, Volume 14, Issue 3, pp 1043–1055 | Cite as

Effects of climate change on shallow landslides in a small coastal catchment in southern Italy

Original Paper


In different areas of the world, shallow landslides represent a remarkable hazard inducing fatalities and economic damages. Then, the evaluation about potential variation in frequency of such hazard under the effect of climate changes should be a priority for defining reliable adaptation measurements. Unfortunately, current performances of climate models on sub-daily scales, relevant for heavy rainfall events triggering shallow landslides, are not reliable enough to be used directly for performing slope stability analysis. In an attempt to overcome the constrains by gap in time resolution between climate and hazard models, the paper presents an integrated suitable approach for estimating future variations in shallow landslide hazard and managing the uncertainties associated with climate and sub-daily downscaling models. The approach is tested on a small basin on Amalfi coast (southern Italy). Basing on available basin scale critical rainfall thresholds, the paper outlines how the projected changes in precipitation patterns could affect local slope stability magnitude scenarios with different relevances as effect of investigated time horizon and concentration scenario. The paper concludes with qualitative evaluations on the future effectiveness of the local operative warning system in a climate change framework.


Climate changes Shallow landslides Global climate models (GCMs) Regional climate models (RCMs) Random parameter Bartlett-Lewis (RPBL) Critical rainfall thresholds (CRTs) Warning systems 



The research leading to these results received funding from the Italian Ministry of Education, University and Research and the Italian Ministry of Environment, Land and Sea under the GEMINA and Next Data projects. The authors would like to thank the Regional Civil Protection Department (Campania region) for having kindly provided the rainfall data and the Italian Military Geographical Institute. The authors are also grateful to the River Basin Authority Campania Sud e Interregionale per il bacino idrografico del fiume Sele and GEORES – A. Carbone and A. Gallo Associated.


  1. Baum RL, Savage WZ, Godt J W (2002) TRIGRS: a Fortran program for transient rainfall infiltration and grid-based regional slope-stability analysis US geological survey open-file report. 424 38Google Scholar
  2. Bo Z, Islam S, Eltahir EAB (1994) Aggregation-disaggregation properties of a stochastic rainfall model. Water Resour Res 30(12):3423–3435CrossRefGoogle Scholar
  3. Bovolin V (2012) Studio idraulico dell’evento alluvionale avvenuto ad Atrani (SA) il 9 settembre 2010 Parte I: ricostruzione dell’evento. Cooperativa Universitaria Editrice Studi, Fisciano, p 54. (in Italian)Google Scholar
  4. Breugem WP, Hazeleger W, Haarsma RJ (2007) Mechanisms of northern tropical Atlantic variability and response to CO2 doubling. J Clim 20(11):2691–2705CrossRefGoogle Scholar
  5. Bucchignani E, Montesarchio M, Zollo AL, Mercogliano P (2015) High-resolution climate simulations with COSMO-CLM over Italy: performance evaluation and climate projections for the XXI century. Int J Climatol. doi: 10.1002/joc.4379 Google Scholar
  6. Buma J, Dehn M (2000) Impact of climate change on a landslide in South East France, simulated using different GCM scenarios and downscaling methods for local precipitation. Climate Research 15(1):69-81Google Scholar
  7. Cascini L, Sorbino G, Cuomo S, Ferlisi S (2014) Seasonal effects of rainfall on the shallow pyroclastic deposits of the Campania region (southern Italy). Landslides 11(5):779–792CrossRefGoogle Scholar
  8. Cempid (2005) Il Sistema di Allertamento Regionale per il rischio idrogeologico e idraulico ai fini di protezione civile, Centro Funzionale per la previsione meteorologica e il monitoraggio meteo-idro-pluviometrico e delle frane. Protezione Civile Regione CampaniaGoogle Scholar
  9. Chan SC, Kendon EJ, Fowler HJ, Blenkinsop S, Roberts NM (2014) Projected increases in summer and winter UK sub-daily precipitation extremes from high-resolution regional climate models. Environ Res Lett 9(8):084019CrossRefGoogle Scholar
  10. Christensen JH, Christensen OB (2007) A summary of the PRUDENCE model projections of changes in European climate by the end of this century. Climate Change 81:7–30CrossRefGoogle Scholar
  11. Ciervo F, Papa MN, Medina V, Bateman A (2015) Simulation of flash floods in ungauged basins using post-event surveys and numerical modelling. J Flood Risk Manag 8(4):343–355CrossRefGoogle Scholar
  12. Coe JA, Godt JW (2012) Review of approaches for assessing the impact of climate change on landslide hazards, pp 371–377Google Scholar
  13. Collison A, Wade S, Griffiths J, Dehn M (2000) Modelling the impact of predicted climate change on landslide frequency and magnitude in SE England. Eng Geol 55(3):205–218CrossRefGoogle Scholar
  14. Comegna L, Picarelli L, Bucchignani E, Mercogliano P (2013) Potential effects of incoming climate changes on the behaviour of slow active landslides in clay. Landslides 10:373–391CrossRefGoogle Scholar
  15. Cowpertwait P, Isham V, Onof C (2007) Point process models of rainfall: developments for fine-scale structure. In Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, The Royal Society 463(2086):2569–2587CrossRefGoogle Scholar
  16. Crozier MJ (2010) Deciphering the effect of climate change on landslide activity: a review. Geomorphology 124:260–267CrossRefGoogle Scholar
  17. De Luca C (2012) Prevision and prevention of extreme hydrological events. University of Salerno, Italy PhD ThesisGoogle Scholar
  18. Dijkstra TA, Dixon N (2010) Climate change and slope stability in the UK: challenges and approaches. Q J Eng Geol Hydrogeol 43(4):371–385CrossRefGoogle Scholar
  19. Efstratiadis A, Koutsoyiannis D (2002) An evolutionary annealing-simplex algorithm for global optimisation of water resource systems. In Proceedings of the Fifth International Conference on Hydroinformatics, Cardiff, UK, pp 1423–1428. International Water AssociationGoogle Scholar
  20. Ehret U, Zehe E, Wulfmeyer V, Warrach-Sagi K, Liebert J (2012) HESS opinions “should we apply bias correction to global and regional climate model data?”. Hydrol Earth Syst Sci 16:3391–3404. doi: 10.5194/hess-16-3391-2012 2012CrossRefGoogle Scholar
  21. Furcolo P, Pelosi A, Rossi F (2015) Statistical identification of orographic effects in the regional analysis of extreme rainfall. Hydrol Process. doi: 10.1002/hyp.10719 Google Scholar
  22. Gudmundsson L, Bremnes JB, Haugen JE, Engen-Skaugen T (2012) Technical note: downscaling RCM precipitation to the station scale using statistical transformations—a comparison of methods. Hydrol Earth Syst Sci 16(9):3383–3390CrossRefGoogle Scholar
  23. Guyennon N, Romano E, Portoghese I, Salerno F, Calmanti S, Petrangeli AB, Tartari G, Copetti D (2013) Benefits from using combined dynamical-statistical downscaling approaches—lessons from a case study in the Mediterranean region. Hydrol Earth Syst Sci 17(2):705–720CrossRefGoogle Scholar
  24. Haque U, Blum P, da Silva PF, Andersen P, Pilz J, Chalov SR, et al. (2016) Fatal landslides in Europe. Landslides:1–10. doi: 10.1007/s10346-016-0689-3
  25. Huggel C, Clague JJ, Korup O (2012) Is climate change responsible for changing landslide activity in high mountains? Earth Surf Process Landforms 37:77–91CrossRefGoogle Scholar
  26. Huong HTL, Pathirana A (2013) Urbanization and climate change impacts on future urban flooding in Can Tho city, Vietnam. Hydrol Earth Syst Sci 17:379–394. doi: 10.5194/hess-17-379-2013 CrossRefGoogle Scholar
  27. IPCC (2013) Summary for policymakers. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Climate change (2013): the physical science basis contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change, Cambridge (United Kingdom) and New York (NY, USA). Cambridge University Press, Cambridge, p. 229Google Scholar
  28. Islam S, Entekhabi D, Bras RL, Rodriguez-Iturbe I (1990) Parameter estimation and sensitivity analysis for the modified Bartlett-Lewis rectangular pulses model of rainfall. Journal of Geophysical Research: Atmospheres (1984–2012) 95(D3):2093–2100CrossRefGoogle Scholar
  29. Iverson RM (2000) Landslide triggering by rain infiltration. Water Resour Res 36(7):1897–1910CrossRefGoogle Scholar
  30. Koutsoyiannis D, Manetas A (1996) Simple disaggregation by accurate adjusting procedures. Water Resour Res 32(7):2105–2117CrossRefGoogle Scholar
  31. Koutsoyiannis D, Onof C (2001) Rainfall disaggregation using adjusting procedures on a Poisson cluster model. J Hydrol 246(1):109–122CrossRefGoogle Scholar
  32. Lafon T, Dadson S, Buys G, Prudhomme C (2013) Bias correction of daily precipitation simulated by a regional climate model: a comparison of methods. Int J Climatol 33(6):1367–1381CrossRefGoogle Scholar
  33. Maraun D, Wetterhall F, Ireson AM, Chandler RE, Kendon EJ, Widmann M, et al. (2010) Precipitation downscaling under climate change: recent developments to bridge the gap between dynamical models and the end user. Rev Geophys 48(3)Google Scholar
  34. Maurer EP, Das T, Cayan DR (2013) Errors in climate model daily precipitation and temperature output: time invariance and implications for bias correction. Hydrological Earth System Science 17:2147–2159CrossRefGoogle Scholar
  35. Moss R, Edmonds J, Hibbard K, Manning M, Rose S, van Vuuren DP, Carter T, Emori S, Kainuma M, Kram T, Meehl G, Mitchell J, Nakicenovic N, Riahi K, Smith S, Stouffer R, Thomson A, Weyant J, Wilbanks T (2010) The next generation of scenarios for climate change research and assessment. Nature 463:747–756CrossRefGoogle Scholar
  36. Muerth MJ, Gauvin St-Denis B, Ricard S, Velázquez JA, Schmid J, Minville M, et al. (2013) On the need for bias correction in regional climate scenarios to assess climate change impacts on river runoff. Hydrol Earth Syst Sci 17(3):1189–1204CrossRefGoogle Scholar
  37. Napolitano E, Fusco F, Baum RL, Godt JW, De Vita P (2015) Effect of antecedent-hydrological conditions on rainfall triggering of debris flows in ash-fall pyroclastic mantled slopes of Campania (southern Italy). Landslides:1–17Google Scholar
  38. Nardi F, Annis A, Biscarini C (2015) On the impact of urbanization on flood hydrology of small ungauged basins: the case study of the Tiber river tributary network within the city of Rome. J Flood Risk Manag. doi: 10.1111/jfr3.12186 Google Scholar
  39. Olivares L, Damiano E, Mercogliano P, Picarelli L, Netti N, Schiano P, Savastano V, Cotroneo F, Manzi MP (2014) A simulation chain for early prediction of rainfall-induced landslides. Landslides 11(5):765–777CrossRefGoogle Scholar
  40. Onof C, Wheater HS (1994) Improvements to the modelling of British rainfall using a modified random parameter Bartlett-Lewis rectangular pulse model. J Hydrol 157(1):177–195CrossRefGoogle Scholar
  41. Onof C, Chandler RE, Kakou A, Northrop P, Wheater HS, Isham V (2000) Rainfall modelling using Poisson-cluster processes: a review of developments. Stoch Env Res Risk A 14(6):384–411CrossRefGoogle Scholar
  42. Onof C, Townend J, Kee R (2005) Comparison of two hourly to 5-min rainfall disaggregators. Atmos Res 77(1):176–187CrossRefGoogle Scholar
  43. Ormsbee LE (1989) Rainfall disaggregation model for continuous hydrologic modeling. J Hydraul Eng 115(4):507–525Google Scholar
  44. Pagano L, Picarelli L, Rianna G, Urciuoli G (2010) A simple numerical procedure for timely prediction of precipitation-induced landslides in unsaturated pyroclastic soils. Landslides 7(3):273–289CrossRefGoogle Scholar
  45. Panagos P, Ballabio C, Borrelli P, Meusburger K (2016) Spatio-temporal analysis of rainfall erosivity and erosivity density in Greece. Catena 137:161–172CrossRefGoogle Scholar
  46. Papa MN, Medina V, Ciervo F, Bateman A (2013) Derivation of critical rainfall thresholds for shallow landslides as a tool for debris flow early warning systems. Hydrol Earth Syst Sci 17(10):4095–4107CrossRefGoogle Scholar
  47. Pelosi A, Furcolo P (2015) An amplification model for the regional estimation of extreme rainfall within orographic areas in Campania region (Italy). Water 7(12):6877–6891CrossRefGoogle Scholar
  48. Piani C, Weedon GP, Best M, Gomes SM, Viterbo P, Hagemann S, Haerter JO (2010) Statistical bias correction of global simulated daily precipitation and temperature for the application of hydrological models. Journal of Hydrology 2010 395(3–4):199–215Google Scholar
  49. Picarelli L, Santo A, Di Crescenzo G, Olivares L (2008) Macro-zoning of areas susceptible to flowslide in pyroclastic soils in Campania region. Landslides and Engineered Slopes Taylor and Francis Group, London 1951–1957Google Scholar
  50. Pirone M, Papa R, Nicotera MV, Urciuoli G (2015) In situ monitoring of the groundwater field in an unsaturated pyroclastic slope for slope stability evaluation. Landslides 12(2):259–276CrossRefGoogle Scholar
  51. Porfido S, Esposito E, Alaia F, Molisso F, Sacchi M (2009) The use of documentary sources for reconstructing flood chronologies on the Amalfi rocky coast (southern Italy). Geol Soc Lond, Spec Publ 322(1):173–187CrossRefGoogle Scholar
  52. Quevauviller PP (2014) Hydrometeorological hazards: interfacing science and policy. Wiley, New YorkCrossRefGoogle Scholar
  53. Revellino P, Guadagno FM, Hungr O (2008) Morphological methods and dynamic modelling in landslide hazard assessment of the Campania Apennine carbonate slope. Landslides 5(1):59–70CrossRefGoogle Scholar
  54. Rianna G, Pagano L, Urciuoli G (2014) Rainfall patterns triggering shallow flowslides in pyroclastic soils. Eng Geol 174:22–35CrossRefGoogle Scholar
  55. Rockel B, Will A, Hense A (2008) The regional climate model COSMO-CLM (CCLM). Meteorol Z 17(4):347–348CrossRefGoogle Scholar
  56. Rodríguez-Iturbe I, Febres Power B, Valdes JB (1987) Rectangular pulses point process models for rainfall: analysis of empirical data. J Geophys Res Atmos 92(D8):9645–9656CrossRefGoogle Scholar
  57. Scoccimarro E, Gualdi S, Bellucci A, Sanna A, Fogli P, Manzini E, Vichi M, Oddo P, Navarra A (2011) Effects of tropical cyclones on ocean heat transport in a high resolution coupled general circulation model. J Clim 24:4368–4384CrossRefGoogle Scholar
  58. Segond ML, Neokleous N, Makropoulos C, Onof C, Maksimovic C (2007) Simulation and spatio-temporal disaggregation of multi-site rainfall data for urban drainage applications. Hydrol Sci J 52(5):917–935CrossRefGoogle Scholar
  59. Steppeler J, Doms G, Schättler U, Bitzer HW, Gassmann A, Damrath U, Gregoric G (2003) Meso-gamma scale forecasts using the nonhydrostatic model LM. Meteorog Atmos Phys 82:75–96CrossRefGoogle Scholar
  60. Stoffel M, Tiranti D, Huggel C (2014) Climate change impacts on mass movements—case studies from the European Alps. Sci Total Environ 493:1255–1266CrossRefGoogle Scholar
  61. Teutschbein C, Seibert J (2012) Bias correction of regional climate model simulations for hydrological climate change impact studies: review and evaluation of different methods. J Hydrol 456:12–29CrossRefGoogle Scholar
  62. Verhoest N, Troch PA, De Troch FP (1997) On the applicability of Bartlett–Lewis rectangular pulses models in the modeling of design storms at a point. J Hydrol 202(1):108–120CrossRefGoogle Scholar
  63. Villani V, Rianna G, Mercogliano P, Zollo AL, Schiano P (2015) Statistical approaches versus weather generator to downscale rcm outputs to point scale: a comparison of performances. Journal of Urban and Environmental Engineering 8(2):142–154CrossRefGoogle Scholar
  64. Violante C (2009) Rocky coast: geological constraints for hazard assessment. Geol Soc Lond, Spec Publ 322(1):1–31CrossRefGoogle Scholar
  65. Vrac M, Naveau P (2007) Stochastic downscaling of precipitation: from dry events to heavy rainfalls. Water Resour Res 43(7)Google Scholar
  66. Wheater HS, Chandler RE, Onof CJ, Isham VS, Bellone E, Yang C, ... and Segond ML (2005) Spatial-temporal rainfall modelling for flood risk estimation. Stoch Env. Res Risk A 19(6):403–416Google Scholar
  67. Woolhiser DA, Osborn HB (1985) A stochastic model of dimensionless thunderstorm rainfall. Water Resour Res 21(4):511–522Google Scholar
  68. Zollo AL, Rillo V, Bucchignani E, Montesarchio M, Mercogliano P (2015) Extreme temperature and precipitation events over Italy: assessment of high resolution simulations with COSMO-CLM and future scenarios. Int J Climatol. doi: 10.1002/joc.4401 Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • F. Ciervo
    • 1
    • 2
  • G. Rianna
    • 1
  • P. Mercogliano
    • 1
    • 3
  • M. N. Papa
    • 2
  1. 1.REgional Models and geo-Hydrological Impacts (REMHI)Euro-Mediterranean Center on Climate Change, CMCC FoundationCapuaItaly
  2. 2.Department of Civil EngineeringUniversity of SalernoFiscianoItaly
  3. 3.Italian Aerospace Research Center (CIRA)CapuaItaly

Personalised recommendations