Border-independent multi-functional, multi-hazard exposure modelling in Alpine regions

M. Pittore (), P. Campalani, K. Renner, M. Plörer and F. Tagliavini
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M. Pittore: EURAC Research
P. Campalani: EURAC Research
K. Renner: EURAC Research
M. Plörer: Federal Research and Training Centre for Forests, Natural Hazards and Landscape (BFW)
F. Tagliavini: ARPA Veneto

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2023, vol. 119, issue 2, No 4, 837-858

Abstract: Abstract Extreme hydrometeorological events such as the 2018 Vaia storm increasingly threaten alpine regions with multiple hazards often compounded and with cascading effects. Currently available risk assessment and prevention tools may therefore prove inadequate, particularly for transborder and vulnerable mountain areas, calling for comprehensive multi-hazard and transdisciplinary approaches. In particular, the exposed assets should not anymore be considered a sheer collection of static items, but the models should also reflect functional features. In this paper, we propose an integrated approach to multi-hazard exposure modelling including both static and functional components. The model is based on a homogeneous planar tessellation composed of hexagonal cells and a graph-like structure which describes the functional connections among the cells. To exemplify the methodology, a combination of static (buildings, protective forests), dynamic (population) and functional (road-based transport system) components has been considered together, targeting a ca. 10,000 km2 region across Italy and Austria. A cell-based aggregation at 250 m resolution and an innovative graph-based simplification allow for a good trade-off between the complexity of the model and its computational efficiency for risk-related applications. Furthermore, aggregation ensures protection of sensitive data at a scale still useful for civil protection. The resulting model can be used for different applications including scenario-based risk analysis and numeric simulation, probabilistic risk assessment, impact forecasting and early warning.

Keywords: Exposure; Risk; Multi-hazard; Flow; Traffic (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11069-023-06134-3

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