Effective management of water resources depends on accurately predicting future water supplies and demands that regularly fluctuate because of population growth, climate change, and many other factors. To deal with large uncertainties in these considerations, water resource planners often use what is known as a scenario-neutral approach in their projections.
In contrast to scenario-driven methods, which assess the potential effects of specific, model-derived conditions, a scenario-neutral approach uses sensitivity analysis to determine which input factors, such as seasonal precipitation and population growth, most affect performance. The sensitivity analysis is performed assuming these factors are independent, with no combination of factors more likely than any other. The results of sensitivity analyses have been used widely to design monitoring programs to detect changes in critical climatic and socioeconomic factors so that water management policies can be adapted as these critical conditions change.
Now Quinn et al. question whether this approach is truly scenario neutral. The authors argue that sensitivity analyses incorporate implicit assumptions about the ranges of and correlations among factors that have large uncertainties and that these assumptions could, in turn, influence conclusions regarding which factors are most important and which policies will therefore be the most robust, essentially negating the approach’s neutrality.
To evaluate this effect, the researchers conducted exploratory modeling to evaluate the vulnerability of hundreds of Upper Colorado River Basin water rights holders to potential drought conditions. The team based their analysis on four different experimental designs, including scenarios informed by future climate projections, scenarios informed by multiple paleohydrologic reconstructions, and scenario-neutral cases centered around the past century’s historical conditions.
The results indicated that the choice of experimental design used for vulnerability assessments can strongly affect an assessment’s outcome and that both the distribution of shortages among water users and the choice of which factors to monitor can vary starkly depending upon the experimental design. The results highlight challenges of designing scenarios to evaluate water resource vulnerability under deep uncertainty, the authors say. And because there is no way of knowing which scenarios are most plausible, they recommend that planners consider numerous, competing hypotheses in future climate vulnerability assessments. (Earth’s Future, https://doi.org/10.1029/2020EF001650, 2020)
—Terri Cook, Science Writer
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