From many futures to one: climate-informed planning scenario analysis for resource-efficient deep climate uncertainty analysis

Baptiste François (), Alexis Dufour (), Thi Nhu Khanh Nguyen (), Alexa Bruce (), Dong Kwan Park () and Casey Brown ()
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Baptiste François: University of Massachusetts Amherst
Alexis Dufour: San Francisco Public Utilities Commission
Thi Nhu Khanh Nguyen: University of Massachusetts Amherst
Alexa Bruce: University of Massachusetts Amherst
Dong Kwan Park: University of Massachusetts Amherst
Casey Brown: University of Massachusetts Amherst

Climatic Change, 2024, vol. 177, issue 7, No 9, 23 pages

Abstract: Abstract Water resources managers face decisions related to building new infrastructure to increase water system resilience to climate and demand changes. To inform this adaptation planning process, current decision-making methods commonly use scenario approaches to estimate the benefit of adaptation options. While effective, these new analyses require communication of complicated findings to often nontechnical audiences. This paper introduces a pragmatic approach that uses the results from a bottom-up assessment of vulnerability of the water system with future climate projection-based probabilities of climate change to select a single planning scenario that encapsulates the decision-makers’ chosen level of robustness for their system. Contrary to typical implementation of option analysis under deep climate uncertainty, the proposed pragmatic approach does not require the analyst to evaluate each portfolio of adaptation options against all possible states of the world, significantly reducing the required computational costs and communication challenges. It also aligns with the planning scenario approach used in practice by water utilities. The modeling framework is illustrated for the regional water system operated by the San Francisco Public Utilities Commission (California, United States) for which changes in average temperature, precipitation and urban demand are considered.

Keywords: Decision-making; Deep Uncertainty; Water Systems; Climate Adaptation; Infrastructure Planning (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10584-024-03772-9

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