Closed · W81EWF-20-SOI-0025 · CFDA 12.630 · Discretionary

Data Anomaly Detection and Sediment Yield Estimation in the US Army Corps of Engineers’ Reservoir Sedimentation Information (RSI) Database

Federal grant opportunity posted by Dept. of the Army -- Corps of Engineers, cataloged on Grants.gov.

up to $40K
Award range
Closed
Status
August 24, 2020
Close date
1
Expected awards

The verdict

Data Anomaly Detection and Sediment Yield Estimation in the US Army Corps of Engineers’ Reservoir Sedimentation Information (RSI) Database is a closed discretionary listing from Dept. of the Army -- Corps of Engineers that offered Up to $40,000 across 1 expected award. Future funding cycles may be published under the same CFDA number. PlainGrants indexes 145 other opportunities from Dept. of the Army -- Corps of Engineers.

up to $40K
award range
Closed
application status
1
expected award
12.630
CFDA program

Archived opportunity record

Data Anomaly Detection and Sediment Yield Est… is closed (last close August 24, 2020). Check the agency catalog for replacement NOFOs. Dept. of the Army -- Corps of Engineers still indexes 145 other opportunities here.

According to Grants.gov (extract vintage 2026-08-10), this record reflects the officially published listing. See methodology.

Deadline tracker

Application window closed

Closed August 24, 2020

Posted Jun 22 Closes Aug 24

Expected Awards

1

Instrument

Cooperative Agreement

Description

The primary objective is to develop a method to identify erroneous data within the RSI system. Ideally, the investigator(s) will utilize machine learning algorithms to identify anomalies within the dataset. A secondary goal of the study is to use the RSI data, with supplementary data from other available data sources, to develop a machine-learning approach to estimate sedimentation rates. Research tasks should include: identifying appropriate supplemental data from other data sources; 2) identify any patterns and trends in the RSI data; 3) develop a machine-learning method to identify anomalies within the RSI data based on the composite dataset; and 4) develop a machine-learning method for estimating reservoir sedimentation rates.

Catch-all / unrestricted eligibility mark · W81EWF-20-SOI-0025

Grants.gov marks Data Anomaly Detection and Sediment Yield Est… with a catch-all / unrestricted eligibility code (Others (see official listing text)). Read the official announcement text for the real applicant filter — the code alone is not a door list. The extract does not mark applicant cost-sharing as required. Instrument: Cooperative Agreement. Funding-activity code maps to Science and Technology / R&D (ST). This eligibility-code string dominates the Dept. of the Army -- Corps of Engineers book (92 peers, 63% of 146).

Code 25
Others (see official listing text)

Codes are Grants.gov eligibility category values from the extract vintage 2026-08-10. Confirm the full eligibility statement on the official listing or the Grants.gov eligibility reference.

Official Listing on Grants.gov

View full details, application forms, and submission instructions.

View on Grants.gov

Agency Contact

Chelsea M Whitten Grants Officer Phone 601-634-4679

What to do next

Data Anomaly Detection and Sediment Yield Est… is closed; use the parent program and agency catalog for the next funding cycle.

  • Browse open federal opportunities in the same category when this listing is closed. Open opportunities
  • Look up CFDA 12.630 across all indexed listings before you commit to this opportunity alone. Eligibility finder
  • Compare award ranges across federal categories before you pick a single CFDA. All categories

Opportunity deadlines and eligibility change on Grants.gov; PlainGrants mirrors the extract and is not the submission system.

Disclaimer: This information is sourced from Grants.gov and SAM.gov and is for informational purposes only. Opportunity details, deadlines, and eligibility requirements change frequently. Always verify current information directly on Grants.gov before applying. PlainGrants is not affiliated with any federal agency.

Read our methodology - how this data is sourced, computed, and verified.

Data sourced from the SAM.gov Assistance Listings and Grants.gov. See our methodology for details. Retrieved and formatted by PlainGrants