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Deformation,structure and potential hazard of a landslide based on InSAR in Banbar county,Xizang(Tibet)

China Geology 2024年第2期7卷 203-221页

作者： Guan-hua Zhao Heng-xing Lan Hui-yong Yin Lang-ping Li Alexander Strom Wei-feng Sun Chao-yang Tian College of Earth Science and engineering Shandong University of Science and TechnologyQingdao 266590China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China School of geological engineering and Geomatics Chang’an UniversityXi’an 710054China Key Laboratory of Ecological Geology and Disaster Prevention Ministry of Natural ResourcesXi’an 710054China University of Chinese Academy of Sciences Beijing 100049China JSC“Hydroproject Institute” Moscow 125993Russia

The Tibetan Plateau is characterized by complex geological conditions and a relatively fragile ecological environment.In recent years,there has been continuous development and increased human activity in the Tibetan Plateau region,leading to a rising risk of landslides.The landslide in Banbar County,Xizang(Tibet),have been perturbed by ongoing disturbances from human engineering activities,making it susceptible to instability and displaying distinct features.In this study,small baseline subset synthetic aperture radar interferometry(SBAS-InSAR)technology is used to obtain the Line of Sight(LOS)deformation velocity field in the study area,and then the slope-orientation deformation field of the landslide is obtained according to the spatial geometric relationship between the satellite’s LOS direction and the landslide.Subsequently,the landslide thickness is inverted by applying the mass conservation criterion.The results show that the movement area of the landslide is about 6.57×10^(4)m^(2),and the landslide volume is about 1.45×10^(6)m^(3).The maximum estimated thickness and average thickness of the landslide are 39 m and 22 m,respectively.The thickness estimation results align with the findings from on-site investigation,indicating the applicability of this method to large-scale earth slides.The deformation rate of the landslide exhibits a notable correlation with temperature variations,with rainfall playing a supportive role in the deformation process and displaying a certain lag.Human activities exert the most substantial influence on the spatial heterogeneity of landslide deformation,leading to the direct impact of several prominent deformation areas due to human interventions.Simultaneously,utilizing the long short-term memory(LSTM)model to predict landslide displacement,and the forecast results demonstrate the effectiveness of the LSTM model in predicting landslides that are in a continuous development and movement phase.The landslide is still active,and based on the spatial heterogeneity of landslide deform

关键词： Landslide InSAR Human activity Deformation Structure LSTM model engineering construction Thickness Neural network Machine learning Prediction and prevention Tibetan Plateau geological hazards survey engineering

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Analysis of debris flow control effect and hazard assessment in Xinqiao Gully,Wenchuan M_(s)8.0 earthquake area based on numerical simulation

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China Geology 2024年第2期7卷 248-263页

作者： Chang Yang Yong-bo Tie Xian-zheng Zhang Yan-feng Zhang Zhi-jie Ning Zong-liang Li Chinese Academy of geological Sciences Beijing 100037China Chengdu Center of China geological survey China Geological SurveyChengdu 610081China Technology innovation center for risk prevention and mitigation of geohazard Ministry of Natural ResourcesChengdu 611734China Observation and Research Station of Chengdu geological hazards Ministry of Natural ResourcesChengdu 610000China

Xinqiao Gully is located in the area of the 2008 Wenchuan M_(s)8.0 earthquake in Sichuan province,China.Based on the investigation of the 2023"6-26"Xinqiao Gully debris flow event,this study assessed the effectiveness of the debris flow control project and evaluated the debris flow hazards.Through field investigation and numerical simulation methods,the indicators of flow intensity reduction rate and storage capacity fullness were proposed to quantify the effectiveness of the engineering measures in the debris flow event.The simulation results show that the debris flow control project reduced the flow intensity by41.05%to 64.61%.The storage capacity of the dam decreases gradually from upstream to the mouth of the gully,thus effectively intercepting and controlling the debris flow.By evaluating the debris flow of different recurrence intervals,further measures are recommended for managing debris flow events.

关键词： Landslide Debris flow Hazard assessment Numerical simulation OpenLISEM Prevention and control project Wenchuan M_(s)8.0 earthquake Xinqiao Gully Sichuan province geological hazards survey engineering

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Runout prediction of potential landslides based on the multi-source data collaboration analysis on historical cases

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China Geology 2024年第2期7卷 264-276页

作者： Jun Sun Yu Zhuang Ai-guo Xing Guizhou Geology and Mineral engineering Construction Co. LtdGuiyang 550000China State Key Laboratory of Ocean engineering Shanghai Jiao Tong UniversityShanghai 200240China

Long runout landslides involve a massive amount of energy and can be extremely hazardous owing to their long movement distance,high mobility and strong destructive power.Numerical methods have been widely used to predict the landslide runout but a fundamental problem remained is how to determine the reliable numerical parameters.This study proposes a framework to predict the runout of potential landslides through multi-source data collaboration and numerical analysis of historical landslide events.Specifically,for the historical landslide cases,the landslide-induced seismic signal,geophysical surveys,and possible in-situ drone/phone videos(multi-source data collaboration)can validate the numerical results in terms of landslide dynamics and deposit features and help calibrate the numerical(rheological)parameters.Subsequently,the calibrated numerical parameters can be used to numerically predict the runout of potential landslides in the region with a similar geological setting to the recorded events.Application of the runout prediction approach to the 2020 Jiashanying landslide in Guizhou,China gives reasonable results in comparison to the field observations.The numerical parameters are determined from the multi-source data collaboration analysis of a historical case in the region(2019 Shuicheng landslide).The proposed framework for landslide runout prediction can be of great utility for landslide risk assessment and disaster reduction in mountainous regions worldwide.

关键词： Landslide runout prediction Drone survey Multi-source data collaboration DAN3D numerical modeling Jianshanying landslide Guizhou Province geological hazards survey engineering

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Dynamic simulation insights into friction weakening effect on rapid long-runout landslides:A case study of the Yigong landslide in the Tibetan Plateau,China

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China Geology 2024年第2期7卷 222-236页

作者： Zi-zheng Guo Xin-yong Zhou Da Huang Shi-jie Zhai Bi-xia Tian Guang-ming Li School of Civil and Transportation engineering Hebei University of TechnologyTianjin 300401China School of geological engineering and Geomatics Chang’an UniversityXi’an 710054China Tianjin Municipal engineering Design&Research Institute(TMEDI) Tianjin 300392China

This study proposed a novel friction law dependent on velocity,displacement and normal stress for kinematic analysis of runout process of rapid landslides.The well-known Yigong landslide occurring in the Tibetan Plateau of China was employed as the case,and the derived dynamic friction formula was included into the numerical simulation based on Particle Flow Code.Results showed that the friction decreased quickly from 0.64(the peak)to 0.1(the stead value)during the 5s-period after the sliding initiation,which explained the behavior of rapid movement of the landslide.The monitored balls set at different sections of the mass showed similar variation characteritics regarding the velocity,namely evident increase at the initial phase of the movement,followed by a fluctuation phase and then a stopping one.The peak velocity was more than 100 m/s and most particles had low velocities at 300s after the landslide initiation.The spreading distance of the landslide was calculated at the two-dimension(profile)and three-dimension scale,respectively.Compared with the simulation result without considering friction weakening effect,our results indicated a max distance of about 10 km from the initial unstable position,which fit better with the actual situation.

关键词： Rapid long-runout landslide PFC Friction weakening Three-dimension Numerical simulation Tibetan Plateau Hydrogeology engineering geological hazards survey engineering

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Exploring mechanism of hidden,steep obliquely inclined bedding landslides using a 3DEC model:A case study of the Shanyang landslide in Shaanxi Province,China

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China Geology 2024年第2期7卷 303-314,I0001-I0003页

作者： Jia-yun Wang Zi-long Wu Xiao-ya Shi Long-wei Yang Rui-ping Liu Na Lu Xi’an Center of China geological survey/Northwest China Center for Geoscience Innovation Xi’an 710119China Xi’an University of Science and Technology Xi’an 710054China Wuhan Design&Research Institute Co. Ltd.of China Coal Technology&Engineering GroupWuhan 430064China

Catastrophic geological disasters frequently occur on slopes with obliquely inclined bedding structures(also referred to as obliquely inclined bedding slopes),where the apparent dip sliding is not readily visible.This phenomenon has become a focal point in landslide research.Yet,there is a lack of studies on the failure modes and mechanisms of hidden,steep obliquely inclined bedding slopes.This study investigated the Shanyang landslide in Shaanxi Province,China.Using field investigations,laboratory tests of geotechnical parameters,and the 3DEC software,this study developed a numerical model of the landslide to analyze the failure process of such slopes.The findings indicate that the Shanyang landslide primarily crept along a weak interlayer under the action of gravity.The landslide,initially following a dip angle with the support of a stable inclined rock mass,shifted direction under the influence of argillization in the weak interlayer,moving towards the apparent dip angle.The slide resistance effect of the karstic dissolution zone was increasingly significant during this process,with lateral friction being the primary resistance force.A reduction in the lateral friction due to karstic dissolution made the apparent dip sliding characteristics of the Shanyang landslide more pronounced.Notably,deformations such as bending and uplift at the slope’s foot suggest that the main slide resistance shifts from lateral friction within the karstic dissolution zone to the slope foot’s resistance force,leading to the eventual buckling failure of the landslide.This study unveils a novel failure mode of apparent dip creep-buckling in the Shanyang landslide,highlighting the critical role of lateral friction from the karstic dissolution zone in its failure mechanism.These insights offer a valuable reference for mitigating risks and preventing disasters related to obliquely inclined bedding landslides.

关键词： Landslide Steep obliquely inclined bedding slope Failure mode Failure mechanism Apparent dip creep-buckling Lateral friction 3DEC model Landslide numerical model geological hazards survey engineering

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Identification and distribution of 13003 landslides in the northwest margin of Qinghai-Tibet Plateau based on human-computer interaction remote sensing interpretation

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China Geology 2024年第2期7卷 171-187页

作者： Wei Wang Yuan-dong Huang Chong Xu Xiao-yi Shao Lei Li Li-ye Feng Hui-ran Gao Yu-long Cui Shuai Wu Zhi-qiang Yang Kai Ma National Institute of Natural hazards Ministry of Emergency Management of ChinaBeijing 100085China Key Laboratory of Compound and Chained Natural hazards Dynamics Ministry of Emergency Management of Chin12eijing 100085China School of Emergency Management Science and engineering University of Chinese Academy of SciencesBeijing 100049China School of Soil and Water Conservation Beijing Forestry UniversityBeijing 100083China School of Civil engineering and Architecture Anhui University of Science and TechnologyHuainan 232001China No.3 Bureau of China Metallurgical Geology Bureau Taiyuan 030031China

The periphery of the Qinghai-Tibet Plateau is renowned for its susceptibility to landslides.However,the northwestern margin of this region,characterised by limited human activities and challenging transportation,remains insufficiently explored concerning landslide occurrence and dispersion.With the planning and construction of the Xinjiang-Tibet Railway,a comprehensive investigation into disastrous landslides in this area is essential for effective disaster preparedness and mitigation strategies.By using the human-computer interaction interpretation approach,the authors established a landslide database encompassing 13003 landslides,collectively spanning an area of 3351.24 km^(2)(36°N-40°N,73°E-78°E).The database incorporates diverse topographical and environmental parameters,including regional elevation,slope angle,slope aspect,distance to faults,distance to roads,distance to rivers,annual precipitation,and stratum.The statistical characteristics of number and area of landslides,landslide number density(LND),and landslide area percentage(LAP)are analyzed.The authors found that a predominant concentration of landslide origins within high slope angle regions,with the highest incidence observed in intervals characterised by average slopes of 20°to 30°,maximum slope angle above 80°,along with orientations towards the north(N),northeast(NE),and southwest(SW).Additionally,elevations above 4.5 km,distance to rivers below 1 km,rainfall between 20-30 mm and 30-40 mm emerge as particularly susceptible to landslide development.The study area’s geological composition primarily comprises Mesozoic and Upper Paleozoic outcrops.Both fault and human engineering activities have different degrees of influence on landslide development.Furthermore,the significance of the landslide database,the relationship between landslide distribution and environmental factors,and the geometric and morphological characteristics of landslides are discussed.The landslide H/L ratios in the study area are mainly concentrated between 0.4 and 0.64.It mea

关键词： Landslides Human-computer interaction interpretation Landslide database Spatial distribution Earthquake Rainfall Human engineering activity Qinghai-Tibet Plateau geological hazards survey engineering

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Automated machine learning for rainfall-induced landslide hazard mapping in Luhe County of Guangdong Province,China

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China Geology 2024年第2期7卷 315-329页

作者： Tao Li Chen-chen Xie Chong Xu Wen-wen Qi Yuan-dong Huang Lei Li National Institute of Natural hazards Ministry of Emergency Management of ChinaBeijing 100085China Key Laboratory of Compound and Chained Natural hazards Dynamics Ministry of Emergency Management of ChinaBeijing 100085China Institute of Disaster Prevention Sanhe 065201China School of Emergency Management Science and engineering University of Chinese Academy of SciencesBeijing 100049China

Landslide hazard mapping is essential for regional landslide hazard management.The main objective of this study is to construct a rainfall-induced landslide hazard map of Luhe County,China based on an automated machine learning framework(AutoGluon).A total of 2241 landslides were identified from satellite images before and after the rainfall event,and 10 impact factors including elevation,slope,aspect,normalized difference vegetation index(NDVI),topographic wetness index(TWI),lithology,land cover,distance to roads,distance to rivers,and rainfall were selected as indicators.The WeightedEnsemble model,which is an ensemble of 13 basic machine learning models weighted together,was used to output the landslide hazard assessment results.The results indicate that landslides mainly occurred in the central part of the study area,especially in Hetian and Shanghu.Totally 102.44 s were spent to train all the models,and the ensemble model WeightedEnsemble has an Area Under the Curve(AUC)value of92.36%in the test set.In addition,14.95%of the study area was determined to be at very high hazard,with a landslide density of 12.02 per square kilometer.This study serves as a significant reference for the prevention and mitigation of geological hazards and land use planning in Luhe County.

关键词： Landslide hazard Heavy rainfall Harzard mapping Hazard assessment Automated machine learning Shallow landslide Visual interpretation Luhe County geological hazards survey engineering

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Extensive identification of landslide boundaries using remote sensing images and deep learning method

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China Geology 2024年第2期7卷 277-290页

作者： Chang-dong Li Peng-fei Feng Xi-hui Jiang Shuang Zhang Jie Meng Bing-chen Li Faculty of engineering China University of GeoscienceWuhan 430074China Badong National Observation and Research Station of Geohazards China University of GeosciencesWuhan 430074China School of Mechanical engineering and Electronic Information China University of GeosciencesWuhan 430074China College of Geology engineering and Geomatics Chang’an UniversityXi’an 710054China

The frequent occurrence of extreme weather events has rendered numerous landslides to a global natural disaster issue.It is crucial to rapidly and accurately determine the boundaries of landslides for geohazards evaluation and emergency response.Therefore,the Skip Connection DeepLab neural network(SCDnn),a deep learning model based on 770 optical remote sensing images of landslide,is proposed to improve the accuracy of landslide boundary detection.The SCDnn model is optimized for the over-segmentation issue which occurs in conventional deep learning models when there is a significant degree of similarity between topographical geomorphic features.SCDnn exhibits notable improvements in landslide feature extraction and semantic segmentation by combining an enhanced Atrous Spatial Pyramid Convolutional Block(ASPC)with a coding structure that reduces model complexity.The experimental results demonstrate that SCDnn can identify landslide boundaries in 119 images with MIoU values between 0.8and 0.9;while 52 images with MIoU values exceeding 0.9,which exceeds the identification accuracy of existing techniques.This work can offer a novel technique for the automatic extensive identification of landslide boundaries in remote sensing images in addition to establishing the groundwork for future inve stigations and applications in related domains.

关键词： Geohazard Landslide boundary detection Remote sensing image Deep learning model Steep slope Large annual rainfall Human settlements Infrastructure Agricultural land Eastern Tibetan Plateau geological hazards survey engineering

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Short-term displacement prediction for newly established monitoring slopes based on transfer learning

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China Geology 2024年第2期7卷 351-364页

作者： Yuan Tian Yang-landuo Deng Ming-zhi Zhang Xiao Pang Rui-ping Ma Jian-xue Zhang Institute of Remote Sensing and Geographical Information Systems Peking UniversityBeijing 100871China Beijing Key Laboratory of Spatial Information Integration and Its Applications Beijing 100871China Institute of Public Safety Research Department of Engineering PhysicsTsinghua UniversityBeijing 100084China China Institute of Geo-Environment Monitoring Beijing 100081China Technology Innovation Center for Geohazard Monitoring and Risk Early Warning Ministry of Natural ResourcesBeijing 100081China

This study makes a significant progress in addressing the challenges of short-term slope displacement prediction in the Universal Landslide Monitoring Program,an unprecedented disaster mitigation program in China,where lots of newly established monitoring slopes lack sufficient historical deformation data,making it difficult to extract deformation patterns and provide effective predictions which plays a crucial role in the early warning and forecasting of landslide hazards.A slope displacement prediction method based on transfer learning is therefore proposed.Initially,the method transfers the deformation patterns learned from slopes with relatively rich deformation data by a pre-trained model based on a multi-slope integrated dataset to newly established monitoring slopes with limited or even no useful data,thus enabling rapid and efficient predictions for these slopes.Subsequently,as time goes on and monitoring data accumulates,fine-tuning of the pre-trained model for individual slopes can further improve prediction accuracy,enabling continuous optimization of prediction results.A case study indicates that,after being trained on a multi-slope integrated dataset,the TCN-Transformer model can efficiently serve as a pretrained model for displacement prediction at newly established monitoring slopes.The three-day average RMSE is significantly reduced by 34.6%compared to models trained only on individual slope data,and it also successfully predicts the majority of deformation peaks.The fine-tuned model based on accumulated data on the target newly established monitoring slope further reduced the three-day RMSE by 37.2%,demonstrating a considerable predictive accuracy.In conclusion,taking advantage of transfer learning,the proposed slope displacement prediction method effectively utilizes the available data,which enables the rapid deployment and continual refinement of displacement predictions on newly established monitoring slopes.

关键词： Landslide Slope displacement prediction Transfer learning Integrated dataset Transformer Pre-trained model Universal Landslide Monitoring Program(ULMP) geological hazards survey engineering

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Airblast evolution initiated by Wangjiayan landslides in the M_(s)8.0 Wenchuan earthquake and its destructive capacity analysis

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China Geology 2024年第2期7卷 237-247页

作者： Yu-feng Wang Qian-gong Cheng Qi Zhu Department of geological engineering Southwest Jiaotong UniversityChengdu 610031China Sichuan Highway Planning SurveyDesign and Research Institute LtdChengdu 610041China

Airblasts,as one common phenomenon accompanied by rapid movements of landslides or rock/snow avalanches,commonly result in catastrophic damages and are attracting more and more scientific attention.To quantitatively analyze the intensity of airblast initiated by landslides,the Wangjiayan landslide,occurred in the Wenchuan earthquake,is selected here with the landslide propagation and airblast evolution being studied using FLUENT by introducing the Voellmy rheological law.The results reveal that:(1)For the Wangjiayan landslide,its whole travelling duration is only 12 s with its maximum velocity reaching 36 m/s at t=10 s;(2)corresponding to the landslide propagation,the maximum velocity,28 m/s,of the airblast initiated by the landslide also appears at t=10 s with its maximum pressure reaching594.8 Pa,which is equivalent to violent storm;(3)under the attack of airblast,the load suffered by buildings in the airblast zone increases to 1300 Pa at t=9.4 s and sharply decreased to-7000 Pa as the rapid decrease of the velocity of the sliding mass at t=10 s,which is seriously unfavorable for buildings and might be the key reason for the destructive collapse of buildings in the airblast zone of the Wangjiayan landslide.

关键词： Landslide Voellmy rheological law 3D FLUENT simulation Airblast Intensity Building destructive collapse Wenchuan earthquake geological hazards survey engineering

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