2013 Annual Report
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.
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,.
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.
Development of real time irrigation scheduling tool. A major issue in biofuel production is efficient water management. The SWAT (Soil and Water Assessment Tool) model was utilized in this project to simulate the impact of water management and climate on biofuel production. SWAT input files for more than 700 sugarcane fields were developed using current data. Evapotranspiration algorithms were refined and compared to evapotranspiration estimates in two sugar cane fields. Web-based software was developed to allow users to remotely run the model, automatically update daily precipitation and irrigation, and automatically map irrigation scheduling requirements on the web. The web–based SWAT tool provides Hawaiian Commercial and Sugar Company with a simple, real-time interface for irrigation scheduling decisions. Since water is a critical resource for all biofuel production, with modification, this tool will be applicable to biofuel production in other areas of the U.S.
Model parameterization of bioenergy crops. Parameter values for key bioenergy crops were developed for the ALMANAC model. Soil parameter data gathered by project cooperating partners (University of Hawaii and USDA-ARS, Parlier, CA) has proved invaluable in correcting soil parameter errors in some sites. Given the competition for the water resources in Hawaii, sustainable production of bioenergy feedstocks will be driven by management strategies that optimize water use efficiency, enhance feedstock yields, while minimizing environmental impacts. Working with project cooperators, we obtained parameterization data for evaluating water use efficiency and potential bioenergy cropping systems' impacts on ecosystems services; soil organic carbon by depth, greenhouse gas fluxes, pH, and soil nutrient content. Simulations compared productivity and global warming potentials of sugarcane and banagrass at three irrigation levels. This information will be used in 2014 to adapt generated technologies to the Southeastern U.S.
Bioenergy crop evaluation across the U.S. Evaluating the potential of alternative second generation bioenergy crops across large geographic regions, as well as over time, is necessary to determine if biofuel production is feasible and sustainable in the face of growing energy production demands and climate change. ARS scientists at Temple, Texas, together with university collaborators parameterized the ALMANAC models for representative ecotypes of switchgrass across the central and eastern United States. Switchgrass productivity was estimated under current and future climate change scenarios, revealing substantial variation in productivity both within regions and over time. In particular, the southern United States has the highest current biomass potential but was also predicted to have the largest future decrease in productivity where temperature is predicted to increase and precipitation is predicted to decrease. Our results will help develop a better understand of large-scale biofuel production from perennial grasses.
CEAP models completed to support USDA conservation policy for the majority of the U.S. Regional models have been developed, calibrated, and published for the Ohio, Tennessee, Great Lakes, Upper Mississippi, Chesapeake Bay, Arkansas-Red, and the Lower Mississippi. Models are developed and calibrated for the Texas Gulf, South Atlantic and Pacific Northwest. An article detailing CEAP efforts in the Mississippi River Basin and the effects of cropland conservation has been accepted for publication. The congressionally mandated CEAP was initiated by the USDA in 2003 to quantify the benefits of U.S. agricultural conservation title spending by the federal government ($3.7 billion per year in 2008). This work has been critical to USDA analyses and the release of six CEAP reports to date for major river basins in the U.S. These reports warranted official announcement by the Secretary of Agriculture and are widely cited by agriculture stakeholders. These CEAP predictions justify 50 years and billions of dollars of conservation spending to Congress and OMB.
Poultry litter application should not impact E. coli concentrations in runoff. Fecal bacteria contamination of surface waters continues to be a critical water quality concern with serious human health implications. Litter application sites are often assumed to be major contributors to bacterial contamination, and grazing lands often receive a similar focus. However, based on three years of water quality data collected from 13 watersheds, ARS investigators at Temple, Texas, found that poultry litter applications did not impact E. coli concentrations in runoff. A late summer application practice minimizes E. coli runoff from litter application sites since the litter is produced and removed from poultry houses during hot, dry conditions unfavorable for E. coli survival. Studies showed that cultivated watersheds with and without litter application produced the lowest E. coli concentrations in runoff, presumably due to limited wildlife presence and livestock exclusion. In contrast, the ungrazed native prairie reference site produced relatively high E. coli concentrations in runoff, presumably due to increased fecal deposition from abundant wildlife. The high concentrations of E. coli from grazed lands emphasize the need for livestock producers to follow best management practice recommendations to minimize bacteria contribution.
SWAT modularization for enhanced development and maintenance. Hundreds of scientists and students around the world are adding processes to SWAT and refining exiting algorithms. To facilitate multiple model developers, the SWAT model was recoded using modern Fortran data structures and modules. Modifications include:.
1)modules of all spatial processes,.
2)data structures for model state variables, inputs, and outputs,.
3)data input file restructuring to allow efficient management of large simulations, and.
4)initial attempts at parallelization of landscape processes. The next phase of recoding will involve modularization of landscape (soil and plant) routines to increase efficiency when adding new process modules. When the library of modules is completed, it will simplify maintenance and support and allow for efficient addition of new modules. It will also allow us to more efficiently take advantage of new developments made by scientists and students around the world.
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.
Woli, P., Paz, J.O., Lang, D.J., Baldwin, B.S., Kiniry, J.R. 2012. Soil and variety effects on the energy and carbon balances of switchgrass-derived ethanol. Journal of Sustainable Bioenergy Systems (JSBS). 2(4):65-74.
Arnold, J.G., Moriasi, D.N., Gassman, P.W., Abbaspour, K.C., White, M.J., Srinivasan, R., Santhi, C., Harmel, R.D., Van Griensven, A., Van Liew, M.W., Kannan, N., Jha, M.K. 2012. SWAT: Model use, calibration, and validation. Transactions of the ASABE. 55(4):1491-1508.
Bonuma, N.B., Rossi, C.G., Arnold, J.G., Reichert, J.M., Paiva, E.M. 2013. Hydrology evaluation of the Soil and Water Assessment Tool considering measurement uncertainty for a small watershed in southern Brazil. Applied Engineering in Agriculture. 29(2):189-200.
Damoff, G.A., Hamlett, P., Grubh, A., Jin, V.L., Johnson, M.V., Arnold, J.G., Fries, L. 2013. Earthworms (Oligochaeta: Acanthodrilidae and Lumbricidae) associated with Hornsby Bend Biosolids Management Plant, Travis County, Texas, USA. Megadrilogica. 15(12):251-265.
Harmel, R.D., Wagner, K.L., Martin, E., Gentry, T., Karthikeyan, R., Dozier, M., Coufal, C. 2013. Impact of poultry litter application and land use on E. coli runoff from small agricultural watersheds. Biological Engineering Transactions (ASABE). 6(1):3-16.
Joseph, J.F., Sharaif, H., Arnold, J.G., Bosch, D.D. 2013. The impact of asynchronicity on event-flow estimation in basin-scale hydrologic model calibration. Journal of the American Water Resources Association. 49(2):300-318. DOI: 10.1111/jawr.12011.
Kiniry, J.R., Johnson, M., Venuto, B.C., Burson, B.L. 2013. Novel application of ALMANAC: Modelling a functional group, exotic warm-season perennial grasses. American Journal of Experimental Agriculture. 3(3):631-650.
White, M.J., Harmel, R.D., Haney, R.L. 2012. Development and Validation of the Texas Best Management Practice Evaluation Tool (TBET). Journal of Soil and Water Conservation. 67(6):525-535.
Wagner, K.L., Redmon, L.A., Gentry, T.J., Harmel, R.D. 2012. Assessment of cattle grazing effects on E. coli runoff. Transactions of the ASABE. 55(6):2111-2122.
Jeong, J., Kannan, N., Arnold, J.G., Glick, R., Gosselink, L., Srinivasan, R., Harmel, R.D. 2011. Development of sub-daily erosion and sediment transport algorithms in SWAT. Transactions of the ASABE. 54(5):1685-1691.
Behrman, K.D., Kiniry, J.R., Winchell, M., Juenger, T.E., Keitt, T.H. 2013. Spatial forecasting of switchgrass productivity under current and future climate change scenarios. Ecological Applications. 23(1):73-85.
Luo, Y., Arnold, J.G., Liu, S., Wang, X., Chen, X. 2013. Inclusion of glacier processes for distributed hydrological modeling at basin scale with application to a watershed in Tianshan Mountains, northwest China. Journal of Hydrology. 477(16):72-85.
Jeong, J., Kannan, N., Arnold, J.G., Glick, R., Gosselink, L., Srinivasan, R., Barrett, M.E. 2013. Modeling sedimentation-filtration basins for urban watersheds using Soil and Water Assessment Tool. Journal of Environmental Engineering. 139(6):838-848.
Somura, H., Takeda, I., Arnold, J.G., Mori, Y., Jeong, J., Kannan, N., Hoffman, D. 2012. Impact of suspended sediment and nutrient loading from land uses against water quality in the Hii River basin, Japan. Journal of Hydrology. 450-451:25-35.
Zhang, X., Izaurralde, R.C., Arnold, J.G., Williams, J.R. 2013. Modifying SWAT to simulate cropland carbon flux: Model development and initial evaluation. Science of the Total Environment. 463-464C:810-822.
Williams, J.R., Kannan, N., Wang, X., Santhi, C., Arnold, J.G. 2012. Evolution of the SCS curve number method and its applications to continuous runoff simulation. Journal Hydrologic Engineering. 17(11):1221-1229.
Zhang, X., Beeson, P.C., Link, R., Manowitz, D., Izaurralde, R.C., Sadeghi, A.M., Thomson, A.M., Sahajpal, R., Srinivasan, R., Arnold, J.G. 2013. Efficient multi-objective calibration of a computationally intensive hydrologic model with parallel computing software in Python. Environmental Modelling & Software. 46:208-218.
Moriasi, D.N., Rossi, C.G., Arnold, J.G., Tomer, M.D. 2012. Evaluating hydrology of the soil and water assessment tool (SWAT) with new tile drain equations. Journal of Soil and Water Conservation. 67(6):513-524.
Moriasi, D.N., Wilson, B.N., Douglas-Mankin, K.R., Arnold, J.G., Gowda, P. 2012. Hydrologic and water quality models: Use, calibration, and validation. Transactions of the ASABE. 55(4):1-7.