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ARS Home » Plains Area » El Reno, Oklahoma » Grazinglands Research Laboratory » Agroclimate and Natural Resources Research » Research » Research Project #422757

Research Project: AGRICULTURAL LAND MANAGEMENT TO OPTIMIZE PRODUCTIVITY AND NATURAL RESOURCE CONSERVATION AT FARM AND WATERSHED SCALES

Location: Agroclimate and Natural Resources Research

2015 Annual Report


1a. Objectives (from AD-416):
The long-term objective is to bridge the gap between farm management goals and landscape or watershed goals that are shared across farms and communities, using research watersheds as the primary outdoor laboratories to address these issues of global relevance. The project is structured around four objectives, namely: Obj 1: Improve watershed management and ecosystem services in mixed use agricultural watersheds by developing remote sensing and modeling tools and techniques for the selection and placement of conservation practices for maximum effectiveness. 1A: Assess potential impacts of conservation practice targeting strategies to meet desired environmental endpoints. 1B: Develop and evaluate a sequentially linked evapotranspiration, surface, and groundwater hydrology model system. 1C: Develop, evaluate, and refine new subsurface tile drainage and water table depth algorithms in SWAT to improve water budget and water quality predictions. 1D: Develop remote sensing-based techniques to quantify landscape variables to inform the selection or application of conservation practices in grazing areas. Obj 2: Quantify impacts of land management, land cover, and climate on the generation, movement, and fate of sediments and nutrients in watersheds. 2A: Quantify interactive effects of land cover, land management, and climate on reservoir sedimentation. 2B: Quantify impacts of changing land use on hydrologic model simulations. 2C: Quantify impacts of juniper removal on surface and groundwater resources in central Oklahoma. Obj 3: Develop climate-informed decision support tools for crop and forage management, natural resource conservation, and policy options assessments. 3A: Develop and maintain a fundamental climate database and statistical analyses covering two CEAP watersheds in Oklahoma. 3B: Generate synthetic weather patterns that are both spatially and temporally coherent with recent observations for use in hydrologic models. 3D: Develop multi-scale, multiple-objective optimization framework for agricultural production, conservation, and policy assessment. Obj 4. As part of the LTAR network, and in concert with similar long-term, land-based research infrastructure in Southern Great Plains region, use the SP LTAR to improve the observational capabilities and data accessibility of the LTAR network, to support research to sustain or enhance agricultural production and environmental quality in agroecosystems characteristic of the Southern Great Plains region, as per the LTAR site responsibilities and other information outlined in the 2011 USDA Long- LTAR Network Request for Information (RFI) to which the location successfully responded, and the LTAR Shared Research Strategy, a living document that serves as a roadmap for LTAR implementation. Participation in the LTAR network includes research and data management in support of the ARS GRACEnet and/or Livestock GRACEnet projects.


1b. Approach (from AD-416):
The Soil and Water Assessment Tool (SWAT) will be the primary hydrologic model used to address watershed scale studies. SWAT will be linked to the USGS groundwater model, MODFLOW, and will be coupled to an energy balance/evapotranspiration (EB_ET) model to fully address the project’s conservation targeting research objectives. Field studies will be conducted to provide relevant data to SWAT and to verify SWAT performance and accuracy, and to assess the impacts of climate variability and land cover/land use on reservoir sedimentation. New remotely sensed products will be evaluated for their ability to better characterize landscape variables needed for watershed-scale hydrologic simulations. Mathematical and statistical analysis of climate data will be conducted to generate more realistic climatologies (e.g., non-stationary conditions, extreme conditions) and to produce spatiotemporally coherent daily weather grids required by SWAT. Farm to watershed scale process modeling will be conducted in the context of the project’s research watersheds and will focus on identifying practices or policies that optimize economic enterprise and environmental goals across farm to landscape scales. In addition, the SP LTAR will be used to improve observational capacities and data accessibility of the LTAR network and to support research to sustainh or enhance agricultural production and environmental quality.


3. Progress Report:
The focus for Long Term Agroecosystem Research (LTAR) included contributions to updating of the Shared Research Strategy and development of the Common Experiment research plan. For the Southern Plains LTAR, installation of flux towers in the wheat sites that will be part of the Common Experiment was completed and monitoring of soil greenhouse gases (GHG) was initiated. The flux stations and soil GHG measurements in the two perennial grassland sites continued in collaboration with University of Oklahoma collaborators. Soil microclimate monitoring stations were installed in the perennial grassland sites to support footprint analysis of the field-scale COSMOS soil moisture sensor. Participated in the LTAR Annual Meeting and contributed to planning for the common data set and protocols. The Laboratory will provide soil biology assessments for LTAR sites not having the phospholipid-derived fatty acids (PLFA) capacity. Additionally, hosted the Archbold-University of Florida LTAR site manager and develop cross-LTAR research plans. Also, as part of LTAR, 10 crop and animal production research watersheds have been delineated on a 400 acre area on the laboratory grounds; the entire 400 acre area was tilled and planted to wheat to prepare all watersheds for treatment implementation in fall of 2015; water control structures have been designed and the control structure specifications are being released for construction bids. The second year of data collection (shear tests on stream bank materials, topographic analysis, etc.) for the USDA-NIFA-NIWQP grant (Implementation of In-Stream, Streambank, and Riparian Practices in Conjunction with Upland Practices for Conservation of Water Resources) was completed and meeting among project investigators was held in May 2015 to share data, check progress, and make plans for upcoming data collection activities. Hyperspectral reflectance data of native and improved pastures was collected during the summer as part of our AFRI Grazing-CAP grant for the purpose of developing techniques to quantify forage quality in real-time, and a meeting among a sub-group of project investigators was held in Bushland in August 2015 to discuss data needs and availability to meet modeling goals of the project. Remotely sensed hyperspectral canopy reflectance, soil physical and hydrologic property, and vegetation (mass, height, LAI, and nutrient) data continued to be collected at the AFRI Grazing-CAP field sites located on the USDA ARS Grazinglands Research Laboratory (GRL) property. Unmanned aerial vehicles equipped with miniature hyperspectral and thermal band sensors were acquired for the use of pasture/range assessment and development of near-real time assessment of evapotranspiration. Seven more groundwater wells were drilled and instrumented in the Fort Cobb Reservoir Experimental watershed (FCREW) under the multi-agency partnership developed last year to study the Rush Springs aquifer, which underlies most of our research watersheds. These are in addition to two that were implemented in FY14. The partnership consists of ARS, the USEPA, USGS, the Oklahoma Water Resources Board, the Oklahoma Water Survey, the Oklahoma Mesonet, and others. The Oklahoma Mesonet is responsible for logging and storing real-time groundwater elevations. The partnership is designed to maximize resource allocation, data collection, optimize research activities, and to test and validate the linked SWAT_MODFLOW model being developed in this project. Bi-weekly collection of water samples is being continued in the Ft. Cobb watershed. Seven ISCO water samplers were installed in the Fort Cobb Reservoir (FCREW) and Little Washita River (LWREW) experimental watersheds to measure nutrients and sediments during streamflow events. ARS researchers at El Reno, Oklahoma, continued to lead efforts on a special collection of papers on model calibration and validation submitted for publication in the transaction of ASABE journal. Eight of nine topic-specific papers have been accepted and the last one is still undergoing review. This effort will result in the development of ASABE engineering practices standards in hydrologic model calibration and validation. The USDA Office of Environmental Marketing (OEM) provided funding, which resulted in the development of guidelines for parameterization, calibration, and validation of the Agricultural Policy Environmental eXtender (APEX) model to support the nutrient tracking tool (NTT). These guidelines were developed a collaborative effort USDA ARS scientists from Tifton, Georgia; Kimberly, Idaho; and Columbus, Ohio, using data from sub-watersheds within the CEAP Upper Big Walnut Creek Watershed (UBWCW), Ohio. This initiative resulted in the development of guidelines for parameterization, calibration, and validation of APEX to support the nutrient tracking tool (NTT). Additional funding was provided to use the developed guidelines to parameterize and validate NTT to support nation-wide deployment.


4. Accomplishments
1. Evaluating land management sustainability requires careful use of soil quality indexes. Reliable, scientifically established methods are needed to quantify the environmental benefits of USDA conservation programs. A team of ARS scientists at Lubbock, Texas; El Reno, Oklahoma; Ames, Iowa; and West Lafayette, Indiana evaluated two soil quality indexes, the soil management assessment framework (SMAF) and the soil conditioning index (SCI), during an assessment of conservation treatments at the Fort Cobb Reservoir Experimental Watershed in southwestern Oklahoma. The study included sites in annual cropping with conventional tillage, and either conservation or no-tillage, cropland that had been converted to perennial grass, and native grass. The SCI and SMAF gave similar assessments, indicating that soil quality within conventional and conservation systems was similar but lower than in either managed or native grassland systems. SMAF and SCI index parameters were correlated in tilled systems with limited vegetative cover, but not for no-tillage or forage-based pasture/grassland systems that were in place for at least 10 years. The SMAF provided more detailed assessments when evaluating agroecosystem management effects on soil quality, including soil organic carbon enrichment, especially within forage-based systems. However, SMAF does not consider the effects of current management practices on soil loss, and thus may not fully capture the effects of management on soil quality, particularly in tilled systems.

2. A shared research strategy for the Long Term Agroecological Research network. While current weather patterns and rapidly accelerated changes in technology often focus attention on short-term trends in agriculture, the fundamental demands on agriculture to meet society food, feed, fuel and fiber production while providing the foundation for a healthy environment requires long-term perspective. The Long-Term Agroecosystem Research (LTAR) network was established to ensure sustained crop and livestock production and ecosystem services from agriculture, as well as to forecast and verify the effects of environmental trends, public policies, and emerging technologies. The LTAR network is comprised of 18 locations across the US, with ARS scientists leading at 15 sites and collaborating at three additional sites. Scientists in the network developed a shared research strategy that specifies common measurements using shared protocols for collection, verification, organization, archives, access, and distribution of data. Each LTAR site is engaged in a local adaptation of a “common experiment” which contrasts conventional production systems with innovative systems that optimize services. Findings that flow from the LTAR will advance four areas of foundational science: (1) agro-ecosystem productivity; (2) climate variability and change; (3) conservation and environmental quality; and (4) socio-economic viability and opportunities, resulting in improved agricultural applications, improved predictive capability, linkages to other scientific networks, and enhanced educational outreach.


Review Publications
Mwangi, J., Shisanya, C., Gathenya, J., Namirembe, S., Moriasi, D.N. 2015. A modeling approach to evaluate the impact of conservation practices on runoff and sediments in Sasumua watershed, Kenya. Journal of Soil and Water Conservation. 70(2):75-90.

Zobeck, T.M., Steiner, J.L., Stott, D.E., Duke, S.E., Starks, P.J., Moriasi, D.N., Karlen, D.L. 2015. Soil quality index comparisons using Fort Cobb, Oklahoma, watershed-scale land management data. Soil Science Society of America Journal. 79(1):224-238.

Wu, G., Fanzo, J., Miller, D.D., Pingali, P., Post, M., Steiner, J.L., Thalacker-Mercer, A.E. 2014. Production and supply of high-quality food protein for human consumption: Sustainability, challenges, and innovations. Annals of the New York Academy of Sciences. 1321:1-19.

Steiner, J.L., Engle, D.M., Xiao, X., Saleh, A., Tomlinson, P., Rice, C.W., Cole, N.A., Coleman, S.W., Osei, E., Basara, J., Middendorf, G., Gowda, P., Todd, R.W., Moffet, C., Swamy, A., Starks, P.J. 2014. Development of knowledge and tools to enhance resilience of beef grazing systems for sustainable animal protein production. Annals of the New York Academy of Sciences. 1328:10-17.

Takle, E.S., Anderson, C.J., Anderson, J., Angel, J., Elmore, R.W., Gramig, B.M., Guinan, P., Hilberg, S., Kluck, D., Schneider, J.M. 2014. Climate forecasts for corn producer decision making. Earth Interactions. 18(5):1-8.

Guzman Jaimes, J.A., Chu, M.L., Starks, P.J., Moriasi, D.N., Steiner, J.L., Fiebrich, C.A., Mccombs, A.G. 2014. Upper Washita River experimental watersheds: Data screening procedure for data quality assurance. Journal of Environmental Quality. 43:1250-1261.

Steiner, J.L., Franzluebbers, A.J., Neely, C., Ellis, T., Betemariam, E. 2014. Enhancing soil and landscape quality in smallholder grazing systems. In: Lal, R., Steward, B.A., editors. Soil Management of Smallholder Agriculture. Boca Raton, FL:CRC Press. p. 63-104.

Starks, P.J., Steiner, J.L., Stern, A.J. 2014. Upper Washita River experimental watersheds: Land cover data sets (1974-2007) for two southwestern Oklahoma agricultural watersheds. Journal of Environmental Quality. 43:1310-1318.