Decision analysis for prioritizing climate change adaptation options: a systematic review

Abstract

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.