Modelling a Landslide Probability Through Time as a Basis for the Landslide Hazard Forecast System

  • Marko Komac
  • Mateja Jemec Auflič


In the past 20 years, intense short- and long-duration rainfall has triggered numerous shallow landslides worldwide, caused extensive material damage to buildings, infrastructure, and roads, and unfortunately also caused loss of human life. Slovenia was no exception in this regard. But these landslide-related problems could be identified and minimised if the knowledge of the landslide occurrence would be upgraded with the more in-depth knowledge of the relationship between the triggering factors (rainfalls) and landslides. In the frame of the national project Masprem, we aim to develop an automated, online tool for predicting landslide hazard forecast at the national level. This tool will provide an early warning system for landslide events in Slovenia, a regional country that is highly vulnerable to extreme meteorological events and to landslides. A system for landslide hazard forecast will be based on the real-time rainfall data, rainfall thresholds for landslide triggering, and the landslide susceptibility map. The proposed system will inform inhabitants of an increased landslide hazard as a consequence of heavy precipitation that would exceed the landslide triggering values.


Landslide hazard Early warning system Real-time rainfall Slovenia 


  1. Aleotti P (2004) A warning system for rainfall-induced shallow failures. Eng Geol 73:247–265CrossRefGoogle Scholar
  2. ARSO Ministry for Environment and Spatial Planning (2012) Environmental Agency of the Republic of Slovenia. Accessed 20 June 2012
  3. Bubnová RG, Hello P, Béenard P, Geleyn JF (1995) Integration of the fully elastic equations cast in the hydrostatic pressure terrain following coordinate in the framework of the ALADIN NWP system. Mon Wea Rev 123:515–535CrossRefGoogle Scholar
  4. Buchanan P, Savigny KW (1990) Factors controlling debris avalanche initiation. Can Geotech J 27:659–667CrossRefGoogle Scholar
  5. Caine N (1980) The rainfall intensity-duration control of shallow landslides and debris flows. Geogr Ann A 62:23–27. doi: 10.2307/520449 CrossRefGoogle Scholar
  6. CATHALAC (2012) Water centre for the humid tropics of Latin America and the Caribbean. Accessed 25 Aug 2012
  7. Ceglar A, Črepinšek Z, Zupanc V, Kajfež-Bogataj L (2008) A Comparative study of rainfall erosivity for eastern and western Slovenia. Acta Agric Slov 91(2):331–341CrossRefGoogle Scholar
  8. Chleborad AF (2003) Preliminary evaluation of a precipitation threshold for anticipating the occurrence of landslides in the Seattle, Washington, Area, US Geological Survey Open-File Report 03-463Google Scholar
  9. Crosta G (1998) Rationalization of rainfall threshold: an aid to landslide hazard evaluation. Environ Geol 35:131–145CrossRefGoogle Scholar
  10. Crozier MJ (1999) Prediction of rainfall-triggered landslides: a test of the antecedent water status model. Earth Surf Proc Land 24:825–833CrossRefGoogle Scholar
  11. Crozier MJ, Eyles RJ (1980) Assessing the probability of rapid mass movement. In: Technical Groups (eds) Proceedings of 3rd Australia-New Zealand Conference on Geomechanics, vol 6. New Zealand Institution of Engineers, Wellington, pp 247–251Google Scholar
  12. Fukuzono T, Moriwaki H, Inokuchi T, Maki M, Iwanami K, Misumi R, Takami S, Shikoku T (2004) Landslide disaster prediction support system based on Web GIS.
  13. García-Ruiz JM, Martí-Bono C, Lorente A, Beguería S (2003) Geomorphological consequences of frequent and infrequent rainfall and hydrological events in Pyrenees Mountains of Spain. Mitig Adapt Strategies Glob Chang 7:303–320CrossRefGoogle Scholar
  14. Glade T (1998) Establishing the frequency and magnitude of landslide-triggering rainstorm events in New Zealand. Env Geol 35(2):160–174CrossRefGoogle Scholar
  15. Glade T, Crozier MJ, Smith P (2000) Applying probability determination to refine landslide-triggering rainfall thresholds using an empirical ‘‘Antecedent Daily Rainfall Model’’. Pure Appl Geophys 157(6/8):1059–1079. doi: 10.1007/s000240050017 CrossRefGoogle Scholar
  16. Heyerdahl H, Harbitz CB, Domaas U, Sandersen F, Tronstad K, Nowacki F, Engen A, Kjekstad O, De´voli G, Buezo SG, Diaz MR, HernandezW (2003) Rainfall induced lahars in volcanic debris in Nicaragua and El Salvador: practical mitigation. In: Proceedings of international conference on fast slope movements—prediction and prevention for risk mitigation, IC-FSM2003. Patron Pub, Naples, pp 275–282Google Scholar
  17. IDD (2009) The international disaster database— Accessed 3 Sept 2012
  18. Jemec Auflič M, Komac M (2011) Rainfall patterns for shallow landsliding in perialpine Slovenia. Nat Hazards. doi:  10.1007/s11069-011-9882-9
  19. Keefer DK, Wilson RC, Mark RK, Brabb EE, Brown WM III, Ellen SD, Harp EL, Wieczorek GF, Alger CS, Zatkin RS (1987) Real-time landslide warning during heavy rainfall: Science 238:921–925Google Scholar
  20. Kim SK, Hong WP, Kim YM (1992) Prediction of rainfall-triggered landslides in Korea. In: Bell DH (ed) Landslides. Proc. of the sixth Int. Symp. on landslides, vol 2. Christchurch, Balkema, Rotterdam, pp 989–994Google Scholar
  21. Komac M (2005) Rainstorms as a landslide-triggering factor in Slovenia. Geologija 48(2):263–279CrossRefGoogle Scholar
  22. Komac M (2012) Regional landslide susceptibility model using the Monte Carlo approach—the case of Slovenia. Geol Q 56(1):41–54Google Scholar
  23. Komac M, Ribičič M (2006) Landslide susceptibility map of Slovenia at scale 1:250.000. Geologija 49(2):295–309Google Scholar
  24. Mercogliano P, Schiano P, Picarelli L, Olivares L, Catani F, Tofani V, Segoni S, Rossi G (2010) Short term weather forecasting for shallow landslide prediction. In: Malet JP, Glade T, Casagli N (eds) Int. Conf. Mountain Risks: Bringing Science to Society, Firenze, pp 525–530Google Scholar
  25. Ortigao B (2000) Rio‐watch: the Rio de Janeiro landslide watch. MonoSys Guide to Monitoring Quarter 1 2000.
  26. Pasuto A, Silvano S (1998) Rainfall as a triggering factor of shallow mass movements. A case study in the Dolomites, Italy. Environ Geol 35(2–3):184–189Google Scholar
  27. Pristov N, Cedilnik J, Jerman J, Strajnar B (2012) Priprava numerične meteorološke napovedi ALADIN-SI. Vetrnica, pp 17–23Google Scholar
  28. Schmidt J, Turek G, Clark MP, Uddstrom M, Dymond JR (2008) Probabilistic forecasting of shallow, rainfall-triggered landslides. Nat Hazards Earth Syst Sci 8:349–357CrossRefGoogle Scholar
  29. Terlien MTJ (1998) The determination of statistical and deterministic hydrological landslide-triggering thresholds. Environ Geol 35(2–3):124–130CrossRefGoogle Scholar
  30. White ID, Mottershead DN, Harrison J (1996) Environmental Systems, 2nd edn. Chapman & Hall, London, p 616CrossRefGoogle Scholar
  31. Wieczorek GF (1987) Effect of rainfall intensity and duration on debris flows in central Santa Cruz Mountains, California. Geol Soc Am, Rev Eng Geol 7:93–104CrossRefGoogle Scholar
  32. Wilson RC (2000) Climatic variations in rainfall thresholds for debris-flows activity. In: Claps P, Siccardi F (eds) Proceedings 1st Plinius conference on mediterranean storms. Maratea, pp 415–424Google Scholar
  33. Xiaoping L, Junling X, Hesheng L, Gongxian W (1996) Recent development of time prediction for landslide in China. In: Senneset (ed) Landslides. Balkema, RotterdamGoogle Scholar
  34. Zezere JL, Trigo RM, Trig IF (2005) Shallow and deep landslides induced by rainfall in the Lisbon region (Portugal): assessment of relationships with the North Atlantic Oscillation. Nat Hazards Earth Syst Sci 5:331–344CrossRefGoogle Scholar

Copyright information

© Springer Japan KK 2017

Authors and Affiliations

  1. 1.Faculty of Civil and Geodetic EngineeringUniversity of LjubljanaLjubljanaSlovenia
  2. 2.Geological Survey of SloveniaLjubljanaSlovenia

Personalised recommendations