确定气候变化适应备选方案优先次序的决策分析:系统综述

Eri Amanuma, Minoru Fujii, Kenichi Nakajima, Yasuaki Hijioka
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引用次数: 0

摘要

需要对气候变化适应方案进行优先排序,以便决策者利用决策分析方法在多种方案中做出适当选择。尽管不同部门采用了不同的决策分析方法,但由于这是一个快速发展的研究领域,因此迄今为止尚未对这些方法在不同部门的应用现状和挑战进行调查。我们系统回顾了气候变化适应方面的决策分析文献,以调查决策分析方法在各部门的应用情况,并确定当前面临的挑战。我们发现,大多数文章都集中在农业、水资源、沿海灾害和河流洪水等子领域,而在贫困、定居和福利等子领域则没有发现任何文章。能够解释适应的深度不确定性的决策分析方法的应用(深度不确定性组)约占总数的15%,主要集中在水资源和灾害相关分部门。在贫困、定居和福利分部门,可以推断学术文章很少,因为社会经济条件的强烈影响使得研究气候变化预测具有挑战性,而且行为者通常是在地方或个人层面进行报告。虽然气候变化影响预测的部门可能导致深度不确定性组的应用比例相对较大,但应用数量较少表明对所有部门的不确定性考虑不足。未来,每个部门都必须制定评估深度不确定性的方法;其中包括使用深度不确定性组中的应用,并结合多种决策分析方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Decision analysis for prioritizing climate change adaptation options: a systematic review
Climate change adaptation options need to be prioritized so that decision-makers make the appropriate choice among multiple options using decision analysis methods. Although different decision analysis methods are applied in different sectors, the status and challenges of applying the methods in various sectors have not been investigated to date because this is a rapidly developing research field. We systematically reviewed the decision analysis literature in climate change adaptation to investigate how decision analysis methods have been applied in each sector and to identify ongoing challenges. We found that most articles focused on the agriculture, water resources, coastal disaster, and river flooding subsectors, whereas no articles were found in the poverty, settlement, and wellbeing subsectors. The applications of decision analysis methods that can account for the deep uncertainty of adaptation (the Deep Uncertainty group) comprised about 15% of the total, and they were concentrated in the water resources and disaster-related subsectors. In the poverty, settlement, and wellbeing subsectors, it can be inferred that academic articles are scarce because it is challenging to study climate change projections due to the strong impact of socioeconomic conditions, and because the actors are often reported at the local or individual levels. Although the sectors where climate change impact projections have been developed may have led to a relatively large proportion of applications of the Deep Uncertainty group, the small number of applications suggests inadequate consideration of uncertainty in all sectors. In the future, it will be crucial for each sector to develop methods to evaluate deep uncertainty; these include using applications in the Deep Uncertainty group and combining multiple decision analysis methods.
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