# Improved Harmful Algal Blooms Prediction with Hybrid Models

Source: https://welltoldgrants.com/grants/w81ewf-24-soi-0041-improved-harmful-algal-blooms-prediction-with-hybrid-models/  
Official notice: https://www.grants.gov/search-results-detail/355494

> Engineer Research and Development Center offered grants of up to $142,324 to the applicants described in the notice. It expected to make one award worth $212,770 in total. Applications closed on September 16, 2024.

| Field | Value |
|---|---|
| Opportunity number | W81EWF-24-SOI-0041 |
| Agency | Engineer Research and Development Center |
| Status | Forecast |
| Deadline | September 16, 2024 |
| Award ceiling | $142,324 |
| Award floor | not stated |
| Expected awards | 1 |
| Total funding | $212,770 |
| Cost sharing | not required |
| Assistance Listings | 12.630 |

## Who can apply

- 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).

## 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.

## Questions people ask

### Is W81EWF-24-SOI-0041 still open?

No. It closed on September 16, 2024. A newer notice is open: W912HZ26S0001, closes January 1, 2027 (55 days left).

### Who can apply for Improved Harmful Algal Blooms Prediction with Hybrid Models?

Engineer Research and Development Center accepted applications from the applicants described in the notice. The notice adds further conditions, so read its eligibility section.

### What is the deadline for Improved Harmful Algal Blooms Prediction with Hybrid Models?

Closed September 16, 2024. Applications are no longer accepted; the program's newer notices are on this page when there are any.

### How much funding is available?

Awards of up to $142,324 each. About $212,770 in total for one award.

### Who has won Basic, Applied, and Advanced Research in Science and Engineering grants before?

The largest recipients over five fiscal years were Battelle Memorial Institute, Msi Stem Research & Development Consortium, University of California San Diego. The program made 1,101 awards worth $1.3 billion in that time.