Frontiers of Earth Science

, Volume 10, Issue 4, pp 740–750 | Cite as

Newmark displacement model for landslides induced by the 2013 Ms 7.0 Lushan earthquake, China

  • Renmao YuanEmail author
  • Qinghai Deng
  • Dickson Cunningham
  • Zhujun Han
  • Dongli Zhang
  • Bingliang Zhang
Research Article


Predicting approximate earthquake-induced landslide displacements is helpful for assessing earthquake hazards and designing slopes to withstand future earthquake shaking. In this work, the basic methodology outlined by Jibson (1993) is applied to derive the Newmark displacement of landslides based on strong ground-motion recordings during the 2013 Lushan Ms 7.0 earthquake. By analyzing the relationships between Arias intensity, Newmark displacement, and critical acceleration of the Lushan earthquake, formulas of the Jibson93 and its modified models are shown to be applicable to the Lushan earthquake dataset. Different empirical equations with new fitting coefficients for estimating Newmark displacement are then developed for comparative analysis. The results indicate that a modified model has a better goodness of fit and a smaller estimation error for the Jibson93 formula. It indicates that the modified model may be more reasonable for the dataset of the Lushan earthquake. The analysis of results also suggests that a global equation is not ideally suited to directly estimate the Newmark displacements of landslides induced by one specific earthquake. Rather it is empirically better to perform a new multivariate regression analysis to derive new coefficients for the global equation using the dataset of the specific earthquake. The results presented in this paper can be applied to a future co-seismic landslide hazard assessment to inform reconstruction efforts in the area affected by the 2013 Lushan Ms 7.0 earthquake, and for future disaster prevention and mitigation.


Newmark displacement of landslide Arias intensity critical acceleration empirical relationship the Lushan Ms 7.0 earthquake 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Ambraseys N N, Menu J M (1988). Earthquake-induced ground displacements. Earthquake Eng Struct Dynam, 16(7): 985–1006CrossRefGoogle Scholar
  2. Arias A (1970). A measure of earthquake intensity. In: Hansen R J, ed. Seismic Design for Nuclear Power Plants. Cambridge: Massachusetts Institute of Technology Press, 438–483Google Scholar
  3. Bray J D, Rathje E M (1998). Earthquake-induced displacements of solid-waste landfills. Journal of Geotechnical and Geoenvironmental Engineering, 124(3): 242–253CrossRefGoogle Scholar
  4. Chen X L, Yu L, Wang M M, Li J Y (2013). Brief communication: landslides triggered by the Ms = 7.0 Lushan earthquake, China. Nat Hazards Earth Syst Sci, 1(4): 3891–3918CrossRefGoogle Scholar
  5. Dai F C, Xu C, Yao X, Xu L, Tu X B, Gong Q M (2010). Spatial distribution of landslides triggered by the 2008 Ms 8.0 Wenchuan earthquake, China. J Asian Earth Sci, doi: 10.1016/j.jseaes.2010.04.010Google Scholar
  6. Del Gaudio V, Pierri P, Wasowski J (2003). An approach to timeprobabilistic evaluation of seismically induced landslide hazard. Bull Seismol Soc Am, 93(2): 557–569CrossRefGoogle Scholar
  7. Haneberg W C (2006). Effects of digital elevation model errors on spatially distributed seismic slope stability calculations: an example from Seattle, Washington. Environ Eng Geosci, 12(3): 247–260CrossRefGoogle Scholar
  8. Hsieh S Y, Lee C T (2011). Empirical estimation of the Newmark displacement from the Arias intensity and critical acceleration. Eng Geol, 122(1-2): 34–42CrossRefGoogle Scholar
  9. Jibson R W (1993). Predicting earthquake-induced landslide displacements using Newmark’s sliding block analysis. Transp Res Rec, 1411: 9–17Google Scholar
  10. Jibson R W (2007). Regression models for estimating coseismic landslide displacement. Eng Geol, 91(2-4): 209–218CrossRefGoogle Scholar
  11. Jibson R W, Harp E L, Michael J M (1998). A method for producing digital probabilistic seismic landslide hazard maps: an example from the Los Angeles, California area. US Geological Survey Open-File Report 98–113, 17Google Scholar
  12. Jibson R W, Harp E L, Michael J M (2000). A method for producing digital probabilistic seismic landslide hazard maps. Eng Geol, 58(3-4): 271–289CrossRefGoogle Scholar
  13. Jibson R W, Keefer D K (1993). Analysis of the seismic origin of landslides: examples from the New Madrid seismic zone. Geol Soc Am Bull, 105(4): 521–536CrossRefGoogle Scholar
  14. Keefer D K, Wartman J, Ochoa C N, Rodriguez-Marek A, Wieczorek G F (2006). Landslides caused by the M 7.6 Tecomán, Mexico earthquake of January 21, 2003. Eng Geol, 86(2-3): 183–197CrossRefGoogle Scholar
  15. Newmark N M (1965). Effects of earthquakes on dams and embankments. Geotechnique, 15(2): 139–160CrossRefGoogle Scholar
  16. Pradel D, Smith P M, Stewart J P, Raad G (2005). Case history of landslide movement during the Northridge earthquake. J Geotech Eng ASCE, 131(11): 1360–1369CrossRefGoogle Scholar
  17. Sarma S K (1981). Seismic displacement analysis of earth dams. J Geotech Eng ASCE, 107: 1735–1739Google Scholar
  18. Saygili G, Rathje E M (2008). Empirical predictive models for earthquake-induced sliding displacements of slopes. J Geotech Eng ASCE, 134(6): 790–803CrossRefGoogle Scholar
  19. Wilson R C, Keefer D K (1983). Dynamic analysis of a slope failure from the 6 August 1979 Coyote Lake, California, earthquake. Bull Seismol Soc Am, 73: 863–877Google Scholar
  20. Xu XW, Wen X Z, Han Z J, Chen G H, Li C Y, Zheng WJ, Zhnag S M, Ren Z Q, Xu C, Tan X B, Wei Z Y, Wang M M, Ren J J, He Z T, Liang M J (2013). Lushan Ms 7.0 earthquake: a blind reserve-fault event. Chin Sci Bull, 58(28-29): 3437–3443CrossRefGoogle Scholar
  21. Yin Y P (2009). Features of landslides triggered by the Wenchuan Earthquake, J Eng Geol, 17: 29–38 (in Chinese)Google Scholar

Copyright information

© Higher Education Press and Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Renmao Yuan
    • 1
    Email author
  • Qinghai Deng
    • 2
  • Dickson Cunningham
    • 3
  • Zhujun Han
    • 1
  • Dongli Zhang
    • 1
  • Bingliang Zhang
    • 1
  1. 1.Key Laboratory of Active Tectonics and Volcano, Institute of GeologyChina Earthquake AdministrationBeijingChina
  2. 2.College of Earth Science and EngineeringShandong University of Science and TechnologyQingdaoChina
  3. 3.Department of Environmental Earth ScienceEastern Connecticut State UniversityConnecticutUSA

Personalised recommendations