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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

2017 Annual Report


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:
Subobjective 1B: A conceptual model of carbon/nitrogen/phosphorus stoichiometric ratios was developed and tested using data from the River Thames (United Kingdom) which included nutrient and chlorophyll-a concentrations. Chlorophyll-a (the green pigment in algae and higher plants) serves as a proxy for algal productivity, with higher concentrations indicating more algae in the river. Carbon and nitrogen concentrations are not limiting in the River Thames, but the conceptual model was able to predict when phosphorus deficiencies limited algal productivity. This conceptual framework is currently being tested using other datasets to evaluate the influence of land-use and hydrologic flowpath on carbon/nitrogen/phosphorus stoichiometry. Subobjective 2A: The input file structure of the Soil and Water Assessment Tool (SWAT) was modified to allow spatially detailed simulations. The new structure allows input files to be easily maintained, supported and modified. The entire routing structure was redesigned into an object based approach that gives more flexibility in connecting watershed objects (ie: fields, channels, reservoirs, aquifers, etc.). We can now simulate the entire sediment budget for the U.S. including gullies, small tributaries and higher order channels. Drainage and irrigation systems can be modeled more realistically as well as watersheds that do not have main channels such as playa lakes, non-draining lakes, no hydrography, and all wetlands. Additional modules were included in SWAT+ for a simple water balance and plant growth. The modules are simple and efficient enough for real time simulation at high spatial resolution for the entire U.S. The SWAT+ routing structure now allows for routing across landscape units and for overbank flow onto flood plains. Subobjective 3A: A software framework has been developed and tested to perform national export coefficient model simulations. These simulations are the basis for a variety of existing and planned national scale decision support tools. The framework was developed to function on both desktops and computer cluster environments. A server side application was developed to deploy natural resource model data (climate, soils, land cover, management and conservation practice data) and assign simulation jobs to individual computer cores. A client application retrieves and uses that data to perform an individual Soil and Water Assessment Tool (SWAT) model simulation on that computer core. Data from individual simulations is collected in a central Microsoft SQL Server database for later analysis. The framework was tested by producing a database of 100 million individual SWAT simulations each representing differing field conditions. These data are currently being mined to predict the effectiveness of various conservation practices regionally. With this software framework in place, data being developed for the second generation of the Conservation Effects Assessment Project (CEAP II) national assessments is being incorporated as it is produced. Recent datasets produced, published, and integrated into the framework include: cropland management, station based climate, and conservation practice distributions derived from Google Earth imagery. As additional data sources are developed, they too will be ingested to develop more robust export coefficients with which to drive future online decision support tools. Subobjective 3B: A national climatic dataset has been developed from weather stations over the period 1960 to 2016 for the U.S. to support the second generation Conservation Effects Assessment Project (CEAP II) simulations. Soils data has been developed for the U.S. based on the Soil Survey Geographic (SSURGO) and the State Soil Geographic (STATSGO) databases. Land use and soils have been combined in a geographic information system (GIS) to produce draft Soil and Water Assessment Tool (SWAT) Hydrologic Response Units (HRUs) for the entire U.S. A secondary refining of HRUs has been performed for agricultural intensive regions. Multiple year land use data have been combined in a GIS to identify primary crop rotation patterns in the U.S. These data are being used to identify appropriate crop operation templates to use in SWAT. Point source data has been assembled from available sources and systematically patched to provide Hydrologic Unit Code 12 (HUC12, roughly 10,000 acre) level estimates for the U.S. Reservoir depth and water release data have been compiled for 100+ dams. These data are being used to describe reservoir operations in the SWAT model. The National Hydrography Dataset has been analyzed to provide connectivity information for use in SWAT. These data will facilitate the simulation of smaller streams, ponds and flood control structures which are critical sediment and nutrient sinks in many regions.


4. Accomplishments
1. Second generation Conservation Effects Assessment Project initiated. The successful completion of the Conservation Effects Assessment Project (CEAP) cropland assessment highlighted several improvements that are needed in future assessments. Spatial resolution at the watershed scale requires refinement to accurately simulate spatial rainfall variability and to simulate the complete sediment budget including gullies and first order tributaries. This is critical to model legacy sediments and ensure realistic scenario analysis. In order to downscale CEAP, the Soil and Water Assessment Tool (SWAT) model was restructured by ARS scientists in Temple, Texas. The routing structure was redesigned into an object based approach that gives more flexibility in connecting watershed objects (ie: fields, channels, reservoirs, aquifers, etc.). We can now simulate the entire sediment budget for the U.S. including gullies, small tributaries and higher order channels. Drainage and irrigation systems can be modeled more realistically as well as watersheds that do not have main channels such as playa lakes, non-draining lakes, and wetlands. The climate data was downscaled and multiple year land use data have been combined in a Geographic Information System (GIS) to identify primary crop rotation patterns in the U.S. These data are being used to identify appropriate crop operation templates to use in SWAT. Point sources, reservoir, and atmospheric deposition data were all downscaled and restructured. The National Hydrography Dataset has been analyzed to provide connectivity information for use in SWAT. These data will facilitate the simulation of smaller streams, ponds and flood control structures which are critical sediment and nutrient sinks in many regions. These new capabilities will ensure that CEAP provides scientifically-sound conservation policy.

2. Data and methods to support advanced conservation and farm management decision support tools developed. Watershed models are useful tools to inform conservation policy, but are too complex and slow to drive real time decision support tools. Model simulation can be performed ahead of time in some cases. The Real-Time Conservation Effects Assessment Project (CEAP) demonstration prototype was recently developed by ARS scientists in Temple, Texas to help producers make better pesticide/fertilizer application decisions by using Soil and Water Assessment Tool (SWAT) to predict future runoff based on short term forecasts. A web application, grid based national SWAT model, and weather forecast processor has been developed to support this effort. Real-Time CEAP requires only one simulation per day to remain current as weather is the only input variable. More complex decision support tools may require that every conceivable combination of factors that a decision maker may face could require advanced simulation, a daunting computational problem. A software framework has been developed to configure and execute millions of model simulations in advance on the Temple, Texas computing cluster, and later “mining” these data to address a specific inquiry using the export coefficient concept. National datasets developed in part for CEAP II have been incorporated in recent testing. These published data include: crop management schedules, soils, station based climate, and conservation practice distributions derived from Google imagery. A test dataset of 100 million simulations was recently developed to predict the effectiveness of various conservation practices by eco-region. Similar datasets with greater resolution will be developed as additional CEAP II datasets become available. Eventually these data will be used to drive web-based tools to estimate the effect of conservation practices and land use change.

3. Database updated to include crucial nutrient loss pathway. The “Measured Annual Nutrient loads from AGricultural Environments” (MANGE) database has been recognized since 2006 as a resource for information on nutrient losses from agricultural landscapes. However, early versions of this database only contained information on surface runoff pathways. This database was updated by ARS scientists in Temple, Texas to include additional resources for agricultural and forest landscapes, and now includes more than 90 studies with subsurface tile drainage nutrient loss data. The additional data makes this one of the most robust databases in the world in terms of nutrient fate and transport of nutrient losses from agricultural and forested landscapes.


Review Publications
Bieger, K., Arnold, J.G., Rathjens, H., White, M.J., Bosch, D.D., Allen, P.M., Volk, M., Srinivasan, R. 2017. Introduction to SWAT+, a completely restructured version of the soil and water assessment tool. Journal of the American Water Resources Association. 53(1):115-130. https://doi.org/10.1111/1752-1688.12482.

Garcia, A.M., Alexander, R.B., Arnold, J.G., Norfleet, L., White, M.J., Robertson, D.M., Schwarz, G. 2016. Regional effects of agricultural conservation practices on nutrient transport in the Upper Mississippi River Basin. Journal of Environmental Science and Technology. 50:6991-7000. doi:10.1021/acs.est.5b03543.

Rathjens, H., Bieger, K., Chaubey, I., Arnold, J.G., Allen, P.M., Srinivasan, R., Bosch, D.D., Volk, M. 2016. Delineating floodplain and upload areas for hydrologic models: A comparison of methods. Hydrological Processes. 30:4367-4383. doi:10.1002/hyp.10918.

Yen, H., White, M.J., Ascough II, J.C., Smith, D.R., Arnold, J.G. 2016. Augmenting watershed model calibration with incorporation of ancillary data sources and qualitative soft data sources. Journal of the American Water Resources Association. 52(3):788-798. doi:10.1111/1752-1688.12428.

Sun, X., Bernard-Jannin, L., Garneau, C., Volk, M., Arnold, J.G., Srinivasan, R., Sauvage, S., Sanchez-Perez, J.M. 2016. Improved simulation of river water and groundwater exchange in an alluvial plain using the SWAT model. Hydrological Processes. 30:187-202.

Sun, X., Bernard-Jannin, L., Sauvage, S., Garneau, C., Arnold, J.G., Srinivasan, R., Sanchez-Perez, J.M. 2016. Assessment of the denitrification process in alluvial wetlands at floodplain scale using the SWAT model. Ecological Engineering. 103:344-358. doi:10.1016/j.ecoleng.2016.06.098.

Dile, Y.T., Daggupati, P., George, C., Srinivasan, R., Arnold, J.G. 2016. Introducing a new open source GIS user interface for the SWAT model. Environmental Modelling & Software. 85:129-138.

Bailey, R., Rathjens, H., Bieger, K., Chaubey, I., Arnold, J.G. 2017. SWATMOD-PREP: Graphical user interface for preparing coupled SWAT-modflow simulations. Journal of the American Water Resources Association. 53(2):400-410. doi:10.1111/1752-1688.12502.

White, M.J., Gambone, M., Yen, H., Daggupati, P., Bieger, K., Deb, D., Arnold, J.G. 2016. Development of cropland management dataset to support U.S. SWAT assessments. Journal of the American Water Resources Association. 52(1):269-274.

Yen, H., Daggupati, P., White, M.J., Srinivasan, R., Gossel, A., Wells, D., Arnold, J.G. 2016. Application of large-scale, multi-resolution watershed modeling framework using the Hydrologic and Water Quality System (HAWQS). Water. 8(164):1-23.

Kiniry, J.R., Muscha, J.M., Petersen, M.K., Kilian, R.W., Metz, L.J. 2017. Short duration, perennial grasses in low rainfall sites in Montana: Deriving growth parameters and simulating with a process-based model. Journal of Experimental Agriculture International. 15(6):1-13. doi:10.9734/JEAI/2017/32232.

Kim, S., Kiniry, J.R., Loomis, L. 2017. Creosote bush, an arid zone survivor in southwestern U.S.: 1. Identification of morphological and environmental factors that affect its growth and development. Journal of Agriculture and Ecology Research International. 11(4):1-14. doi:10.9734/JAERI/2017/33204.

Kim, S., Kiniry, J.R., Williams, A.S., Meki, M.N., Gaston, L.A., Brakie, M., Shadow, A., Fritschi, F.B., Wu, Y. 2017. Adaptation of C4 bioenergy crop species to various environments within the Southern Great Plains of U.S. Sustainability. 9:89. doi:10.3390/su9010089.

Youkhana, A.H., Ogoshi, R.M., Kiniry, J.R., Meki, M.N., Nakahata, M.H., Crow, S.E. 2017. Allometric models for predicting aboveground biomass and carbon stock of tropical perennial C4 grasses in Hawaii. Frontiers in Plant Science. 8:650. doi:10.3389/fpls.2017.00650.

Meki, M.N., Ogoshi, R.M., Kiniry, J.R., Crow, S.E., Youkhana, A.H., Nakahata, M.H., Littlejohn, K. 2017. Performance evaluation of biomass sorghum in Hawaii and Texas. Industrial Crops and Products. 103:257-266.

Pawlowski, M.N., Crow, S.E., Meki, M.N., Kiniry, J.R., Taylor, A.D., Ogoshi, R., Youkhana, A., Nakahata, M. 2017. Field-based estimates of global warming potential in bioenergy systems of Hawaii: Crop choice and deficit irrigation. PLoS One. 12(1):e0168510. doi:01.1371/journal.pone/0168510.

Mitchell, R., Schmer, M.R., Anderson, W.F., Jin, V.L., Balkcom, K.S., Kiniry, J.R., Coffin, A.W., White Jr, P.M. 2016. Dedicated energy crops and crop residues for bioenergy feedstocks in the Central and Eastern U.S.A. BioEnergy Research. 9:384-398.

Oblath, E.A., Isbell, T.A., Berhow, M.A., Allen, B., Archer, D., Brown, J., Gesch, R.W., Hatfield, J.L., Jabro, J.D., Kiniry, J.R., Long, D.S. 2016. Development of near-infrared spectroscopy calibrations to measure quality characteristics in intact Brassicaceae germplasm. Industrial Crops and Products. 89:52-58.

Hunter, K.M., Archer, D.W., Gesch, R.W., Vigil, M.F., Hatfield, J.L., Allen, B.L., Jabro, J.D., Kim, S., Meki, M.N., Kiniry, J.R. 2017. Degree days to 50% flowering for 12 cultivars of spring canola-like mustard. Journal of Agriculture and Ecology Research International. 11(4):1-8.

Yen, H., Jeong, J., Smith, D.R. 2016. Evaluation of dynamically dimensioned search algorithm for optimizing SWAT by altering sampling distributions and searching range. Journal of the American Water Resources Association. 52(2):443-455. doi:10.1111/1752-1688.12394.

Francesconi, W., Williams, C.O., Smith, D.R., Williams, J.R., Jeong, J. 2016. Phosphorus modeling in tile drained agricultural systems using APEX. Journal of Fertilizers & Pesticides. 7(1):166. doi:10.4172/2471-2728.1000166.

Christianson, L.E., Harmel, R.D., Smith, D.R., Williams, M.R., King, K.W. 2016. Assessment and synthesis of 50 years of published drainage phosphorus losses. Journal of Environmental Quality. 45:1467-1477. doi:10.2134/jeq2015.12.0593.

Her, Y., Chaubey, I., Frankenberger, J., Smith, D.R. 2016. Effect of conservation practices implemented by USDA programs at field and watershed scales. Journal of Soil and Water Conservation. 71(3):204-221.

Harmel, R.D., Christianson, L.E., McBroom, M.W., Smith, D.R., Higgs, K.D. 2016. Expansion of the MANAGE database with forest and drainage studies. Water Resources Research. 52(5):1275-1279. doi:10.1111/1752-1688.12438.

Harmel, R.D., Wagner, K., Martin, E., Smith, D.R., Wanjugi, P., Gentry, T., Gregory, L., Hendon, T. 2016. Effects of field storage method on E. coli concentrations measured in storm water runoff. Environmental Monitoring and Assessment. 188:170. doi:10.1007/S10661-016-5183-9.

Mittelstet, A.R., Storm, D.E., White, M.J. 2016. Using SWAT to enhance watershed-based plans to meet numeric water quality standards. Sustainability of Water Quality and Ecology. 7:5-21.

Sang, J.K., Allen, P.M., Dunbar, J.A., Arnold, J.G., White, J.D. 2015. Sediment yield dynamics during the 1950s multi-year droughts from two ungauged basins in the Edwards Plateau, Texas. Journal of Water Resource and Protection. 7:1345-1362.

Daggupati, P., Yen, H., White, M.J., Srinivasan, R., Arnold, J.G., Keitzer, C.S., Sowa, S.P. 2015. Impact of model development, calibration and validation decisions on hydrological simulations in West Lake Erie Basin. Hydrological Processes. 29:5307-5320.

Dunbar, J., Allen, P., White, J., Neupane, R., Xu, T., Wolfe, J., Arnold, J.G. 2015. Characterizing a shallow groundwater system beneath irrigated sugarcane with electrical resistivity and radon (Rn-222), Puunene, Hawaii. Journal of Environmental & Engineering Geophysics. 20(2):165-181.

Yen, H., Su, Y., Wolfe III, J.E., Chen, S., Hsu, Y., Tseng, W., Brady, D.M., Jeong, J., Arnold, J.G. 2015. Assessment of input uncertainty by seasonally categorized latent variables using SWAT. Journal of Hydrology. 531:685-695.

Bieger, K., Rathjens, H., Allen, P.M., Arnold, J.G. 2016. Development and comparison of multiple regression models to predict bankfull channel dimensions for use in hydrologic models. Journal of the American Water Resources Association. 52(6):1385-1400. doi:10.1111/1752-1688.