Earthquake-induced Landslides Research Articles

Computational modeling of near-fault earthquake-induced landslides considering stochastic ground motions and spatially varying soil

Landslides represent a large-deformation process influenced by various factors of uncertainty, such as types of ground motion (GM), randomness of GMs, and spatial variability of soils. The behavior of landslides is profoundly affected, making their assessment and measurement challenging. This paper proposes a computational approach for simulating the large-deformation process of landslides based on three-dimensional (3D) non-ordinary state-based peridynamics (NOSBPD). The analysis results of NOSBPD indicate that the mean runout distance triggered by pulse-like ground motions (PLGMs) is 16% greater than that induced by non-pulse ground motions (NPGMs), suggesting that PLGMs exhibit higher destructiveness. Besides, this paper establishes a runout distance assessment framework by considering the stochastic nature of PLGMs. This framework allows for the evaluation of the specific risk probability of landslides caused by stochastic PLGMs that match the target spectrum specified by codes. By introducing the theory of random fields and implementing a coupled procedure in peridynamics, we conducted a detailed analysis of the impact of spatial heterogeneity on the evolution process and consequences of landslides. Additionally, compared to two-dimensional (2D) analysis, the mean runout distance obtained from 3D analysis increased by 27.5%. This suggests that 2D analysis may underestimate the consequences of landslides. The findings of this study can serve as a scientific foundation for predicting the extent and scope of landslides triggered by near-fault earthquakes.

Seismic landslide susceptibility evaluation model based on historical data and its application to areas with similar environmental settings

Seismic landslide susceptibility evaluation models are usually built on the basis of historical sample data; however, the evaluation results are often unsatisfactory when the environmental settings differ between the historical sample data region and application region. Therefore, similarity between the environmental settings is important for the application of such models. In this paper, a seismic landslide susceptibility evaluation model was first built using data from the 2008 Ms 8.0 Wenchuan earthquake-induced landslide, and the model was then used to evaluate the 2022 Ms 6.8 Luding earthquake area. In addition, the grade of susceptibility is typically represented by the landslide density, which is insufficient for capturing the details of landslides, such as their sizes, frequencies, and spatial distribution patterns. The authors therefore use a large and concentrated landslide as the susceptibility grade for the Luding earthquake area. The test results demonstrate that these two areas have similar background environments. The area under the curve (AUC) value of the receiver operating characteristics (ROC) curve of the evaluation accuracy for the model applied to the Luding earthquake area is 0.889, which indicates relatively high accuracy. Besides, the results also demonstrate that the evaluations are consistent with the disaster situation of the Moxi Platform, Wandong Village, as well as the Dagangshan Hydropower Station area. Therefore, it is reliable to apply the susceptibility evaluation model based on the Wenchuan earthquake data to the Luding earthquake area. These results show that better evaluations can be obtained based on environmental similarity tests between the areas used for historical data modeling and areas to which the models are applied.

DEM analysis on diffuse failure of soil slope triggered by earthquakes

Earthquake-induced diffuse landslide can cause considerable harm. This study used discrete element modeling (DEM) to investigate the diffuse failure of soil slopes triggered by earthquakes. Initially, the DEM was validated through demonstrating satisfactory agreement with the experimental results of a shaking table test. Subsequently, the time and most realistic location of diffuse failure occurrence was quantified using discrete second-order work. Diffuse failure was associated with abrupt fluctuation of the second-order work and a local burst of kinetic energy. Within the context of second-order analysis, the frictional resiBstance of the slope was analyzed. Both the in-phase and the out-of-phase evolutions of frictional resistance and seismic loading were captured. The distinctive in-phase response was identified as an important feature of diffuse failure. Moreover, the predominant influence of particle rolling behavior on frictional resistance development during diffuse failure progression was highlighted. The magnitude and anisotropy of the contact force are profoundly influenced by the input vibration amplitude, resulting in variations in frictional resistance, which suggests that stress-induced anisotropy plays a crucial role in diffuse failure. The results of this study shed light on the grain-scale failure mechanisms of earthquake-induced landslides, and serve as the basis for elucidating the failure behavior of seismic-induced landslides.

Optimized landslide susceptibility prediction based on SBAS-InSAR: case study of the Jiuzhaigou Ms7.0 earthquake

Earthquake-induced landslides can cause severe surface damage and casualties, posing a serious threat to the overall ecological environment and social stability. Traditional landslide susceptibility prediction (LSP) techniques often suffer from low effectiveness and precision, necessitating the exploration of remote sensing technology. However, this research in this area is limited, and the development of high-performance prediction models remains a pressing scientific issue. This study focuses on the Ms7.0 earthquake in Jiuzhaigou on 8 August 2017. To investigate the optimal integration of remote sensing technology with traditional LSP techniques, the study applies collaborative factor analysis and contingency matrix methods to create four new coupling models (SVM-I, SVM-II, RF-I, RF-II), followed by a comprehensive performance evaluation of these models. The results indicate that the integration of SAR-derived surface deformation data significantly enhances the accuracy of Landslide Susceptibility Mapping (LSM). Comparing the model performance with the receiver operating characteristic curve and landslide density, the reliability and prediction performance of the RF-I model are outstanding, reflecting that the improved method based on the InSAR collaborative machine learning model with shape variables along the slope direction can optimize the accuracy of the LSM, and has better performance and robustness in earthquake landslide susceptibility evaluation.

Modeling Earthquake-Induced Landslide Risk for Mountain Railway Alignment Optimization

Modeling Earthquake-Induced Landslide Risk for Mountain Railway Alignment Optimization

Investigating the reactivation of historical landslides during the 2022 Luding MS6.8 earthquake

On September 5, 2022, a strong earthquake with a magnitude of MS6.8 struck Luding County in Sichuan Province, China, triggering thousands of landslides along the Dadu River in the northwest-southeast (NW-SE) direction. We investigated the reactivation characteristics of historical landslides within the epicentral area of the Luding earthquake to identify the initiation mechanism of earthquake-induced landslides. Records of the two newly triggered and historical landslides were analyzed using manual and threshold methods; the spatial distribution of landslides was assessed in relation to topographical and geological factors using remote sensing images. This study sheds light on the spatial distribution patterns of landslides, especially those that occur above historical landslide areas. Our results revealed a similarity in the spatial distribution trends between historical landslides and new ones induced by earthquakes. These landslides tend to be concentrated within a range of 0.2 km from the river and 2 km from the fault. Notably, both rivers and faults predominantly influenced the reactivation of historical landslides. Remarkably, the reactivated landslides are characterized by their small to medium size and are predominantly situated in historical landslide zones. The number of reactivated landslides surpassed that of previously documented historical landslides within the study area. We provide insights into the critical factors responsible for historical landslides during the 2022 Luding earthquake, thereby enhancing our understanding of the potential implications for future co-seismic hazard assessments and mitigation strategies.

Recent Jishishan earthquake ripple hazard provides a new explanation for the destruction of the prehistoric Lajia Settlement 4000a B.P.

The Jishishan Ms 6.2 earthquake occurred at 23:59 on December 18, 2023 in Gansu Province, China. We conducted a field survey to assess the hazards and damages caused by the earthquake and its associated geo-activities. Subsequently, we organized a seminar to discuss the possible causes of the destruction of a prehistoric site—Lajia Settlement—dated back to four thousand years B.P. and located only several kilometers away from the epicenter of the Jishishan earthquake. The Jishishan earthquake was unique for its hazard and disaster process, which featured ground shaking and a series of complex geological and geomorphological activities: sediment and soil spray piles, liquefaction, collapse, landslide, and mudflow along water channels. We define this phenomenon as the Jishishan earthquake ripple hazard (JERH). The most recent evidence from the JERH suggests that a prehistoric earthquake similar to the JERH, instead of riverine floods or earthquake-induced landslide dam outburst flood, as previously hypothesized, destroyed the Lajia Settlement.

Directionality of Arias intensity in the Wenchuan Mw 7.9 earthquake, China

There is a strong correlation between Arias intensity and the possibility of earthquake-induced landslides. Since landslides have distinct sliding directions, it is necessary to investigate the directional characteristics of Arias intensity. The free-field recordings from 40 stations within 200 km of fault distance in the Wenchuan Mw 7.9 earthquake were selected for this study. We discovered that the fluctuation of Arias intensity with azimuth exhibits distinct features of cosine (or sine) curve with a period of 180°, and we proposed a theoretical expression (Eq. 3) of Arias intensity considering directionality using the maximum value (Ia100), the minimum value (Ia00), and the polarization direction (Amax). The maximum-to-minimum ratios of Arias intensity (Ia100/Ia00) decrease as fault distance increases and can be represented as a piecewise linear decreasing relationship that declines significantly faster in the near-middle field than in the middle-far field. The polarization directions (Amax) for stations near the epicenter are consistent with the coseismic displacement directions, which should be further validated by testing various faulting styles; an estimated equation for the azimuth of the projection of the trace of fault movement on the ground surface was employed to predict Amax using the fault's strike, dip, and rake. Finally, we provided a framework for constructing empirical directional model of Arias intensity using the traditional attenuation relationship, the empirical relationship of Ia100/Ia00, and the estimated equation of Amax, as well as thereby a method for predicting Newmark displacement considering directionality. There is an imperfect solution for Amax estimation, other than our work would still serve as a point of reference for future research into the regional directionality of Arias intensity.

Susceptibility assessment of earthquake-induced landslide by using back-propagation neural network in the Southwest mountainous area of China

Susceptibility assessment of earthquake-induced landslide by using back-propagation neural network in the Southwest mountainous area of China

Earthquake-Induced Landslides in Italy: Evaluation of the Triggering Potential Based on Seismic Hazard

Earthquake-Induced Landslides in Italy: Evaluation of the Triggering Potential Based on Seismic Hazard

Submarine landslides and tsunami genesis in Sagami Bay, Japan, caused by the 1923 Great Kanto earthquake

The 1923 Great Kanto earthquake occurred on September 1, in Japan, and caused severe damage mainly in the Kanto region. Tsunamis were observed over wide regions from the east coast of the Izu Peninsula to the west coast of the Boso Peninsula, and particularly, the damage in Atami was devastating. Many earthquake fault models including those of Kanamori (1971) and Ando (1971) were proposed based on the records of land deformation. However, such fault models cannot sufficiently explain the tsunami elevation and its initial sea-level motion on the coasts. Hence, the detailed mechanisms remain elusive. This study examines the possibility that a leading mechanism of the tsunami in the 1923 Great Kanto earthquake was a large-scale submarine landslide that occurred at Sagami Bay and at the mouth of Tokyo Bay based on the records of depth data measured by the Imperial Japanese Navy (1924) before and after the earthquake. We first show that the tsunami calculated by each fault model was inconsistent with the waveform at Yokosuka, the coastal tsunami elevations, and initial sea-level motion. Then, based on statistical analysis of the depth changes at the 1923 Great Kanto earthquake, we found that the seafloor bathymetric changes represented large-scale submarine landslides that may correspond to long-runout submarine liquefied sediment flows. The seafloor gradient over a 40 km flow-out distance was equal to or less than 0.4∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^\\circ$$\\end{document}. Through the identification of the submarine landslide source by tsunami backpropagation analysis and utilizing an analytical solution of a high-density gravity flow and a sensitivity analysis, we conducted a range of numerical simulations of the 1923 Great Kanto earthquake tsunamis using a fault model and a submarine landslide tsunami source model due to a high-density liquefied gravity flow. The results quantitatively accounted for the discrepancy between the observed tsunami records with maximum tsunami elevations over 12 m and the fault-model–based simulations with maximum tsunami elevations of 2 to 5 m and explained consistently the maximum tsunami elevation distributions as well as the time-series tsunami waveforms. These results may thus facilitate and deepen our understanding of the earthquake-induced submarine landslide tsunami risk as cascading multi-geohazards.

The formation mechanism of low-angle loess-mudstone seismic landslides

Seismic-induced landslides represent intricate geological phenomena requiring a multidisciplinary investigative approach. This study examines the formation mechanisms of low-angle loess-mudstone landslides triggered by the 1920 Haiyuan M8.5 earthquake. We employ a synthesis of field investigations, high-density electrical resistivity tests, drilling, laboratory experiments, and numerical simulations. High-density resistivity results support the identified zone at the loess-mudstone interface, indicating a saturated area prone to liquefaction. Dynamic triaxial tests further verify liquefaction occurrences during seismic events within this zone. Additionally, numerical simulations conducted with FLAC2D and the PM4Silt constitutive model provide valuable insights into the temporal and spatial progression of landslides. The liquefaction zone experiences severe shear strain, precisely aligning with the location of the sliding band. Shear strain time-history analyses elucidate early manifestations and time-dependent behaviors at interfaces, providing a nuanced understanding of deformation patterns. The study delineates a comprehensive failure mechanism, unraveling how liquefaction in the saturated loess layer initiates in the upper and toe regions, subsequently propagating throughout the slope. Tension in the upper part and compressive uplift at the toe manifest, resulting in overall landslide movement. These findings highlight the significance of differential shear strain, leading to a layered shear deformation zone. The results yield invaluable insights for seismic stability assessments in regions with similar geological characteristics. This research not only advances the understanding of earthquake-induced landslides but also demonstrates the synergy between field investigations, advanced geotechnical testing, and numerical modeling in unraveling complex geological processes.

Carbon Loss from Earthquake Induced Landslides in Fiordland

Landslides triggered by two earthquakes in Fiordland, New Zealand, were mapped using Google Earth Pro retro satellite imagery (eye altitude of 1.5-2.5 km, enabling ± 50 m precision), then catalogued and classified in a GIS inventory. Ground acceleration during the 2003 Mw 7.2 Secretary Island Earthquake resulted in at least 1852 landslides, but the larger Mw 7.8 2009 Dusky Sound Earthquake had lower accelerations and produced only 313. Both events dislodged large swaths of native forest, grassland vegetation and soil from Fiordland’s steep slopes in similar proportions, some landing in rivers and fiords. The landslide maps and magnitude-frequency distributions show close similarity to a published Global Forest Loss dataset derived from 2001-2022 satellite imagery. Assuming forest loss in this wilderness is predominantly landslide-related, it enables the more-precise earthquake-induced landslide mapping to be placed in a longer-term context of other vegetation loss, mostly rainfall-induced landslides, during the past two decades. The total area of forest loss during the 2003 earthquake was anomalous, whereas during 2009 the earthquake losses were similar to areas of forest loss assumed to be rainfall-induced landslides throughout Fiordland each year. Carbon concentrations of landslide vegetation and soil were calculated by defining vegetation types from a published Land Cover Database, and soil organic carbon concentration from a 1 km resolution raster dataset. Total carbon loss from earthquake-induced landslides amounts to 2.05E+06 tonnes for the 2003 Mw7.2 and 2.17E+05 tonnes for the 2009 Mw 7.8. By way of comparison, New Zealand’s total annual carbon sequestration was 6.3E+06 tonnes in 2020. Earthquake-induced and rainfall-induced landslides are shown to account for significant changes in stored carbon and available carbon sequestration, especially in areas of densely vegetated land, such as Fiordland. Processes of landscape disturbance should be included in carbon accounting and estimates of national greenhouse gas emissions.
 
 Supervised by: Caroline Orchiston
 Scholarship Project Funded by: Centre for Sustainability

Quick analysis model for earthquake-induced landslide movement based on energy conservation

Quick analysis model for earthquake-induced landslide movement based on energy conservation

Pixel-based classification method for earthquake-induced landslide mapping using remotely sensed imagery, geospatial data and temporal change information

Pixel-based classification method for earthquake-induced landslide mapping using remotely sensed imagery, geospatial data and temporal change information

Source area morphometry and high depletion rate of landslides may indicate their coseismic origin

Ancient coseismic landslides indicate prehistoric earthquakes and may also be a measure of their intensity. Their identification in the landscape remains, however, challenging. We used field geologic observations of source areas of recent rainfall-induced and earthquake-induced landslides to define a morphometric index that can distinguish between these two types of triggers. Morphometries of 129 landslides from tropical, subtropical and temperate zones developed in a variety of bedrock types were described by using the following parameters: i) depletion index (Id), i.e. the ratio between the length of the depleted part and the length of the source area; ii) relative slope height (Hrel) and iii) source area angle (φS), i.e. the angle between the top of the line connecting the scarp top with the toe of the source area and the horizontal plane. They were obtained using globally available digital elevation models and satellite images. Their combination into an Index of Potential Trigger (IPT) successfully distinguished between the two types of landslide triggers with an overall accuracy of 87%. The rainfall-induced landslides had a significantly lower average IPT value of 0.01 as compared with 0.37 for the coseismic landslides. The index of potential trigger may be a useful and readily implemented morphometric tool for preliminary identification of prehistoric coseismic landslides recorded in the current topography.

The analysis of seismic induced progressive instability and failure mechanisms: A case study

The 2008 Wenchuan Ms8.0 earthquake triggered a catastrophic landslide, i.e., the Daguangbao (DGB) landslide (1.2 ✕ 109 m3). Its shear failure occurred within a deep-seated (average depth of 400 m) saturated carbonate bedding fault in the Paleozoic Formation. The frequent seismic events in the tectonic belt make the landslide initiation mechanism more complex. Shake table tests were conducted on the DGB landslide to understand the coupling effect of multiple earthquakes, geology and hydrology. The results showed that the multiple earthquakes weakened the friction coefficient as the Boltzmann function on the sliding surface of the landslide. The friction law of the basal surface related to seismic energy was established and incorporated into the Newmark analysis. And the seismic energy consumed in the steep scarp surface release of landslide during an earthquake is also considered. It found that the traditional Newmark model overestimates the time for earthquake-induced landslides due to ignoring the steep scarp surface release stage. It proposed that evaluating pre-earthquake induced slope damage, and critical seismic energy for triggering co-seismic landslides are important for predicting post-seismic landslides.

Impacts of vegetation restoration strategies on soil nutrients and stoichiometry of the earthquake-induced landslides in Jiuzhaigou, eastern Qinghai-Tibet Plateau

Natural and artificial approaches are the mainly management strategy used in degraded lands restoration, while few studies examine the effect of the two strategies on soil nutrient properties in an earthquake-triggered degraded ecosystem. We compared soil chemical traits and major nutrient stoichiometry from areas following landslides that had undergone natural restoration (D. NR.) and artificial restoration (D. AR.), as well as neighboring undisturbed areas (Und.), following the 2017 magnitude 7.0 earthquake in Jiuzhaigou, eastern Qinghai-Tibet Plateau. The results showed that soil organic carbon (C), total nitrogen (N), available nitrogen (AN), available phosphorus (AP), exchangeable calcium (eCa), exchangeable magnesium (eMg), C/P, C/K, N/P, N/K, P/K, cation exchange capacity, and vegetation cover in landslides of D. NR. and D. AR. were lower than those in Und. land, while their pH and total potassium (K) concentration were higher. Compared to D. NR., most of these traits were higher in D. AR., except for the C/N, which was reduced in D. AR. Soil C was positively related to AN, C/K, N/P, N/K, P/K in each land type, while in D. NR., it was not related to N, AP, AK, eCa, eMg, C/N, although it was negatively related to P and K concentration. The findings demonstrated that vegetation restoration strategies could affect not only soil nutrient content but also the macronutrient stoichiometry (N, P, K). Furthermore, artificial restoration projects can enhance soil nutrient concentration and facilitate vegetation recovery more quickly than natural restoration, which is primarily driven by soil N rather than P or K.

Reconnaissance of the Effects of the MW5.7 (ML6.4) Jajarkot Nepal Earthquake of 3 November 2023, Post-Earthquake Responses, and Associated Lessons to Be Learned

On 3 November 2023, a moment magnitude (MW) 5.7 (Local Magnitude, ML6.4) earthquake struck the western region of Nepal, one of the most powerful seismic events since 1505 in the region. Even though the earthquake was of moderate magnitude, it caused significant damage to several masonry buildings and caused slope failures in some regions. The field reconnaissance carried out on 6–9 November by the study team, following the earthquake, conducted the first-hand preliminary damage assessment in the three most affected districts—Jajarkot; West Rukum; and Salyan. This study covers the observed typical structural failures and geotechnical case studies from the field study. To have a robust background understanding, this paper examines the seismotectonic setting and regional seismic activity in the region. The observations of earthquake damage suggest that most of the affected buildings were made of stone or brick masonry without seismic consideration, while most of the reinforced concrete (RC) buildings remained intact. Case histories of damaged buildings, the patterns, and the failure mechanisms are discussed briefly in this paper. Significant damage to Khalanga Durbar, a historical monument in Jajarkot, was also observed. Medium- to large-scale landslides and rockfalls were recorded along the highway. The motorable bridge in the Bheri River suffered from broken bolts, rotational movement at the expansion joint, and damage to the stoppers. The damage observations suggest that, despite the existence of building codes, their non-implementation could have contributed to the heavy impact in the region. This study highlights that the local population faces a potential threat of subsequent disasters arising from earthquakes and earthquake-induced landslides. This underscores the necessity for proactive measures in preparedness for future disasters.

An open-source application software for spatial prediction of permanent displacements in earthquake-induced landslides by the Newmark sliding block method: pyNewmarkDisp

This paper presents pyNewmarkDisp, an open-source application software developed in Python for calculating the spatial distribution of permanent displacements (up) in earthquake-triggered shallow landslides through the Newmark sliding block method. up are often estimated by simplified methods using empirical correlations instead of the direct Newmark method in which ground motion accelerations exceeding a critical value are integrated twice. These simplified procedures have traditionally been justified because of the time consumption, labor intensiveness, and impracticality of the direct Newmark method at large spatial scales. However, pyNewmarkDisp has a well-optimized code taking advantage of NumPy array operations and just-in-time Numba compilation that allows performing the direct Newmark method at large-scale spatial domains, even on general-purpose computers. pyNewmarkDisp is exemplified through a hypothetical study case, and its results are compared to three empirical correlations, showing significant differences and confirming that simplified methods can lead to inaccurate results.