Natural Hazards

, Volume 95, Issue 3, pp 883–890 | Cite as

Rainfall thresholds for landslide occurrence: systematic underestimation using coarse temporal resolution data

  • Francesco MarraEmail author
Research Letter


Rainfall thresholds for landslides occurrence derived in real applications tend to be lower than the ones one would obtain using exact data. This letter shows how the use of coarse temporal resolution rainfall data causes a systematic overestimation of the duration of the triggering rainfall events that directly contributes to thresholds underestimation. A numerical experiment is devised to quantify this systematic effect for the relevant case of power-law depth/intensity–duration thresholds. In the examined conditions, i.e., the frequentist method at 5% non-exceedance probability level, ~ 70% underestimation of the scale parameter and ~ 60% overestimation of the shape parameter of the thresholds is to be expected using daily resolution rainfall data, but the exact quantification depends on the specific characteristics of each study case. The underestimation increases as the temporal resolution becomes larger than the expected minimal duration of the triggering events. Under operational conditions, sensitivity analyses based on the methods and datasets of interest are advised.


Landslides Early warning Rainfall thresholds Systematic underestimation 



The author is grateful to Efrat Morin and the Hydrometeorology Laboratory at the Hebrew University of Jerusalem for the support and acknowledges Marco Borga, Stefano Crema, and Efthymios Nikolopoulos for the fruitful discussions on the topic.

Compliance with ethical standards

Conflict of interest

The authors declared that they have no conflict of interest.

Supplementary material

11069_2018_3508_MOESM1_ESM.pdf (305 kb)
Supplementary material 1 (PDF 305 kb)


  1. Bogaard T, Greco R (2018) Invited perspectives: hydrological perspectives on precipitation intensity–duration thresholds for landslide initiation: proposing hydro-meteorological thresholds. Nat Hazards Earth Syst Sci 18:31–39. CrossRefGoogle Scholar
  2. Brunetti MT, Perruccacci S, Rossi M, Luciani S, Valigi D, Guzzetti F (2010) Rainfall thresholds for the possible occurrence of landslides in Italy. Nat Hazards Earth Syst Sci 10:447–458. CrossRefGoogle Scholar
  3. Brunetti MT, Melillo M, Peruccacci S, Ciabatta L, Brocca L (2018) How far are we from the use of satellite rainfall products in landslide forecasting? Remote Sens Environ 210:65–75. CrossRefGoogle Scholar
  4. Caine N (1980) The rainfall intensity–duration control of shallow landslides and debris flows. Geogr Ann 62A:23–27Google Scholar
  5. Destro E, Marra F, Nikolopoulos EI, Zoccatelli D, Creutin JD, Borga M (2017) Spatial estimation of debris flows-triggering rainfall and its dependence on rainfall return period. Geomorphology 278:269–279. CrossRefGoogle Scholar
  6. Guzzetti F, Peruccacci S, Rossi M, Stark CP (2008) The rainfall intensity–duration control of shallow landslides and debris flows: an update. Landslides 5(1):3–17. CrossRefGoogle Scholar
  7. Kirschbaum DB, Adler R, Hong Y, Kumar S, Peters-Lidard C, Lerner-Lam A (2012) Advances in landslide nowcasting: evaluation of a global and regional modeling approach. Environ Earth Sci 66:1683–1696. CrossRefGoogle Scholar
  8. Leonarduzzi E, Molnar P, McArdell BW (2017) Predictive performance of rainfall thresholds for shallow landslides in Switzerland from gridded daily data. Water Resour Res 53:6612–6625. CrossRefGoogle Scholar
  9. Marra F, Nikolopoulos EI, Creutin JD, Borga M (2014) Radar rainfall estimation for the identification of debris-flow occurrence thresholds. J Hydrol 519:1607–1619. CrossRefGoogle Scholar
  10. Marra F, Nikolopoulos EI, Creutin JD, Borga M (2016) Space–time organization of debris flows-triggering rainfall and its effect on the identification of the rainfall threshold relationship. J Hydrol 541:246–255. CrossRefGoogle Scholar
  11. Marra F, Destro E, Nikolopoulos EI, Zoccatelli D, Creutin JD, Guzzetti F, Borga M (2017) Impact of rainfall spatial aggregation on the identification of debris flow occurrence thresholds. Hydrol Earth Syst Sci 21:4525–4532. CrossRefGoogle Scholar
  12. Melillo M, Brunetti MT, Peruccacci S, Gariano SL, Guzzetti F (2015) An algorithm for the objective reconstruction of rainfall events responsible for landslides. Landslides 12:311–320. CrossRefGoogle Scholar
  13. Nikolopoulos EI, Borga M, Creutin JD, Marra F (2015) Estimation of debris flow triggering rainfall: influence of rain gauge density and interpolation methods. Geomorphology 243:40–50. CrossRefGoogle Scholar
  14. Nikolopoulos EI, Destro E, Maggioni V, Marra F, Borga M (2017) Satellite-rainfall estimates for debris flow prediction: an evaluation based on rainfall accumulation–duration thresholds. J Hydrometeorol 18:2207–2214. CrossRefGoogle Scholar
  15. Peres DJ, Cancelliere A (2014) Derivation and evaluation of landslide-triggering thresholds by a Monte Carlo approach. Hydrol Earth Syst Sci 18:4913–4931. CrossRefGoogle Scholar
  16. Peres DJ, Cancelliere A, Greco R, Bogaard TA (2018) Influence of uncertain identification of triggering rainfall on the assessment of landslide early warning thresholds. Nat Hazards Earth Syst Sci 18:633–646. CrossRefGoogle Scholar
  17. Peruccacci S, Brunetti MT, Luciani S, Vennari C, Guzzetti F (2012) Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy. Geomorphology 139–140:79–90. CrossRefGoogle Scholar
  18. Piciullo L, Gariano SL, Melillo M, Brunetti MT, Peruccacci S, Guzzetti F, Calvello M (2017) Definition and performance of a threshold-based regional early warning model for rainfall-induced landslides. Landslides 14(3):995–1008. CrossRefGoogle Scholar
  19. Piciullo L, Calvello M, Cepeda J (2018) Territorial early warning systems for rainfall-induced landslides. Earth-Science Rev. 179:228–247. CrossRefGoogle Scholar
  20. Robbins JC (2016) A probabilistic approach for assessing landslide triggering event rainfall in Papua New Guinea, using TRMM satellite precipitation estimates. J Hydrol 541:296–309. CrossRefGoogle Scholar
  21. Rossi M, Luciani S, Valigi D, Kirschbaum D, Brunetti MT, Peruccacci S, Guzzetti F (2017) Statistical approaches for the definition of landslide rainfall thresholds and their uncertainty using rain gauge and satellite data. Geomorphology 285:16–27. CrossRefGoogle Scholar
  22. Segoni S, Piciullo L, Gariano SL (2018) A review of the recent literature on rainfall thresholds for landslide occurrence. Landslides. Google Scholar
  23. Staley D, Kean JW, Cannon SH, Schmidt KM, Laber JL (2013) Objective definition of rainfall intensity–duration thresholds for the initiation of post-fire debris flows in southern California. Landslides 10:547–562. CrossRefGoogle Scholar
  24. Vessia G, Parise M, Brunetti MT, Peruccacci S, Rossi M, Vennari C, Guzzetti F (2014) Automated reconstruction of rainfall events responsible for shallow landslides. Nat Hazards Earth Syst Sci 14:2399–2408. CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Fredy & Nadine Herrmann Institute of Earth Sciences, Hebrew University of JerusalemJerusalemIsrael

Personalised recommendations