Government Grants
Business Grants
Home Owner Programs
Federal Programs
About Us
Evaluating Non-floodplain Wetlands for Flood-Risk Reduction and Nutrient Mediation in the Mississippi River Basin
Background:
The USACE and Environmental Protection Agency (EPA) are in the process of evaluating the hydrological and biogeochemical benefits of non-floodplain wetlands (NFWs).
These NFWs can mitigate down-stream flood-risk hazards through landscape water storage.
Additionally, there
is limited understanding of how these landscape water storage features interact with nutrient sources to affect stream nutrient loading and concentrations, particularly in large river basins.
There is thus a need to explicitly integrate NFWs into process-based watershed models to improve quantification of water-storage capacity and water-quality simulations.
This explicit integration is intended to quantify the influence of NFWs on large-scale flood-risk reduction and excess-nutrient yields through improved spatial representation and hydrologic modeling.
Brief Description of Anticipated Work:
The tasks identified below will be used to assess the water and nutrient yields resulting from landscape water storage capacities of NFWs in the Mississippi River Basin.
Task 1 – Collaboratively and Cooperatively Develop the Quality Assurance Project Plan.
A Quality Assurance Project Plan (QAPP) describes in comprehensive detail the necessary quality assurance, quality control, and other technical activities that must be implemented to ensure that the results of the work performed will satisfy the stated performance criteria.
Task 2 – Develop High-Resolution Inundation and Flowpath Dataset.
A high-resolution (e.g., 1-m) spatial dataset of wetland inundation extent and flowpaths will be created using available LiDAR data and imagery (aerial and/or satellite) for the Upper Mississippi River Basin, Missouri River Basin, and Ohio River Basin.
This geospatial dataset will display depressions, streams, flowpaths, inundation characterization, and drainage catchment delineations for depressions.
Data collected in this task will be consolidated into layers for use in subsequent tasks.
Task 3 – Develop Parameterized Model.
A parameterized process-based watershed model (e.g., the Soil and Water Assessment Tool, SWAT) will be initially developed for the Upper Mississippi River Basin and will be extended to the Missouri River Basin and the Ohio River Basin.
The models will be built using the dataset created in Task 2 to directly integrate small depressions, water bodies, and their catchments.
The models will be calibrated, verified, and validated over a multi-year period using available USGS, EPA, and USACE data for hydrologic flows and nutrients (e.g., nitrogen, phosphorus).
Task 4 – Quantify Watershed-Scale Water and Nutrient Yields.
Watershed-scale water and nutrient yields will be quantified across Mississippi River basins using the small water body-integrated model developed in Task 3. The results from multiple model runs will be analyzed and synthesized to quantify the nutrient and flood reduction capacity of NFWs and similar waters within the Mississippi River Basin.
Particular emphasis will be focused on yields of nitrogen (N) and phosphorous (P) species.
Task 5 – Prepare Draft Journal Manuscript.
A draft journal manuscript will be prepared that analyzes and synthesizes the results of this study.
Additional manuscripts may be created if the results warrant multiple papers to document and communicate these efforts.
The manuscript development will be coordinated with input from the ERDC and the ERDC/EPA research team.
Task 6 – Upper Mississippi River Basin Model Uncertainty Analyses.
The resource-management applicability of large spatial-scale modeling efforts is predicated on understanding data and parameter uncertainty.
Therefore, this task extensively analyzes, documents, and reports the uncertainty associated with modeling results for the Upper Mississippi River Basin.
Task 7 – Ohio River Basin Model Uncertainty Analyses.
The resource-management applicability of large spatial-scale modeling efforts is predicated on understanding data and parameter uncertainty.
Therefore, this task extensively analyzes, documents, and reports the uncertainty associated with modeling results for the Ohio River Basin.
Task 8 – Missouri River Basin Model Uncertainty Analyses.
The resource-management applicability of large spatial-scale modeling efforts is predicated on understanding data and parameter uncertainty.
Therefore, this task extensively analyzes, documents, and reports the uncertainty associated with modeling results for the Missouri River Basin.
Completion of the noted tasks will lead to the accomplishment of the below noted deliverables.
1) A Quality Assurance Project Plan (QAPP) that describes in comprehensive detail the necessary quality assurance, quality control, and other technical activities that must be implemented to ensure that the results of the work performed will satisfy the stated performance criteria.
2) Spatially explicit model layers developed and/or delivered in GIS-raster format consolidating the high-resolution inundation and flowpath data for the Upper Mississippi River Basin, Missouri River Basin, and Ohio River Basin.
3) A parameterized hydrologic model with input data layers and code for the three noted basins.
To be initiated concurrently with Task 2. Analyses and syntheses of multiple model runs characterizing the nutrient and flood reduction capacity of the Mississippi River Basin.
4) Quantified hydrologic and nutrient yields across the multiple basins, including analyses and syntheses of multiple model output to characterize the nutrient and flood reduction capacity of NFWs in the Mississippi River Basin.
5) One or more draft scientific journal manuscripts will be created to document and communicate the results of this research effort.
6) The model output uncertainty associated with potential water-quality and pollution prevention and flood-risk mitigation will be analyzed, documented, and synthesized and reports identifying watersheds with low, medium, and high uncertainty associated with modeling results for the Upper Mississippi River Basin will be delivered.
7) The model output uncertainty associated with potential water-quality and pollution prevention and flood-risk mitigation will be analyzed, documented, and synthesized and reports identifying watersheds with low, medium, and high uncertainty associated with modeling results for the Ohio River Basin will be delivered.
8) The model output uncertainty associated with potential water-quality and pollution prevention and flood-risk mitigation will be analyzed, documented, and synthesized and reports identifying watersheds with low, medium, and high uncertainty associated with modeling results for the Missouri River Basin will be delivered.
The USACE and Environmental Protection Agency (EPA) are in the process of evaluating the hydrological and biogeochemical benefits of non-floodplain wetlands (NFWs).
These NFWs can mitigate down-stream flood-risk hazards through landscape water storage.
Additionally, there
is limited understanding of how these landscape water storage features interact with nutrient sources to affect stream nutrient loading and concentrations, particularly in large river basins.
There is thus a need to explicitly integrate NFWs into process-based watershed models to improve quantification of water-storage capacity and water-quality simulations.
This explicit integration is intended to quantify the influence of NFWs on large-scale flood-risk reduction and excess-nutrient yields through improved spatial representation and hydrologic modeling.
Brief Description of Anticipated Work:
The tasks identified below will be used to assess the water and nutrient yields resulting from landscape water storage capacities of NFWs in the Mississippi River Basin.
Task 1 – Collaboratively and Cooperatively Develop the Quality Assurance Project Plan.
A Quality Assurance Project Plan (QAPP) describes in comprehensive detail the necessary quality assurance, quality control, and other technical activities that must be implemented to ensure that the results of the work performed will satisfy the stated performance criteria.
Task 2 – Develop High-Resolution Inundation and Flowpath Dataset.
A high-resolution (e.g., 1-m) spatial dataset of wetland inundation extent and flowpaths will be created using available LiDAR data and imagery (aerial and/or satellite) for the Upper Mississippi River Basin, Missouri River Basin, and Ohio River Basin.
This geospatial dataset will display depressions, streams, flowpaths, inundation characterization, and drainage catchment delineations for depressions.
Data collected in this task will be consolidated into layers for use in subsequent tasks.
Task 3 – Develop Parameterized Model.
A parameterized process-based watershed model (e.g., the Soil and Water Assessment Tool, SWAT) will be initially developed for the Upper Mississippi River Basin and will be extended to the Missouri River Basin and the Ohio River Basin.
The models will be built using the dataset created in Task 2 to directly integrate small depressions, water bodies, and their catchments.
The models will be calibrated, verified, and validated over a multi-year period using available USGS, EPA, and USACE data for hydrologic flows and nutrients (e.g., nitrogen, phosphorus).
Task 4 – Quantify Watershed-Scale Water and Nutrient Yields.
Watershed-scale water and nutrient yields will be quantified across Mississippi River basins using the small water body-integrated model developed in Task 3. The results from multiple model runs will be analyzed and synthesized to quantify the nutrient and flood reduction capacity of NFWs and similar waters within the Mississippi River Basin.
Particular emphasis will be focused on yields of nitrogen (N) and phosphorous (P) species.
Task 5 – Prepare Draft Journal Manuscript.
A draft journal manuscript will be prepared that analyzes and synthesizes the results of this study.
Additional manuscripts may be created if the results warrant multiple papers to document and communicate these efforts.
The manuscript development will be coordinated with input from the ERDC and the ERDC/EPA research team.
Task 6 – Upper Mississippi River Basin Model Uncertainty Analyses.
The resource-management applicability of large spatial-scale modeling efforts is predicated on understanding data and parameter uncertainty.
Therefore, this task extensively analyzes, documents, and reports the uncertainty associated with modeling results for the Upper Mississippi River Basin.
Task 7 – Ohio River Basin Model Uncertainty Analyses.
The resource-management applicability of large spatial-scale modeling efforts is predicated on understanding data and parameter uncertainty.
Therefore, this task extensively analyzes, documents, and reports the uncertainty associated with modeling results for the Ohio River Basin.
Task 8 – Missouri River Basin Model Uncertainty Analyses.
The resource-management applicability of large spatial-scale modeling efforts is predicated on understanding data and parameter uncertainty.
Therefore, this task extensively analyzes, documents, and reports the uncertainty associated with modeling results for the Missouri River Basin.
Completion of the noted tasks will lead to the accomplishment of the below noted deliverables.
1) A Quality Assurance Project Plan (QAPP) that describes in comprehensive detail the necessary quality assurance, quality control, and other technical activities that must be implemented to ensure that the results of the work performed will satisfy the stated performance criteria.
2) Spatially explicit model layers developed and/or delivered in GIS-raster format consolidating the high-resolution inundation and flowpath data for the Upper Mississippi River Basin, Missouri River Basin, and Ohio River Basin.
3) A parameterized hydrologic model with input data layers and code for the three noted basins.
To be initiated concurrently with Task 2. Analyses and syntheses of multiple model runs characterizing the nutrient and flood reduction capacity of the Mississippi River Basin.
4) Quantified hydrologic and nutrient yields across the multiple basins, including analyses and syntheses of multiple model output to characterize the nutrient and flood reduction capacity of NFWs in the Mississippi River Basin.
5) One or more draft scientific journal manuscripts will be created to document and communicate the results of this research effort.
6) The model output uncertainty associated with potential water-quality and pollution prevention and flood-risk mitigation will be analyzed, documented, and synthesized and reports identifying watersheds with low, medium, and high uncertainty associated with modeling results for the Upper Mississippi River Basin will be delivered.
7) The model output uncertainty associated with potential water-quality and pollution prevention and flood-risk mitigation will be analyzed, documented, and synthesized and reports identifying watersheds with low, medium, and high uncertainty associated with modeling results for the Ohio River Basin will be delivered.
8) The model output uncertainty associated with potential water-quality and pollution prevention and flood-risk mitigation will be analyzed, documented, and synthesized and reports identifying watersheds with low, medium, and high uncertainty associated with modeling results for the Missouri River Basin will be delivered.
Related Programs
Basic, Applied, and Advanced Research in Science and Engineering
Department Of Defense
Agency: Department of Defense
Office: Engineer Research and Development Center
Estimated Funding: $250,000
Office: Engineer Research and Development Center
Estimated Funding: $250,000
Who's Eligible
Obtain Full Opportunity Text:
http://grants.nih.gov/grants/guide/rfa-files/RFA-ES-20-015.html
Additional Information of Eligibility:
This opportunity is restricted to non-federal partners of the Gulf Coast Cooperative Ecosystems Studies Unit (CESU).
Full Opportunity Web Address:
http://grants.nih.gov/grants/guide/rfa-files/RFA-ES-20-015.html
Contact:
Agency Email Description:
Robyn D. Wells
Agency Email:
Date Posted:
2020-07-21
Application Due Date:
Archive Date:
2020-10-18
Social Entrepreneurship
Spotlight
Why People Buy from Social Enterprises?
The Guardian has compiled a list of responses to its latest open thread, and has announced the winner of the social enterprise gift hamper packed with presents.
Learn How to Identify and Avoid Grant Scams
