Closed · G21AS00564 · CFDA 15.808 · Discretionary
Cooperative Agreement for CESU-affiliated Partner with Great Lakes Cooperative Ecosystem Studies Unit
Federal grant opportunity posted by Geological Survey, cataloged on Grants.gov.
- up to $180K
- Award range
- Closed
- Status
- July 23, 2021
- Close date
- -
- Expected awards
The verdict
Cooperative Agreement for CESU-affiliated Partner with Great Lakes Cooperative Ecosystem Studies Unit is a closed discretionary listing from Geological Survey that offered Up to $180,000. Future funding cycles may be published under the same CFDA number.
- up to $180K
- award range
- Closed
- application status
- 15.808
- CFDA program
Opportunity snapshot. This Grants.gov announcement - Cooperative Agreement for CESU-affiliated Partner with Great Lakes Cooperative Ecosystem Studies Unit - is cataloged under number G21AS00564 and tied to CFDA assistance listing 15.808, posted by Geological Survey. Grants.gov currently shows the opportunity as closed, first posted on June 23, 2021. The funding category is Discretionary, delivered as a cooperative agreement.
Award economics. The award range on file is Up to $180,000. Cost sharing is not required, so applicants do not need to commit matching funds to be competitive on this opportunity. Federal award ranges are often upper bounds; actual allocations reflect program appropriations, the strength of the applicant pool, and the evaluation committee's scoring.
Deadline and action path. This opportunity closed on July 23, 2021. Future funding cycles may be published under the same CFDA number, so monitoring the parent program page is the most reliable way to catch re-announcements. Every Grants.gov submission requires an active SAM.gov registration and a Unique Entity ID. Review the Eligibility section below carefully, federal eligibility categories (nonprofit, state or local government, tribal, individual, educational institution, small business) have distinct registration and reporting requirements. Pre-application outreach to the listed agency contact is permitted and often welcomed, it helps clarify scope and scoring priorities. Before acting on the deadline or award figures above, verify them directly on the official Grants.gov listing, amendments can change dates and amounts after this page was last refreshed.
Award Range
Up to $180,000
Close Date
July 23, 2021
Electronically submitted applications must be submitted no later than 5:00 p.m., ET, on the listed application due date.
Posted
June 23, 2021
Instrument
Cooperative Agreement
Description
The USGS is offering a funding opportunity to a CESU partner for research in stream and reservoir water quality modeling, with a focus on temperature. Water temperature is a “master variable” for many important aquatic outcomes, including the suitability of habitat, evaporation rates, greenhouse gas exchange, and efficiency of thermoelectric energy production. Stream temperature is one of the most widely measured water characteristics by the USGS, though monitoring gaps in time and space requires modeling efforts to understand broad-scale temperature dynamics and supply decision-ready data to our stakeholders. Currently, stream and lake temperature are modeled separately, despite our knowledge that water flowing into a reservoir affects its temperature, and that reservoirs greatly impact the temperature of downstream river reaches. Further, in some places, water managers can affect downstream temperatures via reservoir releases, and understanding when to release, how much to release, and the expected water temperature changes from the release can support better decision making. The USGS and collaborators are developing process-guided machine learning models for streams and lakes that leverage the benefits of both process and machine learning models; the models are grounded in physical realism and perform well in data sparse and data rich conditions (e.g., Read et al., 2019). But key processes related to stream temperature remain unexplored or not accurately predicted or represented in the process-guided deep learning framework. These include but are not limited to: the impact of reservoir releases on downstream temperature, sub-daily prediction to accurately predict extremes, inclusion of different data types that may have lower accuracy (e.g., satellite estimated surface temperature), translation to finer resolution stream segments, prediction beneath reservoirs with varying amounts of data, and representation of certain processes that might be critical to evaluate long term change like groundwater contribution to stream temperature dynamics.
Eligibility
Grants.gov lists this opportunity under eligibility category code 25. These codes correspond to applicant types (state/local government, tribal organization, nonprofit, educational institution, individual, small business, etc.) defined in Grants.gov's own eligibility reference. See the current Grants.gov eligibility categories or check the official listing below for this opportunity's exact eligibility statement.
Official Listing on Grants.gov
View full details, application forms, and submission instructions.
Agency Contact
FAITH GRAVES fgraves@usgs.gov
Key Dates
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| Sources | the SAM.gov Assistance Listings and Grants.gov |