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
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 analyzed. After the compartmentalized version of the ALMANAC (Agricultural Land Management Alternatives with Numerical Assessment Criteris) model was incorporated into the SWAT (Soil and Water Assessment Tool) model to improve SWAT's plant simulation components, the ALMANAC model has been extensively tested against NRCS Ecological Site Descriptions in the Intermountain West. Work is continuing to progress 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 fertilizer, nitrogen and phosphorus can run off into streams and lakes, degrading water quality. 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 contributor to 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 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 identify places where conservation practices such as conservation tillage, terraces, and CRP (Conservation Reserve Program) will be most efficient and provide the greatest benefits. This will help guide USDA conservation policy. The model is also being used in more than 30 states by US EPA and is impacting the selection of land management alternatives to resolve water quality concerns.
3. Development of key parameters to enable the ALMANAC (Agricultural Land Management Alternatives with Numerical Assessment Criteria) Model to simulate grasslands. 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 several western rangeland plant species and some new varieties of the major improved grass species, including the major grasses for biofuel. This involved field measurements to determine potential leaf area index, optimum nutrient concentrations, and potential dry matter production. Switchgrass, the major perennial grass species used for biofuel feedstock in the U.S., was given special consideration. 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.
Kiniry, J.R., MacDonald, J.D., Kemanian, A.R., Watson, B., Putz, G., Prepas, E.E. 2008. Plant growth simulation for landscape-scale hydrologic modelling. Hydrological Sciences Journal. 53(5):1030-1042.