Abstract
In two areas located in the north-western part of Tuscany, central Italy, Lunigiana and Garfagnana, noticeable heavy rainfall events occurred in the last years. During these events, the rainfall amounts and intensities triggered a great number of shallow landslides, causing damages, injuries and human losses. Steep slopes and deep valleys induced a persistently high relief of energy and high shallow landsliding susceptibility. In the present paper, the authors considered 4 heavy rainfall events that affected the area in 2009–2011. They carried out an analysis including a statistical modelling of spatial landslide occurrence by using Random Forest classifiers (RFc) after model selection by means of a stepwise AIC (Akaike Information Criterion) procedure. Event landslides occurrences permitted to build four event-specific RFc training sets, considering a large number of predictors reliable to characterize landslide susceptibility. Furthermore, the analysis took into account some relevant meteorological variables directly linked to the events themselves. An exploratory evaluation of the skills of a numerical weather prediction (NWP) model was conducted, to give a reliable supply to the RFc framework by using its weather forecast. For one selected event, a shallow landslide hazard model with meteorological inputs was validated. The preliminary results are shown and discussed.
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Akaike H (1974) A new look at the statistical model identification. IEEE Trans Autom Contr 19:716–723
Alpert P, Ben-Gai T, Baharad A, Benjamin Y, Yekutieli D, Colacino M, Diodato L, Ramis C, Homar V, Romero R, Michaelides S, Manes A (2002) The paradoxical increase of mediterranean extreme daily rainfall in spite of decrease in total values. Geophys Res Lett 29:1536. doi:10.1029/2001GL013554
Bartolini G, Grifoni D, Torrigiani Malaspina T, Vallorani R, Meneguzzo F, Gozzini B (2014) Precipitation changes from two long-term hourly dataset in Tuscany (Italy). Int J Climatol. doi:10.1002/joc.3956
Catani F, Lagomarsino D, Segoni S, Tofani V (2014) Exploring model sensitivity issues across different scales in landslide susceptibility. In: NHESSD—abstract—exploring model sensitivity issues across different scales in landslide susceptibility. http://www.nat-hazards-earth-syst-sci-discuss.net/1/583/2013/nhessd-1-583-2013.html. Accessed 29 Jan 2014
Chen F, Mitchell K, Schaake J, Xue Y, Pan HL, Koren V, Duan QY, Ek M, Betts A (1996) Modeling of land surface evaporation by four schemes and comparison with FIFE observations. J Geophys Res 101:7251–7268
Guzzetti F, Carrara A, Cardinali M, Reichenbach P (1999) Landslide hazard evaluation: an aid to a sustainable development. Binghamton symposium on geomorphology, Geomorphology, vol 31, pp 181–216
Hijmans RJ, Phillips S, Leathwick J, Elith J (2013) Dismo: species distribution modeling. R package version 0.8–11. http://CRAN.R-project.org/package=dismo
Hong Y, Adler R, Huffman G (2006) Evaluation of the potential of NASA multi-satellite precipitation analysis in global landslide hazard assessment. Geophys Res Lett 33:L22402
Hong Y, Adler RF, Huffman G, Negri A (2007) Use of satellite remote sensing data inmapping of global shallow landslides susceptibility. J Nat Hazards 43(2):245–256
IPCC (2013) Climate change 2013: the physical science basis. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA
Skamarock WC, Klemp JB (2008) A time-split nonhydrostatic atmospheric model for weather research and forecasting applications. J Comput Phys 227(7):3465–3485
Wilks DS (2006) Statistical methods in the atmospheric sciences, 2nd edn. Elsevier, Amsterdam
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Perna, M. et al. (2015). Sensitivity Analysis for Shallow Landsliding Susceptibility Assessment in Northern Tuscany. In: Lollino, G., et al. Engineering Geology for Society and Territory - Volume 2. Springer, Cham. https://doi.org/10.1007/978-3-319-09057-3_26
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DOI: https://doi.org/10.1007/978-3-319-09057-3_26
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