Grants / Department of Defense / Engineer Research and Development Center

W81EWF-24-SOI-0041: Improved Harmful Algal Blooms Prediction with Hybrid Models

Closed Closed September 16, 2024 Opportunity W81EWF-24-SOI-0041 ☆ Save

This grant is closed. A newer notice from the same program is open now: ERDC Broad Agency Announcement (W912HZ26S0001). Status: Closes January 1, 2027 (55 days left). It is in our archive of Engineer Research and Development Center notices from 2024.

• Award ceiling$142,324
• Total funding$212,770
• Expected awards1
• Cost sharingNot required
• Funding typeCooperative Agreement

Key dates

Who can apply

This opportunity was open to the applicants described in the notice.

• Others (see text field entitled "Additional Information on Eligibility" for clarification)

This opportunity is restricted to non-federal partners of the Pacific Northwest Cooperative Ecosystems Studies Unit (CESU).

Is this a realistic fit?

• Past Basic, Applied, and Advanced Research in Science and Engineering awards averaged $1.1 million; this notice allows up to $142,324 per award.
• Most of the program's money (69% over five years) went to colleges and universities.
• No cost sharing or match is required.

What the grant funds

Methods to quantify and predict vulnerability to harmful algal blooms (HABs) has not been developed for most lakes and reservoirs in the U.S. (and the world). This limits the ability for water quality stakeholders to 1) avoid costly emergency events, 2) efficiently design source water monitoring, 3) evaluate the impact of interventions, and 4) maintain trust with the public. Current approaches for detection and prediction of harmful algal blooms rely on infrequent satellite imagery and/or water samples, and provide predictions only at specific sites (i.e., where samples are taken). Furthermore, the models used to make predictions do not typically provide an ability to diagnose the specific drivers of HABs, beyond weather variables. The challenges confronting water quality stakeholders like the USACE are to 1) improve the spatial and temporal resolution of HAB predictions; 2) have the ability to diagnose the causes of HABs in managed reservoirs. The overarching goal of this project is to develop and test a hybrid modeling system that combines watershed, hydrodynamic and machine learning models to provide accurate predictions of HABs in USACE reservoirs, at high spatial and temporal resolution. The products that this project will create include: 1) A hybrid modeling system for making accurate predictions of HABs at USACE reservoirs, improving on the state-of-the-art in terms of spatial coverage and temporal frequency; 2) Demonstrated utility of the hybrid modeling system for identifying the drivers of HABs, and for estimating the efficacy of interventions; Documentation and training to enable deployment of the hybrid modeling system at additional USCAE reservoirs.

Category: Science and Technology and other Research and Development.

Applying now

This notice no longer takes applications. Apply under the newer notice, W912HZ26S0001, which is open now.

The notice on Grants.gov keeps its full text and attachments, which is useful for planning a resubmission.