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Landslides

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Insights from the failure and dynamic characteristics of two sequential landslides at Baige village along the Jinsha River, China

  • Chaojun OuyangEmail author
  • Huicong An
  • Shu Zhou
  • Zhongwen Wang
  • Pengcheng Su
  • Dongpo Wang
  • Duoxiang Cheng
  • Jinxing She
Technical Note
  • 184 Downloads

Abstract

The focus of this paper is on two large sequential landslides which formed a dam and the resulting lake that occurred along the Jinsha River on October 11 and November 3, 2018. About 24 and 9 × 106 m3 of material failed and rushed into the river, respectively. Both landslides totally blocked the river and induced hazard chains. Four multi-temporal unmanned aerial vehicle (UAV)-based high-resolution images and digital elevation models (DEMs) before and after the landslides were obtained and merged. The initial deformation of the two landslides can be clearly captured by optical remote-sensing images and interferometric synthetic aperture radar (InSAR) analysis. The depth-integrated continuum method was adopted to analyze the dynamic process of both landslides, using the same basal friction angle and cohesion. The computational results matched well with field measurements and observations. It is shown that the evaluation of potentially landslide-prone areas by the depth-integrated continuum method is feasible and is able to provide significant information before a possible event.

Keywords

Landslide Landslide dam Barrier lake Remote-sensing image InSAR Numerical modeling 

Notes

Acknowledgments

Sentinel images were provided by the European Space Agency (EAS). Many thanks for discussions with Yong You and Meng Wang and for help from other colleagues in the field. Financial support from the NSFC (Grant No. 41572303, 41520104002), The National Key Research and Development Program of China (Project No. 2017YFC1501000), the CAS Key Research Program of Frontier Sciences (QYZDY-SSW-DQC006), and the Youth Innovation Promotion Association, is acknowledged.

Supplementary material

10346_2019_1177_MOESM1_ESM.gif (625 kb)
ESM 1 (GIF 624 kb)
10346_2019_1177_MOESM2_ESM.gif (620 kb)
ESM 2 (GIF 619 kb)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Key Laboratory of Mountain Hazards and Surface Process & Institute of Mountain Hazards and Environment (IMHE)Chinese Academy of Sciences (CAS)ChengduChina
  2. 2.CAS Center for Excellence in Tibetan Plateau Earth SciencesChinese Academy of Sciences (CAS)BeijingChina
  3. 3.University of Chinese Academy of SciencesBeijingChina
  4. 4.State Key Laboratory of Geohazard Prevention and Geoenvironment ProtectionChengdu University of TechnologyChengduChina
  5. 5.Sichuan Engineering Research Center for Emergency Mapping & Disaster Reduction/Sichuan Geomatics CenterChengduChina

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