SANF-RFI: An operational early warning system for rainfall-induced landslides along the Italian railway network

Rainfall-induced landslides represent one of the most critical natural hazards affecting railway infrastructure in Italy, where complex geological settings and increasing climate-driven extremes challenge the reliability of transport services. This paper presents the SANF-RFI system, a national-scale early warning and decision-support platform developed through the collaboration between Rete Ferroviaria Italiana (RFI) and the Italian National Research Council – Institute for Geo-Hydrological Protection (CNR-IRPI). SANF-RFI adapts the national landslide early warning framework (SANF) to railway-specific requirements. It integrates near-real-time and forecast precipitation data with territorial susceptibility, railway exposure models, and quality-controlled rainfall observations. The system provides probabilistic estimates of rainfall-induced landslide triggering at the level of railway segments and sections, explicitly accounting for uncertainty related to rainfall measurement, spatial representativeness, and short-term forecast variability. After describing the system architecture, data flows, and probabilistic algorithms, the paper illustrates an operational application along the Marradi–Faenza railway line, where SANF-RFI enabled safe and flexible traffic management under severe hydro-meteorological conditions. The experience demonstrates how scientifically grounded early warning tools can enhance infrastructure resilience while maintaining essential railway services.

Authors

Institutions

Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part F Journal of Rail and Rapid Transit
Published
2026-05-29
DOI
https://doi.org/10.1177/09544097261456885
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

SANF-RFI: An operational early warning system for rainfall-induced landslides along the Italian railway network

Maura Peca, Federico Innocca, Alessandro Rinaldi, Efisio Murgia et al.
Proceedings of the Institution of Mechanical Engineers Part F Journal of Rail and Rapid Transit
Landslides and related hazards
article

SANF-RFI: An operational early warning system for rainfall-induced landslides along the Italian railway network

Maura Peca, Federico Innocca, Alessandro Rinaldi, Efisio Murgia, Adriana Galli, Mirko Morgia, Ivan Agostino
article en

Abstract

Rainfall-induced landslides represent one of the most critical natural hazards affecting railway infrastructure in Italy, where complex geological settings and increasing climate-driven extremes challenge the reliability of transport services. This paper presents the SANF-RFI system, a national-scale early warning and decision-support platform developed through the collaboration between Rete Ferroviaria Italiana (RFI) and the Italian National Research Council – Institute for Geo-Hydrological Protection (CNR-IRPI). SANF-RFI adapts the national landslide early warning framework (SANF) to railway-specific requirements. It integrates near-real-time and forecast precipitation data with territorial susceptibility, railway exposure models, and quality-controlled rainfall observations. The system provides probabilistic estimates of rainfall-induced landslide triggering at the level of railway segments and sections, explicitly accounting for uncertainty related to rainfall measurement, spatial representativeness, and short-term forecast variability. After describing the system architecture, data flows, and probabilistic algorithms, the paper illustrates an operational application along the Marradi–Faenza railway line, where SANF-RFI enabled safe and flexible traffic management under severe hydro-meteorological conditions. The experience demonstrates how scientifically grounded early warning tools can enhance infrastructure resilience while maintaining essential railway services.

Proceedings of the Institution of Mechanical Engineers Part F Journal of Rail and Rapid Transit
Trenitalia (Italy) (IT)
Openalex Percentile: Top 3%
Landslides and related hazards
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.