Journal of Mountain Science

, Volume 15, Issue 10, pp 2247–2265 | Cite as

Long runout mechanism of the Shenzhen 2015 landslide: insights from a two-phase flow viewpoint

  • Cheng Qiao
  • Guo-qiang Ou
  • Hua-li PanEmail author
  • Chao-jun Ouyang
  • Yang Jia


A catastrophic landslide occurred at Hongao dumpsite in Guangming New District of Shenzhen, South China, on December 20, 2015. An estimated total volume of 2.73×106 m3 of construction spoils was mobilized during this event. The landslide traveled a long distance on a low-relief terrain. The affected area was approximately 1100 m in length and 630 m in width. This landslide made 33 buildings destroyed, 73 people died and 4 people lost. Due to the special dumping history and other factors, soil in this landfill is of high initial water content. To identify the major factors that attribute to the long runout character, a two-phase flow model of Iverson and George was used to simulate the dynamics of this landslide. The influence of initial hydraulic permeability, initial dilatancy, and earth pressure coefficient was examined through numerical simulations. We found that pore pressure has the most significant effect on the dynamic characteristics of Shenzhen landslides. Average pore pressure ratio of the whole basal surface was used to evaluate the degree of liquefaction for the sliding material. The evolution and influence factors of this ratio were analyzed based on the computational results. An exponential function was proposed to fit the evolution curve of the average pore pressure ratio, which can be used as a reasonable and simplified evaluation of the pore pressure. This fitting function can be utilized to improve the single-phase flow model.


Dynamics Landslide Long runout Pore pressure Two-phase 


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This paper was supported by the National Key R&D Program of China (Grant Nos. 2017YFC1502502, 2017YFC1502506), National Nature Science Foundation of China (Grant Nos. 41672318, 51679229, 41372331), and 135 Strategic Program of the Institute of Mountain Hazards and Environment, CAS (Grant No. SDS-135-1701). It was also supported by Youth Innovation Promotion Association of the Chinese Academy of Sciences (2018405).


  1. Berger MJ, George DL, Leveque RJ, et al. (2010) The GeoClaw software for depth–averaged flows with adaptive refinement. Advances in Water Resources 34(9): 1195–1206. CrossRefGoogle Scholar
  2. Bouchut F, Fernandez–Nieto ED, Mangeney A, et al. (2016) A twophase two–layer model for fluidized granular flows with dilatancy effects. Journal of Fluid Mechanics 801: 166–221. CrossRefGoogle Scholar
  3. De Vita P, Reichenbach P, Bathurst J, et al. (1998) Rainfall–triggered landslides: a reference list. Environmental Geology 35(2–3): 219–233. CrossRefGoogle Scholar
  4. Evans SG, Hungr O, Clague JJ (2001) Dynamics of the 1984 rock avalanche and associated distal debris flow on Mount Cayley, British Columbia, Canada; implications for landslide hazard assessment on dissected volcanoes. Engineering Geology 61(1): 29–51. CrossRefGoogle Scholar
  5. Gabet EJ, Mudd SM (2006) The mobilization of debris flows from shallow landslides. Geomorphology 74(1–4): 207–218. CrossRefGoogle Scholar
  6. Gao Y, Yin YP, Li B, et al. (2016) Investigation and dynamic analysis of the long runout catastrophic landslide at the Shenzhen landfill on December 20, 2015, in Guangdong, China. Environmental Earth Sciences 76(1): 13. CrossRefGoogle Scholar
  7. George DL, Iverson RM (2011) A two–phase debris–flow model that includes coupled evolution of volume fractions, granular dilatancy, and pore–fluid pressure. In: Genevois R, Hamilton DL, Prestininzi, A (Eds.), Proceedings of the 5th International Conference on Debris Flow Hazards Mitigation, 14–17 June, 2011. Padova, Italy. Italian Journal of Engineering Geology and Environment pp. 415–424.
  8. George DL, Iverson RM (2014) A depth–averaged debris–flow model that includes the effects of evolving dilatancy. II. Numerical predictions and experimental tests. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 470(2170): 20130820–20130820. CrossRefGoogle Scholar
  9. Hu W, Scaringi G, Xu Q, et al. (2017) Sensitivity of the initiation and runout of flowslides in loose granular deposits to the content of small particles: An insight from flume tests. Engineering Geology 231: 34–44. CrossRefGoogle Scholar
  10. Hungr O (1995) A model for the runout analysis of rapid flow slides, debris flows, and avalanches. Canadian Geotechnical Journal 32(4): 610–623. CrossRefGoogle Scholar
  11. Hungr O (2009) Numerical modelling of the motion of rapid, flowlike landslides for hazard assessment. KSCE Journal of Civil Engineering 13(4): 281–287. CrossRefGoogle Scholar
  12. Hunter G, Fell R (2003) Travel distance angle for “rapid” landslides in constructed and natural soil slopes. Canadian Geotechnical Journal 40(6): 1123–1141. CrossRefGoogle Scholar
  13. Hutter K, Siegel M, Savage SB, et al. (1993) Two–dimensional spreading of a granular avalanche down an inclined plane Part I. theory. Acta Mechanica 100(1–2): 37–68. CrossRefGoogle Scholar
  14. Iverson RM (1997) The physics of debris flows. Reviews of Geophysics 35(3): 245–296. CrossRefGoogle Scholar
  15. Iverson RM (2000) Landslide triggering by rain infiltration. Water Resources Research 36(7): 1897–1910. CrossRefGoogle Scholar
  16. Iverson RM (2005) Regulation of landslide motion by dilatancy and pore pressure feedback. Journal of Geophysical Research 110(F2).
  17. Iverson RM, George DL (2014) A depth–averaged debris–flow model that includes the effects of evolving dilatancy. I. Physical basis. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 470(2170): 20130819. CrossRefGoogle Scholar
  18. Iverson RM, George DL (2016) Modelling landslide liquefaction, mobility bifurcation and the dynamics of the 2014 Oso disaster. Géotechnique 66(3): 175–187. CrossRefGoogle Scholar
  19. Iverson RM, Logan M, LaHusen RG, et al. (2010) The perfect debris flow? Aggregated results from 28 large–scale experiments. Journal of Geophysical Research: Earth Surface 115(F03005). Google Scholar
  20. Iverson RM, Reid ME, LaHusen RG (1997) Debris–flow mobilization from landslides. Annual Review of Earth and Planetary Sciences 25(1): 85–138. CrossRefGoogle Scholar
  21. Iverson RM, Reid ME, Logan M, et al. (2011) Positive feedback and momentum growth during debris–flow entrainment of wet bed sediment. Nature Geoscience 4(2): 116–121. CrossRefGoogle Scholar
  22. Kaitna R, Dietrich WE, Hsu L (2014) Surface slopes, velocity profiles and fluid pressure in coarse–grained debris flows saturated with water and mud. Journal of Fluid Mechanics 741: 377–403. CrossRefGoogle Scholar
  23. Kaitna R, Palucis MC, Yohannes B, et al. (2016) Effects of coarse grain size distribution and fine particle content on pore fluid pressure and shear behavior in experimental debris flows. Journal of Geophysical Research: Earth Surface 121(2): 415–441. Google Scholar
  24. Legros F (2002) The mobility of long–runout landslides. Engineering Geology 63(3–4): 301–331. CrossRefGoogle Scholar
  25. Leveque RJ (2002) Finite volume methods for hyperbolic problems. Cambridge University PressCrossRefGoogle Scholar
  26. Major JJ, Iverson RM (1999) Debris–flow deposition: Effects of pore–fluid pressure and friction concentrated at flow margins. Geological Society of America Bulletin 111(10): 1424–1434.<1424:DFDEOP>2.3.CO;2 CrossRefGoogle Scholar
  27. Matsushi Y, Hattanji T, Matsukura Y (2006) Mechanisms of shallow landslides on soil–mantled hillslopes with permeable and impermeable bedrocks in the Boso Peninsula, Japan. Geomorphology 76(1–2): 92–108. CrossRefGoogle Scholar
  28. Medina V, Hürlimann M, Bateman A (2008) Application of FLATModel, a 2D finite volume code, to debris flows in the northeastern part of the Iberian Peninsula. Landslides 5(1): 127–142. CrossRefGoogle Scholar
  29. Okada Y, Sassa K, Fukuoka H (2000) Liquefaction and the steady state of weathered granitic sands obtained by undrained ring shear tests: a fundamental study of the mechanism of liquidized landslides. Journal of Natural Disaster Science 22(2): 75–85. CrossRefGoogle Scholar
  30. Ouyang CJ, Zhao W, He SM, et al. (2017) Numerical modeling and dynamic analysis of the 2017 Xinmo landslide in Maoxian County, China. Journal of Mountain Science 14(9): 1701–1711. CrossRefGoogle Scholar
  31. Ouyang CJ, He SM, Xu Q, et al. (2013) A MacCormack–TVD finite difference method to simulate the mass flow in mountainous terrain with variable computational domain. Computers & Geosciences 52: 1–10. CrossRefGoogle Scholar
  32. Ouyang CJ, Zhou K, Xu Q, et al. (2016) Dynamic analysis and numerical modeling of the 2015 catastrophic landslide of the construction waste landfill at Guangming, Shenzhen, China. Landslides 14(2): 705–718. CrossRefGoogle Scholar
  33. Pailha M, Pouliquen O (2009) A two–phase flow description of the initiation of underwater granular avalanches. Journal of Fluid Mechanics 633: 115–135. CrossRefGoogle Scholar
  34. Pirulli M, Bristeau MO, Mangeney A, et al. (2007) The effect of the earth pressure coefficients on the runout of granular material. Environmental Modelling & Software 22(10): 1437–1454. CrossRefGoogle Scholar
  35. Pudasaini SP (2012) A general two–phase debris flow model. Journal of Geophysical Research 117(F3).
  36. Reynolds O (1885) On the dilatancy of media composed of rigid particles in contact. With experimental illustrations. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science 20(127):469–481Google Scholar
  37. Roux S, Radjai F (1998) Texture–dependent rigid–plastic behavior. In: Physics of dry granular media. Springer, Dordrecht. pp. 229–23.CrossRefGoogle Scholar
  38. State Administration of Work Safety (2016) The Investigation report of “12·20” extremely large accident of landfill landslide at Guangming new district of Shenzhen, Guangdong. Available online at:, accessed on 2017-03-0.Google Scholar
  39. Sassa K (1998) Mechanisms of landslide triggered debris flows. In: Environmental forest science, vol 54. Springer, Dordrecht, pp 499–518. CrossRefGoogle Scholar
  40. Sassa K (2002) Mechanism of rapid and long traveling flow phenomena in granular soils. In: Proceedings of the UNESCO/IGCP International Symposium on Landslide Mitigation and Protection of Cultural and Natural Heritage, Kyoto, Japan. pp 21–25.Google Scholar
  41. Savage SB, Hutter K (1989) The motion of a finite mass of granular material down a rough incline. Journal of fluid mechanics 199: 177–215. CrossRefGoogle Scholar
  42. Schaeffer DG, Iverson RM (2008) Steady and intermittent slipping in a model of landslide motion regulated by pore–pressure feedback. SIAM Journal on Applied Mathematics 69(3): 769–786. CrossRefGoogle Scholar
  43. Scheidegger AE (1973) On the prediction of the reach and velocity of catastrophic landslides. Rock Mechanics and Rock Engineering 5(4):231–236.CrossRefGoogle Scholar
  44. Scheidl C, Rickenmann D (2009) Empirical prediction of debrisflow mobility and deposition on fans. Earth Surface Processes and Landforms: 35(2): 157–173. Google Scholar
  45. Schuster RL, Highland LM (2007) The Third Hans Cloos Lecture. Urban landslides: socioeconomic impacts and overview of mitigative strategies. Bulletin of Engineering Geology and the Environment 66(1): 1–27. Google Scholar
  46. Terzaghi K (1944) Theoretical soil mechanics. Chapman And Hali, Limited John Wiler And Sons, Inc., New York.Google Scholar
  47. Wang G, Sassa K (2003) Pore–pressure generation and movement of rainfall–induced landslides: effects of grain size and fine–particle content. Engineering Geology 69(1): 109–125. CrossRefGoogle Scholar
  48. Xu Q, Peng D, Li W, et al. (2016) The catastrophic landfill flowslide at Hongao dumpsite on December 20, 2015 in Shenzhen, China. Natural Hazards and Earth System Sciences 2016: 1–19. Google Scholar
  49. Yin YP, Li B, Wang W, et al. (2016) Mechanism of the December 2015 Catastrophic Landslide at the Shenzhen Landfill and Controlling Geotechnical Risks of Urbanization. Engineering 2(2): 230–249. CrossRefGoogle Scholar

Copyright information

© Science Press, Institute of Mountain Hazards and Environment, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengduChina
  2. 2.Key Laboratory of Mountain Surface Process and HazardsChinese Academy of SciencesChengduChina
  3. 3.University of Chinese Academy of SciencesBeijingChina
  4. 4.Anhui University of Science & TechnologyHuainanChina

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