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Expected frontiers: Incorporating weather uncertainty into a policy analysis using an integrated bi-level multi-objective optimization framework
Citation:
Whittaker, G., M. Bostian, B. Barnhart, R. Fare, AND S. Grosskopf. Expected frontiers: Incorporating weather uncertainty into a policy analysis using an integrated bi-level multi-objective optimization framework. INFORMS 2015, Philadelphia, PA, November 01 - 04, 2015.
Impact/Purpose:
The multi-criteria decision making section within the INFORMs conference in Philadelphia, PA from November 1-4, 2015 will be an extraordinary opportunity to showcase EPA’s abilities in integrated systems modeling. We present a methodology to track the propagation of errors and uncertainty within integrated modeling systems and to demonstrate their impact on resulting trade-offs within multi-objective optimization systems. This will be pertinent for groups interested in the effects of climate change and will be particularly important to policy makers and watershed groups who are interested in incorporating weather uncertainty within policy analysis.
Description:
Weather is the main driver in both plant use of nutrients and fate and transport of nutrients in the environment. In previous work, we evaluated a green tax for control of agricultural nutrients in a bi-level optimization framework that linked deterministic models. In this study, we use a time series bootstrap approach to generate a large number of time series that are possible alternatives to the observed weather. We then calculate the Pareto frontier of the bi-level optimization using many different possible weather samples. The distribution of the results show that the deterministic Pareto frontier is sensitive to climate. Some policy configurations that appeared equally effective in a deterministic model setup were strongly differentiated when weather uncertainty was included in the policy evaluation.