A comprehensive framework for empirical modeling of landslides induced by rainfall: the Generalized FLaIR Model (GFM)

• Published in: Landslides Vol. 14; no. 3; pp. 1009 - 1030
• Main Authors: De Luca, D. L., Versace, P.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2017; Springer Nature B.V
• Subjects: Agriculture; Alpine environments; Atmospheric precipitations; Case studies; Civil Engineering; Damage; Disasters; Earth and Environmental Science; Earth Sciences; Empirical models; False alarms; Geography; Hydrologic models; Hydrology; Land subsidence; Landslides; Landslides & mudslides; Natural Hazards; Original Paper; Precipitation; Precipitation models; Rain; Rainfall; Technical literature; Thresholds; Italy; Italy, Calabria; Antecedent precipitation (AP) models; Intensity-duration (ID) models; Nonstationary rainfall thresholds; Landslide prediction
• ISSN: 1612-510X; 1612-5118
• DOI: 10.1007/s10346-016-0768-5

In this paper, a new version of the hydrological model named FLaIR (Forecasting of Landslides Induced by Rainfall) is described, and it is indicated as GFM (Generalized FLaIR Model). Nonstationary rainfall thresholds, depending on antecedent precipitation, are introduced in this new release, which allows for a better prediction of landslide occurrences. Authors demonstrate that GFM is able to reproduce all the antecedent precipitation models (AP) proposed in technical literature as particular cases, besides intensity-duration schemes (ID) and more conceptual approaches, like Leaky Barrel, whose reconstruction with the first release of FlaIR model, which adopts only stationary thresholds, was already discussed in technical literature. Authors applied GFM for two case studies: 1) Gimigliano municipality, which is located in Calabria region (southern Italy) and where a consistent number of landslides occurred in the past years; in particular, during the period 2008–2010, this area (like the whole Calabria region) was affected by persistent rainfall events, which severely damaged infrastructures and buildings; 2) Barcelonnette Basin, which is located in the dry intra-Alpine zone (South French Alps). The high flexibility of GFM allows to obtain significant improvements in landslide prediction; in details, a substantial reduction of false alarms is obtained with respect to application of classical ID and AP schemes.