Advertisement

Environmental Earth Sciences

, 78:685 | Cite as

Innovative consideration of a directional appraisal parameter as destabilized criterion of the colluvial landslide

  • He KeqiangEmail author
  • Liu Honghua
  • Guo Lu
  • Yuan Xilong
  • Zhang Peng
  • Cui Xianli
Original Article
  • 18 Downloads

Abstract

As the instability criteria of the singular dimension displacement of a landslide are limited and insufficient, a new appraisal parameter, the vertical displacement direction rate is considered in landslide stability model in this paper. Then, the displacement directional rate variation at different evolutional stages of landslide stability and its significance in landslide forecasting are systematic analyzed. On the basis of the different evolutional rules of the vertical displacement directional rate in the different deformation stages, the destabilized criterion of this kind of parameter is established in terms of the principle of statistics. Furthermore, according to the destabilized criterion, a calculation and evaluation of the stability of Xintan landslide is carried out by means of the appraisal parameter of the vertical displacement direction rate. The result of analysis is basically consistent with the practical deforming law of the landslide. The result above indicates that the vertical displacement direction rate is an effective appraisal parameter serving as an essential and stable criterion for the stability evaluation of a slope. Therefore, this directional appraisal parameter is of very special significance and also suitable and effective in the prediction of landslides.

Keywords

Colluvial landslide Vertical displacement direction rate Stability prediction Xintan landslide 

Notes

Acknowledgements

The study was supported by Natural Science Foundation of China (41372297), the Open Found of Tsingtao Geological Engineering Survey Institute (2019-QDDZYKF02), the Open Found of the Key Laboratory of Geological Hazards on Three Gorges Reservoir Area (China Three Gorges University), Ministry of Education (2017KDZ03), and the Cooperative Innovation Center of Engineering Construction and Safety in Shandong Blue Economic Zone.

References

  1. Baker R (2003) Inter-relations between experimental and computational aspects of slope stability analysis. Int J Numer Anal Methods Geomech 27(5):379–401CrossRefGoogle Scholar
  2. Dario T, Giuseppe A, Nicola C et al (2005) On the use of ground-based SAR interferometry for slope failure early warning: the cortenova rock slide (Italy). Landslides, pp 337–342Google Scholar
  3. Er L, Xu Y, Dai SL (2010) Slope engineering (M). Science press, Beijing, pp 64–85 (in Chinese) Google 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. Eng Geol 61:29–51CrossRefGoogle Scholar
  5. Fukuzono T (1990) Recent studies on time prediction of slope failure. Landslide News 115(5):51–52Google Scholar
  6. He KQ, Yang JB (1996) The forecast and prevention of the accumulation formation landslide (M). Seismic Press, Beijing, pp 51–52 (in Chinese) Google Scholar
  7. Huang JA, Wang SJ (1984) Regression analysis of the properties and stress field of rock mass. Scientia Geologica Sinica 2:173–185 (in Chinese) Google Scholar
  8. Hungr O, Leroueil S, Picarelli L (2014) The Varnes classification of landslide types, un update. Landslides 11(2):167–194CrossRefGoogle Scholar
  9. Li XZ, Xu Q (2003) Models and criteria of landslide prediction. J Catastrophology 18(4):71–78 (in Chinese) Google Scholar
  10. Mufundirwa A, Fujii Y, Kodama J (2010) A new practical method for prediction of geomechanical failure-time. Int J Rock Mech Min 47(7):1079–1090CrossRefGoogle Scholar
  11. Paolo A, Andrea M, Daniele G et al (2013) ADVICE: a new approach for near-real-time monitoring of surface displacements in landslide hazard scenarios. Sensors 13(7):8285–8302CrossRefGoogle Scholar
  12. Pierre B, Bertrand A, Séverine B et al (2014) The application of an innovative inverse model for understanding and predicting landslide movements. Landslides 11(3):343–355CrossRefGoogle Scholar
  13. Saito M (1965) Forecasting the time occurrence of a slope failure [A]. In: Proceedings of the 6th International Conference on soil Mechanics and Foundation Engineering [C], Montreal, Que. Pergamon Press, Oxford, pp 537–541Google Scholar
  14. Shen JH, Sun BJ, Jin XG et al (2002) Application of displacement monitoring in appraising and forecasting landslide. J Southeast Univ 32(5):814–817 (in Chinese) Google Scholar
  15. Su AJ (1990) On methodology of landslide prognosis. Hydrogeol Eng Geol 5:50–51 (in Chinese) Google Scholar
  16. Tazio S, Paolo F, Alessandro C et al (2005) Survey and monitoring of landslide displacements by means of L-band satellite SAR interferometry. Landslides 2(3):193–201CrossRefGoogle Scholar
  17. Voight B (1988) A method for prediction of volcanic eruption. Nature 332:125–130CrossRefGoogle Scholar
  18. Voight B (1989) A method to describe rate-dependent material failure. Science 243:200–203CrossRefGoogle Scholar
  19. Wang FD (1995) First exploration on features of landslide of shallow accumulation and its relationship with rainfall. Hydrogeol Eng Geol 1:20–23 (in Chinese) Google Scholar
  20. Wang SJ (1996) Research of a dynamic prediction method of displacement of landslide. Chin J Geol Hazard Controlm 4(6):271–275 (in Chinese) Google Scholar
  21. Wang SQ (1999) Monitoring and forecast of the landslides in three Gorge region of the Yangtze River. Geological Press, Beijing, pp 32–84 (in Chinese) Google Scholar
  22. Wang LS, Zhang ZY, Zhan Z et al (1988) On the mechanism of starting, sliding and braking of Xintan landslide in Yangtze Gorge. In: Proceedings of the 5th international symposium on landslides, Lausanne, Switzerland, pp 341–344 (in Chinese) Google Scholar
  23. Wen T, Tang H, Wang Y et al (2017) Landslide displacement prediction using the GA-LSSVM model and time series analysis: a case study of Three Gorges Reservoir, China. Nat Hazard Earth Sys 17(12):1–20CrossRefGoogle Scholar
  24. Xu Q, Zeng YP (2009) Research on acceleration variation characteristics of creep landslide and early-warning prediction indicator of critical sliding. Rock and Soil Mechanics 28(6):1099–1106 (in Chinese) Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • He Keqiang
    • 1
    Email author
  • Liu Honghua
    • 2
  • Guo Lu
    • 1
  • Yuan Xilong
    • 2
  • Zhang Peng
    • 3
  • Cui Xianli
    • 4
  1. 1.Department of Civil EngineeringQingdao University of TechnologyQingdaoChina
  2. 2.Tsingtao Geological Engineering Survey InstituteQingdaoChina
  3. 3.Qingdao Municipal Engineering Design and Research Institute Co., LtdQingdaoChina
  4. 4.Qingdao Vocational and Technical College of Hotel MangementQingdaoChina

Personalised recommendations