Impact of Scenario Selection on Robustness

C. McPhail*, H. R. Maier, S. Westra, J. H. Kwakkel, L. van der Linden

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

28 Citations (Scopus)
110 Downloads (Pure)

Abstract

Multiple plausible future scenarios are being used increasingly in preference to a single deterministic or probabilistic prediction of the future in the long-term planning of water resources systems. These scenarios enable the determination of the robustness of a system—the consideration of performance across a range of plausible futures—and allow an assessment of which possible future system configurations result in a greater level of robustness. There are many approaches to selecting scenarios, and previous studies have observed that the choice of scenarios might affect the estimated robustness of the system. However, these observations have been anecdotal and qualitative. This paper develops a systematic, quantitative methodology for exploring the influence of scenario selection on the robustness and the ranking of decision alternatives. The methodology is illustrated on the Lake Problem. The quantitative results obtained confirm the qualitative observations of previous works, showing that the selection of scenarios is important, as it has a large influence on the robustness value calculated for each decision alternative. However, we show that it has a relatively small influence on how those decision alternatives are ranked. This implies that despite the difference in robustness values, similar decision outcomes will be reached in this case study, regardless of the basis on which the scenarios are obtained. It is also revealed that the impact of the scenarios on the robustness values is due to complex interactions with the system model and robustness metrics.

Original languageEnglish
Article numbere2019WR026515
JournalWater Resources Research
Volume56
Issue number9
DOIs
Publication statusPublished - 2020

Keywords

  • decision making
  • deep uncertainty
  • robustness
  • scenarios

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