Landslides最新文献

{"title":"Numerical modelling of static and dynamic factors controlling the progressive retreat of rocky coastal cliffs.","authors":"F Feliziani, G M Marmoni, M Montagnese, R Sobhani, D Istrati, E Eberhardt, S Martino","doi":"10.1007/s10346-026-02800-2","DOIUrl":"10.1007/s10346-026-02800-2","url":null,"abstract":"<p><p>This study investigates instability mechanisms in soft rocky coastal cliffs through an integrated numerical framework that couples computational fluid dynamics (CFD) with the finite-discrete element method (FDEM), applied to the tuffaceous cliffs of Ventotene Island (Italy). The modelling strategy systematically explores the role of structural predisposition, marine erosion, wave-induced loading, thermal forcing, and time-dependent strength degradation in controlling cliff stability and failure evolution. The results show that neither gravity loading nor basal undercutting alone can reproduce realistic failure mechanisms, even in the presence of a DFN. Progressive rock failure (PRF) emerges only when basal erosion is explicitly coupled with inward-migrating strength degradation, implemented using a simplified fatigue-based S-N approach. Under the considered lithology and the present Mediterranean climatic conditions, wave impacts and thermal forcing induce predominantly elastic or sub-critical mechanical responses and do not directly trigger failure. However, wave-induced dynamic perturbations concentrate displacements in fractured cliff sectors, suggesting a preparatory role through fatigue and stress redistribution, with potential triggering effects once critical degradation thresholds are approached. Thermal forcing becomes mechanically effective only under amplified temperature excursions or in lithologies with higher thermal sensitivity. The coupled CFD-FDEM approach is therefore interpreted as a process-based, exploratory framework that captures the dynamic response of coastal cliffs to realistic environmental boundary conditions, rather than as a direct predictor of wave-driven collapse. The methodology provides a physically grounded and transferable framework for investigating multi-forcing interactions, damage accumulation, and PRF in coastal cliffs, offering new insights into the mechanisms governing coastal instability and long-term cliff evolution.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at https://doi.org/10.1007/s10346-026-02800-2.</p>","PeriodicalId":17938,"journal":{"name":"Landslides","volume":"23 10","pages":"2909-2931"},"PeriodicalIF":7.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13574890/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148977220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How well can rock avalanche runout be forecasted? GPU-Accelerated validation of a method for forecasting rock avalanche motion using a numerical model.","authors":"Guotong Deng, Jordan Aaron","doi":"10.1007/s10346-026-02831-9","DOIUrl":"10.1007/s10346-026-02831-9","url":null,"abstract":"<p><p>Rock avalanches are extremely rapid, flowlike landslides that can threaten people and infrastructure, making accurate forecasts of their motion using numerical models critical for risk assessment. These forecasts are a primary input into land use and evacuation decisions; however, a comprehensive analysis of the effectiveness of various forecasting approaches applied to a wide variety of rock avalanche types has never been done. This is primarily due to a lack of field data, as well as the prohibitive computational cost. In this work, we address both limitations by applying a Bayesian posterior analysis and leave-one-out cross validation strategy to a dataset of 22 case histories. This enables us to calibrate the GPU (Graphics Processing Unit)-accelerated runout model ORIN-3D (parallel simulatOR of landslIde motioN over 3D terrain) for three rheological parameterizations: (1) Frictional, (2) Voellmy, and (3) a combined Frictional-Voellmy rheology. The analysis involves around 400,000 simulations, which is a computational effort that would be impractical with CPU (Central Processing Unit)-based models. Probabilistic forecasts for each case history are conducted using calibration results across eight forecast sets and evaluated with the Tversky loss function (TLF). The results show that the best performing model parameterization uses a volume-dependent friction angle in the source zone (Frictional rheology) and Voellmy rheology in the path zone. This work thus provides systematically validated, probabilistic forecasts of a database of 22 rock avalanche case histories, enabling improved hazard and risk assessments of this damaging phenomenon.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at https://doi.org/10.1007/s10346-026-02831-9.</p>","PeriodicalId":17938,"journal":{"name":"Landslides","volume":"23 11","pages":"3247-3263"},"PeriodicalIF":7.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13669184/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149216399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Community-scale slope stability assessment of urbanisation scenarios in North Quito, Ecuador.","authors":"R Hen-Jones, C Zapata, E Jiménez, E A Holcombe, P J Vardanega","doi":"10.1007/s10346-025-02608-6","DOIUrl":"10.1007/s10346-025-02608-6","url":null,"abstract":"<p><p>Quito is home to nearly three million inhabitants, many of whom live in informal settlements on the steep soil-mantled slopes that surround the city. Within Quito's multi-hazard environment, the combination of rapid urban expansion onto already landslide-prone slopes-often without adequate urban planning or provision of services-and rainfall associated with the subtropical highland climate, generates a risk to life and infrastructure from landslides. Landslide hazard assessment and mitigation is challenging due to the large area involved, complexity of urban slopes and sparsity of data. In this study, conceptual models of characteristic slope geometries, soil properties and urban features are developed based on three landslide-prone communities in North Quito. These models form the basis for investigating different urbanisation scenarios and the slope stability response to simulated rainfall. They are used to configure the physics-based Combined Hydrology And Stability Model, CHASM, which is run stochastically allowing tens-of-thousands of combinations of slope input factors to be investigated. Analysis of simulation data includes regional sensitivity analysis and the identification of different rainfall-intensity thresholds for triggering landslides. Slope cutting is identified as the primary driver of small-scale urban landslides. Analysis of simulated landslide characteristics allows the trigger mechanisms for different scenarios to be hypothesised and shows a close correlation with the ratio of strata thickness to effective apparent cohesion. These results support revegetation within existing informal communities, and the preservation of existing vegetation and careful design of cut slopes in new settlements.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s10346-025-02608-6.</p>","PeriodicalId":17938,"journal":{"name":"Landslides","volume":"23 1","pages":"55-71"},"PeriodicalIF":7.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12764695/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145906194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Urban poor are the most endangered by socio-natural hazards, but not exclusively: the 2025 Granizal Landslide case.","authors":"Ugur Ozturk, Anika Braun, Juan Camilo Gómez-Zapata, Edier Aristizábal","doi":"10.1007/s10346-025-02680-y","DOIUrl":"10.1007/s10346-025-02680-y","url":null,"abstract":"<p><p>In June 2025, the rainfall-induced Granizal Landslide claimed 27 lives across two jurisdictions in the Medellín metropolitan area. Based on our empirical analyses of a local socio-economic index, we argue that socio-spatial segregation may have increased the likelihood and impact of the disaster. The event's location also underscores the challenges faced during emergency response and post-disaster recovery across administrative boundaries, particularly given the stark contrast in the capacities of municipal authorities. We suggest that intensifying climate change may lead to events that exceed current engineering design criteria, thereby exposing even formal neighborhoods-often considered more physically resilient-to substantially elevated risk levels and narrowing the gap with informal settlements.</p>","PeriodicalId":17938,"journal":{"name":"Landslides","volume":"23 4","pages":"1179-1185"},"PeriodicalIF":7.4,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12979284/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147463665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Devastating landslide incident in Ramban District of Jammu and Kashmir (J&amp;K), India on April 20, 2025: a combined effect of intense rainfall, anthropogenic factors, flash floods, and geomorphology","authors":"Prateek Sharma, Rahul Verma, Rajesh Singh","doi":"10.1007/s10346-025-02580-1","DOIUrl":"https://doi.org/10.1007/s10346-025-02580-1","url":null,"abstract":"","PeriodicalId":17938,"journal":{"name":"Landslides","volume":"22 10","pages":"3525-3535"},"PeriodicalIF":0.0,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147882584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Brief report on the catastrophic landslide in Papua New Guinea on May 24, 2024","authors":"Zhigang Li, Weile Li, Qiang Xu, Pu Feng, Wenlong Yu, Yunfeng Shan, Pengyu Guo, Congwei Yu, Shengsen Zhou, Chuanhao Pu, Xiaochen Wang","doi":"10.1007/s10346-025-02511-0","DOIUrl":"https://doi.org/10.1007/s10346-025-02511-0","url":null,"abstract":"","PeriodicalId":17938,"journal":{"name":"Landslides","volume":"22 6","pages":"1877-1889"},"PeriodicalIF":0.0,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147899824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preliminary analysis of the wildfire on March 15, 2024, and the following post-fire debris flows in Yajiang County, Sichuan, China","authors":"Kun He, Xiewen Hu, Zhanglei Wu, Yutian Zhong, Yonghao Zhou, Xueqiang Gong, Gang Luo","doi":"10.1007/s10346-024-02364-z","DOIUrl":"https://doi.org/10.1007/s10346-024-02364-z","url":null,"abstract":"<p>On March 15, 2024, a wildfire occurred in Yajiang County, Sichuan Province, China, burned an area of 278.8 km² and influenced 250 catchments in the burned area. On April 23 and May 10–11, 2024, two rainfall events struck the burned area, inducing 8 and 54 post-fire debris flows, respectively. This news investigates the characteristics of the burned area, involving the burn severity mapping, and geometry analysis on the burned catchments. Then, the characteristics of the debris flows following the fire are unravelled based on preliminary field investigations. It is expected that the debris flows after the wildfire, particularly in the first rainy season, with the high susceptibility and low rainfall threshold, will attract researchers’ interest in monitoring and mitigating such unique debris flow disasters.</p>","PeriodicalId":17938,"journal":{"name":"Landslides","volume":"49 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142256495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing reservoir landslide stability assessment via TS-InSAR and airborne LiDAR observations in the Daping landslide group, Three Gorges Reservoir Area, China","authors":"Lele Zhang, Ruiqi Zhang, Jie Dou, Shiping Hou, Zilin Xiang, Heng Wang, Pucai Yang, Xian Liu","doi":"10.1007/s10346-024-02337-2","DOIUrl":"https://doi.org/10.1007/s10346-024-02337-2","url":null,"abstract":"<p>The Three Gorges Reservoir Area (TGRA) is highly susceptible to the reactivation of ancient landslides and the emergence of new ones due to the fragile geological conditions and the regulation of water levels. This study integrated multi-source data from space-air-ground-based platforms to investigate the dynamics and stability of the Daping landslide group on the bank of TGRA. Monitoring active landslide deformation is essential to ensure the safety of coastal residents and waterways. The results demonstrate that combining Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) and Distributed Scatterer InSAR (DS-InSAR) methods effectively increases measurement point density and enhances the visibility of displacement. The reliability of using InSAR monitoring results for landslide analysis has been validated through the consistent displacement trends between the InSAR and Global Positioning System (GPS) points with a high correlation (<i>R</i>² = 0.968). Spatial-temporal variations in the displacement of the Daping landslide group were observed during the monitoring period, attributable to fluctuating reservoir water levels and rainfall events. Additionally, Light Detection and Ranging (LiDAR)-derived Digital Elevation Model (DEM) from Unmanned Aerial Vehicle (UAV) was employed to reveal the actual micro-geomorphological and topographical features related to landslide movement, such as the bank slump at the toe of the landslide. This bank slump itself is a consequence of water-level fluctuations following the impoundment of TGRA. Numeric simulation was conducted to quantitatively assess the influence of bank slump on the slope’s stability, the displacement results of which were consistent with those of GPS and InSAR. The evolution characteristics of the Daping landslide group were summarized as a sequence of events: bending-tensile cracking-sliding failure along weak surfaces and predicted future development. The findings of this study hold significant importance for effective monitoring of slope bodies in reservoir areas, providing valuable insights into potential landslide risks and contributing to overall safety measures.</p>","PeriodicalId":17938,"journal":{"name":"Landslides","volume":"31 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142256494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new remote-sensing-based volcanic debris avalanche database of Northwest Argentina (Central Andes)","authors":"Emilce Bustos, Gianluca Norini, Walter Ariel Báez, Pablo Grosse, Marcelo Arnosio, Lucia Capra","doi":"10.1007/s10346-024-02365-y","DOIUrl":"https://doi.org/10.1007/s10346-024-02365-y","url":null,"abstract":"<p> Volcanic debris avalanches are significant landslide events that shape volcanic landscapes globally. This study focuses on creating a comprehensive database of volcanic debris avalanches in Northwest Argentina through remote sensing analysis, leveraging the region’s well-preserved deposits in arid conditions. The database includes morphometric parameters extracted from 12-m spatial resolution TanDEM-X digital elevation models and literature, providing insights into the occurrence and characteristics of these potentially catastrophic events. The methodology involved compiling bibliographic and cartographic data, manual digitization of collapse scars and deposits, and computation of morphometric parameters in a GIS, integrating structural lineaments and hydrothermal alteration zones. The database, which comprises 19 records, features detailed data on scars and deposits, morphometric characteristics, and additional layers for regional lineaments and hydrothermal alteration zones. Statistical analyses reveal correlations between various morphometric parameters, with most avalanche directions aligning perpendicularly to regional tectonic trends and hydrothermal alteration zones identified as significant factors in volcanic instability. The majority of collapses originate from composite volcanoes, with larger collapses linked to dacitic compositions. Collapses have ages between the Upper Miocene and Pliocene. We deem that the database, accessible via the IBIGEO website, will be a valuable tool for researchers and national authorities for geological risk assessment, enhancing the understanding of the spatial and temporal distribution of volcanic debris avalanches in the Central Volcanic Zone of the Andes. Continuous updates and fieldwork are essential to validate and expand the database, addressing gaps and confirming remote observations, thereby contributing to global knowledge on volcanic sector collapses and associated risks.</p>","PeriodicalId":17938,"journal":{"name":"Landslides","volume":"16 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142256496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Typical characteristics and causes of giant landslides in the upper reaches of the Yellow River, China","authors":"Junyan Zhao, Qiangbing Huang, Jianbing Peng, Zuopeng Wang, Penghui Ma, Yanqiu Leng, Lijie Chen, Zhiyuan He, Luqing Zhao, Qingyu Xie, Gaofeng Yang","doi":"10.1007/s10346-024-02363-0","DOIUrl":"https://doi.org/10.1007/s10346-024-02363-0","url":null,"abstract":"<p>The canyon section from Longyangxia to Liujiaxia in the upper reaches of the Yellow River, which is characterized by a significant number and large scale of landslides, is a typical area prone to landslides. Investigating the characteristics and causes of giant landslides in this region holds great significance for understanding and mitigating the risks associated with such disasters. This paper explored the development characteristics and induced causes of these giant landslides via field surveys, remote sensing interpretations, unmanned aerial vehicle (UAV) surveys, geological dating methods, and numerical simulation methods. There were 22 giant landslides in the study area. Their sliding face is deeply buried in sandy mudstone or sandy stone that is landslide strata and shows large differences in elevation of landslide front and back edges. Most of these landslides mainly occurred tens of thousands of years ago that is indicated by geological dating results. The causes behind these giant landslides have been discussed from various perspectives. Multiple factors, such as tectonic activity, rock properties (“genes”), river erosion dynamics, climate change influences, and ancient earthquakes, are believed to have contributed to the development of giant landslides in this region. Regional tectonic activities exert tectonic forces leading to structural plane formation within rock masses while providing initial conditions for deformation and failure processes associated with giant landslide occurrences. Since the Pleistocene, Yellow River erosion has created favorable spatial environments conducive to giant landslide development by altering slope stress conditions; furthermore, climate change weakens rock mass strength. Finally, earthquakes generate substantial energy serving as catalysts for triggering massive landslide events by inducing rock mass failures.</p>","PeriodicalId":17938,"journal":{"name":"Landslides","volume":"72 1","pages":""},"PeriodicalIF":6.7,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142256490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}