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Scenario Discovery with Multiple Criteria: An Evaluation of the Robust Decision‐Making Framework for Climate Change Adaptation

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  • Julie E. Shortridge
  • Seth D. Guikema

Abstract

There is increasing concern over deep uncertainty in the risk analysis field as probabilistic models of uncertainty cannot always be confidently determined or agreed upon for many of our most pressing contemporary risk challenges. This is particularly true in the climate change adaptation field, and has prompted the development of a number of frameworks aiming to characterize system vulnerabilities and identify robust alternatives. One such methodology is robust decision making (RDM), which uses simulation models to assess how strategies perform over many plausible conditions and then identifies and characterizes those where the strategy fails in a process termed scenario discovery. While many of the problems to which RDM has been applied are characterized by multiple objectives, research to date has provided little insight into how treatment of multiple criteria impacts the failure scenarios identified. In this research, we compare different methods for incorporating multiple objectives into the scenario discovery process to evaluate how they impact the resulting failure scenarios. We use the Lake Tana basin in Ethiopia as a case study, where climatic and environmental uncertainties could impact multiple planned water infrastructure projects, and find that failure scenarios may vary depending on the method used to aggregate multiple criteria. Common methods used to convert multiple attributes into a single utility score can obscure connections between failure scenarios and system performance, limiting the information provided to support decision making. Applying scenario discovery over each performance metric separately provides more nuanced information regarding the relative sensitivity of the objectives to different uncertain parameters, leading to clearer insights on measures that could be taken to improve system robustness and areas where additional research might prove useful.

Suggested Citation

  • Julie E. Shortridge & Seth D. Guikema, 2016. "Scenario Discovery with Multiple Criteria: An Evaluation of the Robust Decision‐Making Framework for Climate Change Adaptation," Risk Analysis, John Wiley & Sons, vol. 36(12), pages 2298-2312, December.
  • Handle: RePEc:wly:riskan:v:36:y:2016:i:12:p:2298-2312
    DOI: 10.1111/risa.12582
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    References listed on IDEAS

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    Cited by:

    1. Julia Reis & Julie Shortridge, 2020. "Impact of Uncertainty Parameter Distribution on Robust Decision Making Outcomes for Climate Change Adaptation under Deep Uncertainty," Risk Analysis, John Wiley & Sons, vol. 40(3), pages 494-511, March.
    2. Julie Shortridge & Janey Smith Camp, 2019. "Addressing Climate Change as an Emerging Risk to Infrastructure Systems," Risk Analysis, John Wiley & Sons, vol. 39(5), pages 959-967, May.
    3. Julia Reis & Julie Shortridge, 2022. "Robust decision outcomes with induced correlations in climatic and economic parameters," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 27(1), pages 1-23, January.
    4. Julie E. Shortridge & Benjamin F. Zaitchik, 2018. "Characterizing climate change risks by linking robust decision frameworks and uncertain probabilistic projections," Climatic Change, Springer, vol. 151(3), pages 525-539, December.

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