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.

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.

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.

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.

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

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.

How do the landslide and non-landslide sampling strategies impact landslide susceptibility assessment? d A catchment-scale case study from China

The aim of this study is to investigate the impacts of the sampling strategy of landslide and non-landslide on the performance of landslide susceptibility assessment(LSA).The study area is the Feiyun catchment in Wenzhou City,Southeast China.Two types of landslides samples,combined with seven non-landslide sampling strategies,resulted in a total of 14 scenarios.The corresponding landslide susceptibility map(LSM)for each scenario was generated using the random forest model.The receiver operating characteristic(ROC)curve and statistical indicators were calculated and used to assess the impact of the dataset sampling strategy.The results showed that higher accuracies were achieved when using the landslide core as positive samples,combined with non-landslide sampling from the very low zone or buffer zone.The results reveal the influence of landslide and non-landslide sampling strategies on the accuracy of LSA,which provides a reference for subsequent researchers aiming to obtain a more reasonable LSM.

Fiber optic monitoring of an anti-slide pile in a retrogressive landslide

Anti-slide piles are one of the most important reinforcement structures against landslides,and evalu-ating the working conditions is of great significance for landslide mitigation.The widely adopted analytical methods of pile internal forces include cantilever beam method and elastic foundation beam method.However,due to many assumptions involved in calculation,the analytical models cannot be fully applicable to complex site situations,e.g.landslides with multi-sliding surfaces and pile-soil interface separation as discussed herein.In view of this,the combination of distributed fiber optic sensing(DFOS)and strain-internal force conversion methods was proposed to evaluate the working conditions of an anti-sliding pile in a typical retrogressive landslide in the Three Gorges reservoir area,China.Brillouin optical time domain reflectometry(BOTDR)was utilized to monitor the strain distri-bution along the pile.Next,by analyzing the relative deformation between the pile and its adjacent inclinometer,the pile-soil interface separation was profiled.Finally,the internal forces of the anti-slide pile were derived based on the strain-internal force conversion method.According to the ratio of calculated internal forces to the design values,the working conditions of the anti-slide pile could be evaluated.The results demonstrated that the proposed method could reveal the deformation pattern of the anti-slide pile system,and can quantitatively evaluate its working conditions.

Landslide hazard susceptibility evaluation based on SBAS-InSAR technology and SSA-BP neural network algorithm:A case study of Baihetan Reservoir Area

Landslide hazard susceptibility evaluation takes on critical significance in early warning and disaster prevention and reduction.In order to solve the problems of poor effectiveness of landslide data and complex calculation of weights for multiple evaluation factors in the existing landslide susceptibility evaluation models,in this study,a method of landslide hazard susceptibility evaluation is proposed by combining SBAS-InSAR(Small Baseline Subsets-Interferometric Synthetic Aperture Radar)and SSA-BP(Sparrow Search Algorithm-Back Propagation)neural network algorithm.The SBAS-InSAR technology is adopted to identify potential landslide hazards in the study area,update the cataloging data of landslide hazards,and 11 evaluation factors are chosen for constructing the SSA-BP model for training and validation.Baihetan Reservoir area is selected as a case study for validation.As indicated by the results,the application of SBAS-InSAR technology,combined with both ascending and descending orbit data,effectively addresses the incomplete identification of landslide hazards caused by geometric distortion of single orbit SAR data(e.g.,shadow,overlay,and perspective contraction)in deep canyon areas,thereby enabling the acquisition of up-to-date landslide hazard data.Moreover,in comparison to the conventional BP(Back Propagation)algorithm,the accuracy of the model constructed by the SSA-BP algorithm exhibits a significant increase,with mean squared error and mean absolute error reduced by 0.0142 and 0.0607,respectively.Additionally,during the process of susceptibility evaluation,the SSA-BP model effectively circumvents the issue of considerable manual interventions in calculating the weight of evaluation factors.The area under the curve of this model reaches 0.909,surpassing BP(0.835),random forest(0.792),and the information value method(0.699).The risk of landslide occurrence in the Baihetan Reservoir area is positively correlated with slope,surface temperature,and deformation rate,while it is negatively correlated with fault distance and normalized difference vegetation index.Geological lithology exerts minimal influence on the occurrence of landslides,with the risk being low in forest land and high in grassland.The method proposed in this study provides a useful reference for disaster prevention and mitigation departments to perform landslide hazard susceptibility evaluations in deep canyon areas under complex geological conditions.

Thermo-hydro-poro-mechanical responses of a reservoir-induced landslide tracked by high-resolution fiber optic sensing nerves

Thermo-poro-mechanical responses along sliding zone/surface have been extensively studied.However,it has not been recognized that the potential contribution of other crucial engineering geological interfaces beyond the slip surface to progressive failure.Here,we aim to investigate the subsurface multiphysics of reservoir landslides under two extreme hydrologic conditions(i.e.wet and dry),particularly within sliding masses.Based on ultra-weak fiber Bragg grating(UWFBG)technology,we employ specialpurpose fiber optic sensing cables that can be implanted into boreholes as“nerves of the Earth”to collect data on soil temperature,water content,pore water pressure,and strain.The Xinpu landslide in the middle reach of the Three Gorges Reservoir Area in China was selected as a case study to establish a paradigm for in situ thermo-hydro-poro-mechanical monitoring.These UWFBG-based sensing cables were vertically buried in a 31 m-deep borehole at the foot of the landslide,with a resolution of 1 m except for the pressure sensor.We reported field measurements covering the period 2021 and 2022 and produced the spatiotemporal profiles throughout the borehole.Results show that wet years are more likely to motivate landslide motions than dry years.The annual thermally active layer of the landslide has a critical depth of roughly 9 m and might move downward in warmer years.The dynamic groundwater table is located at depths of 9e15 m,where the peaked strain undergoes a periodical response of leap and withdrawal to annual hydrometeorological cycles.These interface behaviors may support the interpretation of the contribution of reservoir regulation to slope stability,allowing us to correlate them to local damage events and potential global destabilization.This paper also offers a natural framework for interpreting thermo-hydro-poro-mechanical signatures from creeping reservoir bank slopes,which may form the basis for a landslide monitoring and early warning system.

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.

Numerical Simulation of Rainfall-induced Xianchi Reservoir Landslide in Yunyang,Chongqing,China

A calamitous landslide happened at 22:00 on September 1,2014 in the Yunyang area of Chongqing City,southwest China,enforcing the evacuation of 508 people and damaging 23 buildings.The landslide volume comprised 1.44 million m^(3) of material in the source area and 0.4 million m^(3) of shoveled material.The debris flow runout extended 400 m vertically and 1600 m horizontally.The Xianchi reservoir landslide event has been investigated as follows:(1)samples collected from the main body of landslide were carried out using GCTS ring shear apparatus;(2)the parameters of shear and pore water pressure have been measured;and(3)the post-failure characteristics of landslide have been analyzed using the numerical simulation method.The excess pore-water pressure and erosion in the motion path are considered to be the key reasons for the long-runout motion and the scale-up of landslides,such as that at Xianchi,were caused by the heavy rainfall.The aim of this paper is to acquired numerical parameters and the basic resistance model,which is beneficial to improve simulation accuracy for hazard assessment for similar to potentially dangerous hillslopes in China and elsewhere.

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.

Multistate transition and coupled solid-liquid modeling of motion process of long-runout landslide

The recognition,repetition and prediction of the post-failure motion process of long-runout landslides are key scientific problems in the prevention and mitigation of geological disasters.In this study,a new numerical method involving LPF3D based on a multialgorithm and multiconstitutive model was proposed to simulate long-runout landslides with high precision and efficiency.The following results were obtained:(a)The motion process of landslides showed a steric effect with mobility,including gradual disintegration and spreading.The sliding mass can be divided into three states(dense,dilute and ultradilute)in the motion process,which can be solved by three dynamic regimes(friction,collision,and inertial);(b)Coupling simulation between the solid grain and liquid phases was achieved,focusing on drag force influences;(c)Different algorithms and constitutive models were employed in phase-state simulations.The volume fraction is an important indicator to distinguish different state types and solid‒liquid ratios.The flume experimental results were favorably validated against long-runout landslide case data;and(d)In this method,matched dynamic numerical modeling was developed to better capture the realistic motion process of long-runout landslides,and the advantages of continuum media and discrete media were combined to improve the computational accuracy and efficiency.This new method can reflect the realistic physical and mechanical processes in long-runout landslide motion and provide a suitable method for risk assessment and pre-failure prediction.