Coastal vulnerability describes the susceptibility of a system to adverse effects from natural hazards. It is typically evaluated using spatial data on geographical attributes and is often synthesized using tools such as a Coastal Vulnerability Index (CVI). However, the literature highlights that there is no universal method for assessing vulnerability, emphasizing the importance of site-specific adaptations. A key challenge in coastal risk management is dealing with the inherent uncertainty of environmental variables and their future dynamics. Incorporating this uncertainty is essential for producing reliable assessments and informed decision-making. In this paper, we present an R package that facilitates the implementation of probabilistic graphical models explicitly incorporating epistemic uncertainty. This approach allows for vulnerability assessments even in situations where data availability is limited. The proposed methodology aims to deliver a more flexible and transparent framework for vulnerability analysis under uncertainty, providing valuable support to local policymakers, in particular during the early phases of intervention planning and technology selection for coastal mitigation strategies.

vulneraR: An R Package for Uncertainty Analysis in Coastal Vulnerability Studies / F.M. Stefanini, S. Ambrosini, F. D′Alessandro. - In: MATHEMATICS. - ISSN 2227-7390. - 13:22(2025 Nov 10), pp. 1-17. [10.3390/math13223603]

vulneraR: An R Package for Uncertainty Analysis in Coastal Vulnerability Studies

F.M. Stefanini
Primo
;
F. D′Alessandro
Ultimo
2025

Abstract

Coastal vulnerability describes the susceptibility of a system to adverse effects from natural hazards. It is typically evaluated using spatial data on geographical attributes and is often synthesized using tools such as a Coastal Vulnerability Index (CVI). However, the literature highlights that there is no universal method for assessing vulnerability, emphasizing the importance of site-specific adaptations. A key challenge in coastal risk management is dealing with the inherent uncertainty of environmental variables and their future dynamics. Incorporating this uncertainty is essential for producing reliable assessments and informed decision-making. In this paper, we present an R package that facilitates the implementation of probabilistic graphical models explicitly incorporating epistemic uncertainty. This approach allows for vulnerability assessments even in situations where data availability is limited. The proposed methodology aims to deliver a more flexible and transparent framework for vulnerability analysis under uncertainty, providing valuable support to local policymakers, in particular during the early phases of intervention planning and technology selection for coastal mitigation strategies.
Bayesian models; epistemic uncertainty; graphical models; coastal vulnerability; coastal protection intervention; CVI
Settore STAT-01/A - Statistica
10-nov-2025
https://www.mdpi.com/2227-7390/13/22/3603
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1196270
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