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:
Site research for the Southern Plains Long-Term Agroecosystem Research( LTAR) was continued on two perennial long-term observational sites. The integrated 10-paddock crop-livestock Common Experiment study site was divided into no-till and till treatments following the 2015 wheat harvest. Two paddocks were planted into canola to position the site to have a wheat after canola sequence during the first full implementation of the treatments with wheat planting in September, 2016. The other 8 paddocks were cropped to grain-only wheat. The planned yield map for 2016 harvest was not obtained due to damage to the contractor’s equipment at the last minute when it was too late to get another contractor, so baseline yields were measured on a paddock basis. During this year all fencing and water tanks were installed to support grazing treatments during the 2016-17 wheat crop. Baseline soil sampling was completed on a one-acre grid for chemical and physical characterization. In collaboration with Oklahoma State University, flumes were designed and installation initiated for the ten paddocks. Soil greenhouse gases were measured by static chambers in perennial and annual long-term sites and the second year of a tillage study was completed. Progress statement linked to Objective 4. Long-term watershed research: Automated stream gauging, groundwater monitoring, and climate stations were operated collaboratively in the watersheds with numerous partners under formal and informal agreements. There is now a groundwater meteogram button on the ARS Micronet website with near real-time ground water table elevations. New collaboration was initiated with Oklahoma State University focused on irrigation system efficiency and irrigation management in the Fort Cobb watershed. A new long-term weather station is being developed to improve timeliness of data delivery to the Ag Data Commons. The new weather station will be a potential evapotranspiration (ET) station, irrigated to maintain a green transpiring surface through as much of the year as possible. This will complement the rainfed climate station that has been operated at the Grazinglands Research Laboratory (GRL) in collaboration with Oklahoma Mesonet since 1992. Progress statement linked to Objective 4. Long-term research sites were leveraged to support National Institute of Food and Agriculture (NIFA)-funded Grazing Conservation Activity Plan (CAP) research that focused on carbon, water, and energy fluxes from perennial and annual sites. Nutrient use efficiency of cattle and impact of forage quality on enteric methane emissions were studied during intensive campaigns with CAP collaborations. Studies to calibrate field-scale COsmic-ray Soil Moisture Observing System (COSMOS) soil moisture sensors were established. Equipment to support Unmanned Aerial Vehicle (UAV) -hyperspectral research was obtained and staff was trained in operation. The scientists and technicians worked with the Ag Commons team on a focused workshop for the GRL data base design which is now in development. The GRL database will facilitate efficient delivery of data to the Ag Data Commons. The animal science team from Bushland, Woodward, Noble Foundation, and El Reno met to discuss analysis and manuscript development from multiple intensive campaigns focused on enteric methane emissions as related to forage/feed quality and environmental conditions. Progress statement linked to Objective 4. At the Long-Term Agroecosystem Research (LTAR) network level, scientist from the project participated in working groups for biological monitoring, rangeland monitoring, and hydrologic monitoring, data base design. Additionally, we participated in planning sessions for the Cropland Common Experiment and in developing a data base system for the Rangeland/Pasture Common Experiment. Five unit members attended the 2016 Annual Meeting and the laboratory volunteered to host the 2017 Annual Meeting. Progress statement linked to Objective 4. The third year of data collection (shear tests on stream bank materials, topographic analysis, etc.) for the USDA- National Institute of Food and Agriculture - National Integrated Water Quality Program (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 February 2016 to share data, check progress, and make plans for upcoming data collection activities. Black-and-white aerial photographs, acquired for the 1940s, 1950s, and 1960s, were mosaicked and processed to produce “decadal” watershed-scale images for determination of land cover, identification and measurement of gullies, and measurement of riparian characteristics. Additionally, a 2012 land cover map of the Fort Cobb watershed was developed using image data collected by the Daimos-1 satellite. Progress statement linked to Objective 2. ARS researchers at El Reno, Oklahoma, led efforts on a special collection of topic-specific papers on model calibration and validation submitted for publication in the transaction of ASABE journal. Nine articles including the introductory paper were published in January 2016. ARS researchers and university researchers are leading efforts using the recommendations from these papers and other information to develop American Society of Agricultural and Biological Engineers (ASABE) guidelines for calibration and validation of hydrologic and water quality models. First draft of guidelines has been completed for review and discussion by the larger ASABE modeling community. Progress statement linked to Objective 1. 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). As part of this OEM funded project, ARS researchers at El Reno, Oklahoma are in the process of developing a modeling software capable of performing uncertainty and sensitivity analysis to help APEX modelers and stakeholders better allocate their resources to measure important model parameters and devise cost-effective measurement campaigns for different study areas. Progress statement linked to Objective 1.
1. Key calibration and validation recommendations developed for application of hydrologic and water quality models. A team of ARS scientists at El Reno, Oklahoma; Temple, Texas; Columbus, Missouri; Ames, Iowa; and other scientists worked to determine critical topics related to model calibration and validation (C/V), performed a synthesis of a previously published special collection of articles and other relevant literature, and provided topic-specific recommendations based on the synthesis as well as personal modeling expertise. The topics include: terminology, hydrologic processes and model representation, spatial and temporal scales, model parameterization, C/V strategies, sensitivity, uncertainty, performance measures and criteria, and documentation and reporting. Individually, the articles provide model practitioners with detailed topic-specific recommendations related to model calibration, validation, and use. Collectively, the articles present recommendations to enhance hydrologic and water quality modeling. Recommendations from these papers are being considered in the development of American Society of Agricultural and Biological Engineers (ASABE) guidelines for calibration, validation, and use of hydrologic and water quality models.
2. Assessing the impacts of anthropogenic and naturally driven changes in watershed dynamics (e.g., hydrological response, transport of contaminants, and ecosystem services) requires integration of knowledge and modeling capacities spanning biophysical responses, environmental problems, policies, economic activity, and datasets that are either connected to the surface watershed or aquifer (subsurface) system. A team of ARS scientists at El Reno, Oklahoma; Bushland, Texas; Temple Texas; and Texas A&M University in College Station, Texas, linked the Soil and Water Assessment Tool (SWAT) and Modular Three-Dimensional Finite-Difference Groundwater Flow (MODFLOW) models to improve hydrologic and water quality simulations in the surface and groundwater domains. The study involved development of a framework for a new application tool to setup the integrated/coupled model and inserting model computer software interfacing the models into a single model, known as SWATmf. The integrated SWATmf model was tested using datasets from the Fort Cobb Reservoir experimental watershed in Oklahoma. Simulated streamflow and groundwater levels generally agreed with observations trends showing that the SWATmf can be used for simulating surface and groundwater interactions. The integrated modeling framework is expected to improve watershed-scale model simulations and provide a modeling platform to better understand linked surface-subsurface hydrologic processes and associated transport phenomena under time-variant conditions.
5. Significant Activities that Support Special Target Populations:
Partnered with non-profit organization to establish BlueSTEM AgriLearning Center at El Reno, Oklahoma. BlueSTEM supported a range of STEM educational efforts including assessment of STEM training and curriculum needs in the local school district, facilitation of undergraduate student research internships with ARS scientists, and teacher training workshops. Through BlueSTEM we are partnering with educational institutions that have high student enrollment from Native American and other underserved groups who will gain a better understanding of agriculture and research through this effort. Hosted six interns (five female and one male) from the Redlands Community College (RCC) NASA internship program. The students were mentored by project scientists and conducted 10-week research projects relevant to the Southern Plains LTAR and BlueSTEM AgriLearning Center.
Moriasi, D.N., Gitau, M.W., Pai, N., Daggupati, P. 2015. Hydrologic and water quality models: Performance measures and evaluation criteria. Transactions of the ASABE. 58(6):1763-1785.
Starks, P.J., Turner, K.E., Brown, M.A., Venuto, B.C. 2015. Canopy visible and near-infrared reflectance data to estimate alfalfa nutritive attributes before harvest. Crop Science. 56:484-494.
Arnold, J.G., Youssef, M.A., Yen, H., White, M.J., Sheshukov, A.Y., Sadeghi, A.M., Moriasi, D.N., Steiner, J.L., Amatya, D.M., Skaggs, R.W., Haney, E.B., Jeong, J., Arabi, M., Gowda, P. 2015. Hydrological processes and model representation: Impact of soft data on calibration. Transactions of the ASABE. 58(6):1637-1660.
Boles, C.M., Frankenberger, J.R., Moriasi, D.N. 2015. Tile drainage simulation in SWAT2012: Parameterization and evaluation in an Indiana watershed. Transactions of the ASABE. 58(5):1201-1213.
Franzluebbers, A.J., Steiner, J.L. Ecosystem services and grasslands in America. In: Potschin, M., Haines-Young, R., Fish, R., and Turner, R.K. (editors), Handbook of Ecosystem Services, Routledge. p. 421-424. Book Chapter 2016.
Guzman Jaimes, J.A., Moriasi, D.N., Gowda, P., Steiner, J.L., Arnold, J.G., Srinivasan, R., Starks, P.J. 2015. A model integration framework for linking SWAT and MODFLOW. Journal of Environmental Modeling and Software. 73:103-116.
Moran, M.S., Ponce Campos, G., Huete, A., Mcclaran, M., Zhang, Y., Hamerlynck, E.P., Augustine, D.J., Gunter, S.A., Kitchen, S.G., Peters, D.C., Starks, P.J., Hernandez, M. 2014. Functional response of U.S. grasslands to the early 21st century drought. Ecology. 95:2121-2133.
Webb, N.P., Herrick, J.E., Van Zee, J.W., Courtright, E.M., Hugenholtz, C.H., Zobeck, T.M., Okin, G., Barchyn, T.E., Billings, B.J., Boyd, R., Clingan, S., Cooper, B., Duniway, M., Derner, J.D., Fox, F.A., Havstad, K.M., Heilman, P., Laplante, V.K., Ludwig, N., Metz, L.J., Nearing, M.A., Norfleet, M., Pierson Jr, F.B., Sanderson, M.A., Sharratt, B.S., Steiner, J.L., Tatarko, J., Tedela, N., Toledo, D.N., Unnasch, R., Van Pelt, R.S., Wagner, L.E. 2016. The National Wind Erosion Research Network: Building a standardized long-term data resource for aeolian research, modeling and land management. Aeolian Research. 22:23-36.