Calibration and validation of rockfall modelling along a railway section in an mountain area in Central Italy

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Authors: Francesca Ardizzone, MAURO ROSSI, Michele Santangelo
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Abstract

Rockfalls represent a substantial threat to railway routes, due to their rapidity, destructive potential and high probability of occurrence on steep topographies. Approaches for the assessment of rockfall susceptibility range from statistical methods, for modeling large areas, to deterministic ones, for application in local analyses. A common requirement is the need to locate the source areas, often found uphill on cliffs, and the subsequent assessment of the runout areas of rockfalls stemming from such areas. Modelling rockfall phenomena is complex and requires various inputs, including: accurate location of the source areas, geomorphological and geological setting, and other geo-environmental factors.We present an application conducted along the Rocca San Zenone - Giuncano Scalo railway line, in a study area (26 km2) in Central Italy, where rockfall are abundant. The activity consisted in creating rockfall trajectory maps, in geotiff format, starting from possible source areas, and in classifying and validating the maps. The following software was used to create the trajectory map: i) rockyfor3D (https://www.ecorisq.org/ecorisq-tools); and ii) STONE (Guzzetti et al., 2002). The classification and validation phase was carried out using the R RF-Tools software (Rossi, 2023). Methodology for the Creation of Landslide Susceptibility Maps to produce rockfall susceptibility zoning, considering three scenarios: i) plausible scenario, ii) best case scenario; and iii) worst case scenario.The rockfall modeling procedure was developed as part of a national project dedicated to the preparation of an operational methodology for assessing landslide susceptibility along the entire Italian railway network.

Fields of Study & Subjects

Landslides and related hazards Tree Root and Stability Studies Soil erosion and sediment transport

Publication details

Journal / source
EGU General Assembly Conference Abstracts
Publication date
14 March 2026
Language
EN