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ARS Home » Plains Area » Temple, Texas » Grassland Soil and Water Research Laboratory » Research » Research Project #432310

Research Project: Resilient Management Systems and Decision Support Tools to Optimize Agricultural Production and Watershed Responses from Field to National Scale

Location: Grassland Soil and Water Research Laboratory

2020 Annual Report

Objective 1: As part of the LTAR network, and in concert with similar long-term, land-based research infrastructure in the Texas Gulf Region, use the Texas Gulf 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 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. Sub-objective 1A: Evaluate differences in the environmental and agro-economic impacts of conventional and aspirational cropping systems. Sub-objective 1B: Quantify landscape and climatic factors regulating C, N and P loss to surface waters at the field, stream, and river basin scales. Sub-objective 1C: Create “business as usual” and “aspirational” production and ecosystem service system scenarios as outlined by the LTAR common experiment. Assess the sustainability of both systems and develop new strategies to enable greater sustainability. Objective 2: Use new findings from CEAP and other applied research to enhance and validate model algorithms for watershed processes to meet emerging stakeholder needs. Sub-objective 2A: Develop and incorporate SWAT model enhancements to improve logistics, streamline application, foster collaborative development, and meet emerging national and international modeling needs. Sub-objective 2B: Improve Agricultural Land Management Alternatives with Numerical Assessment Criteria (ALMANAC) simulation of bioenergy, rangeland, pastureland, and wetland plants by using field data to develop new phenology algorithms and associated plant parameters. Objective 3: Utilize enhanced models to develop decision support tools for conservation management, planning, and policy at local and national scales to mprove water resources. Sub-objective 3A: Enhance model-based decision support tools to support field and small watershed management decision making to improve ecosystem services. Sub-objective 3B: Enhance and streamline large-scale resource models and decision support tools to support CEAP requirements and other national and international stakeholder needs.

Cropped agricultural fields at the Riesel Watersheds will be monitored for agroenviornmental response to climatic drivers and operations will be recorded to assess the economics between aspirational and business-as-usual treatments. Smaller scale mechanistic studies will be used to evaluate the potential influence of climatic drivers and changing nutrient transport in stream and river networks. Land-use and hydrologic pathway will also be used to evaluate coupled C/N/P biogeochemistry in soils and runoff. The Soil and Water Assessment Tool (SWAT) model will be updated to improve the process-based modeling capabilities for gully erosion, flood plain interactions, riparian wetlands and grazing management. The Agricultural Land Management Alternative with Numerical Assessment Criteria (ALMANAC) model will be updated to better represent wetlands, pasturelands and biofuels cropping systems. The modeling capabilities of the GSWRL will be utilized to develop frameworks and databases that will then be used in a national conservation effects assessment project (CEAP). The GSWRL CEAP tools will be the basis of accounting for the environmental benefits of conservation practice implementation by other USDA programs and other state and federal agencies.

Progress Report
Sub-objective 1A. A scientist and a database manager were hired in support of the Long-Term Agroecosystem Research (LTAR) project during this fiscal year. Both positions are already improving the integration of Texas Gulf LTAR activities into the greater LTAR network. LTAR business-as-usual and aspirational treatments as well as several intermediate treatments continued for the cropping systems component of LTAR at the Riesel Watersheds. A summer drought resulted in poor germination of cover crops following corn in the aspirational and several intermediate treatments. Initial assessments on the impact of LTAR cropland treatments on productivity, economic assessments and soil health are being made through fiscal year 2020. Precision agriculture technologies have been adopted at the Riesel Watersheds and Temple farms, and treatments that push the envelope of precision agriculture toward precision conservation from fiscal year 2019 are currently being assessed. Corn was planted at the Riesel Watersheds on all cropland treatments this year and have been maintained as a part of critical research infrastructure. Enterprise budgets for business-as-usual and aspirational treatments have been made for the 2019 crop year. Sub-objective 1C. Cropped agricultural fields at the Riesel Watersheds were monitored for agro-environmental response to climatic drivers to assess the soil health characteristics between aspirational and business-as-usual treatments. Soil and plant samples were collected to document the nitrogen (N) and phosphorus (P) uptake efficiency in each treatment. Greenhouse gas emission samples were not collected this year due to COVID-19 travel restrictions. However, we evaluated the effect of tillage and fertilizer placement on nitrous oxide emissions in a tillage trial at the Riesel Watersheds. No-tillage and banding fertilizer produced less nitrous oxide (N2O) emissions than conventional tillage and placement of fertilizer. Nitrous oxide emissions were greater for surface applied fertilizer than banded and were higher following rain events. Nitrous oxide emissions factors from conventional till accounted for greater than 2% of fertilizer N, where no-till treatments were below 1%. Phospholipid fatty acid analysis describing microbial communities has been completed. Monthly samples have been analyzed for crop years 2017-2020 from six field-scale watersheds (4.0-8.4 ha) at the Riesel Watersheds. Microbial communities were significantly affected by the level of disturbance (e.g. native, conventional till, no-till), soil organic carbon, and soil chemical properties and correlated well with the Soil Health Index. Treatment analyses will continue in successive years. Subobjective 2A. Development of Soil and Water Assessment Tool plus (SWAT+) continued for national environmental and conservation assessments. Proper calibration of a model is critical to developing realistic conservation scenarios and ultimately national conservation policies. To ensure accurate simulating of water processes in SWAT+, a simple heuristic soft calibration procedure was refined and tested on six LTAR watersheds. Resulting model output of surface runoff, percolation, evapotranspiration, tile flow, and stream flow are being compared using U.S. Geological Survey (USGS) and LTAR water budget estimates from measured data. Algorithms for channel downcutting and widening were developed based on stream power, channel dimensions, erodibility, cover, and median streambed particle diameter. A soft calibration procedure was developed to calibrate channel widths per year of erosion by stream order and will be validated in LTAR watersheds. An additional soft calibration procedure was developed for crop yields using potential leaf area and optimum harvest index. A new model was developed for irrigation water allocation in SWAT+ and is being tested on a river basin in Spain. Rights are assigned to each field within an irrigation district and water is diverted from the stream and allocated to each field based on irrigation rights and demand. Rules for diversion and allocation are defined by users in decision tables that allow the rules to be conditioned on any model parameter including stream flow rate, crop water stress, and crop growth stage. We worked closely with researchers at Colorado State University to incorporate a new groundwater flow model in SWAT+. Compared to the MODular FLOW model (MODFLOW), the new model has fewer inputs, considerably less code to integrate, and only requires 20% increase in runtime over the current SWAT+ model. Sub-objective 3A. Work continues on the development of the Agricultural Conservation Reduction Estimator (ACRE)-Field, a web-based conservation planning tool which allows a user to select a specific field from a map and run conservation scenarios. A draft web interface has been developed and linked to preexisting preliminary SWAT+ simulations results for the U.S. Other work in this area includes the study of Landsat-derived spectral vegetation indices to evaluate the performance of three major crops (citrus, grape, and olive) under dry, wet, and normal climatic conditions. Hyperspectral imagery is also being tested to determine if these data can be used to predict calcium, magnesium, and protein of tef (Eragrostis tef), an understudied plant that is growing in importance worldwide due to both food and forage benefits. These data could be used to drive future decision support tools using an ever-increasing supply of remotely sensed data. Sub-objective 3B. The development of the National Agroecosystem Model (NAM) continues with a focus of meeting the demands of Cropland Conservation Effects Assessment Project (CEAP), LTAR and most recently Wildlife CEAP. The scale of this modeling effort has been further improved to simulate each significant stream segment in the contiguous U.S. Three million stream segments from the National Hydrography Dataset were added to better support the simulation of riparian conservation and factors affecting wildlife populations and habitat. The inclusion of these data also allows us to better represent smaller watersheds within the LTAR network. Water balance components for NAM have been refined for selected watersheds using LTAR data and nationally using USGS stream gage data and National Oceanic and Atmospheric Administration observations. Other national scale work included the development of "manuresheds," the manure-spreadable cropland in the geographic, environmental, and social radius of one or more confined livestock operations. This work seeks to document patterns in manure nutrients and identify nearby areas where opportunities may exist to promote transfers of manure nutrients to croplands that would benefit from their application.

1. Long-term evaluation of adaptive nutrient management demonstrates enhanced economic and environmental outcomes. With increasing variability in climatic and economic drivers, producers who have previously utilized static agricultural management strategies may pursue adaptive management principles to improve net returns and potentially other ecosystem services. ARS researchers at Temple, Texas managed cropped fields in the Riesel Watersheds for 16 years using 0 to 8 tons of poultry litter per acre annual application rates. During this period, management progressed from static management to adaptive management using the Haney Soil Health Test, which reduced nitrogen (N) application rates in fields with poultry litter application, and recommended cover crops. Adoption of adaptive nutrient management decreased N application rates by 25-38% for low rates of poultry litter without sacrificing profitability. Poultry litter application rates in excess of crop phosphorus demand increased phosphorus runoff losses while decreasing profitability. Long-term studies that analyze agronomic, economic and environmental factors at the field scale for long periods are extremely rare, since they are expensive and labor intensive. This study demonstrates the utility of adaptive management principles over the long-term to producers, conservation professionals and policy makers as one potential suite of practices to balance economic and environmental outcomes through agronomic management.

Review Publications
Gaston, L., Beasley, J., Blazier, M., Dodla, S., Felicien, W., Kiniry, J.R. 2019. Miscanthus production on a coastal plain soil nitrogen fertilization and poultry litter. Soil Science. 184(3):69-77.
Kim, S., Kim, S., Cho, J., Park, S., Perez, F., Kiniry, J.R. 2020. Simulated biomass, climate change impacts, and nitrogen management to achieve switchgrass biofuel production at diverse sites in U.S. Agronomy. 10(4):503-521.
Baez-Gonzalez, A.D., Fajardo-Diaz, R., Garcia-Romero, G., Osuna-Ceja, E.O., Kiniry, J.R., Meki, M.N. 2020. High sowing densities in rainfed common beans (Phaseolus vulgaris L.) in Mexican semi-arid highlands under future climate change. Agronomy. 10(3):442-460.
Kiniry, J.R., Kim, S. 2020. A review of modeled water use efficiency of highly productive perennial grasses useful for bioenergy. Agronomy. 10(3):328-341.
Yen, H., Park, S., Arnold, J.G., Srinivasan, R., Chawanda, C.J., Wang, R., Feng, Q., Wu, J., Miao, C., Bieger, K., Daggupati, P., van Griensven, A., Kalin, L., Lee, S., Sheshukov, A.Y., White, M.J., Yuan, Y., Yeo, I., Zhang, M., Zhang, X. 2019. IPEAT+: A built-in optimization and automatic calibration tool of SWAT+. Water. 11(8):1681-1698.
Kiniry, J.R., Kim, S., Tonnang, H.E. 2019. Back to the future: Revisiting the application of an enzyme kinetic equation to maize development nearly four decades later. Agronomy. 9(9):566-577.
Rocateli, A.C., Ashworth, A.J., West, C.P., Brye, K.R., Popp, M.P., Kiniry, J.R. 2020. Simulating switchgrass biomass productivity using ALMANAC. I. Calibration of soil water. Agronomy Journal. 112:183-193.
Smith, D.R., Macrae, M., Kleinman, P.J., Jarvie, H.P., King, K.W., Bryant, R.B. 2019. The latitudes, attitudes, and platitudes of watershed phosphorus management in North America. Journal of Environmental Quality. 48(5):1176-1190.
Smith, D.R., Harmel, R.D., Haney, R.L. 2020. Long-term agro-economic and environmental assessment of adaptive nutrient management on cropland fields with established structural conservation practices. Journal of Soil and Water Conservation. 75(3):416-425.
Bieger, K., Arnold, J.G., Rathjens, H., White, M.J., Bosch, D.D., Allen, P.M. 2019. Representing the connectivity of upland areas to floodplains and streams in SWAT+. Journal of the American Water Resources Association. 55(3):578-590.
Tan, M.L., Gassman, P., Srinivasan, R., Arnold, J.G., Yang, X. 2019. A review of SWAT studies in southeast Asia: Applications, challenges and future directions. Water. 11(5):914-939.
Gesch, R.W., Long, D.S., Palmquist, D.E., Allen, B.L., Archer, D.W., Brown, J., Davis, J.B., Hatfield, J.L., Jabro, J.D., Kiniry, J.R., Vigil, M.F., Oblath, E.A., Isbell, T. 2019. Agronomic performance of Brassicaceae oilseeds in multiple environments across the Western USA. BioEnergy Research. 12(3):509-523.
Chaganti, V.N., Ganjegunte, G., Niu, G., Ulery, A., Flynn, R., Enciso, J.M., Meki, M.N., Kiniry, J.R. 2020. Effects of treated urban wastewater irrigation on bioenergy sorghum and soil quality. Agricultural Water Management. 228:105894.
Meki, M.N., Kiniry, J.R., Worqlul, A., Kim, S., Williams, A.S., Osorio, J.M., Reilley, J. 2020. Field and simulation-based assessment of vetivergrass bioenergy feedstock production potential in Texas. Agronomy Journal. 112(4):2692-2707.
Qi, J., Zhang, X., Yang, Q., Srinivasan, R., Arnold, J.G., Li, J., Waldholf, S.T., Cole, J. 2020. SWAT ungauged: Water quality modeling in the Upper Mississippi River Basin. Journal of Hydrology. 584:124601.
Bailey, R.T., Park, S., Bieger, K., Arnold, J.G., Allen, P.M. 2020. Enhancing SWAT+ simulation of groundwater flow and groundwater-surface water interactions using MODFLOW routines. Environmental Modelling and Software. 126:104660.
Wu, L., Yen, H., Arnold, J.G., Ma, X. 2020. Is the correlation between hydro-environmental variables consistent with their own time variability degrees in a large-scale loessial watershed? Science of the Total Environment. 722:137737.
Wu, J., Yen, H., Arnold, J.G., Yang, E., Cai, X., White, M.J., Santhi, C., Miao, C., Srinivasan, R. 2020. Development of reservoir operation functions in SWAT+ for national environmental assessments. Journal of Hydrology. 583:124556.
Wang, R., Yuan, Y., Yen, H., Grieneisen, M., Arnold, J.G., Wang, D., Wang, C., Zhang, M. 2019. A review of pesticide fate and transport simulation at watershed level using SWAT: Current status and research concerns. Science of the Total Environment. 669:512-526.
Gao, J., Bieger, K., White, M.J., Arnold, J.G. 2020. Development and accuracy assessment of a 12-digit hydrologic unit code based real-time climate database for hydrologic models in the U.S. Journal of Hydrology. 586:124817.