Multi-risk assessment in mountain regions: A review of modelling approaches for climate change adaptation.

Agent-based model Bayesian network Climate change adaptation Event trees Multi-risk assessment System dynamic modelling

Journal

Journal of environmental management
ISSN: 1095-8630
Titre abrégé: J Environ Manage
Pays: England
ID NLM: 0401664

Informations de publication

Date de publication:
15 Feb 2019
Historique:
received: 28 06 2018
revised: 24 09 2018
accepted: 23 11 2018
pubmed: 12 12 2018
medline: 26 9 2019
entrez: 12 12 2018
Statut: ppublish

Résumé

Climate change has already led to a wide range of impacts on our society, the economy and the environment. According to future scenarios, mountain regions are highly vulnerable to climate impacts, including changes in the water cycle (e.g. rainfall extremes, melting of glaciers, river runoff), loss of biodiversity and ecosystems services, damages to local economy (drinking water supply, hydropower generation, agricultural suitability) and human safety (risks of natural hazards). This is due to their exposure to recent climate warming (e.g. temperature regime changes, thawing of permafrost) and the high degree of specialization of both natural and human systems (e.g. mountain species, valley population density, tourism-based economy). These characteristics call for the application of risk assessment methodologies able to describe the complex interactions among multiple hazards, biophysical and socio-economic systems, towards climate change adaptation. Current approaches used to assess climate change risks often address individual risks separately and do not fulfil a comprehensive representation of cumulative effects associated to different hazards (i.e. compound events). Moreover, pioneering multi-layer single risk assessment (i.e. overlapping of single-risk assessments addressing different hazards) is still widely used, causing misleading evaluations of multi-risk processes. This raises key questions about the distinctive features of multi-risk assessments and the available tools and methods to address them. Here we present a review of five cutting-edge modelling approaches (Bayesian networks, agent-based models, system dynamic models, event and fault trees, and hybrid models), exploring their potential applications for multi-risk assessment and climate change adaptation in mountain regions. The comparative analysis sheds light on advantages and limitations of each approach, providing a roadmap for methodological and technical implementation of multi-risk assessment according to distinguished criteria (e.g. spatial and temporal dynamics, uncertainty management, cross-sectoral assessment, adaptation measures integration, data required and level of complexity). The results show limited applications of the selected methodologies in addressing the climate and risks challenge in mountain environments. In particular, system dynamic and hybrid models demonstrate higher potential for further applications to represent climate change effects on multi-risk processes for an effective implementation of climate adaptation strategies.

Identifiants

pubmed: 30529418
pii: S0301-4797(18)31365-3
doi: 10.1016/j.jenvman.2018.11.100
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

759-771

Informations de copyright

Copyright © 2018. Published by Elsevier Ltd.

Auteurs

Stefano Terzi (S)

Department of Environmental Sciences, Informatics and Statistics, University Ca' Foscari Venice, Via Torino155, I-30172 Venezia-Mestre, Venice, Italy; Institute for Earth Observation, Eurac Research, Viale Druso 1, 39100, Bolzano, Italy.

Silvia Torresan (S)

Department of Environmental Sciences, Informatics and Statistics, University Ca' Foscari Venice, Via Torino155, I-30172 Venezia-Mestre, Venice, Italy; Fondazione Centro-Euro Mediterraneo sui Cambiamenti Climatici (CMCC), via Augusto Imperatore 16, I-73100, Lecce, Italy.

Stefan Schneiderbauer (S)

Institute for Earth Observation, Eurac Research, Viale Druso 1, 39100, Bolzano, Italy.

Andrea Critto (A)

Department of Environmental Sciences, Informatics and Statistics, University Ca' Foscari Venice, Via Torino155, I-30172 Venezia-Mestre, Venice, Italy; Fondazione Centro-Euro Mediterraneo sui Cambiamenti Climatici (CMCC), via Augusto Imperatore 16, I-73100, Lecce, Italy.

Marc Zebisch (M)

Institute for Earth Observation, Eurac Research, Viale Druso 1, 39100, Bolzano, Italy.

Antonio Marcomini (A)

Department of Environmental Sciences, Informatics and Statistics, University Ca' Foscari Venice, Via Torino155, I-30172 Venezia-Mestre, Venice, Italy; Fondazione Centro-Euro Mediterraneo sui Cambiamenti Climatici (CMCC), via Augusto Imperatore 16, I-73100, Lecce, Italy. Electronic address: marcom@unive.it.

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