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ARS Home » Plains Area » El Reno, Oklahoma » Grazinglands Research Laboratory » Agroclimate and Natural Resources Research » Research » Research Project #432323

Research Project: Towards Resilient Agricultural Systems to Enhance Water Availability, Quality, and Other Ecosystem Services under Changing Climate and Land Use

Location: Agroclimate and Natural Resources Research

2020 Annual Report


Objectives
Objective 1: Quantify states, fluxes, and cycling of water, carbon, and hydrologic constituents within the soil-plant-hydrologic-atmospheric systems of selected landscapes, watersheds, and agricultural systems of the Southern Great Plains. Objective 2: Develop tools and techniques for the selection, placement, and evaluation of conservation and agricultural practices to improve watershed integrity and ecosystems services. 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.


Approach
The project builds upon the prior 5-year project and is structured around three inter-related research objectives that: 1) develop, maintain, and expand long-term observational research infrastructure and databases to elucidate water-related agroecosystem processes for agricultural systems, 2) conducts studies that help understand processes and improve algorithms of commonly used hydrologic and water quality models, and 3) develops tools and techniques for the selection, placement, and evaluation of conservation and agricultural practices to improve watershed integrity and ecosystems services. Our long-term objective is to elucidate key hydrologic and agroecosystem processes and to bridge the gap between farm management goals and landscape or watershed goals that are shared across farms and communities, using long-term research sites and research watersheds as the primary outdoor laboratories to address these issues of global relevance. Research approaches include field studies, remote sensing analyses, mathematical and statistical assessment of climate, farm to watershed scale process modeling, and development of integrative optimization tools. This research will assist farmers, land owners, governmental action agencies, and residents to contribute to more resilient mixed land-use watersheds, in part by providing tools that help them evaluate and optimize multiple management objectives for mixed-enterprise agricultural systems.


Progress Report
Objective 1: With respect to Subobjective 1A, ARS researchers at El Reno, Oklahoma, continue to collect soil moisture from the installed in-situ soil moisture network around a COsmic-ray Soil Moisture Observing System (COSMOS) site for purposes of evaluating one-time vs. multi-temporal calibration. In addition, scientists continue to perform quality assurance/quality control (QA/QC) on the collected data. With respect to Subobjective 1B, the third season of field evaluation of irrigation fluxes and efficiencies have been wrapped up. With three years of irrigation flux and efficiency data at several fields across the Fort Cobb Reservoir Experimental Watershed (FCREW), researchers are finalizing a manuscript to be submitted to a peer-reviewed journal. As soon as the results are finalized and this manuscript is submitted, its findings will be used to develop a manuscript comparing three different approaches for simulating root distribution under irrigated conditions. The findings of this cooperative project have been presented at conferences and extension events, including the 2019 Caddo Research Station Field Tour, the 2019 Oklahoma Irrigation Conference, the 2020 Southwest Cotton Physiology Meeting, and several one-on-one visits with local producers in the FCREW. With respect to Subobjective 1C, a new agreement with Oklahoma State University seeks to continue work to improve the irrigation algorithm implemented in the Soil and Water Assessment Tool (SWAT) model by our ARS collaborators in Bushland, Texas. With respect to Subobjective 1D, the Revised Universal Soil Loss Equation (RUSLE) in a Geographical Information System (GIS) context model is being used in the Little Washita River Experimental Watershed (LWREW) to determine potential soil erosion as a function of land use, determine most vulnerable areas and correlate potential soil erosion to measured reservoir sedimentation. To date scientists have run 49 RUSLE scenarios (6 of the 12 reservoirs averaging about 8 years per reservoir). Also in the LWREW, a study to determine the influence of reservoir sediment profile depth on carbon thermal stability and carbon functional groups as well nutrients is nearing completion. One peer-reviewed paper under review, focused on concentrations of arsenic and chromium heavy metals in reservoir sediments and their potential ecological risks to organisms living in reservoirs within cropland, forest, and grassland areas. Collaborators from Florida A&M University have also completed analyses on sediment core and water samples with respect to nutrients and specifically phosphorus and a manuscript is in preparation. Objective 2: Due to key retirements and shifting roles of the research staff, and as reported previously, the study in Research Goal 2B.1 has been modified in regards to research site and source of Light Detection and Ranging (LiDAR) data. This work has been further delayed because of travel restrictions, social distancing, and other factors due to the COVID-19 pandemic. However, all Unmanned Aerial Vehicle (UAV) pilot and flight training has been completed by the primary field technician and a second pilot is undergoing training. ARS researchers at El Reno, Oklahoma, have also entered into collaborative arrangements with Natural Resources Conservation Service (NRCS) and our sister ARS laboratory in Stillwater, Oklahoma, to accomplish two broad objectives. The emphasis of the first objective is to evaluate LiDAR data more generally for assessment of selected flood plain characteristics such as upstream and downstream assessment of stream sinuosity, degradation, and land use change and impact on selected conservation structures. The second objective is to conduct preliminary study to qualitatively assess channel stream banks, begin work linking processed LiDAR data to ARS's Bank Stability and Toe Erosion Model (BSTEM), and to determine vulnerable areas that require conservation practices. Currently, a study site in central Oklahoma has been identified for Unmanned Aircraft Systems (UAS)-LiDAR data collection and preliminary experimental objectives and approaches are being discussed. Implementation of these plans is currently constrained by the COVID-19 pandemic. A manuscript was published in the Journal of American Water Resources Association. With respect to Subobjective 2D, the SWAT land use update tool documentation was completed. The tool, manual, and a pdf of the peer-reviewed paper are available on the USDA ARS at El Reno, Oklahoma, website for SWAT users. Future plans are to use landuse maps developed using the UAV-mounted with LiDAR to determine the impact of dynamic landuse on model performance and outputs. Objective 3: A number of papers have been written describing the seasonal and annual fluxes of evapotranspiration (ET) and carbon dioxide (CO2) from the business-as-usual (BAU, winter wheat) and aspirational (ASP, canola) under till and minimum till conditions. These data should be helpful in identifying sustainable and flexible forage/crop systems for the Southern Plains. Due to recent storm damage to infrastructure on the primary Cropland Common Experiment (i.e., the GREEN Farm), the physical experimental layout is being redesigned to reduce the land area involved and to expedite data collection and analysis for comparison of "business-as-usual" to an "aspirational" system. The GREEN Farm should be up to full experimental capacity by the summer of fiscal year 2021. In the meantime, our secondary Common Cropland Experimental site (the Water and Erosion Experimental (WRE) watersheds) will be the focus of LTAR activities. COVID-19 slowed down water equipment installation, with water sampler installation complete and operational in one of the eight sites. Soil and plant biomass measurements have been completed for fall-winter 2019 and spring-summer 2020. Collected samples have been weighed and prepared for storage for future analysis. A manuscript addressing the effects of conservation management on soil quality parameters is in preparation. A paper describing biomass yields of cool and warm season, mixed forage cover crops under variable weather and climatic conditions in the Southern Great Plains was presented virtually at the 2020 Soil Conservation Society of America meeting and The Soil Health Institute's Annual Meeting in July 2020.


Accomplishments
1. Twenty-three years of runoff water quantity and quality data published. Long-term research is important to understanding how land management affects runoff and erosion in agricultural production systems. ARS scientists have compiled, discussed, and published 23 years of historical data measured in eight fields located in El Reno, Oklahoma. Results indicated that native tallgrass prairie fields had 98%, 72%, and 78% lower suspended sediments, total soluble phosphorus, and nitrate-nitrogen losses, respectively, than cropped fields. This research database is essential for determining the impact of different agricultural management systems, understanding the processes related to hydrologic transport and water quality, and the development and validation of the corresponding models. The associated paper was one of the two articles selected for promotion in the news magazine and on social media accounts for the Agronomy, Crop Science, and Soil Science Societies.

2. Prediction of soil carbon fractions using a field spectroradiometer equipped with an illuminating contact probe. Current research combines geospatial data and a landform element classification scheme to derive landform complexes to codify the collection of soil and water data at variable scales within the Water Resources & Erosion Watersheds Experiment (WRE) at USDA-ARS in El Reno, Oklahoma. Interactive effects of climate, crop diversity, including cool season and summer forage cover crops, and tillage vs no-tillage on soil processes that control cycling and storage of soil carbon and nitrogen using reflectance spectra of soils, a rapid and cost effective methodology were addressed. The use of radiometry reduces the number of soil and potentially water samples with the aim of simultaneously determining the impact of conservation and land management practices on soil and water quality, a contribution towards achieving the goals of the Conservation Effects Assessment Project (CEAP) national initiative and the Long-Term Agroecosystem Research (LTAR) network national initiatives.

3. Impact of continuous vs. rotational grazing management systems. The prairie ecosystems of the Southern Great Plains are important for livestock grazing and provide benefits that include habitat for avian, terrestrial and aquatic species, carbon regulation, and hydrologic function. ARS scientists at El Reno, Oklahoma, conducted research to quantify the impact of grazing management systems (continuous (C) compared with rotational (R) stocking). Results revealed that: 1) microbial biomass in the soil surface layer decreased in the C treatments but increased in R treatments, 2) individual calf weaning weights were higher in C than in R, 3) available plant biomass did not differ between treatments, and 4) that R treatments had higher nitrogen concentrations and digestibility and lower fiber concentrations in R than in C. Results from the study indicated that livestock performance may be enhanced in rotational systems.

4. SWAT-LUT: User-friendly Graphical Software for Updating Landuse in SWAT developed. The soil and water assessment tool (SWAT) is a widely used model to evaluate the effects of alternative management decisions on water resources and nonpoint-source pollution in watersheds and large river basins. The land use and land cover (LULC) map is one of the critical inputs to the watershed model. Traditionally, a single map is used to represent LULC of a watershed over a period ranging from several years to decades. However, using a single LULC map does not capture significant land use change within a simulation period. ARS scientists at El Reno, Oklahoma, and others developed the SWAT-LUT, a public domain user-friendly land use update tool (LUT) that simplifies incorporation of multiple land use maps during the simulation period of modeling studies in order to provide realistic model parameterization and scenario simulations. This software will improve simulation outputs in modeling studies related to the Conservation Effects Assessment Project (CEAP) and the Long-Term Agroecosystem Research (LTAR) network national USDA initiatives.


Review Publications
Steiner, J.L., Starks, P.J., Neel, J.P., Northup, B.K., Turner, K.E., Gowda, P.H., Coleman, S., Brown, M.A. 2019. Managing tallgrass prairies for productivity and ecological function: A long-term grazing experiment in the Southern Great Plains, USA. Agronomy. 9(11):699. https://doi.org/10.3390/agronomy9110699.
Fortuna, A., Starks, P.J., Nelson, A.M., Steiner, J.L. 2019. Prediction of soil carbon fractions using a field spectroradiometer equipped with an illuminating contact probe. Soil Systems. 3(4):71. https://doi.org/10.3390/soilsystems3040071.
Steiner, J.L., Wetter, J.T., Robertson, S.D., Teet, S.B., Wang, J., Wu, X., Zhou, Y., Brown, D., Xiao, X. 2020. Grassland wildfires in the Southern Great Plains: Monitoring ecological impacts and recovery. Remote Sensing. 12(4):619. https://doi.org/10.3390/rs12040619.
Turner, K.E., Belesky, D.P., Zobel, R.W., Fortuna, A. 2020. Initial effects of supplemental forages and feedstuffs on bovine rumen ecology in vitro as determined by DNA-based molecular procedures. Journal of Applied Animal Research. 48(1):268-280. https://doi.org/10.1080/09712119.2020.1781648.
Moriasi, D.N., Pai, N., Steiner, J.L., Gowda, P.H., Winchell, M., Rathjens, H., Starks, P.J., Verser, J.A. 2019. SWAT-LUT: A desktop graphical user interface for updating land use in SWAT. Journal of the American Water Resources Association. 55(5):1102-1115. https://doi.org/10.1111/1752-1688.12789.
Acero Triana, J.S., Chu, M.L., Guzman, J., Moriasi, D.N., Steiner, J.L. 2019. Beyond model metrics: The perils of calibrating hydrologic models. Journal of Hydrology. https://doi.org/10.1016/j.jhydrol.2019.124032.
Hou, C., Chu, M.L., Guzman, J., Acero Triana, J.S., Moriasi, D.N., Steiner, J.L. 2019. Field scale nitrogen load in surface runoff: Impacts of management practices and changing climate. Journal of Environmental Management. 249:109327. https://doi.org/10.1016/j.jenvman.2019.109327.
Acero Triana, J., Chu, M.L., Guzman, J., Moriasi, D.N., Steiner, J.L. 2020. Evaluating the risks of groundwater extraction in an agricultural landscape under different climate projections. Water. 12(2):400. https://doi.org/10.3390/w12020400.
Baffaut, C., Baker, J.M., Biederman, J.A., Bosch, D.D., Brooks, E.S., Buda, A.R., Demaria, E.M., Elias, E.H., Flerchinger, G.N., Goodrich, D.C., Hamilton, S.K., Hardegree, S.P., Harmel, R.D., Hoover, D.L., King, K.W., Kleinman, P.J., Liebig, M.A., McCarty, G.W., Moglen, G.E., Moorman, T.B., Moriasi, D.N., Okalebo, J., Pierson Jr, F.B., Russell, E.S., Saliendra, N.Z., Saha, A.K., Smith, D.R., Yasarer, L.M. 2020. Comparative analysis of water budgets across the U.S. long-term agroecosystem research network. Journal of Hydrology. 588. https://doi.org/10.1016/j.jhydrol.2020.125021.
Moriasi, D.N., Duriancik, L.F., Sadler, E.J., Tsegaye, T.D., Steiner, J.L., Locke, M.A., Strickland, T.C., Osmond, D.L. 2020. Quantifying the impacts of the conservation effects assessment project watershed assessments: The first fifteen years. Journal of Soil and Water Conservation. 75(3):57-74. https://doi.org/10.2489/jswc.75.3.57A.
Moriasi, D.N., Starks, P.J., Steiner, J.L., Zhang, X.J., Garbrecht, J.D., Glasgow, S. 2020. An overview of research into conservation practice effects on soil and water resources in the Upper Washita Basin, Oklahoma, United States. Journal of Soil and Water Conservation. 75(3):330-339. https://doi.org/10.2489/jswc.75.3.330.
Ranjan, P., Duriancik, L.F., Moriasi, D.N., Carlson, D., Anderson, K., Prokopy, L.S. 2020. Understanding the use of decision support tools by conservation professionals and their education and training needs: An application of the reasoned action approach. Journal of Soil and Water Conservation. 75(3):387-399. https://doi.org/10.2489/jswc.75.3.387.
Reichle, R., Liu, Q., Koster, R., Crow, W.T., Delannoy, G., Kimball, J., Ardizzone, J., Bosch, D.D., Colliander, A., Cosh, M.H., Kolassa, Mahanama, S., McNairn, H., Prueger, J.H., Starks, P.J., Walker, J. 2020. Version 4 of the SMAP level-4 soil moisture algorithm and data product. Journal of Advances in Modeling Earth Systems. 11:3106-3130. https://doi.org/10.1029/2019MS001729.
Wagle, P., Gowda, P.H., Northup, B.K., Starks, P.J., Neel, J.P. 2019. Response of tallgrass prairie to management in the U.S. Southern Great Plains: Site descriptions, management practices, and eddy covariance instrumentation for a long-term experiment. Remote Sensing. 11(17):1988. https://doi.org/10.3390/rs11171988.
Chaubell, J., Yueh, S., Dunbar, S., Colliander, A., Chen, F., Chan, S., Entekhabi, D., Bindlish, R., O'Neill, P., Asansuma, J., Berg, A., Bosch, D.D., Caldwell, T., Cosh, M.H., Holifield Collins, C.D., Martinez-Fernandez, J., Seyfried, M.S., Starks, P.J., Su, Z., Thibeault, M., Walker, J. 2020. Improved SMAP dual-channel algorithm for the retrieval of soil moisture. IEEE Transactions on Geoscience and Remote Sensing. 58(6):3894-3905. https://doi.org/10.1109/TGRS.2019.2959239.
Lee, J., Cosh, M.H., Starks, P.J., Toth, Z. 2019. Self-correction of Soil Moisture Ocean Salinity (SMOS) soil moisture dry bias. Canadian Journal of Remote Sensing. 45(6):814-828. https://doi.org/10.1080/07038992.2019.1700466.
Colliander, A., Jackson, T., Berg, A., Bosch, D.D., Caldwell, T., Chan, S., Cosh, M.H., Holifield Collins, C.D., Martinez-Fernandez, J., Mcnairn, H., Prueger, J.H., Starks, P.J., Walker, J., Yueh, S. 2020. Effect of rainfall events on SMAP radiometer-based soil moisture accuracy using core validation sites. Journal of Hydrometeorology. 21:255-264.