evolution of landslides and conducted a spatiotemporal analysis of landslides at the subwatershed scale. The historically severe landslide induced by Typhoon Morakot in 2009 was mainly distributed in the central mountainous region and southern Taiwan. The Mann–Kendall trend test revealed that in 2003–2017, 13.2% of subwatersheds in Taiwan exhibited an upward trend of landslide evolution. Local outlier analysis results revealed that the landslide high–high cluster was concentrated in the central mountainous region and southern Taiwan. Moreover, the spatiotemporal analysis indicated 24.2% of subwatersheds in Taiwan in 2003–2017 as spatiotemporal landslide hot spots. The main patterns of spatiotemporal landslide hot spots in 2003–2017 were consecutive, intensifying, persistent, oscillating, and sporadic hot spots. The recovery rate in the first two years after the extreme rainfall-induced landslide event in Taiwan was 22.2%, and that in the third to eighth years was 31.6%. The recovery rate after extreme rainfall-induced landslides in Taiwan was higher than that after major earthquake-induced landslides in the world, and the new landslides were easily induced in the area of rivers and large landslide cases after Typhoon Morakot in 2009.

Microzonation Site Effects and Shear Strain during Earthquake Induced Landslide Using HVSR Measurement in Ulu Mana Sub-District, South Bengkulu Regency Indonesia

The Ulu Manna area is classified as an area with high landslide potential because of its location and geological structure, which is hilly. The risk of landslides in the Ulu Manna area due to earthquakes in weak areas can be studied using ground shear strain (GSS). This study aimed to provide information on the potential of landslides in the Ulu Manna area, South Bengkulu Regency Indonesia. The data was collected using the Horizontal-to-Vertical Spectral Ratio (HVSR) method. The study area is 195.8 km2 and consists of 32 data collection points. The data processing was performed using WinMASW 5.2 HVSR and ArcGIS Desktop 10.8.2 software to obtain dominant frequency values, amplification values, subsurface soil vulnerability index values, maximum soil acceleration values, and soil shear strain values. The soil shear strain values obtained are on the order of 10-4 to 10-3, meaning that the dynamic characteristics of the soil in the study area are elastic-plastic. This plastic-elastic nature characterizes the area as an area with high landslide potential

Rainfall and Earthquake-induced Landslide Susceptibility Assessment

When rainfall and earthquake occur simultaneously, large-scale landslides can cause direct damage to lives and structures. To reduce such large-scale landslide damage, rainfall and earthquake-induced landslide susceptibility has to be evaluated. Therefore, in this study, landslide susceptibility was evaluated by considering only rainfall, only earthquake, and both rainfall and earthquake in the Atsuma region of Japan, where a large-scale landslide was triggered by a combination of rainfall and earthquake. Through quantitative index analysis, the accuracy of the landslide susceptibility map was improved when both rainfall and earthquake were considered. The proposed method was also applied to the Naari basin in Yangnam-myeon, Gyeongju as a pilot district. We found that the landslide-susceptible area increased when rainfall and earthquake were considered simultaneously than when rainfall and earthquake were considered separately. Through such research, can be used as basic data for complex disaster vulnerability assessment.

Sea-level fluctuations control the distribution of highly liquefaction-prone layers on volcanic-carbonate slopes

AbstractUnderstanding and quantifying the hazards related to earthquake-induced submarine liquefaction and landslides are particularly significant offshore of tropical volcanic-carbonate islands, where carbonate production competes with volcanism to create highly contrasted lithological successions. To improve the detection of liquefaction-prone layers, we analyzed physical properties and mineralogy and performed 70 dynamic triaxial tests on 25 sediment cores offshore of the eastern side of Mayotte (Comoros archipelago in the western Indian Ocean) in an area that has experienced significant seismicity since 2018. We found that the main parameter controlling the liquefaction potential offshore of Mayotte is the presence of low-density layers with high calcite content accumulating along the slope during lowstands. This phasing with sea-level fluctuations implies a significant recurrent geohazard for tropical volcanic-carbonate islands worldwide. Furthermore, the relationship we found between the cyclic resistance of sediment and its density and magnetic susceptibility represents a time-effective approach for identifying the hazards related to earthquake-induced liquefaction.

Evaluating the dynamic response and failure process of a rock slope under pulse-like ground motions

Earthquake-induced landslides represent a significant proportion of seismic hazards in mountainous areas. Numerous slope stability analysis methods exist; however, only a few consider the interactions between pulselike seismic waves and landslides. This study investigates the seismic response characteristics of a homogenous step-like slope to evaluate the acceleration ground motion amplification along the surface. Parametric analysis focusing on the effect of pulselike waves on the slope is conducted using the finite difference modeling code Flac 3 D. Based on the numerical simulation results, pulselike seismic waves greatly influence the acceleration and velocity amplification factor (MPGA & MPGV), with maximum amplification usually obtained at the slope’s crest, where sliding failure initiates. The MPGV of rock slope under pulselike seismic waves is 9.3% higher than near-fault non-pulselike and 16% higher than the far-fault. The displacement for pulselike seismic waves is 20% higher than non-pulselike waves. The dynamic failure analysis presented deep failure for the slope under pulselike seismic wave compared to the non-pulselike. The dynamic failure calculated using Flac 3 D agrees with the results of Newmark-type displacement, with a marginal error between 1 and 8%. The study’s findings can be factored into reinforcing seismic engineering design and probabilistic stability analysis.

Impacts and causative fault of the 2022 magnitude (Mw) 7.0 Northwestern Luzon earthquake, Philippines

At 00:43 UTC on 27 July 2022, a 15-km deep major earthquake with magnitude (Mw) 7.0 struck Northwestern Luzon, Philippines. The strongest ground shaking felt was at PHIVOLCS Earthquake Intensity Scale (PEIS) VII (destructive), equivalent to Modified Mercalli Intensity (MMI) VII, in Abra and along the coastal areas of Ilocos Sur. More than a thousand landslides, rockfalls and tension cracks were mapped, near the epicentral region, in the northwestern part of the Central Cordillera. Most of the landslides were shallow-seated, many of which were situated along road cuts. Liquefaction manifested as lateral spreads, sand boils, fissures, ground subsidence, and localized swelling was documented along the coastal areas of Ilocos Sur and river channels in Abra and Ilocos Sur. Sea level disturbance was also observed in some coastal areas of Ilocos Sur and La Union. Damages to buildings and infrastructures were documented in areas that experienced PEIS VI (very strong), equivalent to MMI VI and PEIS VII (destructive). Earthquake data, including hypocentral location, aftershock distribution, focal mechanism solutions and strong motion data, and InSAR observation indicate that the earthquake was generated by an almost north-south striking reverse left-lateral oblique fault that is gently dipping to the east. There is no clear indication of a surface rupture based on InSAR analysis and field investigation. The spatial distribution of geologic impacts, such as earthquake-induced landslides and liquefaction, is strongly controlled by the causative fault, the direction of rupture propagation and geology. Peak ground acceleration (PGA) records show a unidirectional rupture propagation and are congruent with the spatial distribution of earthquake impacts. Although earthquake parameters, deformation analysis and field data suggest that the Abra River Fault is the probable causative fault, the derived geometry and kinematics from the seismotectonic analysis challenge our existing understanding of the nature of the Abra River Fault, as well as the other segments of the Philippine Fault. The need to understand these earthquake sources in the country is needed for a better seismic hazard and risk assessment.

Multi-hazard performance evaluation of hillside buildings under earthquakes and landslides

Earthquake-induced landslide, a cascading hazard in hilly regions, can substantially increase the damaging effects of an earthquake. This necessitates performance evaluation of buildings situated in hilly regions under the effects of landslide-only and landslides following earthquakes. In this study, the performance of two commonly observed hillside building configurations is assessed—namely, step-back and split foundation—subjected to the above-mentioned multi-hazard scenarios using an uncoupled approach. The uncertainty in the soil properties that influence the landslide-induced forces is considered based on laboratory tests of soil samples collected from active landslide sites and an existing database of landslide events. Three-dimensional hillside buildings are analysed for uphill-side landslide scenarios by performing force-controlled non-linear static analyses. Further, a suite of earthquake ground motions is scaled to a predefined intensity level, and then non-linear time history analyses are performed to obtain the damaged state of the buildings prior to assessing the landslide response. It is observed that the earthquake loading history and its direction of excitation significantly affect the response of hillside buildings to a landslide following an earthquake. Further, the step-back building is observed to be more vulnerable to landslide damage when compared to its split foundation counterpart for a given uphill-side landslide scenario.

A method for calculating permanent displacement of seismic-induced bedding rock landslide considering the deterioration of the structural plane

The mechanism of seismic-induced bedding rock landslide is distinct from that of slope instability/landslide in normal gravity conditions; their failure modes are mainly characterized by vibration deterioration effect of rock mass structural plane due to a seismic loading, which has a significant effect on the stability of the bedding rock landslide. Several advanced methods have been proposed to assess earthquake-induced bedding rock landslide. However, the quantitative evaluation of the vibration deterioration effect of structural plane, along with its application in the dynamic stability analysis of bedding rock slopes, remains a challenging topic that requires further study. In this study, on the basic of the analysis of the cyclic shear condition and the cyclic shear test of the structural plane, the expressions to calculate the dilatancy angle and basic friction angle of structural plane under cyclic shear loading are studied. A deterioration formula for structural plane shear strength is proposed, which fully considers the deterioration effect during cyclic shear. Furthermore, a new calculating method of the seismic-induced permanent displacement of the bedding rock landslide, which introduces the deterioration effect of the structural plane, is developed. A case study was used to compare the permanent displacement calculated with the proposed method with those obtained using the Newmark and Qi methods, which demonstrates the effectiveness and applicability of the proposed method.

Comparison of earthquake-induced shallow landslide susceptibility assessment based on two-category LR and KDE-MLR

Geological hazards caused by strong earthquakes have caused continuous social and economic losses and destruction of the ecological environment in the hazard area, and are mostly manifested in the areas with frequent occurrence of geological hazards or the clustering of geological hazards. Considering the long-term nature of earthquakes and geological disasters in this region, this paper takes ten earthquake-stricken areas in Wenchuan earthquake zone as examples to collect shallow landslide data in 2010, combined with the spatial location of landslides and other factors. Kernel density estimation (KDE) method is used to analyze the spatial characteristics of shallow landslide. Taking the space of shallow landslide as the characteristic variable and fully considering the regulating factors of earthquake-induced landslide: terrain complexity, distance to river, distance to fault, distance to road, lithology, normalized vegetation difference index (NDVI) and ground peak acceleration (PGA) as independent variables, based on KDE and polynomial logistic regression (MLR), A quantitative model of shallow landslide in the earthquake area is constructed. The results show that: (1) PGA has the greatest impact on landslide in the study area. (2) Compared with the two-category logistic regression (two-category LR) model, the susceptibility map of landslide prediction results based on the KDE-MLR landslide susceptibility prediction model is more consistent with the actual situation. (3) The prediction accuracy of the model validation set is 70.7%, indicating that the landslide susceptibility prediction model based on KDE-MLR can effectively highlight the spatial characteristics of shallow landslides in 10 extreme disaster areas. The research results can provide decision-making basis for shallow landslide warning and post-disaster reconstruction in earthquake-stricken areas.

Seafloor Observations Eliminate a Landslide as the Source of the 1918 Puerto Rico Tsunami

ABSTRACT The 11 October 1918 devastating tsunami in northwest Puerto Rico had been used as an example for earthquake-induced landslide tsunami hazard. Three pieces of evidence pointed to a landslide as the origin of the tsunami: the discovery of a large submarine landslide scar from bathymetry data collected by shipboard high-resolution multibeam sonar, reported breaks of submarine cable within the scar, and the fit of tsunami models to flooding observations. Newly processed seafloor imagery collected by remotely operated vehicle (ROV) show, however, pervasive Fe–Mn crust (patina) on the landslide walls and floor, indicating that the landslide scar is at least several hundred years old. C14 dates of sediment covering the landslide floor verify this interpretation. Although we have not searched the region systematically for an alternative tsunami source, we propose a possible source—a two-segment normal-fault rupture along the eastern wall of Mona rift. The proposed fault location matches the published normal faults with steep bathymetry and is close to the International Seismological Center–Global Earthquake Model catalog locations of the 1918 mainshock and aftershocks. The ROV observations further show fresh vertical slickensides and rock exposure along the proposed fault trace. Hydrodynamic models from an Mw 7.2 earthquake rupture along the eastern wall of the rift faithfully reproduce the reported tsunami amplitudes, polarities, and arrival times. Our analysis emphasizes the value of close-up observations and physical samples to augment remote sensing data in natural hazard studies.

SUSCEPTIBILITY ASSESSMENT OF EARTHQUAKE-INDUCED LANDSLIDES: THE 2018 PALU, SULAWESI MW 7.5 EARTHQUAKE, INDONESIA

A catastrophic Palu earthquake on September 28th, 2018 with Mw 7.5 triggered countless slope failures, generating numerous landslides. This paper presents a practical method for susceptibility assessment of earthquake-induced landslides in the Palu region and the surrounding area. The statistical weight of evidence (WoE) model was used to assess the relationship between landslides induced by seismic motion and its causative factors to determine the susceptibility level and derive an earthquake-induced landslide susceptibility map of this study area. The 1273 landslides were classified into two data series, training data for modelling (70%) and test data for validation (30%). The six selected thematic maps as landslide causative factors are lithology, land use, peak ground acceleration (PGA), and slope (gradient, aspect, elevation). The selection of causative factors considerably influences the frequency of landslides in the area. The result is satisfactory because the AUC value of the chosen model excelled the minimum limit, which is 0.6 (60%). The estimated success rate of the model is 85.7%, which shows that the relevancy of the model is good with the occurrence of landslides. The prediction rate of 84.6% indicates that the applied model is very good at predicting new landslides.

Evaluating earthquake-induced widespread slope failure hazards using an AHP-GIS combination

Landslides and slope failures are often caused by earthquakes. This study proposes a method to map earthquake-induced slope failure hazards that uses the analytic hierarchy process (AHP) and a geographic information system (GIS) for four districts where many slope failures were induced by earthquakes (the 2018 Hokkaido Eastern Iburi, 2016 Kumamoto, 2008 Iwate-Miyagi Nairiku, and 2004 Mid Niigata Prefecture earthquakes). The assessment system, which was based on the National Research Institute for Earth Science and Disaster Resilience landslide distribution maps, was analyzed using the methods of previously published. We considered the relationships between the earthquake-induced slope failure distributions and landslide hazard factors (elevation, slope angle, slope type, catchment degree, geology, and vegetation). These relationships were utilized for pairwise comparisons of the factors in the AHP analysis. The slope angle, slope type, and catchment degree exerted the highest effects on the slope failure distribution in the four districts. The four earthquake-induced slope failure distributions were highly consistent with the slope failure hazard rank. These results provide a practical method for evaluating earthquake-induced slope-failure hazards.

Small outbursts into big disasters: Earthquakes exacerbate climate-driven cascade processes of the glacial lakes failure in the Himalayas

Risk assessments for potential glacial lake outburst floods (GLOFs) are primarily focused on large, rapidly expanding lakes. However, the mechanism of cascading hazards that cause small outbursts to transition into big disasters is poorly understood. We investigated the Gongbatongshaco GLOF in the Himalayas, to reveal a novel disaster model and mechanism, considering increasing regional temperature, glacial lake area, and glacial retreat. Global warming drives glacial retreat, and uncover loose sediment that can be mobilized as debris flows, triggering small glacial lake outbursts in high mountain regions. Sediment generated from earthquake-induced landslides exacerbates the flow magnitude in a valley to increase the disaster risk. Concentrations of inhabitants located in these areas are subject to socioeconomic vulnerability, leading to post-disaster poverty within these communities. A reasonable GLOFs resilient mitigation framework is proposed. The results offer new insights into risk assessment, especially for small glacial lakes in tectonically-active high mountain environments influenced by climate change and earthquake activity.