A Hazard Assessment Method for Potential Earthquake-Induced Landslides – A Case Study in Huaxian County, Shaanxi Province

The hazard assessment of potential earthquake-induced landslides is an important aspect of the study of earthquake-induced landslides. In this study, we assessed the hazard of potential earthquake-induced landslides in Huaxian County with a new hazard assessment method. This method is based on probabilistic seismic hazard analysis and the Newmark cumulative displacement assessment model. The model considers a comprehensive suite of information, including the seismic activities and engineering geological conditions in the study area, and simulates the uncertainty of the intensity parameters of the engineering geological rock groups using the Monte Carlo method. Unlike previous assessment studies on ground motions with a given exceedance probability level, the hazard of earthquake-induced landslides obtained by the method presented in this study allows for the possibility of earthquake-induced landslides in different parts of the study area in the future. The assessment of the hazard of earthquake-induced landslides in this study showed good agreement with the historical distribution of earthquake-induced landslides. This indicates that the assessment properly reflects the macroscopic rules for the development of earthquake-induced landslides in the study area, and can provide a reference framework for the management of the risk of earthquakeinduced landslides and land planning.

Long-term Activity of Earthquake-induced Landslides: A Case Study from Qionghai Lake basin, Southwest of China

Earthquake-triggered landslides are a major geological hazard in the eastern Tibetan Plateau, and have prolonged impact on earth surface processes and fluvial system. To determine how long co-seismic landslides affect basins, a massive number of landslides existing in Qionghai Lake Basin were investigated for landslide distribution characteristics and geomorphological evidences, with further comparison and analysis using historic seismic analog method. The landslides found in Qionghai Lake Basin showed clear features of seismic triggering with strongly controlled by Zemuhe fault. These landslides are still active at present. Some new slides generally occur in ancient slope failure zones causing serious secondary hazards in recent years. In this study we strengthen the idea that the landslides triggered by the 185o Xichang earthquake （Ms7.5） have long term activity and prolonged impact on the mountain disasters with a period of more than 16o years. Our results support growing evidence that coseismic landslides have a prolonged effect on secondary disasters in a basin, and invite more careful consideration of the relationship between current basin condition and landslide history for a longer period.

Risk Assessment of Disaster Chain: Experience from Wenchuan Earthquake-induced Landslides in China

This paper deals with the formative process of the Wenchuan earthquake disaster chain risk. Selected earthquake-landslides chain risk is critically evaluated by the probability of landslide displacement failure based on the Newmark's permanent-deformation model. In this context, a conceptual model of regional disaster chain risk assessment was proposed, in which the hazardformative environments sensitivity was the core factor as well as the main difference compared with single disaster risk assessment. The disaster chain risk is accumulation of primary disaster risk and the secondary disasters risks. Results derived from the Wenchuan case proved that the conceptual model was suitable for the disaster chain risk assessment, especially the sudden disaster chain. This experience would offer greater potential in application of conceptual model of disaster chain risk assessment, in the process of large-scale disaster risk governance.

Permanent displacement models of earthquake-induced landslides considering near-fault pulse-like ground motions

The permanent displacement of seismic slopes can be regarded as an effective criterion for stability estimation. This paper studied the characteristics of permanent displacements induced by velocity pulse-like ground motions and developed an empirical model to readily evaluate the stability of seismic slopes in a near-fault region. We identified 264 velocity pulse-like ground motions from the Next Generation Attenuation(NGA) database using the latest improved energy-based approach. All selected ground motions were rotated to the orientation of the strongest observed pulse for considering the directivity of the pulse effect, so that the most dangerous condition for slopes was considered. The results show the velocity pulse-like ground motions have a much more significant effect on permanent displacement of slopes than non-pulse-like ground motions. A regression model based on a function of peak ground velocity(PGV), peak ground acceleration(PGA) and critical acceleration(ac), was generated. A significant difference was found by comparing the presented model with classical models from literatures. This model can be used to evaluate the seismic slope stability considering the effects of nearfault pulse-like characteristics.

A Combined Weight of Evidence and Logistic Regression Method for Susceptibility Mapping of Earthquake-induced Landslides: A Case Study of the April 20, 2013 Lushan Earthquake, China

The M_s 7.0 Lushan earthquake triggered a huge number of landslides. Landslide susceptibility mapping is of great importance. Weight of Evidence（Wo E） and Logistic Regression（LR） methods have been widely used for LSM（Landslide Susceptibility Mapping）. However, limitations still exist. Wo E is capable of assessing the influence of different classes of each factor, but neglects the correlation between factors. LR is able to analyze the relationship among the factors while it is not capable of evaluating the influence of different classes. This paper proposes a combined method of LR and Wo E for LSM, taking advantage of their individual merits and overcoming their limitations. An inventory of 1289 landslides was used： 70% were random-selected for training and the remaining for validation. 11 landslide condition factors were employed in the model and the result was validated using Receiver Operating Characteristic（ROC） curve. The results showed that the LRWo E model had a better accuracy than the LR model, producing an area below the curve with values of 0.802 success and 0.791 predictive, higher than that of the LR model（0.715 success and 0.722 predictive）. It is therefore concluded that the combined method of Wo E and LR can provide a promising level of accuracy for earthquake-induced landslide susceptibility mapping.

Geospatial susceptibility mapping of earthquake-induced landslides in Nuweiba area, Gulf of Aqaba, Egypt

Earthquake induced landslides are one of the most severe geo-environmental hazards that cause enormous damage to infrastructure, property, and loss of life in Nuweiba area. This study developed a model for mapping the earthquake-induced landslide susceptibility in Nuweiba area in Egypt with considerations of geological, geomorphological, topographical, and seismological factors. An integrated approach of remote sensing and GIS technologies were applied for that target. Several data sources including Terra SAR-X and SPOT 5 satellite imagery, topographic maps, field data, and other geospatial resources were used to model landslide susceptibility. These data were used specifically to produce important thematic layers contributing to landslide occurrences in the region. A rating scheme was developed to assign ranks for the thematic layers and weights for their classes based on their contribution in landslide susceptibility. The ranks and weights were defined based on the knowledge from field survey and authors experiences related to the study area. The landslide susceptibility map delineates the hazard zones to three relative classes of susceptibility: high, moderate, and low. Therefore, the current approach provides a way to assess landslide hazards and serves for geo-hazard planning and prediction in Nuweiba area.

Liquefaction Susceptibility of Soils With Clay Particles from Earthquake-induced Landslides

The main reason for earthquake-induced landslides is liquefaction of soil,a process considered to occur mostly in sandy soils.Liquefaction which occurs in clayey soils has also been reported and proven in the recent liters- ture,but liquefaction in clayey soils still remains unclear and there are many questions that need to be addressed.In order to address these questions,an depth study on the liquefaction potential of clayey soils was conducted on the ba- sis of field investigation and a series of laboratory tests on the samples collected from the sliding surface of the land- slides.The liquefaction potential of the'soils was studied by means of undrained cyclic ring-shear tests.Research re- sults show that the liquefaction potential of sandy soils is higher than that of clayey soils given the same void ratio; the soil resistance to liquefaction rises with an increase in plasticity for clayey soils;relation between plasticity index and the liquefaction potential of soil can be used in practical application to estimate the liquefaction potential of

An Uncertainty Analysis of the Newmark Displacement Model for Earthquake-Induced Landslides in the Jiuzhaigou National Geopark

In this paper,we present an approach to generating probabilistic hazard maps for earthquake-induced landslides using the Newmark Displacement Model(NDM).This model takes the uncertainties associated with the slope properties(e.g.,soil shear strengths,groundwater table location)into consideration,which is coupled with the hydrological model based on geomorphological,geological,geotechnical,seismological,and rainfall data.Uncertainties and fluctuations in the input parameters of the NDM are considered by treating these quantities asβ-PERT distributions through Monte Carlo techniques,which allows probability value of the NDM to be cast into hazard maps.Additionally,incorporating Monte Carlo techniques can avoid using conservative input parameters in a deterministic approach to capture these uncertainties.Taking the 2017 Jiuzhaigou M_(w)6.5 Earthquake in Sichuan Province,Western China as an example,earthquake-induced landslides probability distribution map is generated with the most appropriate displacement threshold(λ=1 cm).Our results show good performances for realistic landslide hazard assessment,which can serve as a basis for providing a reference for the prediction of earthquake-induced landslide probability and rapid landslide hazard assessment after a strong earthquake.

Factor analysis for the statistical modeling of earthquake-induced landslides

Earthquake-induced landslides are difficult to assess and predict owing to the inherent unpredictability of earthquakes.In most existing studies,the landslide potential is statistically assessed by collecting and analyzing the data of historical landslide events and earthquake observation records.Unlike rainfall-induced landslides,earthquake-induced landslides cannot be predicted in advance using real-time monitoring systems,and the development of the models for these landslides should instead depend on early earthquake warnings and estimations.Hence,in this study,factor analysis was performed and the frequency distribution method was employed to investigate the potential risk of the landslides caused by earthquakes.Factors such as the slope gradient,lithology(geology),aspect,and elevation were selected and classified as influential factors to facilitate the construction of a landslide database for the area of study.

Near real-time spatial prediction of earthquake-induced landslides:A novel interpretable self-supervised learning method

Near real-time spatial prediction of earthquake-induced landslides(EQILs)can rapidly forecast the occurrence position of widespread landslides just after a violent earthquake;thus,EQIL prediction is very crucial to the 72-hour‘golden window’for survivors.This work focuses on a series of earthquake events from 2008 to 2022 occurring in the Tibetan Plateau,a famous seismically-active zone,and proposes a novel interpretable self-supervised learning(ISeL)method for the near real-time spatial prediction of EQILs.This new method innovatively introduces swap noise at the unsupervised mechanism,which can improve the generalization performance and transferability of the model,and can effectively reduce false alarm and improve accuracy through supervisedfine-tuning.An interpretable module is built based on a self-attention mechanism to reveal the importance and contribution of various influencing factors to EQIL spatial distribution.Experimental results demonstrate that the ISeL model is superior to the excellent state-of-the-art machine learning and deep learning methods.Furthermore,according to the interpretable module in the ISeL method,the critical controlling and triggering factors are revealed.The ISeL method can also be applied in other earthquake-frequent regions worldwide because of its good generalization and transferability.

Assessment of earthquake-induced landslide hazard zoning using the physics-environmental coupled Model

In order to prevent and mitigate disasters,it is crucial to immediately and properly assess the spatial distribution of landslide hazards in the earthquake-affected area.Currently,there are primarily two categories of assessment techniques:the physical mechanism-based method(PMBM),which considers the landslide dynamics and has the advantages of effectiveness and proactivity;the environmental factor-based method(EFBM),which integrates the environmental conditions and has high accuracy.In order to obtain the spatial distribution of landslide hazards in the affected area with near realtime and high accuracy,this study proposed to combine the PMBM based on Newmark method with EFBM to form Newmark-Information value model(N-IV),Newmark-Logic regression model(N-LR)and Newmark-Support Vector Machine model(N-SVM)for seismic landslide hazard assessment on the Ludian Mw 6.2 earthquake in Yunnan.The predicted spatial hazard distribution was compared with the actual cataloged landslide inventory,and frequency ratio(FR),and area under the curve(AUC)metrics were used to verify the model's plausibility,performance,and accuracy.According to the findings,the model's accuracy is ranked as follows:N-SVM>N-LR>N-IV>Newmark.With an AUC value of 0.937,the linked N-SVM was discovered to have the best performance.The research results indicate that the physics-environmental coupled model(PECM)exhibits accuracy gains of 46.406%(N-SVM),30.625%(N-LR),and 22.816%(N-IV)when compared to the conventional Newmark technique.It shows varied degrees of improvement from 2.577%to 12.446%when compared to the single EFBM.The study also uses the Ms 6.8 Luding earthquake to evaluate the model,showcasing its trustworthy in forecasting power and steady generalization.Since the suggested PECM in this study can adapt to complicated earthquake-induced landslides situations,it aims to serve as a reference for future research in a similar field,as well as to help with emergency planning and response in earthquakeprone regions with landslides.

Spatial distribution of shallow landslides caused by Typhoon Lekima in 2019 in Zhejiang Province, China

In recent years, the coastal region of Southeast China has witnessed a significant increase in the frequency and intensity of extreme rainfall events associated with landfalling typhoons. The hilly and mountainous terrain of this area, combined with rapid rainfall accumulation, has led to a surge in flash floods and severe geological hazards. On August 10, 2019, Typhoon Lekima made landfall in Zhejiang Province, China, and its torrential rainfall triggered extensive landslides, resulting in substantial damage and economic losses. Utilizing high-resolution satellite images, we compiled a landslide inventory of the affected area, which comprises a total of 2,774 rainfallinduced landslides over an area of 2965 km2. The majority of these landslides were small to mediumsized and exhibited elongated, clustered patterns. Some landslides displayed characteristics of high-level initiation, obstructing or partially blocking rivers, leading to the formation of debris dams. We used the inventory to analyze the distribution pattern of the landslides and their relationship with topographical, geological, and hydrological factors. The results showed that landslide abundance was closely related to elevation, slope angle, faults, and road density. The landslides were predominantly located in hilly and low mountainous areas, with elevations ranging from 150 to 300 m, slopes of 20 to 30 degrees, and a NE-SE aspect. Notably, we observed the highest Landslide Number Density(LND) and Landslide Area Percentage(LAP) in the rhyolite region. Landslides were concentrated within approximately 4 km on either side of fault zones, with their size and frequency negatively correlated with distances to faults, roads, and river systems. Furthermore, under the influence of typhoons, regions with denser vegetation cover exhibited higher landslide density, reaching maximum values in shrubland areas. In areas experiencing significantly increased concentrated rainfall, landslide density also showed a corresponding rise. In terms of spatial distribution, the rainfall-triggered landslides primarily occurred in the northeastern part of the study area, particularly in regions characterized by complex topography such as Shanzao Village in Yantan Town, Xixia Township, and Shangzhang Township. The research findings offer crucial data on the rainfallinduced landslides triggered by Typhoon Lekima, shedding light on their spatial distribution patterns. These findings provide valuable references for mitigating risks and planning reconstruction in typhoon-affected area.

Centrifuge modeling of unreinforced and multi-row stabilizing piles reinforced landslides subjected to reservoir water level fluctuation

With the construction of the Three Gorges Reservoir dam,frequent reservoir landslide events have been recorded.In recent years,multi-row stabilizing piles(MRSPs)have been used to stabilize massive reservoir landslides in China.In this study,two centrifuge model tests were carried out to study the unreinforced and MRSP-reinforced slopes subjected to reservoir water level(RWL)operation,using the Taping landslide as a prototype.The results indicate that the RWL rising can provide lateral support within the submerged zone and then produce the inward seepage force,eventually strengthening the slope stability.However,a rapid RWL drawdown may induce outward seepage forces and a sudden debuttressing effect,consequently reducing the effective soil normal stress and triggering partial pre-failure within the RWL fluctuation zone.Furthermore,partial deformation and subsequent soil structure damage generate excess pore water pressures,ultimately leading to the overall failure of the reservoir landslide.This study also reveals that a rapid increase in the downslope driving force due to RWL drawdown significantly intensifies the lateral earth pressures exerted on the MRSPs.Conversely,the MRSPs possess a considerable reinforcement effect on the reservoir landslide,transforming the overall failure into a partial deformation and failure situated above and in front of the MRSPs.The mechanical transfer behavior observed in the MRSPs demonstrates a progressive alteration in relation to RWL fluctuations.As the RWL rises,the mechanical states among MRSPs exhibit a growing imbalance.The shear force transfer factor(i.e.the ratio of shear forces on pile of the n th row to that of the first row)increases significantly with the RWL drawdown.This indicates that the mechanical states among MRSPs tend toward an enhanced equilibrium.The insights gained from this study contribute to a more comprehensive understanding of the failure mechanisms of reservoir landslides and the mechanical behavior of MRSPs in reservoir banks.

Characteristics and failure mechanism of an ancient earthquake-induced landslide with an extremely wide distribution area

The Lamuajue landslide is located in Lamuajue village on the tight bank of the Meigu River, Sichuan Province, China. This landslide is an ancient landslide with an extremely wide distribution area, covering an area of 19 km2 with a maximum width of 5-5 km and an estimated residual volume of 3 × 108 ma. The objectives of this study were to identify the characteristics and failure mechanism of this landslide. In this study, based on field investigations, aerial photography, and profile surveys, the boundary, lithology, structure of the strata, and characteristics of the landslide deposits were determined. A gently angled weak interlayer consisting of shale was the main factor contributing to the occurrence of the Lamuajue landslide. The deposition area can be divided into three zones： zone A is an avalanche deposition area mainly composed of blocks, fragments, and debris with diameters ranging from o.i m to 3 m; zone B is a residual integrated rock mass deposition area with large blocks, boulders and ＂fake bedrock＂; and zone C is a deposition zone of limestone blocks and fragments. Three types of failure mechanism were analyzed and combined to explain the Lamuajue landslide based on the features of the accumulation area. First, a shattering-sliding mechanism caused by earthquakes in zone A. Second, a sliding mechanism along the weak intercalation caused by gravity and water in zone B. Third, a shattering-ejection mechanism generated by earthquakes in zone C. The results provide a distinctive case for the study of gigantic landslides induced by earthquakes, which is very important for understanding and assessing ancient earthquakeinduced landslides.

Characterization and spatial analysis of coseismic landslides triggered by the Luding Ms 6.8 earthquake in the Xianshuihe fault zone, Southwest China

On September 5, 2022, a magnitude Ms 6.8 earthquake occurred along the Moxi fault in the southern part of the Xianshuihe fault zone located in the southeastern margin of the Tibetan Plateau,resulting in severe damage and substantial economic loss. In this study, we established a coseismic landslide database triggered by Luding Ms 6.8 earthquake, which includes 4794 landslides with a total area of 46.79 km^(2). The coseismic landslides primarily consisted of medium and small-sized landslides, characterized by shallow surface sliding. Some exhibited characteristics of high-position initiation resulted in the obstruction or partial obstruction of rivers, leading to the formation of dammed lakes. Our research found that the coseismic landslides were predominantly observed on slopes ranging from 30° to 50°, occurring at between 1000 m and 2500 m, with slope aspects varying from 90° to 180°. Landslides were also highly developed in granitic bodies that had experienced structural fracturing and strong-tomoderate weathering. Coseismic landslides concentrated within a 6 km range on both sides of the Xianshuihe and Daduhe fault zones. The area and number of coseismic landslides exhibited a negative correlation with the distance to fault lines, road networks, and river systems, as they were influenced by fault activity, road excavation, and river erosion. The coseismic landslides were mainly distributed in the southeastern region of the epicenter, exhibiting relatively concentrated patterns within the IX-degree zones such as Moxi Town, Wandong River basin, Detuo Town to Wanggangping Township. Our research findings provide important data on the coseismic landslides triggered by the Luding Ms 6.8 earthquake and reveal the spatial distribution patterns of these landslides. These findings can serve as important references for risk mitigation, reconstruction planning, and regional earthquake disaster research in the earthquake-affected area.

Probabilistic back-analysis of rainfall-induced landslides for slope reliability prediction with multi-source information

Probabilistic back-analysis is an important means to infer the statistics of uncertain soil parameters,making the slope reliability assessment closer to the engineering reality.However,multi-source information(including test data,monitored data,field observation and slope survival records)is rarely used in current probabilistic back-analysis.Conducting the probabilistic back-analysis of spatially varying soil parameters and slope reliability prediction under rainfalls by integrating multi-source information is a challenging task since thousands of random variables and high-dimensional likelihood function are usually involved.In this paper,a framework by integrating a modified Bayesian Updating with Subset simulation(mBUS)method with adaptive Conditional Sampling(aCS)algorithm is established for the probabilistic back-analysis of spatially varying soil parameters and slope reliability prediction.Within this framework,the high-dimensional probabilistic back-analysis problem can be easily tackled,and the multi-source information(e.g.monitored pressure heads and slope survival records)can be fully used in the back-analysis.A real Taoyuan landslide case in Taiwan,China is investigated to illustrate the effectiveness and performance of the established framework.The findings show that the posterior knowledge of soil parameters obtained from the established framework is in good agreement with the field observations.Furthermore,the updated knowledge of soil parameters can be utilized to reliably predict the occurrence probability of a landslide caused by the heavy rainfall event on September 12,2004 or forecast the potential landslides under future rainfalls in the Fuhsing District of Taoyuan City,Taiwan,China.

Numerical analysis of downward progressive landslides in long natural slopes with sensitive clay

Landslides occurring in sensitive clay often result in widespread destruction,posing a significant risk to human lives and property due to the substantial decrease in undrained shear strength during deformation.Assessing the consequences of these landslides is challenging and necessitates robust numerical methods to comprehensively investigate their failure mechanisms.While studies have extensively explored upward progressive landslides in sensitive clays,understanding downward progressive cases remains limited.In this study,we utilised the nodal integration-based particle finite element method(NPFEM)with a nonlinear strain-softening model to analyse downward progressive landslides in sensitive clay on elongated slopes,induced by surcharge loads near the crest.We focused on elucidating the underlying failure mechanisms and evaluating the effects of different soil parameters and strainsoftening characteristics.The simulation results revealed the typical pattern for downward landslides,which typically start with a localised failure in proximity to the surcharge loads,followed by a combination of different types of failure mechanisms,including single flow slides,translational progressive landslides,progressive flow slides,and spread failures.Additionally,inclined shear bands occur within spread failures,often adopting distinctive ploughing patterns characterised by triangular shapes.The sensitive clay thickness at the base,the clay strength gradient,the sensitivity,and the softening rate significantly influence the failure mechanisms and the extent of diffused displacement.Remarkably,some of these effects mirror those observed in upward progressive landslides,underscoring the interconnectedness of these phenomena.This study contributes valuable insights into the complex dynamics of sensitive clay landslides,shedding light on the intricate interplay of factors governing their behaviour and progression.

Impact of earthquake-induced landslide on the habitat suitability of giant panda in Wolong,China

Massive geological landslides and unstable landslide areas were triggered by the 2008 Wenchuan earthquake. These landslides caused deaths, damaged infrastructure and threatened endanger species. This study analyzed the impact of landslides on giant pandas and their habitats from the following aspects: threatening pandas‘ lives, damaging pandas‘ habitat, influencing giant panda behavior, increasing habitat fragmentation; the final aspect, and blocking gene flow by cutting off corridors. A habitat suitability map was created by integrating the landslide factors with other traditional factors based on a logistics regression method. According to the landslide inventory map, there are 1313 landslides, 818 rock debris flows, 117 rock avalanches and 43 mud flows occurred in the study area. A correlation analysis indicated that landslides caused the pandas to migrate, and the core landslides within 1 km2 had greater influence on panda migration. These core landslides primarily occurred in mid-altitude regionscharacterized by high slopes, old geological ages, large areas and large rock mass volumes. The habitat suitability assessment results for the Wolong Natural Reserve had better prediction performance(80.9%) and demonstrated that 14.5%, 15.9%, 20.5%, 47.6% and 1.5% of the study area can be classified as very high, high, moderate, low and very low giant panda suitability areas, respectively. This study can be used to inform panda and panda habitat research, management and protection during post-quake reconstruction and recovery periods in China.

Earthquake-induced landslide displacement attenuation models and application in probabilistic seismic landslide displacement analysis

A landslide displacement (DLL) attenuation model has been developed using spectral intensity and a ratio of critical acceleration coefficient to ground acceleration coefficient. In the development of the model,a New Zealand earthquake record data set with magnitudes ranging from 5.0 to 7.2 within a source distance of 175 km is used. The model can be used to carry out deterministic landslide displacement analysis,and readily extended to carry out probabilistic seismic landslide displacement analysis. DLL attenuation models have also been developed by using earthquake source terms,such as magnitude and source distance,that account for the effects of earthquake faulttype,source type,and site conditions. Sensitivity analyses show that the predicted DLL values from the new models are close to those from the Romeo model that was developed from an Italian earthquake record data set. The proposed models are also applied to an analysis of landslide displacements in the Wenchuan earthquake,and a comparison between the predicted and the observed results shows that the proposed models are reliable,and can be confidently used in mapping landslide potential.

Investigating the reactivation of historical landslides during the 2022 Luding M_(S)6.8 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.