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


Location: Agroclimate and Natural Resources Research

2017 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:
Bi-weekly collection of water samples were carried out in our research watershed and the water quality data used for chemical transport and for modeling purposes (Objective 1). Ground-truth data collected in 2012 were used to develop a 2012 land use map for our research watersheds. Also, aerial black and white photographs of the research watersheds have been collected and processed to produce decadal land use maps from 1940s to 1960s. All these decadal and other existing land use maps will be used for modeling purposes and to help determine the impact of land use changes on reservoir sedimentation. A Bathymetric survey was carried out on 12 reservoirs in the Little Washita River Experimental Watershed (LWREW) and analyzed to determine sedimentation rates. Land use, climate, and physiographic factors were analyzed to determine variables affecting reservoir sedimentation rates (Objective 2). In collaboration with other federal agencies and institutions, seven groundwater wells were drilled and instrumented in the Fort Cobb Reservoir Experimental watershed (FCREW) to collect data to support these modeling efforts. Seven water samplers were installed in the FCREW and LWREW to collect to measure nutrients and sediments during streamflow events to help better evaluate hydrologic and water quality models (Objective 1). Data collection for the USDA- National Institute of Food and Agriculture - National Integrated Water Quality Program grant (Implementation of In-Stream, Streambank, and Riparian Practices in Conjunction with Upland Practices for Conservation of Water Resources) was completed and a meeting among project investigators was held in February 2016 to share data, check progress, and make plans for upcoming data collection activities. Manuscripts have been prepared and the project findings will help determine streambank network locations that require implementation of conservation practices (Objective 1). Collaboration with Oklahoma State University focused on irrigation system efficiency and irrigation management in the FCREW was initiated and is ongoing. Most of the sensors have been installed. A new long-term weather station has been developed to improve timeliness of data delivery to the Ag Data Commons. A potential evapotranspiration (ET) station, irrigated to maintain a green transpiring surface all year round is now functional and preliminary data is being collected. These data will be used to improve existing hydrologic models and will be useful for model calibration and validation to fulfill the objectives of the new project (Objective 1). An El Reno, Oklahoma researcher is one of the leaders on the national Long Term Agroecosystem Research (LTAR) leadership team that contributed 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. Eddy co-variance flux measurements of carbon dioxide, methane, and evapotranspiration and soil GHG measurements in two perennial grassland sites continued in collaboration with University of Oklahoma collaborators (Objective 3). As part of the LTAR network, and in concert with similar long-term, land-based research infrastructure in the region, use the Little Washita River/Fort Cobb Reservoir Experimental Watersheds LTAR site to improve the observational capabilities and data accessibility of the LTAR network and support research to sustain or enhance agricultural production and environmental quality in agroecosystems characteristic of the Southern Plains region. Research and data collection are planned and implemented based on the LTAR site application and in accordance with the responsibilities outlined in 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: Part of the new project. Soil microclimate monitoring stations were installed in the perennial grassland sites to support footprint analysis of the field-scale COSmic-ray Soil Moisture Observing System (COSMOS) soil moisture sensor. Ground truthing data were collected for two of four COSMOS soil moisture sensors. The Laboratory provided soil biology assessments for LTAR sites not having the phospholipid-derived fatty acids (PLFA) capacity. Also, as part of the Southern Plains LTAR, 10 crop and animal production research watersheds have been established on a 400 acre area on the laboratory grounds. Water control structures have been installed, and flumes have been installed to measure surface runoff from each of the 10 sites. Electromagnetic induction surveys have been completed on the research area for the purpose of mapping electrical conductivity of the soils. The first year of data collection has been completed and research work will be on going as part of the new project (Objective 1). During the last 5 years, we along with other ARS scientists, developed a new watershed characterization that improves our ability to identify portions of the landscape more vulnerable to phosphorus losses, and developed a more reliable method to evaluate the effects of agroecosystem management effects on soil quality. Unit scientists used instantaneous suspended sediment (SS), total nitrogen (TN), and total phosphorus (TP) and discharge data measured at the FCREW to develop water quality–discharge relationships to generate continuous long-term SS, TN, and TP data needed to determine sediment and nutrient concentrations and loadings to water bodies. Unit scientists published a special collection of USDA-ARS long-term watershed research data in the Upper Washita River basin of Oklahoma to engage collaborative scientists across institutions and disciplines to further explore complex, interactive processes and systems including resilience to current and future climate pressures; sources, fate, and transport of contaminants at a watershed scale; linked atmospheric-surface-subsurface hydrologic processes; high spatiotemporal resolution analyses of linked hydrologic processes; and multiple-objective decision making across linked farm to watershed scales. Unit scientists developed a data model and analysis tool, SPELLmap, to more efficiently manage large datasets and support modeling applications. We, along with other ARS scientists integrated the Soil and Water Assessment Tool (SWAT) and the Modular Three-Dimensional Finite-Difference Groundwater Flow models to better represent distributed surface-subsurface water interaction. We developed a procedure to screen the climate and soil moisture datasets measured within the USDA ARS benchmark watersheds in Oklahoma. These procedures will contribute to ensuring good quality data for hydrologic and water quality modeling applications. Unit scientist, along with other ARS scientists, incorporated and tested new tile drain equations into the widely used SWAT model to improve tile flow simulations and as a tool to design cost-effective and environment-friendly tile drain water management systems. Unit scientist led a group pf scientists that worked towards the development of model calibration and validation guidelines, which significantly contributed to the just approved American Society of Agricultural and Biological Engineers standards (Objective 1). Unit scientists developed a methodology to validate publicly available spatial climate datasets for use in the development of climate-based decision support tools for agroecosystems (Objective 3).

4. Accomplishments
1. Framework to parameterize and validate the Agricultural Policy Environmental eXtender (APEX) model. The APEX model is the scientific basis for the Nutrient Tracking Tool (NTT), which is a user-friendly web-based computer program developed to estimate reductions in nutrient losses to the environment associated with alternative practices. However, the absence of a clearly defined, consistent approach to parameterization and validation has raised questions over the reliability and consistency of simulated results. A team of ARS scientists at El Reno, Oklahoma; Columbus, Ohio; Tifton, Georgia; Kimberly, Idaho, Texas; Columbus, Missouri; Ames, Iowa; and other scientists worked to develop a rigorous procedure to parameterize and validate APEX to ensure realistic model outputs are obtained. The developed guidelines are in the form of recommendations covering essential phases of model simulation studies as well as a clear interpretation of model performance evaluation criteria and model simulation performance results. These guidelines are currently being used to parameterize and validate APEX to support nation-wide deployment of NTT.

2. Impact of Eastern redcedar on water resources quantified. Millions of dollars are spent annually by USDA-NRCS on brush removal programs to increase grazeable area for livestock. However, much of the Southern Great Plains grassland areas are still being encroached by Eastern redcedar, and the impacts of this encroachment on regional hydrology, principally stream discharge on ground water recharge, has not been adequately studied. Research at ARS in El Reno, Oklahoma indicates that a realistic 20% redcedar encroachment into the grasslands of the North Canadian River basin, which provides 25% of the Oklahoma City water supply, will reduce stream discharge into the city’s Overholser Reservoir by 8.5 m3 s-1, which translates into about 27% of Oklahoma City’s current water demand. This study emphasizes the importance of grassland conservation efforts on downstream water supply.

3. A probabilistic hydrologic modeling approach to evaluating the impacts of conservation practices developed. Hydrologic and water quality models are used to assess water quality constituent losses from agricultural systems. A major problem during the model building phase for a specific study site is the uncertainty involved with parameterization. ARS scientists at El Reno, Oklahoma, along with collaborators, developed a framework that facilitates model parameter selection while evaluating uncertainty to assess the impacts of land management practices at the watershed scale. Results from this study can be used to develop strategic decisions on the risks and tradeoffs associated with different management alternatives that aim to increase productivity while also minimizing their environmental impacts.

4. Riparian erosion suitability model based on environmental features. Riparian erosion is one of the major causes of sediment and contaminant load to streams, degradation of riparian wildlife habitats, and land loss hazards. However, assessing erosion vulnerability at the watershed scale is challenging due to complex interactions between the different mechanisms that govern soil erosion and the inherent uncertainties involved in quantifying these processes. ARS El Reno, Oklahoma scientists along with collaborators developed a methodology to identify areas along the riparian zone that are susceptible to erosion. Our research determined that approximately 80% of the riparian zone has up to 30% probability to experience erosion greater than 1 m. Being able to identify the most vulnerable areas for stream and riparian sediment mobilization, conservation and management practices can be focused on areas needing the most attention and resources.

Review Publications
Starks, P.J., Moriasi, D.N. 2017. Impact of eastern redcedar encroachment on stream discharge in the North Canadian River basin. Journal of Soil and Water Conservation. 72(1):12-25.

Van Liew, M.N., Wortmann, C.S., Moriasi, D.N., King, K.W., Flanagan, D.C., Veith, T.L., Mccarty, G.W., Bosch, D.D., Tomer, M.D. 2017. Evaluating the APEX model for simulating streamflow and water quality on ten agricultural watersheds in the U.S. Transactions of the ASABE. 60(1):123-146.

Anaba, L.A., Banadda, N., Kiggundu, N., Wanyama, J., Engel, B., Moriasi, D.N. 2016. Application of SWAT to assess the effects of land use change in the Murchison Bay catchment in Uganda. Computation Water, Energy, and Environmental Engineering. 6:24-40.

Chen, F., Crow, W.T., Colliander, A., Cosh, M.H., Jackson, T.J., Bindlish, R., Reichle, R., Chan, S., Starks, P.J., Goodrich, D.C., Seyfried, M.S. 2016. Application of triple collocation in ground-based validation of soil moisture active/passive (SMAP) level 2 data products. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 99:1-14.

Colliander, A., Jackson, T.J., Bindlish, R., Chan, S., Das, N., Kim, S., Cosh, M.H., Dunbar, R., Dang, L., Pashaian, L., Asanuma, J., Aida, K., Berg, A., Rowlandson, T., Bosch, D.D., Caldwell, T., Caylor, K., Goodrich, D.C., Jassar, H., Lopez-Baeza, E., Martinez-Fernandez, J., Gonzalez-Zamora, Livingston, M.S., McNairn, H., Pacheco, A., Moghaddam, M., Montzka, C., Notarnicola, C., Niedrist, G., Pellarin, T., Prueger, J.H., Pulliainen, J., Rautiainen, K., Ramo, J., Seyfried, M.S., Starks, P.J., Su, Z., Zeng, Y., Velde, R., Thibeault, M., Dorigo, W., Vreugdenhil, M., Walker, J., Wu, X., Monerris, A., O'Neill, P., Entekhabi, D., Njoku, E., Yueh, S. 2017. Validation of SMAP surface soil moisture products with core validation sites. Remote Sensing of Environment. 192:238-262.

Ahiablame, L., Sheshukov, A.Y., Rahmani, V., Moriasi, D.N. 2017. Annual baseflow variations as influenced by climate variability and agricultural land use change in the Missouri River basin. Journal of Hydrology. 188-202.

Botero, A., Chu, M.L., Guzman, J.A., Starks, P.J., Moriasi, D.N. 2017. Riparian Erosion Suitability Model Based on Environmental Features. Journal of Hydrology. 1-11.

Zhou, Y., Xiao, X., Wagle, P., Bajgain, R., Mahan, H., Basara, J., Dong, J., Qin, Y., Zhang, G., Luo, Y., Gowda, P.H., Neel, J.P., Steiner, J.L., Starks, P.J. 2017. Examining the short-term impacts of diverse management practices on plant phenology and carbon fluxes of Old World bluestems pasture. Agricultural and Forest Meteorology. 237:60-70.

Wang, B., Steiner, J.L., Zhang, F., Gowda, P. 2017. Impact of rainfall pattern on interrill erosion process. Earth Surface Processes and Landforms. doi:10.1002/esp.4140.

Junez-Ferreira, H., Mojarro Davila, F., Bautista-Capetillo, C., Villalobos De Alba, A., Steiner, J.L., Avila Carrasco, J. 2013. Quantitative and qualitative analysis of groundwater in aguanaval and chupaderos aquifers (Mexico). Journal of Earth Science and Engineering. 3:425-436.