Automated Organization and Analysis of Hydrologic and Infrastructure Data | W81EWF 24 SOI 0034

Opportunity Information: Apply for W81EWF 24 SOI 0034

The U.S. Army Corps of Engineers Engineer Research and Development Center (ERDC), through its Environmental Laboratory Ecohydrology Team, is seeking one cooperative agreement proposal to build a practical software capability that can rapidly organize and analyze hydrologic and water infrastructure data. The core need is automation: ERDC wants methods that can take widely used stream gauge datasets and dam/reservoir infrastructure datasets and automatically connect them to a river network using geospatial relationships. The intent is to support faster, more repeatable landscape and water-resource assessments, especially in remote or data-limited regions where on-the-ground knowledge and field measurements may be sparse.

The project centers on turning disparate hydrologic observations and infrastructure records into a coherent “node and edge” network model tied to authoritative hydrography layers. In plain terms, gauges, dams, and reservoirs would become nodes, river reaches would become edges, and everything would be positioned and linked based on location relative to a chosen waterway dataset such as the USGS National Hydrography Dataset or HydroRIVERS. Example input sources named in the opportunity include USGS stream gauge data, the European water archive, and Global Data Runoff Center for discharge information, along with the USACE National Inventory of Dams and NASA’s Global Reservoir and Dam database for infrastructure. ERDC is looking for a workflow or program that can ingest these kinds of sources, reconcile them with a river network, and produce a usable connected network representation for analysis.

Beyond organizing the data, the tool is expected to provide analysis and visualization features that let users explore and compute hydrologic metrics directly on the network and its associated time series. A highlighted analytical requirement is baseflow separation (a common technique for splitting streamflow into groundwater-fed “baseflow” versus faster runoff components), but the opportunity is broader than that. ERDC wants an extensible approach: a plug-in for simple baseflow separation should be developed as an initial capability, and then a generalized plug-in architecture should be created so additional hydrologic calculation modules can be added later without rewriting the whole system. Visualization is also part of the deliverable, implying the software should help users see the network, nodes, edges, and associated time series in a way that supports interpretation and decision-making rather than just producing raw tables.

ERDC lays out specific research and development objectives that describe what success looks like. These include: (1) creating the underlying algorithm that generates a connected network from geospatial inputs; (2) generalizing that algorithm so it works across multiple gauge, infrastructure, and hydrography databases rather than being hardwired to one source; (3) implementing a baseflow separation plug-in that runs across the network’s time series data; (4) designing the broader plug-in framework to support other hydrologic computations; and (5) building data visualization capabilities for the network and its attributes. The end product is expected to be maintained in a web-based code repository, and the methods and tools should be documented in at least one peer-reviewed publication, signaling that ERDC wants both an operational tool and publishable technical rigor.

The public benefit case focuses on improving the accuracy and timeliness of waterway information for real-world challenges like drought, water scarcity, and flooding. ERDC notes that existing maps and datasets often do not fully capture water occurrence and flows, which can lead to errors in estimating where and how much water is present. By enabling more detailed and structured time series analysis across a river network, the resulting capability is intended to fill information gaps and produce better assessments of flood and drought conditions. That improved situational awareness is framed as supporting stronger mitigation measures and planning, presumably by helping analysts move more quickly from scattered data sources to actionable hydrologic indicators.

Administratively, this is a discretionary science and technology research and development opportunity offered as a cooperative agreement by the Department of the Army, U.S. Army Corps of Engineers. The funding opportunity number is W81EWF 24 SOI 0034. The announced award ceiling is $75,000, with ERDC expecting to make one award. The original closing date listed is 2024-08-30, and the opportunity was created on 2024-07-10. Eligibility is restricted: only non-federal partners of the Colorado Plateau Cooperative Ecosystems Studies Unit (CESU) may apply, which effectively narrows the applicant pool to organizations already participating in that CESU partnership structure.

• The Dept. of the Army -- Corps of Engineers in the science and technology and other research and development sector is offering a public funding opportunity titled "Automated Organization and Analysis of Hydrologic and Infrastructure Data" 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 2024-07-10.
• Applicants must submit their applications by 2024-08-30. (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 $75,000.00 in funding.
• The number of recipients for this funding is limited to 1 candidate(s).
• Eligible applicants include: Others.

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