Opportunity Information: Apply for W81EWF 24 SOI 0039
This funding opportunity supports applied research to improve how harmful algal blooms (HABs) are detected early and predicted in river systems, where blooms can stretch for hundreds of miles, persist for weeks, and create major public health, ecological, operational, and economic impacts. The U.S. Army Corps of Engineers (USACE), through the Engineer Research and Development Center (ERDC), is looking to form an interdisciplinary collaboration with a non-federal research partner to build a cost-effective and scalable framework that can be transferred beyond a single river. The overarching problem the program is trying to solve is that HABs are becoming more frequent and long-lasting, and managers need practical tools that provide early warning of developing conditions and, when possible, credible forecasts of what could happen next so they can communicate risk and take timely response actions.
A central requirement is that the proposed work be explicitly designed for scalability and transferability. Applicants must name and justify a primary riverine system that will serve as the main case study, and also identify a secondary riverine system that helps test, contextualize, or stress-check the approach. The secondary system is meant to help answer whether insights from the primary river carry over and what system features (for example, hydrology, watershed land use, nutrient regimes, flow regulation, geomorphology, climate, or monitoring constraints) must be considered when applying the framework elsewhere. The opportunity strongly encourages meaningful engagement with tribal, federal, state, and local partners who have on-the-ground knowledge of HAB history, monitoring, management decisions, and public communication needs in the selected rivers. Proposals are expected to identify these stakeholders early and describe how they will be involved during planning, data collection, interpretation, and delivery of final products.
The technical work is organized around building and then demonstrating a systematic approach for early HAB detection and prediction in rivers. The opportunity distinguishes between early warning and prediction, and asks applicants to treat them as related but separate components. Early warning is framed as near-term detection of what is happening now or has just happened, using field sampling, in situ sensors, and/or remote sensing products that may be available in real time or within hours to days. Prediction refers to modeling and forecasting what could happen under upcoming conditions. The requested "systematic approach" should lay out practical monitoring methods, the spatial layout and logic of a monitoring network (where to measure and why), and a quantitative interpretation framework that can turn raw observations into timely, understandable outputs. It also needs to address uncertainty directly, including how uncertainty will be estimated and how results and limitations will be communicated to decision-makers and potentially the public.
After designing the approach, the project must demonstrate it at field scale. That demonstration is expected to include collection of new data while also making maximum use of existing federal and state HAB-related programs, activities, and datasets, which is explicitly encouraged as a way to improve cost-effectiveness and compatibility with ongoing efforts. During the demonstration, the team should pay attention to whether the results reveal patterns in space or time that suggest where prevention-oriented actions might reduce bloom intensity or extent. Prevention is not the main goal of the call, but if the early identification and prediction work highlights actionable leverage points (for example, specific tributaries, flow conditions, seasons, or hotspots linked to bloom initiation or persistence), those observations should be captured and clearly discussed.
Deliverables center on documentation, usability, and data access. The project must produce a draft and final study report that summarizes the field-scale demonstration outcomes and explains how the framework performed in the primary river system. If the case study points to opportunities where actions could reduce HAB severity or intensity, the report should include an applications section describing those possibilities. The final output should be a complete framework for prediction and early identification of riverine HABs that incorporates lessons learned from the final case study and includes guidance on transferability, specifically what changes or considerations are needed to apply the framework to the secondary river system and, by extension, other rivers. A key compliance requirement is that all water quality data collected through the project be uploaded to the Water Quality Portal (https://www.waterqualitydata.us/), and the opportunity calls for complementary data publication so end users can readily access and use what the project generates.
Administratively, this is a discretionary funding opportunity issued as a cooperative agreement, meaning the government anticipates substantial involvement and collaboration during the project rather than a hands-off grant. The opportunity number is W81EWF 24 SOI 0039 under CFDA 12.630, with an award ceiling of $500,000 and an expectation of one award. The posting date is July 18, 2024, with an original closing date of September 16, 2024. Eligibility is restricted to non-federal partners affiliated with the Southern Appalachian Mountains and the Piedmont-South Atlantic Coast Cooperative Ecosystems Studies Units (CESUs), so applicants must fit within that CESU structure to be considered. Proposals are expected to be well-structured and specific: they must clearly state the scientific and technical questions being answered (technical objectives), specify the tasks and data needed to answer them (data quality objectives), define deliverables by task and by year, and include quantitative and qualitative success criteria for each task.Apply for W81EWF 24 SOI 0039
- The Engineer Research and Development Center in the science and technology and other research and development sector is offering a public funding opportunity titled "Prediction and Early Identification of Harmful Algal Bloom (HABs) in Riverine Systems" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 12.630.
- This funding opportunity was created on 2024-07-18.
- Applicants must submit their applications by 2024-09-16. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- Each selected applicant is eligible to receive up to $500,000.00 in funding.
- The number of recipients for this funding is limited to 1 candidate(s).
- Eligible applicants include: Others.
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Frequently Asked Questions (FAQs)
What is the purpose of this funding opportunity?
This opportunity supports applied research to improve early detection (early warning) and prediction (forecasting) of harmful algal blooms (HABs) in river systems. The goal is to produce practical tools that help managers identify developing bloom conditions sooner, communicate risk, and take timely response actions.
Which agency is offering the award?
The U.S. Army Corps of Engineers (USACE), through the Engineer Research and Development Center (ERDC), is offering this discretionary funding opportunity.
What type of funding instrument is being used?
The award will be made as a cooperative agreement. This means the government anticipates substantial involvement and collaboration during the project (not a hands-off grant relationship).
What is the opportunity number and CFDA number?
The opportunity number is W81EWF 24 SOI 0039 under CFDA 12.630.
How much funding is available?
The award ceiling is $500,000.
How many awards are expected?
The opportunity indicates an expectation of one award.
When was the opportunity posted and when does it close?
The posting date is July 18, 2024. The original closing date is September 16, 2024.
Who is eligible to apply?
Eligibility is restricted to non-federal partners affiliated with the Southern Appalachian Mountains and the Piedmont-South Atlantic Coast Cooperative Ecosystems Studies Units (CESUs). Applicants must fit within that CESU structure to be considered.
What problem is the program trying to solve?
The program targets the growing frequency and duration of riverine HABs, which can span hundreds of miles, persist for weeks, and cause public health, ecological, operational, and economic impacts. It aims to deliver credible early warning and, when possible, forecasting capability that managers can use in real decisions.
What does the opportunity mean by "early warning" versus "prediction"?
The opportunity treats them as related but separate components. Early warning focuses on near-term detection of what is happening now or has just happened using field sampling, in situ sensors, and/or remote sensing products available in real time or within hours to days. Prediction focuses on modeling and forecasting what could happen under upcoming conditions.
What is the main technical focus of the proposed work?
The project is expected to build and then demonstrate a systematic approach for early HAB detection and prediction in rivers. The approach should include practical monitoring methods, the spatial layout and logic of a monitoring network (where to measure and why), and a quantitative interpretation framework that turns observations into timely and understandable outputs.
Is scalability and transferability required?
Yes. A central requirement is that the proposed work be explicitly designed for scalability and transferability beyond a single river.
Do applicants have to select a river system?
Yes. Applicants must name and justify a primary riverine system that will serve as the main case study.
Is a second river system required?
Yes. Applicants must also identify a secondary riverine system. It is intended to help test, contextualize, or stress-check whether the approach and insights from the primary system carry over to another river.
What is the role of the secondary river system in the project?
The secondary system is meant to help answer whether results from the primary river transfer and what system features must be considered when applying the framework elsewhere. The opportunity gives examples of relevant features such as hydrology, watershed land use, nutrient regimes, flow regulation, geomorphology, climate, and monitoring constraints.
Are partnerships and stakeholder engagement expected?
Yes. The opportunity strongly encourages meaningful engagement with tribal, federal, state, and local partners who have on-the-ground knowledge of HAB history, monitoring, management decisions, and public communication needs in the selected rivers.
When should stakeholders be identified and how should they be involved?
Proposals are expected to identify stakeholders early and describe how they will be involved during planning, data collection, interpretation, and delivery of final products.
What kinds of monitoring and data sources are expected?
The early warning component may use field sampling, in situ sensors, and/or remote sensing products, including products available in real time or within hours to days. The demonstration is expected to include collection of new data while making maximum use of existing federal and state HAB-related programs, activities, and datasets.
Is using existing HAB programs and datasets encouraged?
Yes. The opportunity explicitly encourages maximizing use of existing federal and state HAB-related programs and datasets to improve cost-effectiveness and compatibility with ongoing efforts.
What does "field-scale demonstration" mean in this call?
After designing the systematic approach, the project must demonstrate it at field scale, including collection of new data and application of the monitoring and interpretation framework in the primary river system.
Does the approach need to address uncertainty?
Yes. The approach must address uncertainty directly, including how uncertainty will be estimated and how results and limitations will be communicated to decision-makers and potentially the public.
Is prevention of HABs the main goal of this opportunity?
No. Prevention is not the main goal. However, during the demonstration the team should note whether spatial or temporal patterns suggest prevention-oriented leverage points (for example, tributaries, flow conditions, seasons, or hotspots linked to bloom initiation or persistence) and clearly discuss those observations.
What are the required deliverables?
Deliverables include a draft and final study report summarizing the field-scale demonstration outcomes and explaining how the framework performed in the primary river system.
What should be included if the case study identifies opportunities to reduce HAB severity?
If the case study points to opportunities where actions could reduce HAB severity or intensity, the report should include an applications section describing those possibilities.
What is expected as the final technical output of the project?
The final output should be a complete framework for prediction and early identification of riverine HABs that incorporates lessons learned from the case study and includes guidance on transferability. This includes what changes or considerations are needed to apply the framework to the secondary river system and, by extension, other rivers.
Are there data sharing or data publication requirements?
Yes. All water quality data collected through the project must be uploaded to the Water Quality Portal (https://www.waterqualitydata.us/). The opportunity also calls for complementary data publication so end users can readily access and use project outputs.
What proposal structure and specificity does the opportunity expect?
Proposals are expected to be well-structured and specific. They must clearly state the scientific and technical questions being answered (technical objectives), specify the tasks and data needed to answer them (data quality objectives), define deliverables by task and by year, and include quantitative and qualitative success criteria for each task.
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