Task 1:

Current operational procedures for the structure’s gates include partially open settings that are not accounted for in historical rating equations. To address this, new rating equations are currently under development by a team at the University of Michigan using advanced physical and computational fluid dynamics (CFD) modeling. A key requirement for a successful proposal under this announcement is a well-defined plan for the awardee to work collaboratively and integrate their efforts with the existing University of Michigan modeling team. This partnership will be essential to ensure the resulting uncertainty analysis is robust and directly applicable to the new ratings. The principal outcome of this work will be a quantified uncertainty band for discharge rates corresponding to various gate openings and water levels. The uncertainty analysis should use the publicly available Large Lake Statistical Water Balance Model, so the uncertainty values are consistent with already operational uncertainty models for all other components of the Great Lakes water balance. This task will require a 12 month performance period so the results can be used in an upcoming study.

Depending on availability of funding, the U.S. Army Corps of Engineers may award the following optional work:

Task 2:

The development and calibration of a high-fidelity hydrodynamic model of the St. Marys River built using the Delft3D FM suite. The scope of this model be the entire St Marys River from Point Iroquois on Lake Superior to the outlet of the River near Detour Village on Lake Huron. The domain shall include the North Channel of Lake Huron to Little Current Ontario but exclude connections to Georgian Bay. The model will be fully three-dimensional, focus on the St Marys Rapids and be able to incorporate the rating equations and uncertainty analysis proposed above.  Delft3D FM must be used as the United States Government as well as partners at Environment Climate Change Canada both have access to this modeling suite. The United States Government will provide water level and velocity data to calibrate the model as well as computational resources.

Successful projects will deliver technically sound uncertainty metrics that can be immediately integrated into USACE operational models, contributing to improved ecological outcomes and more effective water resource management. As well as the ability to provide scopes of work for the additional tasks should they be funded.