In 2018,a catastrophic high-altitude landslide occurred at Baige,located within the tectonic suture zone of the Upper Jinsha River.The failure mechanism of this event remains poorly understood.This study aims to eluci...In 2018,a catastrophic high-altitude landslide occurred at Baige,located within the tectonic suture zone of the Upper Jinsha River.The failure mechanism of this event remains poorly understood.This study aims to elucidate the deformation characteristics and failure mechanism of the Baige landslide by employing a comprehensive methodology,including field geological surveys,analysis of historical remote sensing imagery,high-density electrical resistivity surveys,and advanced displacement monitoring.Additionally,the physical modeling experiments were conducted to replicate the unique failure modes.The findings propose a novel perspective on the failure mechanism of the Baige landslide,which involves two critical stages:first,the brittle shear zone bypasses and fails at the lower locked segment,and second,the failure of the upper locked segment,combined with the shear zone's impact on the lower locked segment,triggers overall slope instability.Physical modeling experiments revealed a transition from initial acceleration to a rapid acceleration phase,particularly marked by a significant increase in velocity following the failure of the upper locked segment.The intensity of acoustic emission signals was found to correlate with the failure of the locked segments and the state of particle collisions post-failure.It offers new insights into the failure mechanisms of tectonic mélange belt large-scale landslides in suture zones,contributing to the broader field of landslide research.展开更多
In 2018,Baige,Xizang,witnessed two consecutive large-scale landslides,causing significant damage and drawing widespread attention.From March 2011 to February 2018,the Baige landslide exhibited a 50-m displacement with...In 2018,Baige,Xizang,witnessed two consecutive large-scale landslides,causing significant damage and drawing widespread attention.From March 2011 to February 2018,the Baige landslide exhibited a 50-m displacement without complete failure,culminating in a collapse in October 2018.The mechanisms behind its resistance to failure despite substantial deformation and the influence of the complex geo-structure within the tectonic mélange belt remain unclear.To address these questions,this study utilized a multidisciplinary approach,integrating on-site geological field mapping,surface deformation monitoring,multielectrode resistivity method,and deep displacement analysis.The aim was to evaluate the impact of the intricate geo-structure within the tectonic mélange belt on the Baige landslide events.Findings reveal that the landslide's geo-structure consists of structurally fractured,mesh-like rock masses,including heterogeneous lenticular rock masses and intermittent brittle shear zones distributed around the lens-shaped rock masses.The study underscores that the inhomogeneous and weakly deformed lenticular rock masses function as natural locked segments,governing the stability of the Baige landslide.Specifically,the relatively intact and hard granodiorite porphyry play a crucial role in locking the landslide's deformation.Deep displacement analysis indicates that the brittle shear zones act as the sliding surfaces.The progressive destruction of the locked segments and the gradual penetration of brittle shear zones,driven by gravitational potential energy,contribute to the landslide occurrence.This research provides critical insights into the formation mechanisms of large-scale landslides within tectonic mélange belts.展开更多
Accurate dynamic modeling of landslides could help understand the movement mechanisms and guide disaster mitigation and prevention.Discontinuous deformation analysis(DDA)is an effective approach for investigating land...Accurate dynamic modeling of landslides could help understand the movement mechanisms and guide disaster mitigation and prevention.Discontinuous deformation analysis(DDA)is an effective approach for investigating landslides.However,DDA fails to accurately capture the degradation in shear strength of rock joints commonly observed in high-speed landslides.In this study,DDA is modified by incorporating simplified joint shear strength degradation.Based on the modified DDA,the kinematics of the Baige landslide that occurred along the Jinsha River in China on 10 October 2018 are reproduced.The violent starting velocity of the landslide is considered explicitly.Three cases with different violent starting velocities are investigated to show their effect on the landslide movement process.Subsequently,the landslide movement process and the final accumulation characteristics are analyzed from multiple perspectives.The results show that the violent starting velocity affects the landslide motion characteristics,which is found to be about 4 m/s in the Baige landslide.The movement process of the Baige landslide involves four stages:initiation,high-speed sliding,impact-climbing,low-speed motion and accumulation.The accumulation states of sliding masses in different zones are different,which essentially corresponds to reality.The research results suggest that the modified DDA is applicable to similar high-level rock landslides.展开更多
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 calcu...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.展开更多
On 10th Oct.and 3rd Nov.2018,two successive landslides occurred in the Jinsha River catchment at Baige Village,Tibet Autonomous Region,China.The landslides blocked the major river and formed the barrier lake,which fin...On 10th Oct.and 3rd Nov.2018,two successive landslides occurred in the Jinsha River catchment at Baige Village,Tibet Autonomous Region,China.The landslides blocked the major river and formed the barrier lake,which finally caused the huge flood disaster loss.The hillslope at Baige landslide site has been still deforming after the 2018 slidings,which is likely to fail and block the Jinsha River again in the future.Therefore the investigation of 2018 flood disaster at the Baige landslide is of a great significance to provide a classic case for flood assessment and early warning for the future disaster.The detailed survey revealed that the outstanding inundations induced bank collapse disasters upstream the Baige landslide dams,and the field investigations and hydrological simulation suggested that the downstream of the Baige landslide were seriously flooded due to the two periods of the outburst floods.On these bases,the early warning process of potential outburst floods at the Baige landslide was advised,which contains four stages:Outburst Flood Simulating Stage,Outburst Flood Forecasting Stage,Emergency Plan and Emergency Evacuation Stage.The study offers a conceptual model for the mitigation of landslides and flood disasters in the high-relief mountain-ous region in Tibet.展开更多
The Karakoram Highway(KKH),a part of the China–Pakistan Economic Corridor(CPEC),is a major highway connecting northern Pakistan to China.The inventorying and analysis of landslides along KKH are challenging because o...The Karakoram Highway(KKH),a part of the China–Pakistan Economic Corridor(CPEC),is a major highway connecting northern Pakistan to China.The inventorying and analysis of landslides along KKH are challenging because of poor accessibility,vast study area,limited availability of ground-based datasets,and the complexity of landslide processes in the region.In order to preserve life,property,and infrastructure,and to enable the uninterrupted and efficient operation of the KKH,it is essential to strengthen measures for the prevention and control of geological disasters.In the present study,SBASInSAR(Small Baseline Subsets-Interferometric Synthetic Aperture Radar)was used to process 150 scenes of Sentinel 1-A images in the year 2017 along the Karakoram Highway.A total of 762 landslides,including 57 complex landslides,126 rock falls,167 debris slides,and 412 unstable slopes,ranging in size between 0.0017 and 10.63 km2 were identified.Moreover,this study also gains an inventory of 40 active glacier movements in this region.Landslide categorization,displacements characteristics,spatial distribution,and their relationship with various contributing factors have been successfully investigated along the entire KKH using image interpretation and frequency-area statistics.The criteria adopted for landslides categorization is presented in the study.The results showed that the 2-D ground deformation derived in Hunza valley echoes well with the general regional landslides characteristics.The spatial distribution analysis revealed that there are clumped distributions of landslides in the Gaizi,Tashkurgan,and Khunjerab in China,as well as in Hunza valley,and north of Chilas city in Pakistan.Statistical results indicated that these landslides mainly occur on south-facing slopes with a slope angle of 20°–45°and elevation relief of 550–2,100 m.Landslide development is also related to low vegetation cover and weathering effects in mountain gullies.Overall,our study provides scientific data support and theoretical references for prevention,control,and mitigation of geological disasters in the Karakoram region.展开更多
SBAS-InSAR technology is characterized by the advantages of reducing the influence of terrain-simulation error,time-space decorrelation,atmospheric error,thereby improving the reliability of surface-deformation monito...SBAS-InSAR technology is characterized by the advantages of reducing the influence of terrain-simulation error,time-space decorrelation,atmospheric error,thereby improving the reliability of surface-deformation monitoring.This paper studies the early landslide identification method based on SBAS-InSAR technology.Selecting the Jiangdingya landslide area in Zhouqu County,Gansu Province as the research area,84 ascendingorbit Sentinel-1A SAR images from 2015 to 2019 are collected.In addition,using SBAS-InSAR technology,the rate and time-series results of surface deformation of the landslide area in Jiangdingya during this period are extracted,and potential landslides are identified.The results show that the early landslide identification method based on SBAS-InSAR technology is highly feasible and is a better tool for identifying potential landslides in large areas.展开更多
The upstream Jinsha River,located in the eastern Tibetan Plateau,has been experiencing intense geological hazards characterized by a high density of ancient landslides,significant deformation and reactivation challeng...The upstream Jinsha River,located in the eastern Tibetan Plateau,has been experiencing intense geological hazards characterized by a high density of ancient landslides,significant deformation and reactivation challenges.In this study,remote sensing interpretation,field investigations,and Small Baseline Subset Interferometric Synthetic Aperture Radar(SBAS-InSAR)technologies have been employed.Along a 17 km stretch of the Jinsha River,specifically in the Xiongba-Sela segment,16 large-scale ancient landslides were identified,9 of which are currently undergoing creeping deformation.Notably,the Sela and Xiongba ancient landslides exhibit significant deformation,with a maximum deformation rate of-192 mm/yr,indicating a high level of sliding activity.The volume of the Sela ancient landslide is estimated to be 1.8×108 to 4.5×108 m3,and characterized by extensive fissures and long-term creeping deformation.The SBAS-InSAR results revealed significant spatial variations in the deformation of the Sela ancient landslide,generally displaying two secondary zones of intense deformation,and landslide deformation exhibits nonlinear behavior with time.Between January 2016 and February 2022,Zone III1 on the southwest side of the Sela ancient landslide,experienced a maximum cumulative deformation of-857 mm,with a maximum deformation rate of-108 mm/yr.Zone III2,on the northeast side of the Sela ancient landslide,the maximum cumulative deformation was-456 mm,with a maximum deformation rate of-74 mm/yr;among these,the H2 and H4 secondary bodies on the south side of III1 are in the accelerative deformation stage and at the Warn warning level.We propose that the large-scale flood and debris flow disasters triggered by the Baige landslide-dammed lake-dam broken disaster chain in Tibetan Plateau during October and November 2018 caused severe erosion at the foot of downstream slopes.This far-field triggering effect accelerated the creep of the downstream ancient landslides.Consequently,the deformation rate of Zone III2 of the Sela ancient landslide increased by 6 to 8 times,exhibiting traction-type style reactivation.This heightened activity raises concerns about the potential for large-scale or overall reactivation of the landslide,posing a risk of damming the Jinsha River and initiating a dam-break disaster chain.Our research on the reactivation characteristics and mechanisms of large ancient landslides in high deep-cut valleys provides valuable guidance for geological hazard investigation and risk prevention.展开更多
This study aims to utilize the Small Baseline Subset Interferometric Synthetic Aperture Radar(SBAS-In SAR)technique and Google Earth optical remote sensing images to analyze the area within 20 km around the epicenter ...This study aims to utilize the Small Baseline Subset Interferometric Synthetic Aperture Radar(SBAS-In SAR)technique and Google Earth optical remote sensing images to analyze the area within 20 km around the epicenter of a M 3.9, earthquake that occurred in Tanchang County, Gansu Province, on December 28, 2020. The objective is to identify potential earthquake-induced landslides, assess their scale, and determine their impact range. The study results reveal the successful identification of two potential landslides in the 20 km radius around the epicenter. Through time-series deformation analysis, it was observed that these potential landslides were significantly influenced by both the earthquake and rainfall. Further estimation of these potential landslides indicates maximum depths of 7.4 m and 14.1 m for the failure surfaces, with volumes of 9.02 × 10~4m~3and 25.5 ×10~4m~3, respectively. Finally, based on the simulation analysis of Massflow software, the maximum thickness of soil accumulation in the final accumulation area after sliding of the potential landslide in Shangyaai is 12 m, the area of the final accumulation area is 1.75 × 10~4m~2, and the farthest movement distance is 1124 m. The maximum thickness of soil accumulation in the final accumulation area after sliding of the potential landslide in Wangshancun is 8 m, the area of the final accumulation area is 7.89 × 10~4m~2, and the farthest movement distance is 742 m.展开更多
Strata in red bed areas have typical characteristics of soft-hard interbedding and high sensitivity to water. Under the comprehensive action of internal stratigraphic structure and external hydrological factors, red b...Strata in red bed areas have typical characteristics of soft-hard interbedding and high sensitivity to water. Under the comprehensive action of internal stratigraphic structure and external hydrological factors, red bed landslides have highly complex spatiotemporal characteristics, presenting significant challenges to the prevention and control of landslide disasters in red bed areas, especially for slope and tunnel engineering projects. In this study, we applied an interdisciplinary approach combining small baseline subset interferometric synthetic aperture radar(SBAS-InSAR), deep displacement monitoring, and engineering geological surveying to identify the deformation mechanisms and spatiotemporal characteristics of the Abi landslide, an individual landslide that occurred in the red bed area of Western Yunnan, China. Surface deformation time series indicated that a basic deformation range developed by March 2020. Based on In SAR results and engineering geological analysis, the landslide surface could be divided into three zones: an upper sliding zone(US), a lower uplifted zone(LU), and a toe zone(Toe). LU was affected by the structure of the sliding bed with variable inclination. Using deep displacement curves combined with the geological profile, a set of sliding surfaces were identified between different lithology. The groundwater level standardization index(GLSI) and deformation normalization index(DNI) showed different quadratic relationships between US and LU. Verification using the Pearson correlation analysis shows that the correlation coefficients between model calculated results and measured data are 0.7933 and 0.7577, respectively, indicating that the DNI-GLSI models are applicable. A fast and short-lived deformation sub stage(ID-Fast) in the initial deformation stage was observed, and ID-Fast was driven by concentrated rainfall.展开更多
The construction of large reservoirs can address the problem of uneven distribution of rivers in time and space,thereby meeting the needs of human production and living.However,the huge elevation of the water level in...The construction of large reservoirs can address the problem of uneven distribution of rivers in time and space,thereby meeting the needs of human production and living.However,the huge elevation of the water level in some areas may modify the distribution of the groundwater level,causing geological disasters,such as surface deformation and landslides.The Yalong reservoir supplies water to the downstream area of Shannan,Tibet;however,since the reservoir started storing water in 2017,the government has discovered two ancient landslides.In this study,to monitor the deformation of the Yalong reservoir since its construction in 2014,we first used synthetic aperture radar(SAR)data and the multidimensional small baseline subset(MSBAS)method to obtain the deformation in the east-west and vertical directions.The result indicated the presence of three large,slow-moving landslides:Landslides I and II,located on the right bank of the Yalong reservoir,which are consistent with the results obtained by the actual survey,and a new discovery,LandslideⅢ,located on the left side of the reservoir.Meanwhile,the experimental results indicated that the dam had undergone obvious deformation after impoundment,which should not be ignored.The global positioning system and interferometric SAR(InSAR)timeseries deformation residual data were used to verify the accuracy of the InSAR method.The results also showed that the deformation caused by the three landslides had te nded to accele rate after the rese rvoir’s impoundment,and that the failure mode was retrogressive landslide.We found that InSAR plays a vital role in landslide detection and failure mode research around reservoirs,and assists in providing early warning for subsequent landslide disasters.展开更多
基金supported by the National Major Scientific Instruments and Equipment Development Projects of China(No.41827808)the Major Program of the National Natural Science Foundation of China(No.42090055)Supported by Science and Technology Projects of Xizang Autonomous Region,China(No.XZ202402ZD0001)。
文摘In 2018,a catastrophic high-altitude landslide occurred at Baige,located within the tectonic suture zone of the Upper Jinsha River.The failure mechanism of this event remains poorly understood.This study aims to elucidate the deformation characteristics and failure mechanism of the Baige landslide by employing a comprehensive methodology,including field geological surveys,analysis of historical remote sensing imagery,high-density electrical resistivity surveys,and advanced displacement monitoring.Additionally,the physical modeling experiments were conducted to replicate the unique failure modes.The findings propose a novel perspective on the failure mechanism of the Baige landslide,which involves two critical stages:first,the brittle shear zone bypasses and fails at the lower locked segment,and second,the failure of the upper locked segment,combined with the shear zone's impact on the lower locked segment,triggers overall slope instability.Physical modeling experiments revealed a transition from initial acceleration to a rapid acceleration phase,particularly marked by a significant increase in velocity following the failure of the upper locked segment.The intensity of acoustic emission signals was found to correlate with the failure of the locked segments and the state of particle collisions post-failure.It offers new insights into the failure mechanisms of tectonic mélange belt large-scale landslides in suture zones,contributing to the broader field of landslide research.
基金supported by the National Major Scientific Instruments and Equipment Development Projects of China(No.41827808)the Major Program of the National Natural Science Foundation of China(No.42090055)Supported by Science and Technology Projects of Xizang Autonomous Region,China(No.XZ202402ZD0001)。
文摘In 2018,Baige,Xizang,witnessed two consecutive large-scale landslides,causing significant damage and drawing widespread attention.From March 2011 to February 2018,the Baige landslide exhibited a 50-m displacement without complete failure,culminating in a collapse in October 2018.The mechanisms behind its resistance to failure despite substantial deformation and the influence of the complex geo-structure within the tectonic mélange belt remain unclear.To address these questions,this study utilized a multidisciplinary approach,integrating on-site geological field mapping,surface deformation monitoring,multielectrode resistivity method,and deep displacement analysis.The aim was to evaluate the impact of the intricate geo-structure within the tectonic mélange belt on the Baige landslide events.Findings reveal that the landslide's geo-structure consists of structurally fractured,mesh-like rock masses,including heterogeneous lenticular rock masses and intermittent brittle shear zones distributed around the lens-shaped rock masses.The study underscores that the inhomogeneous and weakly deformed lenticular rock masses function as natural locked segments,governing the stability of the Baige landslide.Specifically,the relatively intact and hard granodiorite porphyry play a crucial role in locking the landslide's deformation.Deep displacement analysis indicates that the brittle shear zones act as the sliding surfaces.The progressive destruction of the locked segments and the gradual penetration of brittle shear zones,driven by gravitational potential energy,contribute to the landslide occurrence.This research provides critical insights into the formation mechanisms of large-scale landslides within tectonic mélange belts.
基金supported by the National Natural Science Foundations of China(grant numbers U22A20601 and 52209142)the Opening fund of State Key Laboratory of Geohazard Prevention and Geoenvironment Protection(Chengdu University of Technology)(grant number SKLGP2022K018)+1 种基金the Science&Technology Department of Sichuan Province(grant number 2023NSFSC0284)the Science and Technology Major Project of Tibetan Autonomous Region of China(grant number XZ202201ZD0003G)。
文摘Accurate dynamic modeling of landslides could help understand the movement mechanisms and guide disaster mitigation and prevention.Discontinuous deformation analysis(DDA)is an effective approach for investigating landslides.However,DDA fails to accurately capture the degradation in shear strength of rock joints commonly observed in high-speed landslides.In this study,DDA is modified by incorporating simplified joint shear strength degradation.Based on the modified DDA,the kinematics of the Baige landslide that occurred along the Jinsha River in China on 10 October 2018 are reproduced.The violent starting velocity of the landslide is considered explicitly.Three cases with different violent starting velocities are investigated to show their effect on the landslide movement process.Subsequently,the landslide movement process and the final accumulation characteristics are analyzed from multiple perspectives.The results show that the violent starting velocity affects the landslide motion characteristics,which is found to be about 4 m/s in the Baige landslide.The movement process of the Baige landslide involves four stages:initiation,high-speed sliding,impact-climbing,low-speed motion and accumulation.The accumulation states of sliding masses in different zones are different,which essentially corresponds to reality.The research results suggest that the modified DDA is applicable to similar high-level rock landslides.
基金funded by the National Natural Science Foundation of China(Grant No.41861134008)Muhammad Asif Khan academician workstation of Yunnan Province(Grant No.202105AF150076)+6 种基金General program of Yunnan Province Science and Technology Department(Grant No.202105AF150076)Key Project of Natural Science Foundation of Yunnan Province(Grant No.202101AS070019)Key R&D Program of Yunnan Province(Grant No.202003AC100002)General Program of basic research plan of Yunnan Province(Grant No.202001AT070059)Major scientific and technological projects of Yunnan Province:Research on Key Technologies of ecological environment monitoring and intelligent management of natural resources in Yunnan(No:202202AD080010)“Study on High-Level Hidden Landslide Identification Based on Multi-Source Data”of Key Laboratory of Early Rapid Identification,Prevention and Control of Geological Diseases in Traffic Corridor of High Intensity Earthquake Mountainous Area of Yunnan Province(KLGDTC-2021-02)Guizhou Scientific and Technology Fund(QKHJ-ZK[2023]YB 193).
文摘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.
基金The Second Tibetan Plateau Scientific Expedition and Research Program,No.2019QZKK0905National Key R&D Program of China,No.2018 YFC15050004National Natural Science Foundation Projects,No.42007248。
文摘On 10th Oct.and 3rd Nov.2018,two successive landslides occurred in the Jinsha River catchment at Baige Village,Tibet Autonomous Region,China.The landslides blocked the major river and formed the barrier lake,which finally caused the huge flood disaster loss.The hillslope at Baige landslide site has been still deforming after the 2018 slidings,which is likely to fail and block the Jinsha River again in the future.Therefore the investigation of 2018 flood disaster at the Baige landslide is of a great significance to provide a classic case for flood assessment and early warning for the future disaster.The detailed survey revealed that the outstanding inundations induced bank collapse disasters upstream the Baige landslide dams,and the field investigations and hydrological simulation suggested that the downstream of the Baige landslide were seriously flooded due to the two periods of the outburst floods.On these bases,the early warning process of potential outburst floods at the Baige landslide was advised,which contains four stages:Outburst Flood Simulating Stage,Outburst Flood Forecasting Stage,Emergency Plan and Emergency Evacuation Stage.The study offers a conceptual model for the mitigation of landslides and flood disasters in the high-relief mountain-ous region in Tibet.
基金supported by National Key Research and Development Program of China(Grant No.2017YFC1501005)National Natural Science Foundation of China(Grant Nos.41661144046,42007232)+3 种基金the Science and Technology Major Project of Gansu Province(Grant No.19ZD2FA002)the Science and Technology Planning Project of Gansu Province(Grant No.18YF1WA114)the Fundamental Research Funds for the Central Universities(Grant Nos.lzujbky-2021-ey05)Second Tibetan Plateau Scientific Expedition and Research Program(Grant No.2019QZKK0902)。
文摘The Karakoram Highway(KKH),a part of the China–Pakistan Economic Corridor(CPEC),is a major highway connecting northern Pakistan to China.The inventorying and analysis of landslides along KKH are challenging because of poor accessibility,vast study area,limited availability of ground-based datasets,and the complexity of landslide processes in the region.In order to preserve life,property,and infrastructure,and to enable the uninterrupted and efficient operation of the KKH,it is essential to strengthen measures for the prevention and control of geological disasters.In the present study,SBASInSAR(Small Baseline Subsets-Interferometric Synthetic Aperture Radar)was used to process 150 scenes of Sentinel 1-A images in the year 2017 along the Karakoram Highway.A total of 762 landslides,including 57 complex landslides,126 rock falls,167 debris slides,and 412 unstable slopes,ranging in size between 0.0017 and 10.63 km2 were identified.Moreover,this study also gains an inventory of 40 active glacier movements in this region.Landslide categorization,displacements characteristics,spatial distribution,and their relationship with various contributing factors have been successfully investigated along the entire KKH using image interpretation and frequency-area statistics.The criteria adopted for landslides categorization is presented in the study.The results showed that the 2-D ground deformation derived in Hunza valley echoes well with the general regional landslides characteristics.The spatial distribution analysis revealed that there are clumped distributions of landslides in the Gaizi,Tashkurgan,and Khunjerab in China,as well as in Hunza valley,and north of Chilas city in Pakistan.Statistical results indicated that these landslides mainly occur on south-facing slopes with a slope angle of 20°–45°and elevation relief of 550–2,100 m.Landslide development is also related to low vegetation cover and weathering effects in mountain gullies.Overall,our study provides scientific data support and theoretical references for prevention,control,and mitigation of geological disasters in the Karakoram region.
基金Received on May 7th,2020revised on September 27th,2020.This project is sponsored by the Research on Early Identification of Landslide Hazards based on High-resolution SAR Image(KJ-2018-13).
文摘SBAS-InSAR technology is characterized by the advantages of reducing the influence of terrain-simulation error,time-space decorrelation,atmospheric error,thereby improving the reliability of surface-deformation monitoring.This paper studies the early landslide identification method based on SBAS-InSAR technology.Selecting the Jiangdingya landslide area in Zhouqu County,Gansu Province as the research area,84 ascendingorbit Sentinel-1A SAR images from 2015 to 2019 are collected.In addition,using SBAS-InSAR technology,the rate and time-series results of surface deformation of the landslide area in Jiangdingya during this period are extracted,and potential landslides are identified.The results show that the early landslide identification method based on SBAS-InSAR technology is highly feasible and is a better tool for identifying potential landslides in large areas.
基金funded by the National Natural Science Foundation of China(Nos.42007280,42372339)the China Geological Survey Project(No.DD20221816).
文摘The upstream Jinsha River,located in the eastern Tibetan Plateau,has been experiencing intense geological hazards characterized by a high density of ancient landslides,significant deformation and reactivation challenges.In this study,remote sensing interpretation,field investigations,and Small Baseline Subset Interferometric Synthetic Aperture Radar(SBAS-InSAR)technologies have been employed.Along a 17 km stretch of the Jinsha River,specifically in the Xiongba-Sela segment,16 large-scale ancient landslides were identified,9 of which are currently undergoing creeping deformation.Notably,the Sela and Xiongba ancient landslides exhibit significant deformation,with a maximum deformation rate of-192 mm/yr,indicating a high level of sliding activity.The volume of the Sela ancient landslide is estimated to be 1.8×108 to 4.5×108 m3,and characterized by extensive fissures and long-term creeping deformation.The SBAS-InSAR results revealed significant spatial variations in the deformation of the Sela ancient landslide,generally displaying two secondary zones of intense deformation,and landslide deformation exhibits nonlinear behavior with time.Between January 2016 and February 2022,Zone III1 on the southwest side of the Sela ancient landslide,experienced a maximum cumulative deformation of-857 mm,with a maximum deformation rate of-108 mm/yr.Zone III2,on the northeast side of the Sela ancient landslide,the maximum cumulative deformation was-456 mm,with a maximum deformation rate of-74 mm/yr;among these,the H2 and H4 secondary bodies on the south side of III1 are in the accelerative deformation stage and at the Warn warning level.We propose that the large-scale flood and debris flow disasters triggered by the Baige landslide-dammed lake-dam broken disaster chain in Tibetan Plateau during October and November 2018 caused severe erosion at the foot of downstream slopes.This far-field triggering effect accelerated the creep of the downstream ancient landslides.Consequently,the deformation rate of Zone III2 of the Sela ancient landslide increased by 6 to 8 times,exhibiting traction-type style reactivation.This heightened activity raises concerns about the potential for large-scale or overall reactivation of the landslide,posing a risk of damming the Jinsha River and initiating a dam-break disaster chain.Our research on the reactivation characteristics and mechanisms of large ancient landslides in high deep-cut valleys provides valuable guidance for geological hazard investigation and risk prevention.
基金supported by the Natural Science Foundation of Gansu Province (22JR5RA326)The geological disaster prevention projects of Gansu Provincial Bureau of Geology and Mineral Resources (2023-2-9)。
文摘This study aims to utilize the Small Baseline Subset Interferometric Synthetic Aperture Radar(SBAS-In SAR)technique and Google Earth optical remote sensing images to analyze the area within 20 km around the epicenter of a M 3.9, earthquake that occurred in Tanchang County, Gansu Province, on December 28, 2020. The objective is to identify potential earthquake-induced landslides, assess their scale, and determine their impact range. The study results reveal the successful identification of two potential landslides in the 20 km radius around the epicenter. Through time-series deformation analysis, it was observed that these potential landslides were significantly influenced by both the earthquake and rainfall. Further estimation of these potential landslides indicates maximum depths of 7.4 m and 14.1 m for the failure surfaces, with volumes of 9.02 × 10~4m~3and 25.5 ×10~4m~3, respectively. Finally, based on the simulation analysis of Massflow software, the maximum thickness of soil accumulation in the final accumulation area after sliding of the potential landslide in Shangyaai is 12 m, the area of the final accumulation area is 1.75 × 10~4m~2, and the farthest movement distance is 1124 m. The maximum thickness of soil accumulation in the final accumulation area after sliding of the potential landslide in Wangshancun is 8 m, the area of the final accumulation area is 7.89 × 10~4m~2, and the farthest movement distance is 742 m.
基金funded by the List of Key Science and Technology Projects in the Transportation Industry of the Ministry of Transport in 2021(Grant No.2021-MS4-105)the Science and Technology Project of Yunnan Traffic Planning Design Institute Co.,Ltd.(Grant No.ZL-2021-03)+7 种基金the Postgraduate Scientific Research Innovation Project of Yunnan University(Grant No.2020192)the National Key Research and Development Program of China(Grant No.2018YFC1504906)the National Natural Science Foundation of China(Grant No.41872251)the Plateau Mountain Ecology and Earth’s Environment Discipline Construction Project(Grant No.C1762101030017)the Joint Foundation Project between Yunnan Science and Technology Department and Yunnan University(Grants No.C176240210019 and 2019FY003017)the Yunnan Postdoctoral Foundation(Grant No.C615300504031)the China Geological Survey Project(Grant No.DD20221824)the science and technology innovation program of the department of transportation,Yunnan province,China(No.2019301)。
文摘Strata in red bed areas have typical characteristics of soft-hard interbedding and high sensitivity to water. Under the comprehensive action of internal stratigraphic structure and external hydrological factors, red bed landslides have highly complex spatiotemporal characteristics, presenting significant challenges to the prevention and control of landslide disasters in red bed areas, especially for slope and tunnel engineering projects. In this study, we applied an interdisciplinary approach combining small baseline subset interferometric synthetic aperture radar(SBAS-InSAR), deep displacement monitoring, and engineering geological surveying to identify the deformation mechanisms and spatiotemporal characteristics of the Abi landslide, an individual landslide that occurred in the red bed area of Western Yunnan, China. Surface deformation time series indicated that a basic deformation range developed by March 2020. Based on In SAR results and engineering geological analysis, the landslide surface could be divided into three zones: an upper sliding zone(US), a lower uplifted zone(LU), and a toe zone(Toe). LU was affected by the structure of the sliding bed with variable inclination. Using deep displacement curves combined with the geological profile, a set of sliding surfaces were identified between different lithology. The groundwater level standardization index(GLSI) and deformation normalization index(DNI) showed different quadratic relationships between US and LU. Verification using the Pearson correlation analysis shows that the correlation coefficients between model calculated results and measured data are 0.7933 and 0.7577, respectively, indicating that the DNI-GLSI models are applicable. A fast and short-lived deformation sub stage(ID-Fast) in the initial deformation stage was observed, and ID-Fast was driven by concentrated rainfall.
基金This work was partly supported by the National Natural Science Foundation of China(No.41804008)the National Science Fund for Distinguished Young Scholars(No.41925016)the National Key R&D Program of China(No.2018YFC1503603).
文摘The construction of large reservoirs can address the problem of uneven distribution of rivers in time and space,thereby meeting the needs of human production and living.However,the huge elevation of the water level in some areas may modify the distribution of the groundwater level,causing geological disasters,such as surface deformation and landslides.The Yalong reservoir supplies water to the downstream area of Shannan,Tibet;however,since the reservoir started storing water in 2017,the government has discovered two ancient landslides.In this study,to monitor the deformation of the Yalong reservoir since its construction in 2014,we first used synthetic aperture radar(SAR)data and the multidimensional small baseline subset(MSBAS)method to obtain the deformation in the east-west and vertical directions.The result indicated the presence of three large,slow-moving landslides:Landslides I and II,located on the right bank of the Yalong reservoir,which are consistent with the results obtained by the actual survey,and a new discovery,LandslideⅢ,located on the left side of the reservoir.Meanwhile,the experimental results indicated that the dam had undergone obvious deformation after impoundment,which should not be ignored.The global positioning system and interferometric SAR(InSAR)timeseries deformation residual data were used to verify the accuracy of the InSAR method.The results also showed that the deformation caused by the three landslides had te nded to accele rate after the rese rvoir’s impoundment,and that the failure mode was retrogressive landslide.We found that InSAR plays a vital role in landslide detection and failure mode research around reservoirs,and assists in providing early warning for subsequent landslide disasters.
