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United States Department of Agriculture

Agricultural Research Service


Location: Grassland, Soil and Water Research Laboratory

2009 Annual Report

1a.Objectives (from AD-416)
The objectives of this study are to:.
1)Compile environmental, water quality, and agronomic data from the Leon River and Riesel watersheds and deliver to the STEWARDS data system in a compatible format;.
2)Measure and quantify hydrologic and water quality effects of conservation practices and management at the field, farm, and sub-watershed scale within the Leon River and Riesel watersheds;.
3)Validate, quantify uncertainties in model output, and conduct land use and climate analyses with the SWAT and ALMANAC models at field, farm, and watershed scales;.
4)Provide proper output and linkages from SWAT to economic models to ensure appropriate environmental and crop yield output at spatial scales compatible with selected economic models; and.
5)Extract relevant components from the ALMANAC and SWAT models for integration into the Object Modeling System (OMS) and assist in the verification of the ALMANAC and SWAT models for major agricultural regions.

1b.Approach (from AD-416)
For Objective 1 we will provide data to the STEWARDS data system from the Leon River and Riesel watersheds. Data will include environmental and agronomic data, measured water quality data, and SWAT output. Socio-economic data will not be collected. Our role in Objective 2 involves quantifying the effects of conservation practices (with emphasis on nutrient and manure management) in the Leon River and Riesel watersheds. It also involves quantifying nutrient and manure management of grasses and pastures for bio-fuels at three field sites in Texas. Although several models are considered in the overall CEAP Objective 3, our focus is solely on the SWAT and ALMANAC models. SWAT will be evaluated and uncertainty analysis will be performed on varying spatial scales in the Leon and Riesel watersheds. Model development will include:.
1)river basin scale processes in SWAT,.
2)plant growth and land management processes in ALMANAC, and.
3)linkage with remotely sensed data. Our role in Objective 4 is to provide proper output and linkages from the SWAT model to economic models. We will ensure appropriate environmental and crop yield output from SWAT at spatial scales that are compatible with the selected economic models. For Objective 5, we will extract relevant components from SWAT and ALMANAC model for integration into the Object Modeling System (OMS).

3.Progress Report
This report documents research for the project Development of Models and Conservation Practices for Water Quality Management and Resource Assessments. Data collection and public outreach have substantially advanced for two projects investigating application of poultry litter and proper fertilizer management. Experimental results on effects of conservation practices in the Leon River and Riesel watersheds have been compiled and are being analyzed. The compartmentalized version of the ALMANAC (Agricultural Land Management Alternatives with Numerical Assessment Criteris) model is being incorporated into the SWAT (Soil and Water Assessment Tool) model to improve SWAT's plant simulation components. Work is progressing on the SWAT and ALMANAC models, to provide linkages to models with different application and scales.

1. Improved guidelines for applying poultry litter: Poultry litter contains significant amounts of nitrogen and phosphorus which are nutrients essential to plant growth. If excess poultry litter is applied to the land as fertizer, nitrogen and phosphorus can run off into streams and lakes making them unsuitable for fishing, swimming, and drinking. Thus, poultry litter application rates for cultivated crops need to maximize the economic return while minimizing the environmental impact. This research defined the optimum annual application rate to accomplish both objectives. The results of this research, summarized in a fact sheet and a published manuscript, have been distributed to more than 250 local producers and third party applicators to assist them in determining appropriate litter application rates. Numerous scientists and extension personnel are also using these results in their education, outreach, and research programs to balance agronomic and economic concerns. This information will help prevent litter-related water quality degradation in the region and promote economic and environmental sustainability.

2. Improved model to simulate water quality in large river basins: The U.S. Environmental Protection Agency (US EPA) and state environmental agencies have identified approximately 15,000 water-quality-impaired water bodies in the U.S. Agricultural production has been identified as a major nonpoint source of water contamination. At the same time, USDA is mandated to conduct a thorough analysis of the risks and benefits of USDA's conservation programs to human health, safety, and environment; determine alternative ways of reducing risk; and conduct cost-benefits assessments. New algorithms were developed for a river basin scale model called SWAT (Soil and Water Assessment Tool) to simulate carbon dynamics in soil, landscape routing, septic tanks, and urban runoff and management practices. The new routines are currently being tested at watersheds across the United States. To assess the environmental impact of USDA conservation programs, SWAT was applied and validated in the Upper Mississippi River Basin (490,000 Km**2). Scenario runs are being used to target efficient placement of practices and guide USDA conservation policy. The model is also being used in over 30 states by US EPA and is impacting the selection of land management to resolve water quality concerns.

3. Parameterization of the ALMANAC (Agricultural Land Management Alternatives with Numerical Assessment Criteria) Model for Grasses: Simulation of the growth and yield of grasses for conservation and biofuels assessment requires an accurate, realistic simulation model that describes various grass types as well as competition among species when simulating complex grass mixtures. The ALMANAC model was parameterized for the major improved grass species and several common native grasses, including the major grasses for biofuel. This involved field measurements to determine potential leaf area index, optimum nutrient concentrations, and radiation use efficiency. The model was parameterized for switchgrass cultivars in Texas and in the Upper Midwest, and validated using measured data at a wide range of latitudes, from Texas to North Dakota and Wisconsin. Parameters derived for these important grass species, when incorporated into the ALMANAC model, provided realistic simulations of grass growth and productivity in a wide range of soils and climatic conditions. The model is being used by the Department of Energy and university scientists to assess potential biofuel productivity and sustainability of grasslands across the United States.

6.Technology Transfer

Number of Web Sites Managed1
Number of Other Technology Transfer2

Review Publications
Rossi, C.G., Dybala, T.J., Moriasi, D.N., Arnold, J.G., Amonett, C., Marek, T. 2008. Hydrologic calibration and validation of the Soil and Water Assessment Tool for the Leon River watershed. Journal of Soil and Water Conservation. 63(6):533-541.

Harmel, R.D., Rossi, C.G., Dybala, T., Arnold, J.G., Potter, K.N., Wolfe, J., Hoffman, D. 2008. Conservation Effects Assessment Project research in the Leon River and Riesel watersheds. Journal of Soil and Water Conservation. 63(6):453-460.

Harmel, R.D., Qian, S., Reckhow, K., Casebolt, P. 2008. The MANAGE database: Nutrient load and site characteristic updates and runoff concentration data. Journal of Environmental Quality. 37(6):2403-2406.

Kiniry, J.R., Schmer, M.R., Vogel, K.P., Mitchell, R. 2008. Switchgrass biomass simulation at diverse sites in the northern Great Plains of the U.S. BioEnergy Research. 1(3-4):259-264.

Toor, G.S., Harmel, R.D., Haggard, B.E., Schmidt, G. 2008. Evaluation of regression methodology with low-frequency water quality sampling to estimate constituent loads for ephemeral watersheds in Texas. Journal of Environmental Quality. 37(5):1847-1854.

Wachal, D.J., Harmel, R.D., Banks, K.E., Hudak, P.F. 2008. Evaluation of WEPP for runoff and sediment yield prediction on natural gas well sites. Transactions of the ASABE. 51(6):1977-1986.

Harmel, R.D., Smith, D.R., King, K.W., Slade, R.M. 2009. Estimating Storm Discharge and Water Quality Data Uncertainty: A Software Tool for Monitoring and Modeling Applications. Journal of Environmental Modelling and Software. 24(7):832-842.

Wachal, D.J., Banks, K.E., Hudak, P.F., Harmel, R.D. 2009. Modeling erosion and sediment control practices in RUSLE 2.0: A management approach for natural gas well sites in Denton County, TX, USA. Environmental Geology. 56(8):1615-1627.

Veith, T.L., Sharpley, A.N., Arnold, J.G. 2008. Modeling a Small, Northeastern Watershed with Detailed Field-Level Data. Transactions of the ASABE. 51(2):471-483.

Weltz, M.A., Jolley, L., Nearing, M.A., Stone, J.J., Goodrich, D.C., Pierson Jr, F.B., Speath, K., Kiniry, J.R., Arnold, J.G., Bubenheim, D., Hernandez, M., Wei, H. 2008. Assessing the benefits of grazing land conservation practices. Journal of Soil and Water Conservation. 63:214-217.

Moriasi, D.N., Arnold, J.G., Vazquez-Amabile, G.G., Engel, B.A., Rossi, C.G. 2009. Incorporation of a new shallow water table depth algorithm into SWAT 2005. Transactions of the ASABE. 52(3):771-784.

Last Modified: 4/16/2014
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