Advertisement

Dynamic process of the massive Xinmo landslide, Sichuan (China), from joint seismic signal and morphodynamic analysis

  • Xiuqiang Bai
  • Jihao Jian
  • Siming HeEmail author
  • Wei Liu
Original Paper

Abstract

On 24 June 2017, a massive high-position landslide occurred at Diexi, Maoxian county, Sichuan, China, destroying the village of Xinmo with over 80 fatalities. Based on field surveys and DEM data before and after the landslide, the run-out of the landslide had a horizontal extent of 2400 m and a vertical extent of 1200 m and covered an area of about 1.48 × 106 m2. Based on the pre- and post-landslide profiles, the landslide region can be divided into four zones: source area, erosion area, sliding area, and accumulation area. The volume and area of each zone were calculated from DEM data before and after the landslide. Because of the fragmentation and erosion of the landslide during movement, the landslide volume increased from 2.8 × 106 m3 to 6.4 × 106 m3; the fractional amount of volume expansion due to fragmentation (FF) and entrainment ratio (ER) were 0.033 and 1.23, respectively. The velocity and acceleration of the Xinmo landslide were calculated through the inverted forces from seismic waves. The friction coefficients in each zone of the landslide during movement were also obtained, providing a useful parameter for numerical simulation modeling. An inverse relation was found between the absolute velocity and friction coefficient of each zone, demonstrating the existence of frictional velocity-weakening in massive extensive landslides. Based on frictional velocity-weakening, the steady-state apparent friction μ(U, σ) as a function of absolute slip velocity U and normal pressure σ was also obtained.

Keywords

Xinmo village landslide Morphodynamic Seismic signal Frictional velocity-weakening 

Notes

Acknowledgments

This work was supported as a joint research project by NSFC-ICIMOD (Grant No. 41661144041); the NSFC (Grant No. 41772312); The Key Research and Development Program and The Scientific Support Program of the Science and Technology Department of Sichuan Province of China (Grant No.2017SZ0041; Grant No.2016SZ0067). We are thankful for the DEMs data of the study site provided by Sichuan Geomatics Center and the seismic data and suggestions provided by the Sichuan Earthquake Administration. We also thank the previous reviewers and Dr. A. Lucas for helpful suggestions, which greatly improved the quality of this paper.

References

  1. Allstadt K (2013) Extracting source characteristics and dynamics of the August 2010 Mount Meager landslide from broadband seismograms. J Geophys Res Earth Surf 118(3):1472–1490CrossRefGoogle Scholar
  2. Beyabanaki SAR, Bagtzoglou AC, Liu L (2015) Applying disk-based discontinuous deformation analysis (DDA) to simulate Donghekou landslide triggered by the Wenchuan earthquake. Geomech Geoeng 11(3):177–188CrossRefGoogle Scholar
  3. Chai H, Liu H (1995) Landslide dams induced by diexi earthquake in 1933 and its environmental effect. J Geol Hazard Environ Preserv 6(1):7–17 (in Chinese) Google Scholar
  4. Chen SF et al (1994) Active faulting and block movement associated with large earthquakes in the Min Shan and Longmen Mountains, northeastern Tibetan Plateau. J Geophys Res Solid Earth 99(B12):24025–24038CrossRefGoogle Scholar
  5. Chen TC, Lin ML, Wang KL (2014a) Landslide seismic signal recognition and mobility for an earthquake-induced rockslide in Tsaoling, Taiwan. Eng Geol 171:31–44Google Scholar
  6. Chen Q, Cheng H, Yang Y, Liu G, Liu L (2014b) Quantification of mass wasting volume associated with the giant landslide Daguangbao induced by the 2008 Wenchuan earthquake from persistent scatterer InSAR. Remote Sens Environ 152:125–135Google Scholar
  7. Chigira M (2009) September 2005 rain-induced catastrophic rockslides on slopes affected by deep-seated gravitational deformations, Kyushu, southern Japan. Eng Geol 108(1–2):1–15CrossRefGoogle Scholar
  8. Chigira M et al (2010) Landslides induced by the 2008 Wenchuan earthquake, Sichuan, China. Geomorphology 118(3–4):225–238CrossRefGoogle Scholar
  9. Cigna F, Bianchini S, Casagli N (2012) How to assess landslide activity and intensity with Persistent Scatterer Interferometry (PSI): the PSI-based matrix approach. Landslides 10(3):267–283CrossRefGoogle Scholar
  10. Deparis J et al (2008) Analysis of Rock-Fall and Rock-Fall Avalanche Seismograms in the French Alps. Bull Seismol Soc Am 98(4):1781–1796CrossRefGoogle Scholar
  11. Dong JJ, Yang CM, Yu WL, Lee CT, Miyamoto Y, Shimamoto T (2013) Velocity-displacement dependent friction coefficient and the kinematics of giant landslide. Earthquake-Induced Landslides. Springer, Berlin.  https://doi.org/10.1007/978-3-642-32238-9_41
  12. Dong JJ, Tsao CC, Yang CM, Wu WJ, Lee CT, Lin M L et al (2014) The geometric characteristics and initiation mechanisms of the earthquake-triggered Daguangbao landslide. In: Hazarika H, Kazama M, Lee W (eds) Geotechnical hazards from large earthquakes and heavy rainfalls. Springer, Tokyo.  https://doi.org/10.1007/978-4-431-56205-4_19
  13. Dong S, Zhang Y, Wu Z, Yang N, Ma Y, Shi W et al (2008) Surface rupture and co-seismic displacement produced by the Ms 8.0 Wenchuan earthquake of May 12, 2008, Sichuan, China: eastwards growth of the Qinghai-Tibet plateau. Acta Geol Sin 82(5):938–948 (in Chinese) Google Scholar
  14. Ekström G, Stark C.(2013) Simple scaling of catastrophic landslide dynamics. Science 339(6126):1416–1419. http://www.jstor.org/stable/41942420
  15. Gauer P, Dieter I (2004) Possible erosion mechanisms in snow avalanches. Ann Glaciol 38:384–392CrossRefGoogle Scholar
  16. Gong B, Tang C (2017) Slope-slide simulation with discontinuous deformation and displacement analysis. International Journal of Geomechanics 17(5):E4016017CrossRefGoogle Scholar
  17. Guo Y (2004) Influence of normal stress and grain shape on granular friction: results of discrete element simulations. J Geophys Res 109(B12). https://doi.org/10.1029/2004JB003044Google Scholar
  18. Guzzetti F (2000) Landslide fatalities and the evaluation of landslide risk in Italy. Eng Geol 58:89–107CrossRefGoogle Scholar
  19. Hibert C, Ekström G, Stark CP (2017) The relationship between bulk-mass momentum and short-period seismic radiation in catastrophic landslides. J Geophys Res Earth Surf 122(5):1201–1215CrossRefGoogle Scholar
  20. Hungr O, Evans SG (2004) Entrainment of debris in rock avalanches: an analysis of a long run-out mechanism. Geol Soc Am Bull 116(9):1240CrossRefGoogle Scholar
  21. Ingles J et al (2006) Effects of the vertical component of ground shaking on earthquake-induced landslide displacements using generalized Newmark analysis. Eng Geol 86(2–3):134–147CrossRefGoogle Scholar
  22. Irie K, Koyama T, Hamasaki E et al. (2009) DDA simulations for huge landslides in Aratozawa area, Miyagi, Japan caused by Iwate-Miyagi Nairiku earthquake.  https://doi.org/10.3850/9789810844554-0057
  23. Jibson RW (2007) Regression models for estimating coseismic landslide displacement. Eng Geol 91(2–4):209–218CrossRefGoogle Scholar
  24. Jibson RW et al (2004) Landslides Triggered by the 2002 Denali Fault, Alaska, earthquake and the inferred nature of the strong shaking. Earthquake Spectra 20(3):669–691CrossRefGoogle Scholar
  25. Lari S, Frattini P, Crosta GB (2014) A probabilistic approach for landslide hazard analysis. Eng Geol 182:3–14CrossRefGoogle Scholar
  26. Lateltin O et al (2005) Landslide risk management in Switzerland. Landslides 2(4):313–320CrossRefGoogle Scholar
  27. Li Z, Huang X, Xu Q, Yu D, Fan J, Qiao X (2017) Dynamics of the Wulong landslide revealed by broadband seismic records. Earth Planets Space 69(1):27CrossRefGoogle Scholar
  28. Lin C-H (2015) Insight into landslide kinematics from a broadband seismic network. Earth Planets Space 67(1):8CrossRefGoogle Scholar
  29. Lin CH, Kumagai H, Ando M, Shin TC (2010) Detection of landslides and submarine slumps using broadband seismic networks. Geophys Res Lett 37(22):333–345.  https://doi.org/10.1029/2010GL044685 CrossRefGoogle Scholar
  30. Llano-Serna MA, Farias MM, Pedroso DM (2015) An assessment of the material point method for modelling large scale run-out processes in landslides. Landslides 13(5):1057–1066CrossRefGoogle Scholar
  31. Lucas A, Mangeney A, Ampuero JP (2014) Frictional velocity-weakening in landslides on Earth and on other planetary bodies. Nat Commun 5:3417CrossRefGoogle Scholar
  32. McSaveney MJ (2002) Recent rockfalls and rock avalanches in Mount Cook National Park, New Zealand. Geol Soc Am Rev Eng Geol XV:35–70.  https://doi.org/10.1130/REG15-p35 CrossRefGoogle Scholar
  33. Meehan CL, Vahedifard F (2013) Evaluation of simplified methods for predicting earthquake-induced slope displacements in earth dams and embankments. Eng Geol 152(1):180–193CrossRefGoogle Scholar
  34. Nakano M et al (2008) Waveform inversion in the frequency domain for the simultaneous determination of earthquake source mechanism and moment function. Geophys J Int 173(3):1000–1011CrossRefGoogle Scholar
  35. Newmark NM (1965) Effects of earthquakes on dams and embankments. Geothechnique 15(2):139–159CrossRefGoogle Scholar
  36. Numada M, Konagai K, Ito H, Johansson J (2010) Material point method for run-out analysis of earthquake-induced long-traveling soil flows. Env Syst Res 27:227.  https://doi.org/10.11532/proee2003.27.227
  37. Surinach E et al (2005) Seismic detection and characterization of landslides and other mass movements. Nat Hazards Earth Syst Sci 5:791–798CrossRefGoogle Scholar
  38. Tang C-L et al (2012) The mechanism of the 1941 Tsaoling landslide, Taiwan: insight from a 2D discrete element simulation. Environ Earth Sci 70(3):1005–1019CrossRefGoogle Scholar
  39. Vilajosana I et al (2008) Rockfall induced seismic signals: case study in Montserrat, Catalonia. Nat Hazards Earth Syst Sci 8:805–812CrossRefGoogle Scholar
  40. Wakai A, Cai F, Ugai K, Soda T (2015) Numerical simulation for an earthquake-induced catastrophic landslide considering strain-softening characteristics of sensitive clays. In: Lollino G et al (eds) Engineering geology for society and territory, vol 2. Springer, Cham.  https://doi.org/10.1007/978-3-319-09057-3_115 Google Scholar
  41. Wang R (1999) A simple orthonormalization method for stable and efficient computation of Green’s functions. Bull Seismol Soc Am 89(3):733–741 Accession: 029788774 Google Scholar
  42. Wang J, Ward SN, Xiao L (2015) Numerical simulation of the December 4, 2007 landslide-generated tsunami in Chehalis Lake, Canada. Geophys J Int 201(1):372–376CrossRefGoogle Scholar
  43. Wang YF et al (2018) Normal stress-dependent frictional weakening of large rock avalanche basal facies: implications for the rock avalanche volume effect. J Geophys Res Solid Earth.  https://doi.org/10.1002/2018JB015602
  44. Wen B et al (2004) Characteristics of rapid giant landslides in China. Landslides 1(4):247–261CrossRefGoogle Scholar
  45. Yamada M et al (2013) Dynamic landslide processes revealed by broadband seismic records. Geophys Res Lett 40(12):2998–3002CrossRefGoogle Scholar
  46. Yang CM, Chen YR, Dong JJ, Hsu HH, Cheng WB (2015) The normal stress on the slipsurface: a dominating factor on the run-out distance of the sliding rock mass. In: Lollino G et al (eds) Engineering geology for society and territory, vol 2. Springer, Cham.  https://doi.org/10.1007/978-3-319-09057-3_301 Google Scholar
  47. Yang C-M et al (2014) Initiation, movement, and run-out of the giant Tsaoling landslide — what can we learn from a simple rigid block model and a velocity–displacement dependent friction law? Eng Geol 182:158–181CrossRefGoogle Scholar
  48. Yuan RM et al (2014) Mechanism of the Donghekou landslide triggered by the 2008 Wenchuan earthquake revealed by discrete element modeling. Nat Hazards Earth Syst Sci 14(5):1195–1205CrossRefGoogle Scholar
  49. Zhang Y et al (2015) DDA validation of the mobility of earthquake-induced landslides. Eng Geol 194:38–51CrossRefGoogle Scholar
  50. Zou Z et al (2017) Kinetic characteristics of debris flows as exemplified by field investigations and discrete element simulation of the catastrophic Jiweishan rockslide, China. Geomorphology 295:1–15CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Xiuqiang Bai
    • 1
    • 2
    • 3
  • Jihao Jian
    • 4
  • Siming He
    • 1
    • 5
    • 6
    Email author
  • Wei Liu
    • 5
    • 6
  1. 1.CAS Center for Excellence in Tibetan Plateau Earth SciencesBeijingChina
  2. 2.Institute of Tibetan Plateau ResearchChinese Academy of SciencesBeijingChina
  3. 3.University of Chinese Academy of SciencesBeijingChina
  4. 4.College of Environment and Civil EngineeringChengdu University of TechnologyChengduChina
  5. 5.Key Laboratory of Mountain Hazards and Surface ProcessChinese Academy of ScienceChengduChina
  6. 6.Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengduChina

Personalised recommendations