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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/nhess-2017-457
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
24 Jan 2018
Review status
This discussion paper is a preprint. A revision of the manuscript is under review for the journal Natural Hazards and Earth System Sciences (NHESS).
Estimation of the susceptibility of a road network to shallow landslides with the integration of the sediment connectivity
Massimiliano Bordoni1, M. Giuseppina Persichillo1, Claudia Meisina1, Stefano Crema2, Marco Cavalli2, Carlotta Bartelletti3, Yuri Galanti3, Michele Barsanti4, Roberto Giannecchini3, and Giacomo D'Amato Avanzi3 1Department of Earth and Environmental Sciences, University of Pavia, Pavia, 27100, Italy
2Research Institute for Geo-Hydrological Protection, National Research Council, Padova, 35127, Italy
3Department of Earth Sciences, University of Pisa, Pisa, 56126, Italy
4Department of Civil and Industrial Engineering, University of Pisa, Pisa, 56126, Italy
Abstract. Landslides causes severe damages to the road network of a hit zone, in terms of both direct (partial or complete destruction of a road trait, blockages) and indirect (traffic restriction, cut-off of a certain area) costs. Thus, the identification of the parts of the road network which are more susceptible to landslides is fundamental to reduce the risk to the population potentially exposed and the money expense caused by road damaging. For these reasons, this paper aimed to develop and test a data-driven model based on the Genetic Algorithm Method for the identification of road sectors that are susceptible to be hit by shallow landslides triggered in slopes upstream to the infrastructure. This work also analyzed the importance of considering or not the sediment connectivity on the estimation of the susceptibility. The study was carried out in a catchment of north-eastern Oltrepò Pavese (northern Italy), where several shallow landslides affected roads in the last 8 years. The random partition of the dataset used for building the model in two parts (training and test subsets), within a 100-fold bootstrap procedure, allowed to select the most significant explanatory variables, providing a better description of the occurrence and distribution of the road sectors potentially susceptible to damages induced by shallow landslides. The presented methodology allows the identification, in a robust and reliable way, of the most susceptible road sectors that could be hit by sediments delivered by landslides. The best predictive capability was obtained using a model which took into account also the index of connectivity, calculated according to a linear relationship. Most susceptible road traits resulted to be located below steep slopes with a limited height (lower than 50 m), where sediment connectivity is high. Different scenarios of land use were implemented in order to estimate possible changes in road susceptibility. Land use classes of the study area were characterized by similar connectivity features with a consequent loss of variations also on the susceptibility of the road networks according to different scenarios of distribution of land cover. Larger effects on sediment connectivity and, as a consequence on road susceptibility, could be due to modifications in the morphology of the slopes (e.g. drainage system, modification of the slope angle) caused by the abandonment or by the recovery of cultivations. The results of this research demonstrate the ability of the developed methodology in the assessment of susceptible roads. This could give to the managers of an infrastructure information on the criticality of the different road traits, thereby allowing attention and economic budgets to be shifted towards the most critical assets, where structural and non-structural mitigation measures could be implemented.
Citation: Bordoni, M., Persichillo, M. G., Meisina, C., Crema, S., Cavalli, M., Bartelletti, C., Galanti, Y., Barsanti, M., Giannecchini, R., and D'Amato Avanzi, G.: Estimation of the susceptibility of a road network to shallow landslides with the integration of the sediment connectivity, Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2017-457, in review, 2018.
Massimiliano Bordoni et al.
Massimiliano Bordoni et al.
Massimiliano Bordoni et al.

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Short summary
This paper aimed to develop and test a data-driven model for the identification of road sectors that are susceptible to be hit by shallow landslides triggered in slopes upstream to the infrastructure. Most susceptible road traits resulted in the ones located below steep slopes with a limited height (lower than 50 m), where sediment connectivity is high. The results of the susceptibility analysis can give asset managers indispensable information on the relative criticality of the different roads.
This paper aimed to develop and test a data-driven model for the identification of road sectors...
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