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

Federico Mattia Stefanini (), Sid Ambrosini and Felice D′Alessandro
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Federico Mattia Stefanini: Department of Environmental Science and Policy, University of Milan, 20133 Milan, Italy
Sid Ambrosini: Department of Environmental Science and Policy, University of Milan, 20133 Milan, Italy
Felice D′Alessandro: Department of Environmental Science and Policy, University of Milan, 20133 Milan, Italy

Mathematics, 2025, vol. 13, issue 22, 1-17

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.

Keywords: Bayesian models; epistemic uncertainty; graphical models; coastal vulnerability; coastal protection intervention; CVI (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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