Skip to main content
SpringerLink
Log in

Ground Based Real Time Monitoring System Using Wireless Instrumentation for Landslide Prediction

  • Chapter
  • First Online:
Landslides: Theory, Practice and Modelling

Part of the book series: Advances in Natural and Technological Hazards Research ((NTHR,volume 50))

Abstract

Despite of our increasing knowledge on the subject, the damage tolls due to landslides are on rise during monsoon in hilly terrain. Hence, landslide prediction on temporal scale is a viable option for risk reduction. Prediction of shallow landslides developing rainfall thresholds using information on landslide occurrences and precipitation will be a cost effective risk reduction measure and may be applicable at a regional/catchment/district/tehsil/village/road corridor level in hilly terrain. Further, the installation of a real-time monitoring system can also be an alternate effective risk mitigation measure for perennial severe landslides and will be useful for community and traffic control on roads and railway tracks in hilly terrain. A Landslide Observatory with wireless instrumentation for real time monitoring of ground deformation and hydrologic parameters has been established at Pakhi Landslide in Garhwal Himalayas, India. The measurement sensors include in-place inclinometers (IPI), piezometers, wire-line extensometers and an automatic weather station (AWS). The real time data is being monitored to establish warning thresholds. The annual cumulative rainfall during 2015 was 1388 mm with cumulative monsoon period (June to September 2015) rainfall of 825 mm. At the crown of landslide beyond main scarp, there is negligible displacement being the stable part. Within the main body of the landslide, it could be inferred that the colluvium, greatly weathered bedrock and their interface experience somehow greater extent of movement at different depths in comparison to the interface between greatly weathered bedrock and unweathered bedrock. A correlation between higher intensity rainfall events and displacement pattern across the inclinometer sensors is also witnessed. However, these inferences can only be established with further data analysis of later periods. The principal aim of this chapter is to discuss the processes involved in establishment of a ground based real time monitoring system for landslides in hilly regions, in particular Indian Himalayas. Apart from establishing a landslide observatory in one of the severe landslide, the data acquisition and analysis for one monsoon season is also discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 119.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 159.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Finlay PJ, Fell R, Maguire PK (1997) The relationship between the probability of landslide occurrence and rainfall. Can Geotech J 34(6):811–824

    Article  Google Scholar 

  2. Ortigao B, Justi MG (2004) Rio-Watch: the Rio de Janeiro landslide alarm system. Geotech News 22(3):28–31

    Google Scholar 

  3. Wilson RC (2005) The rise and fall of debris-flow warning system for the San Francisco Bay region, California. In: Glade T, Anderson M, Crozier MJ (eds) Landslide hazard and risk. Wiley, West Sussex, pp 493–516

    Google Scholar 

  4. Chleborad AF, Baum RL, Godt JP (2006) Rainfall thresholds for forecasting landslides in the Seattle, Washington, Area - exceedance and probability. US Geol Surv Open-File Report:2006–1064

    Google Scholar 

  5. Aleotti P (2004) A warning system for rainfall-induced shallow failures. Eng Geol 73(3–4):247–265

    Article  Google Scholar 

  6. Chien-Yuan C, Tien-Chien C, Fan-Chieh Y, Wen-Hui Y, Chun-Chieh T (2005) Rainfall duration and debris-flow initiated studies for real-time monitoring. Environ Geol 47:715–724

    Article  Google Scholar 

  7. Schmidt J, Turek G, Clark M, Uddstrom M (2007) Real-time forecasting of shallow, rainfall-triggered landslides in New Zealand. Geophys Res Abstr 9:5778

    Google Scholar 

  8. Keefer DK, Wilson RC, Mark RK, Brabb EE, Brown WM, Ellen SD, Harp EL, Wieczorek GF, Alger CS, Zatkin RS (1987) Real-time landslide warning during heavy rainfall. Science 238(4829):921–925

    Article  Google Scholar 

  9. NOAA-USGS Debris Flow Task Force (2005) NOAAUSGS debris-flow warning system—final report. U.S. Geological Survey Circular 1283

    Google Scholar 

  10. Reid ME, LaHusen RL (1998) Real-time monitoring of active landsides along Highway 50, El Dorado County. Calif Geol 51(3):17–20

    Google Scholar 

  11. Baum RL, Godt JP, Harp EL, McKenna JW, McMullen SR (2005) Early warning of landslides for rail traffic between Seattle and Everett, Washington, USA. Proceedings of 2005 International Conference on Landslide Risk Management, A.A. Balkema, New York, pp 731–740

    Google Scholar 

  12. Angeli MG, Gasparetto P, Menotti RM, Pasuto A, Silvano S (1994) A system of monitoring and warning in a complex landslide in northeastern Italy. Landslide News 8:12–15

    Google Scholar 

  13. Berti M, Genevois R, LaHusen RL, Simoni A, Tecca PR (2000) Debris flow monitoring in the Acquabona watershed on the Dolomites (Italian Alps). Phys Chem Earth Part B Hydrol Oceans Atmos 26(9):707–715

    Article  Google Scholar 

  14. Husaini O, Ratnasamy M (2001) An early warning system for active landslides. Quar J Eng Geol Hydrogeol 34:299–305

    Article  Google Scholar 

  15. Froese CR, Moreno F (2007) Turtle Mountain Field Laboratory (TMFL): Part 1—overview and activities.: In: Schaefer VR, Schuster RL Turner AK (eds) , Conference presentations: 1st North American Landslide Conference, AEG Special Publication 23. Association of Engineering Geologists, Vail, pp 971–980

    Google Scholar 

  16. Frigerio S, Schenato L, Bossi G, Cavalli M, Crema S, Mantovani M, Marcato G, Pasuto A (2014) Landslide monitoring with an integrated platform: methodology, design and case study. Rend. Online Societa Geologica Italiana 30:24–27

    Article  Google Scholar 

  17. Malet JP, Maquaire O, Calais E (2002) The use of global positioning system techniques for the continuous monitoring of l and slides: application to the Super-Sauze earthflow (Alpes-de-Haute-Provence, France). Geomorphology 43:33–54

    Article  Google Scholar 

  18. Corsini A, Pasuto A, Soldati M, Zannoni A (2005) Field monitoring of the Corvara landslide (Dolomites, Italy) and its relevance for hazard assessment. Geomorphology 66:149–165

    Article  Google Scholar 

  19. Garcia A, Hordt A, Fabian M (2010) Landslide monitoring with high resolution tilt measurements at the Dollendorfer Hardt landslide, Germany. Geomorphology 120:16–25

    Article  Google Scholar 

  20. Brückl E, Brunner FK, Lang E, Mertl S, Müller M, Stary U (2013) The Gradenbach observatory-monitoring deep-seated gravitational slope deformation by geodetic, hydrological, and seismological methods. Landslides 10:815–829

    Article  Google Scholar 

  21. Dixon N, Spriggs MP, Smith A, Meldrum P, Haslam E (2015) Quantification of reactivated landslide behaviour using acoustic emission monitoring. Landslides 12(3):549–560

    Article  Google Scholar 

  22. Kumsar H, Aydan O, Tano H, Celik SB, Ulusay R (2016) An integrated geomechanical investigation, multi-parameter monitoring and analyses of Babadag-Gundogdu Creep-like Landslide. Rock Mech Rock Eng 49(6):2277–2299

    Article  Google Scholar 

  23. Macciotta R, Hendry M, Martin CD (2016) Developing an early warning system for a very slow landslide based on displacement monitoring. Nat Hazards 81(2):887–907

    Article  Google Scholar 

  24. Uhlemann S, Smith A, Chambers J, Dixon N, Dijkstra T, Haslam E, Meldrum P, Merritt A, Gunn D, Mackay J (2016) Assessment of ground-based monitoring techniques applied to landslide investigations. Geomorphology 253:438–451

    Article  Google Scholar 

  25. Teza G, Galgaro A, Zaltron N, Genevois R (2007) Terrestrial laser scanner to detect landslide displacement fields: a new approach. Int J Remote Sens 28(16):3425–3446

    Article  Google Scholar 

  26. Monserrat O, Crosetto M (2008) Deformation measurement using terrestrial laser scanning data and least squares 3D surface matching. ISPRS J Photogramm Remote Sens 63:142–154

    Article  Google Scholar 

  27. Abellán A, Jaboyedoff M, Oppikofer T, Vilaplana JM (2009) Detection of millimetric deformation using a terrestrial laser scanner: experiment and application to a rockfall event. Nat Hazards Earth Syst Sci 9:365–372

    Article  Google Scholar 

  28. Barla G, Antolini F, Barla M, Mensi E, Piovano G (2010) Monitoring of the Beauregard landslide (Aosta Valley, Italy) using advanced and conventional techniques. Eng Geol 116:218–235

    Article  Google Scholar 

  29. Casagli N, Catani F, Del Ventisette C, Luzi G (2010) Monitoring, prediction, and early warning using ground-based radar interferometry. Landslides 7(3):291–301

    Article  Google Scholar 

  30. Intrieri E, Gigli G, Mugnai F, Fanti R, Casagli N (2012) Design and implementation of a landslide early warning system. Eng Geol 147–148:124–136

    Article  Google Scholar 

  31. Barla M, Antolini F (2016) An integrated methodology for landslides early warning systems. Landslides 13(2):215–228

    Article  Google Scholar 

  32. Mittal SK, Singh M, Kapur P, Sharma BK, Shamshi MA (2008) Design and development of instrumentation network for landslide monitoring and issue an early warning. J Sci Ind Res 67:361–365

    Google Scholar 

  33. Chaturvedi P, Jaiswal B, Sharma S, Tyagi N (2014) Instrumentation Based Dynamics Study of Tangni Landslide near Chamoli, Uttrakhand. Int J Res Advent Technol 2(10):127–132

    Google Scholar 

  34. Chaturvedi P, Srivastava S, Kaur B (2016) Landslide Early Warning System Development using Statistical Analysis of Sensors' Data at Tangni Landslide, Uttarakhand, India. 6th International Conference on “Soft Computing for Problem Solving” (SocProS 2016), Patiala, India, December 2016

    Google Scholar 

  35. Mishra PK, Chaturvedi P, Tyagi N, Joglekar PN (2015) Real time landslide monitoring and estimation of its movement velocity. IEEE Int Conf on Research in Computational Intelligence and Communication Networks (ICRCICN), Kolkata, Nov 2015, doi:https://doi.org/10.1109/ICRCICN.2015.7434260

  36. Ramesh MV, Vasudevan N (2012) The deployment of deep-earth sensor probes for landslide detection. Landslides 9(4):457–474

    Article  Google Scholar 

  37. Ramesh MV (2014) Design, development, and deployment of a wireless sensor network for detection of landslides. Ad Hoc Netw 13:2–18

    Article  Google Scholar 

  38. Kanungo DP, Pain A, Sharma S (2013a) Stability assessment of a potential debris slide in Garhwal Himalayas, India. Indian Landslides 6(2):9–20

    Google Scholar 

  39. Kanungo DP, Pain A, Sharma S (2013b) Finite element modeling approach to assess the stability of debris and rock slopes: a case study from the Indian Himalayas. Nat Hazards 69:1–24

    Article  Google Scholar 

  40. Krishnan MS (1982) Geology of India and Burma, 6th edn. CBS Publishers and Distributors, Delhi, 536p

    Google Scholar 

  41. Reid M E, Baum R L, LaHusen R G, Ellis W L, (2008) Landslides and Engineered Slopes. Chen et al.. Taylor & Francis Group, London, (ISBN 978-0-415-41196-7) 179–191

    Google Scholar 

  42. Dunnicliff J (1993) Geotechnical instrumentation for monitoring field performance. Wiley, New York

    Google Scholar 

  43. Mikkelsen PE (1996) Field Instrumentation. In: Turner AK, Schuster RL (eds) Landslides: investigation and mitigation, Special report 247. National Academy Press, Washington, DC, pp 278–316

    Google Scholar 

Download references

Acknowledgments

Authors are grateful to the Director, CSIR-Central Building Research Institute, Roorkee, Uttarakhand (India) for granting permission to publish this paper.

Author information

Authors and Affiliations

  1. Geotechnical Engineering Division, CSIR-Central Building Research Institute, Roorkee, India

    D. P. Kanungo

Authors
  1. D. P. Kanungo
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Earth Sciences, Indian Institute of Technology Roorkee, Roorkee, India

    S.P. Pradhan

  2. Department of Earth Sciences, Indian Institute of Technology Bombay, Mumbai, Maharashtra, India

    V. Vishal

  3. Department of Earth Sciences, Indian Institute of Technology Bombay, Mumbai, India

    T.N. Singh

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Kanungo, D.P. (2019). Ground Based Real Time Monitoring System Using Wireless Instrumentation for Landslide Prediction. In: Pradhan, S., Vishal, V., Singh, T. (eds) Landslides: Theory, Practice and Modelling. Advances in Natural and Technological Hazards Research, vol 50. Springer, Cham. https://doi.org/10.1007/978-3-319-77377-3_6

Download citation

Publish with us

Policies and ethics

Search

Navigation