气候变化领域集成服务门户(CCPortal): Addressing ambiguity in probabilistic assessments of future coastal flooding using possibility distributions

CCPortal

DOI	10.1007/s10584-019-02443-4
	Addressing ambiguity in probabilistic assessments of future coastal flooding using possibility distributions
	Rohmer J.; Le Cozannet G.; Manceau J.-C.
发表日期	2019
ISSN	0165-0009
起始页码	95
结束页码	109
卷号	155 期号:1
英文摘要	Decision-making in the area of coastal adaptation is facing major challenges due to ambiguity (i.e., deep uncertainty) pertaining to the selection of a probability model for sea level rise (SLR) projections. Possibility distributions are mathematical tools that address this type of uncertainty since they bound all the plausible probability models that are consistent with the available data. In the present study, SLR uncertainties are represented by a possibility distribution constrained by likely ranges provided in the IPCC Fifth Assessment Report and by a review of high-end scenarios. On this basis, we propose a framework combining probabilities and possibilities to evaluate how SLR uncertainties accumulate with other sources of uncertainties, such as future greenhouse gas emissions, upper bounds of future sea level changes, the regional variability of sea level changes, the vertical ground motion, and the contributions of extremes and wave effects. We apply the framework to evaluate the probability of coastal flooding by the year 2100 at a local, low-lying coastal French urban area on the Mediterranean coast. We show that when adaptation is limited to maintaining current defenses, the level of ambiguity is too large to precisely assign a probability model to future flooding. Raising the coastal walls by 85 cm creates a safety margin that may not be considered sufficient by local stakeholders. A sensitivity analysis highlights the key role of deep uncertainties pertaining to global SLR and of the statistical uncertainty related to extremes. The ranking of uncertainties strongly depends on the decision-maker’s attitude to risk (e.g., neutral, averse), which highlights the need for research combining advanced mathematical theories of uncertainties with decision analytics and social science. © 2019, The Author(s).
语种	英语
scopus关键词	Advanced Analytics; Decision making; Floods; Gas emissions; Greenhouse gases; Sea level; Sensitivity analysis; Uncertainty analysis; Mediterranean coasts; Possibility distributions; Probabilistic assessments; Probability modeling; Regional variability; Sources of uncertainty; Statistical uncertainty; Vertical ground motion; Probability distributions; adaptive management; attitudinal survey; coastal zone; decision making; environmental assessment; flooding; future prospect; probability; public attitude; sea level change; spatial distribution; stakeholder; uncertainty analysis; urban area; France; Mediterranean Coast [France]
来源期刊	Climatic Change
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/147449
作者单位	BRGM, 3 av. C. Guillemin, B.P. 36009, Orléans Cedex 2, 45060, France
推荐引用方式 GB/T 7714	Rohmer J.,Le Cozannet G.,Manceau J.-C.. Addressing ambiguity in probabilistic assessments of future coastal flooding using possibility distributions[J],2019,155(1).
APA	Rohmer J.,Le Cozannet G.,&Manceau J.-C..(2019).Addressing ambiguity in probabilistic assessments of future coastal flooding using possibility distributions.Climatic Change,155(1).
MLA	Rohmer J.,et al."Addressing ambiguity in probabilistic assessments of future coastal flooding using possibility distributions".Climatic Change 155.1(2019).