Addressing ambiguity in probabilistic assessments of future coastal flooding using possibility distributions
Addressing ambiguity in probabilistic assessments of future coastal flooding using possibility distributions
复制标题
使用可能性分布解决未来沿海洪水概率评估中的模糊性
作者：
J. Rohmer;G. Cozannet;J. Manceau
沿海适应领域的决策由于模糊性而面临重大挑战（即，深不确定性）有关的海平面上升（SLR）预测的概率模型的选择。可能性分布是解决这种不确定性的数学工具，因为它们约束了与可用数据一致的所有合理概率模型。在本研究中，SLR的不确定性表示的可能性分布的IPCC第五次评估报告中提供的可能的范围和高端情景的审查。在此基础上，我们提出了一个框架，结合概率和可能性，以评估如何SLR的不确定性积累与其他来源的不确定性，如未来的温室气体排放，未来海平面变化的上限，海平面变化的区域变化，垂直地面运动，极端和波浪效应的贡献。我们应用该框架来评估到2100年在当地，低洼的沿海城市地区的地中海沿岸的沿海洪水的概率。我们表明，当适应仅限于维持当前的防御，模糊的水平太大，精确分配的概率模型，以未来的洪水。将海岸墙提高85厘米，创造了当地利益攸关方可能认为不够的安全裕度。敏感性分析突出了与全球SLR相关的深度不确定性和与极端情况相关的统计不确定性的关键作用。不确定性的排序在很大程度上取决于决策者对风险的态度（例如，中性，厌恶），这突出了研究的需要结合先进的数学理论的不确定性与决策分析和社会科学。
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.
影响因子：
4.8
作者：
Slangen, A. B. A.;Carson, M.;Stammer, D.
通讯作者：
Stammer, D.
DOI：
10.1073/pnas.1703568114
发表时间：
2017-11-07
影响因子：
11.1
作者：
Garner AJ;Mann ME;Emanuel KA;Kopp RE;Lin N;Alley RB;Horton BP;DeConto RM;Donnelly JP;Pollard D
通讯作者：
Pollard D