Opportunity Information: Apply for G19AS00049
The U.S. Geological Survey (USGS), within the Department of the Interior, released a discretionary research funding opportunity under the Cooperative Ecosystem Studies Unit (CESU) network, specifically the Colorado Plateau CESU. The opportunity is issued as a cooperative agreement, meaning the work is expected to be carried out in close coordination with USGS and to involve substantial federal involvement during the project. The program focus falls under Science and Technology and other Research and Development (CFDA 15.808). The funding announcement is identified as G19AS00049, was created on April 15, 2019, and originally closed on April 29, 2019. USGS anticipated making a single award, with an award ceiling of $115,768.
The purpose of the project is to continue an ongoing investigation that combines remotely sensed satellite imagery with hydrological and geological datasets to better map the potential for groundwater resources. In practical terms, the funded partner would help integrate multiple data streams (satellite-derived information alongside ground-based or compiled hydrologic and geologic inputs) to produce decision-support mapping products. The emphasis is on developing digital image-based maps for a defined Area of Interest (AOI). These maps are intended to depict where shallow groundwater is more likely to be available across the study sites, supporting improved understanding of groundwater potential and, by extension, better-informed planning or field investigations.
A key deliverable described in the opportunity is the continuation and refinement of a modeling and mapping workflow that produces a Potential Shallow Ground Water (PSGW) product. The PSGW model is meant to translate the combined remote sensing and Earth science inputs into a spatial representation of relative groundwater availability near the surface. Alongside the PSGW work, the project also includes development of a second model and associated map product focused on Potential Infiltration (PI). The PI map is intended to characterize where infiltration is more likely to occur, which is relevant because infiltration patterns influence recharge processes and can help interpret or predict shallow groundwater presence and sustainability.
Eligibility is limited to CESU partners, with the notice listing eligible applicants generally as "Others" and pointing applicants to additional eligibility language in the full announcement. The intent is to leverage the CESU partnership framework to support collaborative research that aligns with USGS priorities, using advanced remote sensing techniques combined with hydrologic and geologic analysis to produce actionable, spatially explicit groundwater-related maps for the AOI.Apply for G19AS00049
- The Department of the Interior, U. S. Geological Survey in the science and technology and other research and development sector is offering a public funding opportunity titled "Cooperative Ecosystem Studies Unit, Colorado Plateau CESU" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 15.808.
- This funding opportunity was created on Apr 15, 2019.
- Applicants must submit their applications by Apr 29, 2019. (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 $115,768.00 in funding.
- The number of recipients for this funding is limited to 1 candidate(s).
- Eligible applicants include: Others (see text field entitled Additional Information on Eligibility for clarification).
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Frequently Asked Questions (FAQs)
What agency is offering this funding opportunity?
This opportunity is offered by the U.S. Geological Survey (USGS) within the Department of the Interior.
What type of award is being offered?
The announcement describes the award as a cooperative agreement. This indicates the project is expected to be performed in close coordination with USGS and to include substantial federal involvement during the work.
What program or topic area does this opportunity fall under?
The program focus is described as Science and Technology and other Research and Development, and it is associated with CFDA 15.808.
What is the funding announcement ID?
The funding announcement is identified as G19AS00049.
When was the funding announcement created?
The announcement was created on April 15, 2019.
What was the original closing date for applications?
The opportunity originally closed on April 29, 2019.
How many awards did USGS anticipate making?
USGS anticipated making a single award.
What is the maximum award amount (award ceiling)?
The award ceiling listed in the opportunity is $115,768.
Which CESU network is associated with this opportunity?
The opportunity is issued under the Cooperative Ecosystem Studies Unit (CESU) network, specifically the Colorado Plateau CESU.
Who is eligible to apply?
Eligibility is limited to CESU partners. The notice lists eligible applicants generally as "Others" and indicates that additional eligibility language is included in the full announcement.
What is the overall purpose of the project?
The project is intended to continue an ongoing investigation that combines remotely sensed satellite imagery with hydrological and geological datasets to better map the potential for groundwater resources.
What kind of work is the funded partner expected to perform?
The funded partner is expected to help integrate multiple data streams, including satellite-derived information and ground-based or compiled hydrologic and geologic inputs, to produce decision-support mapping products.
What is the main emphasis of the mapping work?
The emphasis is on developing digital image-based maps for a defined Area of Interest (AOI).
What are the maps intended to show?
The maps are intended to depict where shallow groundwater is more likely to be available across the study sites, supporting improved understanding of groundwater potential and better-informed planning or field investigations.
What is the PSGW product mentioned in the opportunity?
PSGW refers to a Potential Shallow Ground Water product. The project calls for continuation and refinement of a modeling and mapping workflow that produces this PSGW output.
What does the PSGW model represent?
The PSGW model is intended to translate combined remote sensing and Earth science inputs into a spatial representation of relative groundwater availability near the surface.
Is there a second model or map product included in the scope?
Yes. In addition to PSGW, the project includes development of a second model and associated map product focused on Potential Infiltration (PI).
What is the purpose of the Potential Infiltration (PI) map?
The PI map is intended to characterize where infiltration is more likely to occur. Infiltration patterns matter because they influence recharge processes and can help interpret or predict shallow groundwater presence and sustainability.
Why does the announcement emphasize remote sensing?
The project is centered on combining remotely sensed satellite imagery with hydrologic and geologic datasets to produce actionable, spatially explicit groundwater-related maps for the AOI.
What does "substantial federal involvement" mean in this context?
Because the award is a cooperative agreement, the work is expected to be carried out in close coordination with USGS, with meaningful participation from the federal side during the project (as described in the opportunity summary).
What is meant by "decision-support mapping products"?
In this opportunity, decision-support mapping products refer to map outputs derived from integrated satellite, hydrologic, and geologic data that can support understanding of groundwater potential and inform planning or field investigations within the AOI.
What is the intended benefit of integrating satellite imagery with hydrologic and geologic datasets?
The integration is intended to improve mapping of where shallow groundwater may be available, using complementary information sources to generate spatial products that are more informative than any single dataset alone.
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