Cooperative Ecosystem Studies Unit, Great Lakes Northern Forests CESU | G20AS00139

Opportunity Information: Apply for G20AS00139

This funding opportunity, titled "Cooperative Ecosystem Studies Unit, Great Lakes Northern Forests CESU" (Funding Opportunity Number G20AS00139), was issued by the Department of the Interior, U.S. Geological Survey (USGS) as a discretionary science and technology research award. It is structured as a cooperative agreement, meaning the project is intended to be carried out in close collaboration with USGS rather than as a simple pass-through grant. The opportunity was created on August 17, 2020, with an original closing date of September 7, 2020. USGS anticipated making a single award, with an award ceiling of $110,000, and eligibility was limited to a CESU partner under the Great Lakes Northern Forests Cooperative Ecosystem Studies Unit framework (listed under "Others" with additional eligibility details referenced in the full notice).

The core purpose of the project is to advance research and modeling capabilities for water temperature across connected stream and reservoir systems. USGS frames water temperature as a "master variable" because it influences a wide range of critical aquatic and operational outcomes, including habitat suitability for fish and other organisms, evaporation rates, greenhouse gas exchange at the water surface, and the efficiency of thermoelectric power generation that depends on cooling water. While USGS collects extensive stream temperature observations nationwide and stream temperature is among the most commonly measured water quality parameters, those measurements still have substantial gaps across both time and geography. Because decision makers often need continuous, spatially complete information, USGS highlights modeling as essential for filling monitoring gaps and producing decision-ready temperature estimates at broad scales.

A central problem identified in the notice is that stream and lake (including reservoir) temperature are often modeled separately, even though the systems are physically linked. Water entering a reservoir can significantly shape reservoir thermal conditions, and reservoirs in turn can strongly alter downstream river temperatures. In many managed systems, reservoir operators can influence downstream temperatures through the timing, volume, and depth of releases. Having credible tools to predict how release decisions translate into downstream temperature changes can directly support water management decisions, especially where temperature targets relate to ecological protection, regulatory compliance, or operational constraints.

USGS notes that it and its collaborators are developing process-guided machine learning approaches for both streams and lakes. The intent is to combine the strengths of physically based (process) models with the predictive performance and flexibility of machine learning, producing models that remain grounded in physical realism while still performing well in both data-rich and data-sparse settings. The opportunity references prior work in this area (for example, Read et al., 2019) as an illustration of the modeling philosophy. The key research gap this award aims to address is that, despite progress on separate stream and lake temperature models, USGS has not yet developed an integrated model of an entire stream network that captures the coupled dynamics between streams and reservoirs in a unified framework. In practical terms, the funded work is meant to help move from parallel modeling efforts toward a connected modeling system that can represent how reservoirs and river networks interact thermally, improving predictive capability and supporting management decisions involving reservoir operations and downstream temperature outcomes.

• The Department of the Interior, U. S. Geological Survey in the science and technology and other research and development sector is offering a public funding opportunity titled "Cooperative Ecosystem Studies Unit, Great Lakes Northern Forests CESU" and is now available to receive applicants.
• Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 15.808.
• This funding opportunity was created on Aug 17, 2020.
• Applicants must submit their applications by Sep 07, 2020. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
• Each selected applicant is eligible to receive up to $110,000.00 in funding.
• The number of recipients for this funding is limited to 1 candidate(s).
• Eligible applicants include: Others (see text field entitled Additional Information on Eligibility for clarification).

Apply for G20AS00139

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