The Great Lakes Region's water quality and ecological health are threatened by the export of nutrients from agricultural lands, which causes eutrophication, hypoxia, and destructive algal blooms. The intensification of hydrologic cycles by climate change is expected to exacerbate nutrient loading in the region, and, at the same time, agricultural adaptation to changing conditions is also expected to affect loading through shifting amounts and timing of fertilization and crop/watershed management practices. Quantifying these future effects and their interactions necessitates modeling both the human and natural processes as a coupled system, by pairing land use and agricultural management with hydrologic modeling. Also, compounding uncertainties arising from the complex interactions in both systems significantly limit our predictive understanding of the region's impacts.

Here, we explore how uncertainties in a coupled systems model affect nutrient loading outcomes in the Western Lake Erie watershed. To do so, we combine a watershed model (SWAT) with a newly developed agent-based model (ABM) for agricultural management decisions. We take a global sensitivity analysis approach, which includes Sobol sensitivity analysis experiments at different levels of coupling assumptions to quantify how various uncertain factors (e.g., soil moisture and crop choice) and their interactions affect nutrient loading estimates. The results quantify how complex interactions and dependencies between both systems amplify the effect of uncertainties. Insights gained from this study will have broader implications for modeling the adaptive co-evolution of human and natural systems under climate change and can inform effective management of nutrient loading in the Great Lakes Region.