Synthetic modeling to manage the nexus of food, energy, and water systems under uncertainty: The case of the Columbia River Basin

Abstract

Managing the nexus of food, energy, and water (FEW) systems is complex due to uncertainties, especially concerning climate change’s effects on resource demand. To assess these uncertainties’ impacts, we crafted optimization models treating the FEW nexus as a spatially distributed multi-agent system (MAS). Applied to a synthetic Columbia River Basin (CRB), our methodology offers guidance for CRB management. Results inform optimal energy investments, food production, and water allocation, highlighting a reversed water accessibility priority among irrigation and industrial agents. Hydropower’s relevance to policy is minimal but susceptible to climate change, affecting river inflow. Our alternate model evaluates emissions policy, suggesting current caps yield the highest marginal profit. Benchmark tests against a deterministic model reveal significantly increased regional profit potential with our proposed model.