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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/nhess-2020-289
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2020-289
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  27 Oct 2020

27 Oct 2020

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This preprint is currently under review for the journal NHESS.

Numerical investigation on the kinetic characteristics of the Yigong landslide in Tibet, China

Zili Dai1, Fawu Wang2, Hufeng Yang3, and Shiwei Qin1 Zili Dai et al.
  • 1Department of Civil Engineering, Shanghai University, Shanghai, 200444, China
  • 2Department of Geotechnical Engineering, Tongji University, Shanghai 200092, China
  • 3Department of Geological Engineering, Southwest Jiaotong University, Chengdu 610031, China

Abstract. To analyse the kinetic characteristics of a rapid landslide that occurred on 9 April 2000 in Tibet, China, a meshfree numerical method named Smoothed Particle Hydrodynamics (SPH) is introduced, and two-dimensional and three-dimensional models are established in this work. Based on the numerical simulation, the landslide motion process is reproduced and the kinetic characteristics are analysed combined with the field investigation data. In the kinetic analysis, the landslide velocity, run-out distance, landslide accumulation, and energy features are discussed. Simulation results show that the landslide mass undergoes an acceleration stage after failure, then the kinetic energy dissipates gradually due to the friction and collision during the landslide propagation. Finally, the landslide mass blocks the Yigong river and forms a huge landslide dam and an extensive barrier lake. The peak velocity is calculated to be about 100 m/s, and the run-out distance is approximately 8,500 m. The simulation results basically match the data measured in field, thus verifying the good performance of the presented SPH model. This approach can provide a new way to predict hazardous areas and estimate the hazard intensity of rapid landslides.

Zili Dai et al.

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