The Laurentian Great Lakes are the largest system of connected surface water lakes in the world. Fresh surface and groundwater totaling approximately 27,000 km3 stored within the Great Lake Basin are a critical resource for the region and the rest of North America. However, anthropogenic contaminants, invasive species, increasing water use demands and a changing climate threaten these water resources in the Great Lakes Basin. To mitigate these threats, a better understanding of the processes controlling water resources, and hydrologic modeling frameworks capable of simulating past, current and future conditions are required. This dissertation seeks to apply both of these methods to study water quality and groundwater-surface water interactions within the state of Michigan region. Two primary research questions are addressed in this dissertation. First, what are the landscape and hydrologic factors which control stream nutrient concentrations? This question is addressed in Chapter 2 through the analysis of regional scale repeated synoptic stream chemistry sampling data and statistical analysis. Second, how are groundwater dynamics linked to Great Lakes lake levels, either indirectly through regional climate or directly through boundary condition effects? This topic is investigated in Chapters 3 and 4 using a coupled, process-based surface and groundwater model. Results from Chapter 2 suggest that landscape characteristics are a powerful predictor of stream chemistry early in the year during snowmelt, but that the landscape becomes decoupled from stream chemistry as the seasons progress. Relationships between streamflow and water chemistry during the spring and summer high flow events indicate distinct water chemistry patterns despite similar flow conditions when compared to baseflow. Chapter 3 investigates how groundwater storage changed during a period of extreme lake level variations. Simulations of surface hydrology and groundwater elevations from 2000-2023 using the Landscape Hydrology Model indicate that groundwater elevations increased along with lake elevations between 2013-2020, but that the onset of these storage increases lagged the onset of lake level changes by 2-4 years. In Chapter 4, this model is applied to investigate how coastal wetland connectivity to surface and groundwater changes as lake and groundwater elevations fluctuate. Modeling analysis suggests that rising groundwater elevations between 2000-2023 increased the amount of connected coastal wetland area by 18% when compared to estimates of surface water connectivity change alone. Finally, Chapter 5 provides a summary and proposes a method for more closely integrating field data collection and hydrologic models to groundwater nutrient transport through the use of a model-experiment framework.
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