This project will address United States Environmental Protection Agency (EPA) comments on the preliminary draft Total Maximum Daily Load (TMDL) study and Minnesota Pollution Control Agency (MPCA) comments on the pre-public notice draft TMDL study and Watershed Restoration and Protection Strategy (WRAPS) report, and produce the public notice draft TMDL study and the public notice draft WRAPS report ready for public review and comment. Conduct one public meeting for each watershed to present public notice drafts of the TMDL study and WRAPS report for each watershed.
This project will construct, calibrate, a set of HSPF watershed models covering the entire area of the Lake of the Woods drainage, including the Rainy River watershed. The consultant will produce HSPF models that can readily be used to provide information to support conventional parameter TMDLs. The consultant will clearly demonstrate that these models generate predicted output timeseries for hydrology which are consistent with available sets of observed data.
This project will maximize the utility and usefulness of three HSPF models that have been constructed and calibrated for hydrology. The contractor will identify and reduce parameterization errors in the following three HSPF models: 1) Buffalo River Watershed, 2 ) Thief River Watershed, 3) Bois de Sioux-Mustinka Watersheds. This will result, not only in a better hydrology calibration, but will also improve each of the models’ ability to more accurately estimate sediment and pollutant loads and concentrations.
This project will finalize the Hydrologic Simulation Program FORTRAN (HSPF) watershed model construction and complete the calibration/validation process. The consultant will produce an HSPF watershed model that can readily be used to provide information to support conventional parameter TMDLs. The consultant will clearly demonstrate that this model generates predicted output timeseries for hydrology, sediment, nutrients, and dissolved oxygen which are consistent with available sets of observed data.