Advertisement

Natural Hazards

, Volume 92, Issue 1, pp 415–428 | Cite as

Dynamic process simulation of rainfall-induced Sanxicun landslide based on a thermo-poro-elastic approach

  • Yu Luo
  • Wei Liu
  • Siming He
  • Jiang Yuanjun
  • Xiaoqing Lei
Original Paper
  • 131 Downloads

Abstract

The Sanxicun landslide occurred on July 10, 2013, in Sanxicun Village, which is located in Dujiangyan City, Sichuan Province, China. It travelled up to 1200 m, destroyed 11 houses, and killed 166 people in the village. To explain how this landslide could travel such a large distance and cause such serious damage, this study used a thermo-poro-elastic approach coupled with the Savage–Hutter model to simulate the dynamic process of the Sanxicun landslide. The simulated results were compared with the actual results, as well as those of other researchers. It showed that the simulated results for the landslide profile and mass accumulation scope were basically consistent with the actual results. The simulated landslide runout was 1242 m, which was quite close to the actual value. The simulated maximum mass accumulation thickness was 16.4 m. The maximum velocity was 32.6 m/s, which was between those calculated by Yin et al. (J Eng Geol 22(2):309–318, 2014), Yin et al. (Landslide 13:9–23, 2016), and the various trends were found to be consistent. The temperature change and the pore water pressure evolution in the shear zone during sliding are also obtained by simulation. This study had recreated the Sanxicun landslide motion process from the view of thermo-poro-elastic coupling within the shear zone.

Keywords

Landslide Dynamic process Simulation Thermo-poro-elastic Savage–Hutter model 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (41401004, 41472293), NSFC-ICIMOD (Grant No. 41661144041), Science and Technology Plan Project of Sichuan Province (2016SZ0067), and Key Research and Development Projects of Sichuan Province (2017SZ0041), CAS “Light of West China” program.

References

  1. Anderson DL (1980) An earthquake induced heat mechanism to explain the loss of strength of large rock and earth slides. In: International conference on engineering for protection from natural disasters, BangkokGoogle Scholar
  2. Campbell CS (1989) Self-lubrication for long-runout landslides. J Geol 97:653–665CrossRefGoogle Scholar
  3. Campbell CS, Cleary PW, Hopkins M (1995) Large-scale landslide simulations: global deformation, velocities and basal friction. J Geophys Res 100(B5):8267–8283CrossRefGoogle Scholar
  4. Davies TRH (1982) Spreading of rock avalanche debris by mechanical fluidization. Rock Mech 15:9–24CrossRefGoogle Scholar
  5. Francesco C, Antonis Z (2012) Influence of thermomechanics in the catastrophic collapse of planar landslides. Can Geotech J 49:207–225CrossRefGoogle Scholar
  6. Francesco C, Antonis Z, Emmanuil V (2011) A thermo-mechanical model for the catastrophic collapse of large landslides. Int J Numer Anal Meth Geomech 35:1507–1535CrossRefGoogle Scholar
  7. Gaziev E (1984) Study of the Usoy landslide in Pamir. In: IV International symposium on landslides torontoGoogle Scholar
  8. Goren L, Aharonov E (2007) Long runout landslides: the role of frictional heating and hydraulic diffusivity. Geophys Res Lett 34:L07301CrossRefGoogle Scholar
  9. Goren L, Aharonov E, Anders MH (2010) The long runout of the mountain landslide: heating, Pressurization, and carbonate decomposition. J Geophys Res 115:B10210CrossRefGoogle Scholar
  10. He SM, Liu W, Wang J (2015) Dynamic simulation of landslide based on thermo-poro-elastic approach. Comput Geosci 75:24–32CrossRefGoogle Scholar
  11. Heim A (1932) Landslides and human lives. In: Skermer N (ed) Bi-Tech Publishers, VancouverGoogle Scholar
  12. Hsu KJ (1975) Catastrophic debris streams (sturzsrtoms) generated by rockfalls. Geol Soc Am Bull 86(1):129Google Scholar
  13. Hungr O (2002) Analytical models for slides and flows. Int Symp Landslide Risk Mitig Prot Cult Nat Herit. Kyoto, Japan, pp 559–586Google Scholar
  14. Liu W, He SM, Li XP, Xu Q (2015a) Two-dimensional landslide dynamic simulation based on a velocity-weakening friction law. Landslides.  https://doi.org/10.1007/s10346-015-0632-z Google Scholar
  15. Liu W, He SM, Li XP (2015b) Numerical simulation of landslide over erodible surface. Geoenviron Disasters 2:19.  https://doi.org/10.1186/s40677-015-0027-4 CrossRefGoogle Scholar
  16. Shreve R (1966) Sherman landslide, Alaska. Science 154(3757):1639–1643CrossRefGoogle Scholar
  17. Vandre B (1985) Delineation of landslide, flash flood and debris flow hazards in Utah. In: Proceedings of a specialty conference: Utah Water Research Laboratory. Gen SerRep UWRL/G–85/03 In: Bowles DS (ed) Rudd Creek Debris Flow, pp 117–131Google Scholar
  18. Vardoulakis I (2000) Catastrophic landslides due to frictional heating of the failure plane. Mech Cohes Frict Mater 5:443–467CrossRefGoogle Scholar
  19. Vardoulakis I (2002) Dynamic thermo-poro-mechanical analysis of catastrophic landslides. Geotechnique 52(3):157–171CrossRefGoogle Scholar
  20. Voight B, Faust C (1982) Frictional heat and strength loss in some rapid landslides. Geotechnique 32:43–54CrossRefGoogle Scholar
  21. Xing A, Hu H, Yao L (2001) Pore liquid pressure of large high-speed rockslide in initial stage. Bull Soil Water Conserv 21(3):17–19Google Scholar
  22. Yin ZQ, Xu YQ, Zhao WJ (2014) Sanxi village landslide in Dujiangyan, Sichuan province on July 10, 2013. J Eng Geol 22(2):309–318Google Scholar
  23. Yin Y, Cheng Y, Liang J, Wang W (2016) Heavy-rainfall-induced catastrophic rockslide-debris flow at Sanxicun, Dujiangyan, after the Wenchuan Ms.8.0 earthquake. Landslide 13:9–23CrossRefGoogle Scholar
  24. Zhang M, Yin Y, Wu S, Zhang Y (2010) Development status and prospects of studies on kinematics of long runout rock avalanches. J Eng Geol 18(6):805–817Google Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Key laboratory of Mountain Hazards and Surface ProcessChinese Academy of ScienceChengduChina
  2. 2.Institute of Mountain Hazards and Environment (IMHE)Chinese Academy of SciencesChengduChina
  3. 3.CAS Center for Excellence in Tibetan Plateau Earth SciencesBeijingChina

Personalised recommendations