Reviewing Bayesian Networks potentials for climate change impacts assessment and management: A multi-risk perspective

被引:85
|
作者
Sperotto, Anna [1 ,2 ]
Molina, Jose-Luis [3 ]
Torresan, Silvia [1 ,2 ]
Critto, Andrea [1 ,2 ]
Marcomini, Antonio [1 ,2 ]
机构
[1] Ctr Euromediterraneo Cambiamenti Climatici CMCC, Via Augusto Imperatore 16, I-73100 Lecce, Italy
[2] Univ Ca Foscari Venice, Dept Environm Sci Informat & Stat, Via Ind 21-8, I-30175 Venice, Italy
[3] Univ Salamanca, High Polytech Sch Engn, Av Hornos Caleros 50, Avila 05003, Spain
关键词
Multiple stressors; Climate change; Probabilistic risk assessment; Uncertainty; Integrated modelling; BELIEF NETWORKS; INTEGRATED ASSESSMENT; NEURAL-NETWORKS; RISK-ASSESSMENT; OIL-SPILL; UNCERTAINTY; MODEL; CHALLENGES; HAZARD; TOOL;
D O I
10.1016/j.jenvman.2017.07.044
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The evaluation and management of climate change impacts on natural and human systems required the adoption of a multi-risk perspective in which the effect of multiple stressors, processes and interconnections are simultaneously modelled. Despite Bayesian Networks (BNs) are popular integrated modelling tools to deal with uncertain and complex domains, their application in the context of climate change still represent a limited explored field. The paper, drawing on the review of existing applications in the field of environmental management, discusses the potential and limitation of applying BNs to improve current climate change risk assessment procedures. Main potentials include the advantage to consider multiple stressors and endpoints in the same framework, their flexibility in dealing and communicate with the uncertainty of climate projections and the opportunity to perform scenario analysis. Some limitations (i.e. representation of temporal and spatial dynamics, quantitative validation), however, should be overcome to boost BNs use in climate change impacts assessment and management. (C) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:320 / 331
页数:12
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