1a. Objectives (from AD-416):
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.
1b. Approach (from AD-416):
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.
3. Progress Report:
Soil samples have been collected monthly from the aspirational and business-as-usual cultivated fields as part of the Long-Term Agroecosystem Research (LTAR) network and analyzed for treatment effects on plant uptake, soil nutrient availability, runoff quality, and soil microbial communities using PhosphoLipid Fatty Acid (PLFA) techniques. PLFA analyses of microbial communities showed significant differences among treatments and were related to the level of soil organic matter. Preliminary nutrient budgets of N and P have been derived for the business-as-usual treatments. In situ chambers to measure soil greenhouse gas emissions will be installed in treatments winter 2018. Subobjective 2A: The entire routing structure of Soil and Water Assessment Tool Plus (SWAT+) was refined to include additional processes to simulate water, sediment and nutrient budgets across the U.S. including gullies, small tributaries and higher order channels. Routines were developed and tested at the ARS watersheds in Tifton, Georgia for landscape transport from uplands to flood plains and overbank flow (flooding) from channels to flood plains. In addition, a gully head cut model was developed and tested in Iowa and Texas. Major revisions were made to plant growth algorithms in SWAT+ to simulate tropical plant growth that is regulated by soil moisture and independent of temperature and day length. Decision tables are a precise yet compact way to model the rule sets and corresponding actions found in these models. Decision table theory was incorporated into SWAT+ to simulate automated irrigation and reservoir releases. Decision tables were tested in SWAT+ by using one to schedule automatic irrigation based on a plant water stress threshold for corn in Texas. As expected, predicted soil moisture and corn yield varied based on the plant water stress level which triggered irrigation as defined in the decision table. When irrigation was triggered at lower levels of plant stress, more frequent irrigation resulted in greater yield and moisture. The Grapevine Reservoir near Dallas, Texas was used to illustrate the use of decision tables to simulate reservoir releases. The releases were conditioned on reservoir volumes and flood season. Using decision tables to simulate management in SWAT+ was shown to have several advantages over current approaches, including: (1) ability to accurately represent complex, real world decision-making; (2) code that is efficient, modular, and easy to maintain; and (3) tables that are easy to maintain, support, and modify. Subobjective 2B: Work completed to enhance the Agricultural Land Management Alternative with Numerical Assessment Criteria (ALMANAC) model’s ability to simulate cool season grasses, arid zone plants such as creosote bush, and wetland plants. This involved adding and improving relevant plant parameters and changing the code to enable realistic simulation of the bimodal growth pattern of cool season grasses and the long-term growth of creosote bush, black willow, and green ash. This improved the model’s utility for simulating a wide range of plant types in a diversity of environments. Subobjective 3A: A national database of export coefficients was developed using a simulation framework that utilizes data directly from the Conservation Effects Assessment Project (CEAP) II national assessment. These data have been improved over previous versions by utilizing more advanced soils, management, and crop rotation information. The framework randomly selects a field within the contiguous U.S., and queries CEAP II model input data to develop a single SWAT simulation for that field. The results are then uploaded to a central SQL server and later analyzed to provide a distribution of export coefficients for various soil and cropping system combinations. Several conservation practice scenarios are then applied to each simulation and, in turn, uploaded. Pairwise field comparisons between simulations with and without a particular conservation practice are used to predict practice effectiveness across the U.S. This framework is executed on a local computer cluster of 68 servers to develop databases with hundreds of millions of simulations. Draft export coefficient distributions have been developed for the U.S. by location, soil, and cropping system. These national data were incorporated into a decision support application to predict edge-of-field loads under various conservation scenarios. This application is being evaluated by cooperators for use in supply chain sustainability analysis. A web-based version of this decision support system will be developed for use by producers and conservation planners. Subobjective 3B: A number of datasets have been developed over the past two years to support CEAP II national simulation. These include climate, soils, land use, management, reservoirs, streams and point sources. A system of software has been developed to transform these data into functional SWAT+ models of the U.S. A SWAT+ model was developed for each of 2,109 HUC8 level watersheds in the contiguous U.S. Each of these models is comprised of approximately 40 subbasins and 1,500 Hydrologic Response Units (HRUs). The upland portion of these models are complete, the integration of streams and reservoirs is pending. These models have been coarsely calibrated for evapotranspiration, surface runoff and baseflow using published estimates. By splitting the U.S. into 2,109 separate models, these can be executed very quickly on high performance servers. One version of this national model, the real-time CEAP model, incorporates recent and future rainfall predictions by the National Weather Service. This model is executed each night allowing model predicted soil moisture and runoff to be uploaded to the web. A website has been developed to provide county-based estimates of soil moisture and runoff for the next 3 days to help producers apply agricultural chemicals at the best time to prevent losses in runoff.
1. Real-time decision support tool developed. The Real-time Conservation Effects Assessment Project (CEAP) model is a highly detailed, national scale Soil and Water Assessment Tool Plus (SWAT+) model developed to aid agricultural producers in timing field operations. Real-time CEAP is based on the developing CEAPII framework and contains more than 3 million simulation units within the contiguous U.S. representing various combinations of climate, soils, and land management. This model is updated each day with observed NEXRAD and National Weather Service 3-day forecasted precipitation. Simulations are updated each night on a high-performance server. Predicted soil moisture and surface runoff are used to better inform producers how to time pesticide and fertilizer applications to prevent losses in runoff. County level model predictions, application advisories, and warnings are publicly available via the Real-time CEAP website (https://realtimeceap.brc.tamus.edu/)
2. Tool developed to evaluate carbon, nitrogen and phosphorus limitation in surface waters. Algal blooms in surface waters, such as rivers, lakes and estuaries, depends largely on the availability of carbon, nitrogen and phosphorus. Generally, algae are most prolific when nutrients are at a ratio of 106 carbon and 16 nitrogen for each 1 phosphorus, known as the Redfield Ratio. In this paper, we propose a method to graph the carbon to nitrogen to phosphorus ratio using data from five tributaries to the River Thames in the United Kingdom. The dissolved nutrient values in tributary water samples were used to determine the carbon to nitrogen to phosphorus ratio. The samples were then categorized based on the total phosphorus concentration as well as the chlorophyll-a concentration, which is a proxy for the amount of algae in the sample. Samples with high levels of algae (more than 30 parts per billion chlorophyll-a) tended to only occur when the ration of total dissolved phosphorus accounted for 13% of the carbon to nitrogen to phosphorus ratio. This work has sparked further interest in exploring the role of coupled carbon, nitrogen and phosphorus stoichiometry in streams and rivers by other research groups. Additionally, collaborators on this project have used this tool to compare national small stream and large river datasets across the United Kingdom. This research provides other scientists and policy makers with target levels, below which algal blooms may be inhibited.
3. Unjustified, farmers get sole blame for eutrophication. Phosphorus loading to Lake Erie and the resulting algal blooms has been blamed on farmers and their fertilizer management. Studies conducted by ARS scientists at Temple, Texas explored the role of fertilizer and farm management on the potential for inducing nutrient losses from agricultural fields in the region. Fertilizers applied to fields was recorded for more than 2,000 fields in the region, and 90% of fields had less phosphorus fertilizer applied than was required by fertility guidance. In a complimentary study, the change point in soluble phosphorus loading to the lake occurred just as peak adoption of conservation tillage began. There was little guidance to farmers on how to adjust fertilizer management upon adoption of no till. Based on these analyses, the majority of farmers in the region seem to be adhering to the best available fertility and conservation guidance to protect Lake Erie. However, it may be that very guidance that is creating the algal blooms and should be thoroughly evaluated to limit eutrophication of Lake Erie insofar as possible.
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