1a. Objectives (from AD-416):
The over-arching goals of this project are: 1) to enhance our Laboratory's modeling capacity and breadth with state-of-the-art, scientifically sound decision support tools used in National and International assessments, decision-making, and policy, and 2) to develop and/or evaluate agricultural management practices in terms of profitability, productivity, and environmental impact. Thus, based on recent and expected decision support requests and the need to increase profitability, maintain productivity, and protect ecological resources in agriculture, we will focus specifically on the following objectives during the next five years. Objective 1: Analyze rangeland and cultivated biofuel productivity in various climatic regions in light of regional variations in water use and availability and mitigation alternatives for potential adverse impacts. Subobjective 1A: Improve ALMANAC simulation of bioenergy crops including sugarcane and perennial grass ecotypes in environments in the continental US and the Pacific Rim by using newly collected field data to derive plant parameters required to validate simulations. Objective 2: Improve on-farm decision-making related to conservation practices and their effects on water quantity and quality by enhancing field-scale predictive tools. Subobjective 2A: Assess water quality impacts of in-house windrow composting of poultry litter prior to land application. Subobjective 2B: Develop a simplified modeling system (interface) based on SWAT to support the development and evaluation of nutrient management plans by conservation planners. Subobjective 2C: Develop water quality model algorithm that incorporates metal availability and transport in soil and water environments. Objective 3: Improve the predictive capabilities of SWAT and ALMANAC to meet emerging national and international needs. Subobjective 3A: Conceptualize, develop, and incorporate SWAT model enhancements, which will allow users to meet emerging national and international needs. Subobjective 3B: Validate model results and develop methods to estimate uncertainty for the CEAP project at multiple scales. Subobjective 3C: Improve ALMANAC simulation of rangeland and pastureland grasses. Objective 4: Integrate and enhance assessment tools required for Cropland, Rangeland, and Pastureland CEAP and other national assessments. Subobjective 4A: Enhance and streamline SWAT modeling activities within the CEAP project. Subobjective 4B: Develop, validate, and implement a Windows-based ALMANAC model for user-friendly assessment of biofuel productivity in the continental US and Hawaii.
1b. Approach (from AD-416):
For Objective 1 we will establish plots for simulation model parameter derivation with a diverse set of crop/grass/tree plant species. For Objective 2, we will work with cultivated and pasture fields at the USDA-ARS Riesel Watersheds, Riesel, TX. Litter will be surface applied and soil samples and runoff samples will be collected and analyzed for nutrients and pathogens. In addition for Objective 2, we will develop a simplified interface for SWAT for use by field office staff. A regional tool, the Texas Best management practice Evaluation Tool (TBET), will expanded to a national scope. This research will require the development and adaptation of several datasets at the national level and potentially the migration of TBET to a web-based application. Also for Objective 2, we will perform model parameter sensitivity analyses to identify the most sensitive parameters impacting dissolved metal concentrations in surface and groundwater for low pH and waterlogged conditions. For Objective 3, we will work with processes for routing water across the landscape from ridge to valley bottom in the SWAT model. Also for Objective 3, we will compare model results being produced by the CEAP National Cropland Assessment, looking at the resulting increase in spatial detail of sediment sources and sinks. Also for Objective 3, we will establish field plots for parameter derivation for key rangeland and pastureland species. Measurements will be taken in plots already established on several NRCS Plant Material Centers. For Objective 4, we will develop tools and decision support systems to allow “rapid assessment” of conservation scenarios. We will increase our ability for “rapid assessment” by streamlining the calibration and reporting for remaining CEAP studies and on developing tools to rapidly generate, calibrate, and execute national model runs.
3. Progress Report:
Subobjective 1A: Field trials with perennial grasses were established in 2009 at 10 locations. These data are being used to parameterize the ALMANAC model for switchgrass and miscanthus. Root samples were processed to derive rooting characteristics. Field trials for several oilseed varieties were established in the Pacific Northwest and Great Plains. Subobjective 2A: Data collection was conducted to evaluate water quality impacts of in-house windrow composting of litter prior to land application. Subobjective 2B: Soils data has been derived from NRCS databases for the U.S. Climate information has been processed into forms suitable for model input. An online conservation planning model interface is under development. Databases are being developed to drive the conservation planning tool. A SWAT format U.S. soils database is complete. Weather data have been developed for 19,000 sites in the U.S. Management data in SWAT format have been developed for each county in the U.S. Subobjective 3A: SWAT enhancements being developed include: 1) modularization of code, 2) real time irrigation scheduling, 3) septic systems, 4) landscape grids, 4) channel and floodplain sediment routing. In addition, SWAT in-stream nutrient dynamics are being developed. Phosphorus cycling routines in manures and soils are being enhanced and tested. Subobjective 3B: Phase II of cropland CEAP development includes downscaling from 8-digit to 12-digit subbasins. Stream networks are being redefined to account for location of point sources, ponds, reservoirs, and wetlands. We assembled data from USGS stream gages and from the SPARROW model. Calibration methodology were refined in the Western Lake Erie basin as part of CEAP Wildlife. Phase II will provide a tool for determining impacts of USDA conservation policy at the multiple scales. Subobjective 3C: Field plots were established with NRCS, ARS, and Bureau of Indian Affairs, and first year measurements taken on range sites in Montana and Arizona. We have taken preliminary measurements on key wetland plants. ALMANAC simulations have been validated with cooperator data. A paper is in the process of being published comparing the simulated grasses to real data. Subobjective 4A: CEAP models have been completed for most of the coverage area, including the Ohio, Tennessee, Great Lakes, Upper Mississippi, Chesapeake Bay, Arkansas-Red, the Lower Mississippi, Texas Gulf, South Atlantic, and Pacific Northwest. An article on CEAP efforts in the Mississippi River Basin has been accepted for publication. Aspects of the CEAP project have been enhanced and streamlined, with new software and databases reducing the time for regional simulations. Reservoir databases have been developed based on the National Inventory of Dams and data of the USGS. SWAT model configuration including land use and soils has been finalized. Software has been developed to calibrate large national models. Subobjective 4B: A new windows version of the ALMANAC model was created and released on the web (http://www.ars.usda.gov/Main/docs.htm?docid=16601). This version includes new spatial capabilities.
Kiniry, J.R., Anderson, L.C., Johnson, M.V., Behrman, K.D., Brakie, M., Burner, D.M., Cordsiemon, R.L., Fay, P.A., Fritschi, F.B., Houx III, J.H., Hawkes, C., Juenger, T., Kaiser, J., Keitt, T., Lloyd-Reilley, J., Maher, S., Raper, R., Scott, A., Shadow, A., West, C., Wu, Y., Zibilske, L.M. 2013. Perennial biomass grasses and the Mason-Dixon Line: Comparative productivity across latitudes in the southern Great Plains. BioEnergy Research. 6:276-291.