Opportunity ID: 352822

General Information

Document Type: Grants Notice
Funding Opportunity Number: G24AS00297
Funding Opportunity Title: Cooperative Agreement for CESU-affiliated Partner with North Atlantic Coast Cooperative Ecosystem Studies Unit
Opportunity Category: Discretionary
Opportunity Category Explanation:
Funding Instrument Type: Cooperative Agreement
Category of Funding Activity: Science and Technology and other Research and Development
Category Explanation:
Expected Number of Awards:
Assistance Listings: 15.808 — U.S. Geological Survey Research and Data Collection
Cost Sharing or Matching Requirement: No
Version: Synopsis 1
Posted Date: Mar 06, 2024
Last Updated Date: Mar 06, 2024
Original Closing Date for Applications: Apr 08, 2024 Electronically submitted applications must be submitted no later than 5:00 p.m., ET, on the listed application due date.
Current Closing Date for Applications: Apr 08, 2024 Electronically submitted applications must be submitted no later than 5:00 p.m., ET, on the listed application due date.
Archive Date:
Estimated Total Program Funding:
Award Ceiling: $400,000
Award Floor: $80,000

Eligibility

Eligible Applicants: Others (see text field entitled “Additional Information on Eligibility” for clarification)
Additional Information on Eligibility: This financial assistance opportunity is being issued under a Cooperative Ecosystem Studies Unit (CESU) Program. CESU’s are partnerships that provide research, technical assistance, and education. Eligible recipients must be a participating partner of the North Atlantic Coast Cooperative Ecosystem Studies Unit (CESU) Program.

Additional Information

Agency Name: Geological Survey
Description: The US Geological Survey is offering a funding opportunity to a CESU partner for research on the classification of riverbed substrate for the Colorado River in Grand Canyon.Scientists at the U.S. Geological Survey’s (USGS) Southwest Biological Science Center, Grand Canyon Monitoring and Research Center (GCMRC) conduct a range of studies on the Colorado River in Grand Canyon that are used to inform U.S. Department of the Interior decisions about management of the Colorado River and Glen Canyon Dam. Many of those studies involve characterizing the riverbed and monitoring erosion and deposition of river sediments. These studies involve mapping river bathymetry with high-resolution multibeam sonar to develop detailed bathymetric maps of riverbed elevation. The acoustic backscatter that is simultaneously collected during these measurements may be used to map riverbed subtrate composition, but processing these data requires application of advanced machine learning methods. Methods and a workflow for processing these data have been developed by USGS scientists and cooperators over a period of many years. This opportunity seeks collaboration in adapting and applying the latest machine learning tools for riverbed substrate classification to existing datasets collected by GCMRC. This opportunity will also involve analysis of the resulting substrate classifications in relation to geomorphic characteristics of the Colorado River in Grand Canyon.
Link to Additional Information:
Grantor Contact Information: If you have difficulty accessing the full announcement electronically, please contact:

FAITH GRAVES
fgraves@usgs.gov
Email:fgraves@usgs.gov

Version History

Version Modification Description Updated Date

Folder 352822 Full Announcement-Full Announcement -> CESU FUNDING OPPORTUNITY.pdf

Packages

Agency Contact Information: FAITH GRAVES
fgraves@usgs.gov
Email: fgraves@usgs.gov
Who Can Apply: Organization Applicants

Assistance Listing Number Competition ID Competition Title Opportunity Package ID Opening Date Closing Date Actions
15.808 G24AS00297 Cooperative Agreement for CESU-affiliated Partner with North Atlantic Coast Cooperative Ecosystem Studies Unit PKG00285213 Mar 06, 2024 Apr 08, 2024 View

Package 1

Mandatory forms

352822 SF424_4_0-4.0.pdf

352822 ProjectNarrativeAttachments_1_2-1.2.pdf

352822 SF424A-1.0.pdf

352822 SF424B-1.1.pdf

2025-07-12T07:49:32-05:00

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