When can decision analysis improve climate adaptation planning? Two procedures to match analysis approaches with adaptation problems

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Abstract

Climate adaptation decisions are difficult because the future climate is deeply uncertain. Combined with uncertainties concerning the cost, lifetime, and effectiveness of adaptation measures, this implies that the net benefits of alternative adaptation strategies are ambiguous. On one hand, a simple analysis that disregards uncertainty might lead to near-term choices that are later regretted if future circumstances differ from those assumed. On the other hand, careful uncertainty-based decision analyses can be costly in personnel and time and might not make a difference. This paper considers two questions adaptation managers might ask. First, what type of analysis is most appropriate for a particular adaptation decision? We answer this question by proposing a six-step screening procedure to compare the usefulness of predict-then-act analysis, multi-scenario analysis without adaptive options, and multi-scenario analysis incorporating adaptive options. A tutorial application is presented using decision trees. However, this procedure may be cumbersome if managers face several adaptation problems simultaneously. Hence, a second question is how can managers quickly identify problems that would benefit most from thorough decision analysis? To address this question, we propose a procedure that ranks multiple adaptation problems in terms of the necessity and value of comprehensive analysis. Analysis can then emphasize the highest-ranking problems. This procedure is illustrated by a ranking of adaptation problems in the Chesapeake Bay region. The two complementary procedures proposed here can help managers focus analytical efforts where they will be most useful.

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Shi, R., Hobbs, B. F., & Jiang, H. (2019). When can decision analysis improve climate adaptation planning? Two procedures to match analysis approaches with adaptation problems. Climatic Change, 157(3–4), 611–630. https://doi.org/10.1007/s10584-019-02579-3

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