The development and application of process-based hydrologic models (PBHMs) continues to be a topic of significant interest to the hydrologic community. Although numerous studies have applied PBHMs at small scales ranging from plot and field scales to small-watershed scales, the application of PBHMs to understand large-scale hydrology remains a topic that is relatively unexplored. Understanding controls on large-scale hydrology is key to climate change assessments and effective water resources management; therefore, to quantify the nature and magnitude of fluxes in regional Great Lakes watersheds, we use a new distributed hydrologic model (PAWS+CLM). Here we describe the application of the model to several large watersheds in the State of Michigan including the Grand River, Saginaw Bay, Kalamazoo and Red Cedar River watersheds and evaluate model performance by comparing model results with different types of data including point measurements of streamflows, groundwater heads, soil moisture, soil temperature as well as remotely-sensed datasets for evapotranspiration (ET) and land water thickness equivalent (GRACE). We then report a budget analysis of major hydrologic fluxes and compute annual-average fluxes due to infiltration, ET, surface runoff, sublimation, recharge, and groundwater contributions to streams etc. as percentage of precipitation and use this information to understand the inter-annual variability of these fluxes and to quantify storage in these large watersheds. After testing the model for its ability to describe hydrologic fluxes and states, we describe the development of solute transport models at the watershed scale by using a mechanistic, reactive transport modeling framework in which the advection, dispersion and reaction steps are solved using an operator-splitting strategy. The solute transport models are tested extensively using available analytical solutions for different hydrologic domains and then applied to describe transport with surface - subsurface interactions and to describe the fate and transport of fecal indicator bacteria such as Escherichia coli in the Red Cedar River watershed in Michigan. Following the successful application of the bacterial fate and transport model, we describe detailed reactive transport modules for predicting the levels of nutrients (N and P). The models are tested using available field observations for the Kalamazoo River watershed in Michigan. The watershed-scale fate and transport modules are expected to aid management by quantifying the impacts of upstream watershed influences on water quality in downstream receiving water bodies such as lakes and oceans. Together with the flow modules they represent a comprehensive suite of process-based models to describe the terrestrial hydrologic cycle coupled with vegetation/land surface and biogeochemical processes.
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