College of Food, Ag & Nat Res Sci
The focus of this research is on the modeling of hydrologic and transport processes in watersheds at various spatial scales. The hydrologic processes include infiltration, surface runoff, evapo-transpiration, groundwater recharge, and groundwater discharge into streams. The scale of analysis spans from the soil pedon to the scale of a river basin.
Various approaches are used for models. One approach includes models based on the numerical solution of partial differential equations. Examples of this type of model are the Gridded Surface Subsurface Hydrology Analysis (GSSHA) tool, COMSOL-MP, GSFLOW, and the PHIM. The GSSHA model has been implemented on the supercomputer and applied to Dobbins Creek near Austin, Minnesota where the researchers are modeling the transport of sediment and nutrients out of the watershed. The COMSOL-MP model has been applied for simulation of small-scale infiltration processes, but this group intends to use it for modeling of large-scale flow and transport processes in watersheds. An alternative watershed modeling approach to these is the semi-distributed hydrologic model represented by the HSPF model. For this model the watershed is subdivided into "homogeneous" land units and mass balances are conducted on each of the land units.
One application of all these models will be to provide a conservation of mass constraint in the analysis of combined ground-based hydrologic measurements and satellite-based water volume measurements for a current research project. A second application will be to the simulation of transport of nitrate in groundwater over large areas in the southeast region of Minnesota. Machine learning algorithms will be combined with the physically-based modeling to provide for improved prediction of the distribution of water storage in watersheds, improved prediction of watershed runoff, and improved prediction of solute transport in watersheds. Supercomputer resources are needed to allow the simulation of hydrologic processes over large land surfaces while also allowing high enough spatial resolution to be able to model the processes realistically.