Tailoring Hydrologic Modeling For Improved Water Resources Decision Support

Presenter: Abigail Kahler1
Co-Author(s): -
Advisor(s): Dr. Ty Ferre
1Department of Hydrology and Atmospheric Sciences, University of Arizona

Panapto Presentation Video
Poster PDF
Poster Session 1

Water resources decisions are often made in the context of compromise among stakeholder groups with very different interests, and the extent of an aquifer is such that the impacts of present-day use may take decades to manifest, and equally long to mitigate. Initially small uncertainties can become magnified over time, proportionately increasing the environmental and monetary costs of a miscalculated decision. A stakeholder’s level of satisfaction with a compromise is defined by a utility function. A single outcome may have a low utility for one group and a high utility for another, according to the individual consequences. Hydrologic models help predict consequences but are limited by sparse data and uncertainty. This suggests a need for multiple models. It is worthwhile to pay special attention to less probable, still plausible models that predict consequential outcomes. These are called models of concern (MOCs). To achieve this, we propose a method of combining two ensembles. One is composed of the best-fitting calibrated models, and another entirely of MOCs. Combining these may represent stakeholder concerns more fully than a single ensemble, which only considers goodness-of-fit. This is an iterative process allowing the stakeholder to consider, and reconsider, their utility threshold according to the likelihood of negative outcomes. Preliminary results suggest the combined ensemble increases the identification of these outcomes. Additional work is required to test this method against more complex systems and to communicate predicted outcomes to stakeholders with minimal bias. This work presents the need for, and implications of, ensemble modeling.

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