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The seismic landslide-pipe problem was investigated numerically using finite-difference code and a bounding surface soil constitutive model [Simple ANIsotropic SAND constitutive model (SANISAND)]. The SANISAND model was calibrated using triaxial monotonic and cyclic tests at the element level and shaking-table test results at the boundary value level. The results show that the calibrated parameters of the SANISAND model can predict monotonic and cyclic triaxial test results and slope displacement response properly. After the verification process, the dynamic response of a slope with the presence of buried pipes under sinusoidal input acceleration was evaluated in terms of slope displacement and the pipe axial strain. The results show that the presence of buried pipes in the slope can reduce slope surface displacement by 50%, especially for shallower burial depths of pipe (i.e., 1–1.5 m). The results of the axial strain of the pipe for changes in the burial depth and location indicate that for pipes buried in the downslope and upslope sections, deeper and shallower burial depths, respectively, lead to less axial strain being imposed on the pipe under landslide actions. The variations of slope geometric parameters (slope width and inclination angle) on slope displacement response and pipe strain patterns show that with increasing slope width and inclination angle, the displacement of sliding mass increases, and the depth of the slope failure wedge decreases. Moreover, the maximum strain of the pipe increases by 150% as the width-to-height ratio (W/H) of the slope increases from 1 to 4. With the increase in soil density, the pipe axial strain increases. The results of dynamic analysis under earthquake records showed that the axial strain of the pipe has a high correlation with the cumulative absolute velocity of seismic input. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The accuracy of Seismic Landslide Susceptibility Maps (SLSMs) is imperative for the prevention of seismic landslide disasters. This study enhances the precision of SLSMs by integrating nine distinct machine learning methodologies with the GeoDetector version 0.0.4 tool to filter both numerical and physical factors contributing to landslide susceptibility. The dataset comprises 2317 landslide instances triggered by the 2013 Minxian Ms = 6.6 earthquake, from which redundant factors were pruned using the Recursive Feature Elimination technique. Subsequent evaluations of the optimized factors, both individually and in combination, were conducted through Frequency Ratio analysis and Factor Interaction assessment. The study juxtaposes the Area Under the Receiver Operating Characteristic Curve (AUC) and the accuracy of nine machine learning models before and after factor optimization. The findings indicate an increase in AUC from a maximum of 0.989 to 0.992 in the Random Forest model, and an 8.37% increase in AUC for the SVM model, signifying a notable enhancement in the stability across all models. The establishment of the SLSM notably elevated the frequency ratio in high-risk zones from 50.40 to 85.14, underscoring the efficacy of combining machine learning and detector optimization techniques in sustainable practices. This research proposes a universal framework aimed at eliminating redundancy and noise in SLSMs and hazard risk assessments, thereby facilitating sustainable geological disaster risk management. [ABSTRACT FROM AUTHOR]

Seismic landslide hazard assessment plays a very important guiding role during urgent earthquake relief. In August 2017, an Ms 7.0 earthquake in Jiuzhaigou County, Sichuan Province, China, triggered thousands of landslides. Based on the analysis of geological settings and coseismic landslide characteristics, the Newmark model is used to complete the seismic landslide hazard assessment. Three seismic motion parameters, namely, peak ground acceleration (PGA), traditional Arias intensity (Arias_P), and improved Arias intensity (Arias_C), are adopted. A publicly published coseismic landslide catalog is used as the validation samples. The results show that the coseismic landslides are mainly distributed in the deep gullies and steep mountainous slopes on the north and south sides of the epicenter. The seismic landslide hazard accuracy based on Arias_C is the best, followed by that based on PGA and Arias_P. The spatial distribution of seismic landslide hazards based on Arias_C shows an almost standard elliptical ring and is in good agreement with that of coseismic landslides. These results fully reflect the combined influence of the epicenter and seismogenic fault on landslide development. The middle seismic landslide hazard and over are mainly located at areas with seismic intensity of VII degree and above. The Arias intensity is very suitable for rapid seismic landslide hazard assessment in emergency situations. The study results can provide scientific and technological support for rapid earthquake relief and have reference significance for future seismic landslide hazard assessment. [ABSTRACT FROM AUTHOR]

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.

Objective The shallow potential sliding layer of a slope is an important feature in seismic geological disasters. Its characteristics, such as slope shape and slope structure, tend to complicate the dynamic response and slope damage. Methods In this paper, the landslide in Xinhua Village, triggered by the Lushan Ms 6.1 earthquake, is taken as a case study, and two-dimensional discrete element computational models are developed based on a field investigation. The dynamic response and simulate instability are investigated by comparing numerical simulations of homogeneous and heterogeneous models, representing pure terrain and a shallow potential sliding layer, respectively. Results The findings are as follows: (1) The potential sliding layer at the shallow surface of the slope exhibits significant dynamic amplification, which typically increases nonlinearly with height; (2)The slope surface shape has an obvious influence on the slope amplification effect.In the convex part, the amplification effect of the horizontal and vertical acceleration of the slope surface is significant, while the amplification effect of the concave part is lower than that of the convex part; (3) In the Xinhua Village landslide, the convex terrain is destroyed before the concave terrain under the effect of micromorphology, and its instability process is divided into five stages, namely, local seismic cracking of vibration amplification, convex terrain destruction, concave terrain destruction, complete destruction of the overall slide and gravity accumulation. Conclusion The research results are helpful for deepening the understanding of potential unstable slopes induced by earthquakes and shedding light on disaster prevention and mitigation.

To enable the accurate assessment of landslide susceptibility in the upper reaches of the Minjiang River Basin, this research intends to spatially compare landslide susceptibility maps obtained from unclassified landslides directly and the spatial superposition of different types of landslide susceptibility map, and explore interpretability using cartographic principles of the two methods of map-making. This research using the catalogs of rainfall and seismic landslides selected nine background factors those affect the occurrence of landslides through correlation analysis finally, including lithology, NDVI, elevation, slope, aspect, profile curve, curvature, land use, and distance to faults, to assess rainfall and seismic landslide susceptibility, respectively, by using a WOE-RF coupling model. Then, an evaluation of landslide susceptibility was conducted by merging rainfall and seismic landslides into a dataset that does not distinguish types of landslides; a comparison was also made between the landslide susceptibility maps obtained through the superposition of rainfall and seismic landslide susceptibility maps and unclassified landslides. Finally, confusion matrix and ROC curve were used to verify the accuracy of the model. It was found that the accuracy of the training set, testing set, and the entire data set based on the WOE-RF model for predicting rainfall landslides were 0.9248, 0.8317, and 0.9347, and the AUC area were 1, 0.949, and 0.955; the accuracy of the training set, testing set, and the entire data set for seismic landslides prediction were 0.9498, 0.9067, and 0.8329, and the AUC area were 1, 0.981, and 0.921; the accuracy of the training set, testing set, and the entire data set for unclassified landslides prediction were 0.9446, 0.9080, and 0.8352, and the AUC area were 0.9997, 0.9822, and 0.9207. Both of the confusion matrix and the ROC curve indicated that the accuracy of the coupling model is high. The southeast of the line from Mount Xuebaoding to Lixian County is a high landslide prone area, and through the maps, it was found that the extremely high susceptibility area of seismic landslides is located at a higher elevation than rainfall landslides by extracting the extremely high susceptibility zones of both. It was also found that the results of the two methods of evaluating landslide susceptibility were significantly different. As for a same background factor, the distribution of the areas occupied by the same landslide occurrence class was not the same according to the two methods, which indicates the necessity of conducting relevant research on distinguishing landslide types. [ABSTRACT FROM AUTHOR]

The Beishan area in Tianshui City is located in the transition zone between the mountainous area on the northern edge of the Qinling Mountains and the Loess Plateau. The solid internal and external dynamic coupling has induced large landslide groups with a zonal distribution, which seriously restricts urban planning and disaster risk prevention in Tianshui City. Based on the systematic summary of existing geological hazard data, this study used the space-sky-earth integrated survey method to identify the variations of loess thickness from west to east, typical slope structure types, and key slip-controlling strata. The seismic landslides' development characteristics, distribution rules, and geometric and kinematic features are systematically analyzed. The results show that the landslide groups in the Beishan area are concentrated along the north bank of the Jihe Valley in a zonal distribution. The landslide types are mainly mudstone landslide and loess-mudstone interface landslide, with multi-stage rotation, translation, and multi-stage sliding. The stratigraphic structure consists of the overlying Quaternary loess and the underlying lacustrine-fluvial mudstone and claystone of the Neoproterozoic Yaodian and Ganquan formations. The landslides belonging to the bedding rock slope have three typical slope structures from west to east. The loess thickness increases gradually from west to east, the elevation and apparent friction angle are lower in the east and west and higher in the middle, and the scarp height of the landslides is higher in the east and west and lower in the middle. In addition, the seismic landslides in this region have long-runout characteristics. The equivalent friction coefficients of these landslides are between 0.21 and 0.28, and the seismic landslides in the eastern and western sections have stronger movement.

Seismic landslides are characterized by wide distribution and strong destructiveness. On July 22, 2013, the Min-Zhang earthquake occurred and a large number of casualties and building burying were caused by the geological disasters induced by seismic motion. The present research aims to generate seismic landslides susceptibility prediction maps of Min-Zhang earthquake using different machine learning algorithms, providing reference for disaster prevention and reduction in earthquake-affected areas. Five machine learning algorithms including K Nearest Neighbors (KNN), Naive Bayes (NB), Random Forest (RF), Logistic Regression (LR), and Support Vector Machine (SVM) are implemented and the sample dataset was prepared based on the landslide inventory map from open data repository. A total number of 4660 samples containing seismic landslides and non-landslide were collected. The influencing factors of seismic landslide include peak ground acceleration (PGA), epicenter distance, elevation, slope, aspect, plan curvature, profile curvature, fault distance, river distance, and normalized difference vegetation index (NDVI). The performance of five target machine learning algorithms is evaluated and compared using determination coefficient R2 and AUC value of ROC curve. The results indicate that the RF and SVM model have more accurate prediction ability with higher AUC value reaching 0.999 and 0.998, respectively, and the NR model has relatively poor performance resulting from the potential correlation of various influencing factors. Finally, the seismic landslide susceptibility of the Min-Zhang earthquake was mapped using the five trained models and it could offer useful information for seismic hazard management in the future.

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To enable the accurate assessment of landslide susceptibility in the upper reaches of the Minjiang River Basin, this research intends to spatially compare landslide susceptibility maps obtained from unclassified landslides directly and the spatial superposition of different types of landslide susceptibility map, and explore interpretability using cartographic principles of the two methods of map-making. This research using the catalogs of rainfall and seismic landslides selected nine background factors those affect the occurrence of landslides through correlation analysis finally, including lithology, NDVI, elevation, slope, aspect, profile curve, curvature, land use, and distance to faults, to assess rainfall and seismic landslide susceptibility, respectively, by using a WOE-RF coupling model. Then, an evaluation of landslide susceptibility was conducted by merging rainfall and seismic landslides into a dataset that does not distinguish types of landslides; a comparison was also made between the landslide susceptibility maps obtained through the superposition of rainfall and seismic landslide susceptibility maps and unclassified landslides. Finally, confusion matrix and ROC curve were used to verify the accuracy of the model. It was found that the accuracy of the training set, testing set, and the entire data set based on the WOE-RF model for predicting rainfall landslides were 0.9248, 0.8317, and 0.9347, and the AUC area were 1, 0.949, and 0.955; the accuracy of the training set, testing set, and the entire data set for seismic landslides prediction were 0.9498, 0.9067, and 0.8329, and the AUC area were 1, 0.981, and 0.921; the accuracy of the training set, testing set, and the entire data set for unclassified landslides prediction were 0.9446, 0.9080, and 0.8352, and the AUC area were 0.9997, 0.9822, and 0.9207. Both of the confusion matrix and the ROC curve indicated that the accuracy of the coupling model is high. The southeast of the line from Mount Xuebaoding to Lixian County is a high landslide prone area, and through the maps, it was found that the extremely high susceptibility area of seismic landslides is located at a higher elevation than rainfall landslides by extracting the extremely high susceptibility zones of both. It was also found that the results of the two methods of evaluating landslide susceptibility were significantly different. As for a same background factor, the distribution of the areas occupied by the same landslide occurrence class was not the same according to the two methods, which indicates the necessity of conducting relevant research on distinguishing landslide types.

This study proposes a seismic input method for layered slope sites exposed to obliquely-incident seismic waves which transforms the waves into equivalent nodal forces that act on the truncated boundary of a finite element model. The equivalent nodal forces at the left and right boundaries are obtained by combining the free field response of a one-dimensional layered model with a viscoelastic boundary. The equivalent nodal forces at the bottom boundary are obtained by combining the incident wave field with the viscoelastic boundary. This proposed seismic input method for slope sites exposed to obliquely incident seismic waves is implemented with the aid of MATLAB software; it is applied to the seismic response analysis of slope sites in the commercial finite element ABAQUS software. The calculation results are compared with the reference solutions obtained by using the extended model to verify the correctness of the established seismic input method. The proposed seismic input method is then employed to investigate the influencing factors of the seismic response of layered slope sites exposed to oblique incidence P waves. The results show that the angle of incidence, location of the interface between soft and hard rocks, and impedance ratio have significant effects on the seismic landslide.

On May 21, 2021, at 21:48, the Ms6.4 Yangbi earthquake struck Dali prefecture, Yunnan province, China; the maximum PGA reached 714.78 gal, causing 37 casualties and infrastructures damage. A field investigation demonstrated that seismic landslides were concentrated along the G56 Hangrui and Dayangyun highways, classified as local rock falls and shear slides. The shear slides were more severe than the local rock falls and were located along the Dayangyun highway, which was still under construction when the earthquake occurred, severely impacting following engineering activities. Typical shear slides caused by the earthquake were selected for detailed investigations; electrical resistivity topography (ERT) was conducted to study the failure mechanism. The ERT results indicated that the sliding surface was located at the interface between the overburden layer and the underlying rock stratum. The slope failures along the Dayangyun highway were characterized by several tensile cracks on the rear edge, a relatively short displacement, and an accumulation at the toe of the excavated slope where reinforcement measures had not yet been completed. The combined effect of engineering activities and a geological structure provided favorable conditions for slope failure. In addition, seismic motion triggered the landslides; however, engineering activity was a specific and significant factor contributing to the shear slides during the Yangbi earthquake. Excavation and incomplete construction reduced the stability of the overburden soil layer. Although the scale of the seismic landslides in the Yangbi earthquake was generally small, the coming rainy season after the earthquake may contribute for sliding again. [ABSTRACT FROM AUTHOR]

The critical acceleration model plays an important role in seismic slope stability and determines the predictive accuracy of regional seismic landslide hazard assessments. Recently, the critical acceleration model based on the limit equilibrium method has been used to evaluate the seismic stability of regional slopes. However, when the Hoek-Brown failure criterion is used to evaluate the seismic stability of slopes with angles greater than 60°, the results obtained is unconservative by limit equilibrium method. Therefore, based on the simulation of a typical slope model with finite element limit analysis, prediction equations of the critical acceleration are established. The corresponding results are compared with the prediction results from the limit equilibrium method. This comparison shows that the proposed critical acceleration model has higher predictive accuracy than the limit equilibrium method, especially when the Hoek-Brown failure criterion is used to evaluate the slopes with angles greater than 60°. The proposed model is applicable to the global scope and can be effectively applied to regional seismic landslide hazard assessments.

Abstract Geological disasters are a great threat to people’s lives and property. At present, it is difficult to evaluate quantitatively the cascading effects of regional geological disasters, and the development of new methods for such evaluation is much needed. In this study, the authors have developed a joint procedure that couples the Newmark model and the RockFall Analyst model based on a GIS platform in order to identify the impact of seismic landslides on roads. The new method effectively combines two processes—seismic landslide occurrence probability analysis and mass movement trajectory simulation. The permanent displacement derived from the Newmark model is used to identify potential source areas of landslides. Based on the RockFall Analyst model, the possible impact of mass movement on the roads can be simulated. To verify the reliability of the method, the landslides induced by the 2017 Jiuzhaigou Earthquake were taken as a case study. The results suggest that about 21.37% of the study area is at high risk of seismic landslides, and approximately 3.95 km of road sections are at extremely high risk of large landslides. The simulated area is consistent with the distribution of disasters revealed by post-earthquake remote sensing image interpretation and field investigation in existing studies. This indicates that the procedure, which joins the Newmark and RockFall models, has a high reliability for risk identification and can be applied to seismic landslide risk assessment and prediction in similar areas.

The primary means of transportation for various substances including water, oil and natural gas are the nation's pipelines. From the geotechnical perspective, one of the prime reasons for buried pipeline failure is the impact of ground deformation either resulting from the earthquake (viz. landslide, lateral spreading, fault movement), or from nearby pipe bursting operation. Failure of a pipeline can lead to an explosion, environmental contamination, fire, financial loss, and risk to living beings. Hence, it is crucial to design the buried pipeline considering the impact of potential earth movement. In this regard, the current review article highlighted the impact of seismic landslide and other possible patterns of ground deformation on buried pipeline along with the effect of pipe bursting induced ground movement on surrounding pipeline particularly focusing on analytical works. In addition, a statistical sensitivity analysis is also performed to identify the most influencing pipe-soil input design parameters. • Investigated the impact of ground movement resulting from seismic excitation and pipe bursting on buried pipeline. • Highlighted future research directions particularly emphasising past analytical and semi-analytical works. • Performed a statistical sensitivity analysis to identify most influencing pipe-soil input design parameters. • Highlighted typical failure modes of buried pipe and the importance of proper pipe-soil interaction modelling. [ABSTRACT FROM AUTHOR]

Earthquake-induced landslides, also called seismic landslides (SLs), are some of the most catastrophic natural hazards on the Tibetan Plateau (TP). They have frequently caused disastrous impacts on human society but are also important driving forces in regional evolution. The rapid development of multiple advanced techniques and more relevant studies have contributed to much progress in understanding SLs, but a synoptic survey that combines the insights of related studies to build a comprehensive understanding of SLs on the Tibetan Plateau is currently lacking. Here, we adopt recent SLs triggered by the 2005 Kashmir (Mw 7.6), 2008 Wenchuan (Mw 7.9), 2010 Yushu (Mw 6.9), 2013 Lushan (Mw 6.6), 2013 Minxian (Mw 5.5), 2015 Gorkha (Mw 7.8), 2017 Jiuzhaigou (Mw 6.5), 2017 Nyingchi (Mw 6.5), 2022 Lushan (Mw 5.8) and 2022 Luding (Mw 6.6) earthquakes on the TP to overview some advances in data preparation, spatial patterns and controls, landslide patterns and causes, movement and landslide damming, susceptibility, and long-term evolution. The study first summarizes worldwide seismic events that have triggered SLs since 2000 to confirm the TP is a SL-prone area and points out detailed SL-prone tectonic blocks on the TP. Based on landslide inventories of 10 adopted events, the study investigates the SL spatial distribution and finds tectonic and geomorphic controls of SL distribution. The landslide inventories also help us confirm the relationships of landslide sizes (SL number, SL area and SL volume) and magnitudes. Next, we summarize the landslide patterns and possible failure causes and highlight that seismic amplification could play an important role for SL occurrence on steep mountains. We use two important indicators, namely, landslide mobility (H/L) and landslide velocity, to reveal SL movement characteristics; we analyze the characteristics of SL damming, dam breaks and outburst floods; we analyze the SL susceptibility process and propose the most common landslide controlling factors (altitude, slope, PGA, seismogenic faults, rivers and stratigraphy) for SL susceptibility; we analyze postseismic evolution using two important indicators, namely, landslide activity and debris flow activity. Finally, we compare the results with other earthquakes worldwide and find that the TP is more sensitive to SLs; SL distribution laws of other worldwide seismic events are not fully consistent with those of the TP, including few seismic liquefaction landslides occur on the TP, while it is common for coastal earthquakes, and SLs on the TP require longer recovery periods. [ABSTRACT FROM AUTHOR]

Geological disasters are a great threat to people’s lives and property. At present, it is difficult to evaluate quantitatively the cascading effects of regional geological disasters, and the development of new methods for such evaluation is much needed. In this study, the authors have developed a joint procedure that couples the Newmark model and the RockFall Analyst model based on a GIS platform in order to identify the impact of seismic landslides on roads. The new method effectively combines two processes—seismic landslide occurrence probability analysis and mass movement trajectory simulation. The permanent displacement derived from the Newmark model is used to identify potential source areas of landslides. Based on the RockFall Analyst model, the possible impact of mass movement on the roads can be simulated. To verify the reliability of the method, the landslides induced by the 2017 Jiuzhaigou Earthquake were taken as a case study. The results suggest that about 21.37% of the study area is at high risk of seismic landslides, and approximately 3.95 km of road sections are at extremely high risk of large landslides. The simulated area is consistent with the distribution of disasters revealed by post-earthquake remote sensing image interpretation and field investigation in existing studies. This indicates that the procedure, which joins the Newmark and RockFall models, has a high reliability for risk identification and can be applied to seismic landslide risk assessment and prediction in similar areas. [ABSTRACT FROM AUTHOR]

This work represents a regional potential seismic landslide hazard assessment for the Tianshui area, southeastern Gansu Province, China. The peak ground accelerations for two specific seismic scenarios (Ms 7.0 and 8.0) are estimated through empirical attenuation relationships. They are then combined with the slope threshold accelerations to calculated cumulative displacements through the Newmark’s sliding rigid-block model. Potentially unstable areas are identified based on the predicted Newmark displacement. The results show that both of the scenarios are capable of producing widespread slope instabilities, mainly loess landslides in the near-fault region, and that the Ms 7.0 earthquake would induce more slope instabilities around Tianshui city. The high-risk zones are concentrated mainly in the loess or mudstone areas with slope greater than 30°, especially on the banks of the Wei River, Xi River, and Niutou River, and pose a threat to the Longhai Railway line and the surroundings of Tianshui city. The potential damage to traffic networks and to built-up areas in Tianshui city is also mapped. These maps represent a preliminary assessment that can be utilized by local government to define the seismic landslide hazard better for future detailed risk evaluation, emergency plans, and engineering design. [ABSTRACT FROM AUTHOR]

The estimation uncertainties and spatial variability of input parameters are gaining more attention and have frequently been taken into account in seismic slope deformation predictions, but the influence of DEM resolution has rarely been investigated. In this paper, the impact of DEM resolution on the seismic landslide hazard is investigated through the comparison between various seismic landslide hazard assessments evaluated from multi-resolution (10, 30, and 90 m) DEMs in the loess area of Tianshui, China, using the Newmark displacement method. The results show that the 90 m relatively coarse resolution DEM underestimates the estimated Newmark displacement. The 30 and 10 m resolution DEMs basically give the similar predictions while the 10 m higher-resolution gives higher resolution at the local convex topography such as scarps and ridge crests. It suggests that the ability of Newmark method to predict landslide occurrence accurately not only depends on the assigned shear strengths, but also is controlled predominantly by the distribution of slope angles. Making accurate maps of seismic landslide hazards will require high-resolution DEM, apart from the associated ground-motion parameters and assigned shear strengths. [ABSTRACT FROM AUTHOR]

The eastern Himalayan syntaxis is one of the most tectonically active and earthquake-prone regions on Earth where earthquake-induced geological disasters occur frequently and caused great damages. With the planning and construction of Sichuan-Tibet highway, Sichuan-Tibet railway and hydropower development on the Yarlung Zangbo River etc. in recent years, it is very important to evaluate the seismic landslide hazard of this region. In this paper, a seismic landslide hazard map is produced based on seismic geological background analysis and field investigation using Newmark method with 10% PGA exceedance probabilities in future 50 years by considering the influence of river erosion, active faults and seismic amplification for the first time. The results show that the areas prone to seismic landslides are distributed on steep slopes along the drainages and the glacier horns as well as ridges on the mountains. The seismic landslide hazard map produced in this study not only predicts the most prone seismic landslide areas in the future 50 years but also provides a reference for mitigation strategies to reduce the exposure of the new building and planning projects to seismic landslides. [ABSTRACT FROM AUTHOR]

As a potential destructive secondary hazard initiated by earthquakes, earthquake-triggered landslides can cause significant losses. Seismic landslide hazard maps are important for land use planning and landslide hazard reduction in tectonically active areas. A comprehensive probabilistic seismic landslide hazard mapping approach incorporating the uncertainties of slope properties and displacement prediction is required to promote the application of hazard maps. Based on the definition of the critical slope angle, this paper proposes an alternative seismic landslide hazard category considering the uncertainty of geotechnical properties of soil using Monte Carlo simulations and incorporating the ground motion variability based on the displacement hazard curve. The proposed new hazard category is applied to the region of Anchorage, Alaska, for the seismic landslide hazard mapping process. Subsequently, parameter analyses are performed to explore the sensitivity among the factors that contributed to the seismic landslide hazard map. The results of seismic landslide hazard maps show that the area of hazardous zone of most geologic units in present study is smaller than that in the deterministic analysis. Comparing with the probabilistic method using logic tree analysis, the proposed approach using Monte Carlo simulations predicts different landslide hazardous zone due to the probabilistic distribution of geotechnical properties of soil. The predicted hazardous zone is also sensitive to the resolution of the digital elevation model and different coefficient of variation combinations. • A new procedure to seismic landslide hazard mapping using Monte Carlo simulation. • The uncertainty of geotechnical properties of soil and seismic motions are all considered. • A new seismic landslide hazard category defined by critical slope angle instead of sliding displacement threshold. • Proposed mapping approach is applied to the region of Anchorage, Alaska. • Sensitivity analysis for different influence factors characterized the variability of geotechnical properties of slope. [ABSTRACT FROM AUTHOR]

This paper presents a case study on the Mogangling landslide and its characteristics and geological mechanism. The Mogangling landslide is a giant rock landslide located at the intersection of Dadu river and Moxi river. It is a landslide triggered by an earthquake with large magnitude that occurred in 18th century. Based on detailed site investigation, it shows the Mogangling landslide developed in the Kangding complex strata, composed of completely decomposed aggregates of massive-block stone, debris and soil with some gravels, pebbles and sand layer found distributed in front of the landslide. The control factor of the deformation of this landslide is the combined effect of Detuo fault which is located under the slope, and the regional stress formed along structural planes as well as the free surfaces formed by river cutting. Therefore, when the Kangding-Moxi earthquake (Ms =7.7) occurred on 1st June, 1786, due to seismic shaking, topographic amplification effects and back slope effects, the Mogangling landslide occurred. The Dadu River is the most important river for hydropower development in China; large-scale seismic landslides along the Dadu River are the most important geological issue during the construction of hydropower stations. Therefore, this research is important from the point of view of economic and social benefits. [ABSTRACT FROM AUTHOR]

The present study proposes a simplified analytical solution based on Euler Bernoulli's beam theory to investigate the influence of seismic landslide on buried continuous pipeline. Firstly, the differential equation of the beam (pipe) is derived considering the beam is resting on elastic foundation (soil spring) and then the complete solution (both complementary function and particular integral) of the governing differential equation is developed considering available boundary conditions and continuity conditions of the idealized problem. A quartic polynomial function is adopted to simulate non-uniform ground deformation patterns induced from seismic landslide. The results of analytical solution are compared with the pipe deformation curves obtained by earlier researchers along the permanent ground deformation (PGD) zone. Variation of peak pipe displacement of 9.65% and 9.83% are observed for peak ground deformation of 0.6 m and 1.0 m, respectively. Further, a 3D finite element based numerical analysis is also carried out considering block pattern horizontal transverse ground deformation and compared the result with the proposed analytical solution and maximum variation of 4.31% is observed. Finally, numerically investigated the influence of pipe-soil interface properties on pipe response. The present study will be useful for solving problems related to pipe deformation due to horizontal transverse ground deformation in a simplified manner without performing rigorous numerical analysis and displacement pattern for buried pipe can be obtained. • Proposed an analytical solution for buried pipeline under seismic landslide. • Numerical analysis is done to investigate ground deformation effect on pipeline. • Influence of pipe-soil interfacein numerical analysis is investigated. • Displacement pattern for buried pipe can be obtained using proposed method. • Proposed analytical solution can be used without complicated numerical studies. [ABSTRACT FROM AUTHOR]