2013 Annual Report
1a.Objectives (from AD-416):
The objective of this cooperative research project is to accomplish and provide the deliverables that are outlined in the project work plan entitled "A Project to Develop Databases for the Hydrologic and Water Quality System (HAWQS)". That project work plan is the scope of work for the USDA-ARS's Interagency Agreement with the EPA (ARS-60-6206-9-086 / EPA-DW-12-92219401-6 & 7), and is hereby attached to this agreement as the scope of work for this agreement.
1)developing a HAWQS design that is consistent with EPA's Federal Enterprise Architecture;.
2)developing a HAWQS input database to fully support SWAT and SPARROW model applications on the NHD;.
3)aggregating input data for different spatial and temporal modeling scales;.
4)developing plans for SWAT model upgrades, HAWQS utilities and interfaces, and a model application;.
5)documenting databases; and.
6)participating in an ad-hoc interagency review team sponsored by EPA to discuss the development of HAWQS.
1b.Approach (from AD-416):
The approach is described in detail in the attached scope of work entitled "A Project to Develop Databases for the Hydrologic and Water Quality System (HAWQS)".
This project will provide databases and modeling system utilities to support the development of a large-scale water quality modeling system for national-scale economic benefit assessment. HAWQS will be designed to support a wide variety of national-scale economic benefit assessments for the US EPA Office of Water (OW), and will be an extension of the Hydrologic Unit Model of the United States (HUMUS). HUMUS has recently been updated and is being used to support an assessment of the in-stream water quality benefits of agricultural conservation practices for USDA's Conservation Effects Assessment Project (CEAP). CEAP-HUMUS presently consists of geo-spatial data for modeling hydrology, sediment, nutrients, and pesticides; pre-processors to configure SWAT model input files; and post-processors for SWAT model output. This project will extend CEAP-HUMUS by updating input data and upgrading SWAT modeling capabilities, replacing the existing stream network with the National Hydrology Dataset (NHD), and creating interfaces and data management utilities. This reorganization is necessary to support higher levels of resolution needed for EPA's economic benefit assessments and to maintain consistency across the OW's databases and data management systems.
United States Environmental Protection Agency (EPA) needs a national water quality system to determine the impacts of their environmental programs and for assessing impaired water bodies across the U.S. To meet these needs, a web-based interface was developed that utilizes the SWAT model developed by ARS. For this project, SWAT was parameterized for the Upper Mississippi, Missouri, Ohio, and Tennessee river basins using the USGS 12-digit subwatersheds as subbasins (approximately 100 Km**2). Data input files for the USGS SPARROW regression model, including connectivity, point sources, and reservoir data, were assembled for input to SWAT. Output from SPARROW was assembled to validate total annual sediment, nitrogen, and phosphorus loads at most 12-digit outlets. SWAT is currently being parameterized for all watersheds defined by the National Hydrology Dataset (approximately 3 Km**2) in the Western Lake Erie Basin. A calibration methodology has been developed to efficiently calibrate both the 12-digit and National Hydrology Dataset configurations. A web-based interface for extracting 12-digit SWAT model runs and for running SWAT on a remote server was developed. The system provides EPA and its contractors a powerful and simple tool for running national land use and climate scenarios for policy planning.
A conceptual model for fate and transport of pharmaceuticals (hormones and antibiotics) across the landscape was continued and refined. Experts in fate and transport of pharmaceuticals from Louisiana State University, Texas A&M University, and Baylor University were consulted to refine the conceptual model. The results will be used by ARS scientists to develop and parameterize the emerging contaminant module within SWAT.