Modelling Glacier Ice Avalanches for Infrastructure Risk Assessment in the Alps: Insights from the PNRR - Ecosistema dell'Innovazione "Nord Ovest Digitale e Sostenibile" Project

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Authors: William Boffelli, Maddalena Nicora, Fabrizio Troilo, Pietro Di Sopra, Martina Lodigiani, Luca Mondardini, Paolo Perret
Cited by: 0
References: 8

Abstract

Abstract. Climate change is driving significant cryospheric degradation in the European Alps, potentially increasing the frequency of glacial hazards such as ice avalanches. This study presents an integrated, reproducible workflow to assess the vulnerability of hydroelectric infrastructure in the Aosta Valley, Italy. The methodology combines a statistical analysis of historical European events with stochastic numerical modelling. A robust relationship between collapse volume and the angle of reach was derived using bootstrap regression. Glacier release points were identified by intersecting flowlines with glacier fronts, applying a densification strategy for complex ice bodies. Potential runout scenarios were simulated using the r.randomwalk model on a normalized 24 m Digital Elevation Model (DEM), comparing datasets from 2000 and 2008 to evaluate sensitivity to glacial retreat. Results highlight localized criticalities, particularly in the Valpelline sector, where collapses from the Luseney and Solatset glaciers could directly impact intake structures and reservoirs. In Valtournenche, simulations identify scenarios that approach the Perrères power plant. Despite these specific risks, the regional energy network demonstrates high overall resilience. This approach provides a valuable tool for prioritizing monitoring and mitigation strategies in high-mountain energy planning.

Fields of Study & Subjects

Cryospheric studies and observations Landslides and related hazards Dam Engineering and Safety

Publication details

Journal / source
The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences
Volume
XLVIII-M-11-2026
Pages
1–7
Publication date
3 March 2026
Language
EN