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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

2018 Annual Report


1a. Objectives (from AD-416):
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.


1b. Approach (from AD-416):
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.


3. Progress Report:
Progress statement linked to Objective 1. Several manuscripts using distributed soil water measurements from our long-term watersheds were submitted and published by our NASA and sister laboratory collaborators. These manuscripts deal with developing calibration methods for new satellites used to measure soil moisture. Soil moisture data were collected for calibrating recently installed Cosmic ray Soil Moisture Sensors (COSMOS), which provide hectare-scale footprint measurements of soil moisture. A new in-situ automated soil water measurement network was installed around one COSMOS site to collect data for evaluating stability of one-time calibration of the COSMOS. Collaboration with Oklahoma State University focused on irrigation system efficiency and irrigation management in the Fort Cobb Reservoir Experimental watershed (FCREW). Several fields that cover different crops, soil types, and irrigation management styles were selected and instrumented. Data collection for the first year has been completed. The collected reservoir sediment cores were analyzed to determine thickness for and core textures and bulk densities. Volumetric sedimentation rates were determined based on the bathymetric survey and related to the landscape, climate, and land use variables. A peer-reviewed paper is in press. Pollen samples from sediment cores were prepared and analyzed and the data related to landuse of the reservoir drainage area. The pollen manuscript has been submitted for publication. Progress statement linked to Objective 2. Thirty-two climate (precipitation and temperature) and evapotranspiration (ET) datasets were compiled and processed for the FCREW. The coupled Soil and Water Assessment Tool (SWAT)-Groundwater (MODFLOW) model was revised and updated to the latest SWAT and MODFLOW versions, and compiled. The SWAT auto-irrigation module was revised due to differences in the spatial discretization of the SWAT (semi-distributed) and MODFLOW (fully distributed) models. New algorithms were implemented in SWAT-MODFLOW to scale up extraction volumes needed in MODFLOW from irrigations demands estimated by SWAT while keeping the water balance (surface-subsurface domain) within minimum error. New algorithms were developed to support data transformation from ET datasets to grids needed for SWATmf. A dynamic landuse module was also developed to allow changes in the SWAT model at execution time. A GIS-based modeling study was initiated to evaluate/predict flood-retarding structure sedimentation rates. An Unmanned Aerial Vehicle- Light Detection and Ranging (UAV-LiDAR) system was purchased to measure parameters associated with stream channel stability and to conduct rapid geomorphic assessments of stream corridors. Scientists and postdocs completed development of a modeling software to support to the project funded by the USDA Office of Environmental Marketing (OEM) to parameterize and validate the Agricultural Policy Environmental eXtender (APEX) model to support the nutrient tracking tool (NTT). Four manuscripts have been published, three manuscripts are undergoing the review process and one manuscript is in preparation. Dynamic landuse tool has been developed. SWAT project for testing the impact of dynamic land use on water resources outputs has been built. Progress statement linked to Objective 3. Site research for the Southern Plains Long-Term Agroecosystem Research (LTAR) was continued on two perennial long-term observational sites. The integrated 10-paddock crop-livestock Common Experiment study site (i.e., the GREEN Farm) was divided into no-till and till treatments following the 2016 wheat harvest. Two paddocks were planted into canola to position the site to have a wheat after canola and other 8 paddocks were cropped to wheat. The yield maps for 2017 harvest was obtained except for the no-till canola treatment. The yield map for 2018 was obtained for all harvested cropping systems. Activities on the GREEN Farm included: 1) completion of flume installation, 2) an electromagnetic induction survey was conducted, 3) measurement of greenhouse gases from static chambers were made, 4) in collaboration with the Forage and Livestock Research Unit and the University of Oklahoma, eddy covariance systems were installed on eight of the ten fields to measure fluxes of carbon dioxide, methane, and evapotranspiration, and 5) periodic measurements of biomass, leaf area index, chlorophyll concentration, and hyperspectral canopy reflectance. A new long-term weather station has been established to improve timeliness of data delivery to the Ag Data Commons and provide an irrigated weather station for standard PET calculations, the first in Oklahoma. Equipment to support Unmanned Aerial Vehicle (UAV) -hyperspectral research was obtained and staff were trained in operation. The scientists and technicians worked with the Ag Data Commons team on a focused workshop for the Grazinglands Research Laboratory (GRL) database design, which is now in development. The GRL database will facilitate efficient delivery of data to the Ag Data Commons. In addition, we have collected baseline data for research on diversified-adaptive cropping systems, which will be conducted in collaboration with producers’ soil health network, Oklahoma NRCS, Oklahoma Conservation Commission, and the Southern Plains Climate Hub to better understand the interactions of soil health parameters and hydrologic function. Long-term research sites were leveraged to support National Institute of Food and Agriculture (NIFA)-funded Grazing Coordinated Agricultural Project (CAP) research that focused on resilience of grazing systems to variable climate. Carbon, water, and energy fluxes were measured from perennial and annual grass sites. Nutrient use efficiency of cattle and impact of forage quality on enteric methane emissions were studied during intensive campaigns with CAP collaborations. The animal science team from Bushland, Woodward, Noble Foundation, and El Reno met to discuss analysis and manuscript development from multiple intensive campaigns focused on enteric methane emissions as related to forage/feed quality and environmental conditions. APEX models of the LTAR Grazinglands and Crop Common Experiment for the Southern Plains have been developed and are being validated.


4. Accomplishments
1. Estimation of reservoir sedimentation rates from topographic and climate parameters. Forty reservoirs were installed between 1969 and 1982 in the Little Washita River Experimental Watershed, one of the USDA Conservation Effects Assessment Project (CEAP) watersheds located in central Oklahoma. Over time, these reservoirs have lost flood and sediment storage capacity (FSSC) due to sedimentation whose rates depend on land use changes and climate variability. A team of ARS scientists at El Reno, Oklahoma and a Plains Area statistician, College Station, Texas worked to determine current flood and sediment storage capacity, reservoir sedimentation rate, projected lifespan, and possible factors affecting observed sedimentation rates. Projected lifespans ranged from 45 to 118 years, most of them higher than 50 years design period. The higher projected lifespans attributed to implementation of conservation practices through several NRCS programs over the years. Topographic and geographic factors associated with sedimentation rate are, percent of drainage area with extreme slopes, saturated hydraulic conductivity, and maximum daily rainfall event recorded in spring. The ability to estimate the FSSC and projected lifespan for various reservoirs using these factors provides a reasonable cost-effective approach and is transferrable to other areas with reservoir sedimentation challenges. Current reservoir FSSC and projected lifespan information can help water resource managers in prioritizing dams for rehabilitation and/or decommissioning.

2. Framework allows evaluation of streambank stabilization practices for reach-scale sediment reduction in streams. Process-based models can predict stream response to streambank stabilization. However, a framework does not exist on how to explicitly utilize these models to evaluate stabilization measures prior to implementation. An ARS scientist at El Reno, Oklahoma, along with university collaborators, developed a simulation framework to evaluate stabilization practices using hydraulic and sediment transport models, landowner preferences, construction costs, and effectiveness. Results indicated that incorporating multiple stabilization practices simultaneously resulted in higher sediment load reductions, but also higher costs that were quantifiable using the framework. Therefore, it is essential to consider costs when deciding on stabilization practices to apply. Vegetation with 2:1 bank slopes was the most cost-effective stabilization technique. The framework provides NRCS, and others, with a methodology to evaluate cost-benefit scenarios for selection of the most appropriate channel stabilization practice to implement.

3. Changes in precipitation patterns evaluated from long-term ARS data record. Identification of semi-stable shifts in precipitation patterns and precipitation amounts can inform strategies to help sustain/enhance agricultural productivity. Precipitation data (1962-2015) from the Little Washita River Experimental Watershed (LWREW), part of ARS’ Long Term Agroecosystem Research (LTAR) network, were used by university collaborators and ARS scientists to determine if shifts in precipitation patterns and amounts have occurred. Along the latest 55 years, the LWREW experienced successive long-term wet (1962-1995) and dry (1996-2015) periods. During the wet period of the data record precipitation intensities ranging from 1 to 12 mm in 5-min were 20% less likely to occur when compared to the 55-year baseline while daily average precipitation and number of events increased by 10 and 11%, respectively. During the dry period of the record, precipitation intensity ranging from 1 to 12 mm in 5-min became more likely to occur (64% increase) while event daily average precipitation and number of events decreased by 16 and 18%, respectively. Over the last 20 years, sub-hourly precipitation intensities have increased while daily event duration and extreme 5-min precipitation intensities larger than 24 mm have remained unchanged. Better understanding of precipitation dynamics will allow action agencies and scientists to better assess and evaluate hydrologic budgets and the performance of soil and water conservation practices.


Review Publications
Enlow, H., Fox, G., Boyer, T., Stoecker, A., Storm, D., Starks, P.J., Guertault, L. 2017. A modeling framework for evaluating streambank stabilization practices for reach-scale sediment reduction. Journal of Environmental Modeling and Software. Available at: https://doi.org/10.1016/j.envsoft.2017.11.010.

Nelson, A.M., Moriasi, D.N., Talebizadeh, M., Steiner, J.L., Confesor, R., Gowda, P., Starks, P.J., Tadesse, H.K. 2017. Impact of length of dataset on streamflow calibration parameters and performance of APEX model. Journal of the American Water Resources Association. https://doi.org/10.1111/1752-1688.12564.

Prada, A.F., Chu, M.L., Guzman, J.A., Moriasi, D.N. 2017. Evaluating the impacts of agricultural land management practices: A probabilistic hydrologic modeling approach. Journal of Environmental Management. 193:512-523.

Tadesse, H.K., Moriasi, D.N., Gowda, P., Marek, G.W., Steiner, J.L., Brauer, D.K., Talebizadeh, M., Nelson, A.M., Starks, P.J. 2018. Evaluating evapotranspiration estimation methods in APEX model for dryland cropping systems in a semi-arid region. Agricultural Water Management. 206:217-228. https://doi.org/10.1016/j.agwat.2018.04.007.

Talebizadeh, M., Moriasi, D.N., Gowda, P., Steiner, J.L., Tadesse, H.K., Nelson, A.M., Starks, P.J. 2018. Simultaneous calibration of evapotranspiration and crop yield in agronomic system modeling using the APEX model. Agricultural Water Management. 208: 299-306. https://doi.org/10.1016/j.agwat.2018.06.043.

Bindlish, R., Cosh, M.H., Jackson, T.J., Koike, T., Fuiji, X., De Jeu,, R., Chan, S., Asanuma, J., Berg, A., Bosch, D.D., Caldwell, T., Holifield Collins, C.D., McNairn, H., Martinez-Fernandez, J., Prueger, J.H., Rowlandson, T., Seyfried, M.S., Starks, P.J., Su, Z., Thibeault, M., van der Velde, R., Walker, J., Coopersmith, E. 2018. GCOM-W AMSR2 soil moisture product validation using core validation sites. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 11(1):209-219. https://doi.org/10.1109/JSTARS.2017.2754293.

Colliander, A., Jackson, T.J., Chan, S., O'Neill, P., Bindlish, R., Cosh, M.H., Caldwell, T., Walker, J., Berg, A., McNairn, H., Thibeault, M., Martinez-Fernandez, J., Jensen, K., Asanuma, J., Seyfried, M.S., Bosch, D.D., Starks, P., Holifield Collins, C.D., Prueger, J.H., Su, Z., Lopez-Beeza, E., Yeuh, S. 2018. An assessment of the differences between spatial resolution and grid size for the SMAP enhanced soil moisture product over homogeneous sites. Remote Sensing of Environment. 207:65-70.

Nearing, G., Yatheendrades, S., Crow, W.T., Bosch, D.D., Cosh, M.H., Goodrich, D.C., Seyfried, M.S., Starks, P.J. 2017. Nonparametric triple collocation. Water Research. 53(7):5516-5530. https://doi.org/10.1002/2017WR020359.

Kolassa, J., Reichle, R., Liu, Q., Cosh, M.H., Bosch, D.D., Caldwell, T., Colliander, A., Holifield Collins, C.D., Jackson, T.J., Livingston, S.J., Moghaddam, M., Starks, P.J. 2017. Data assimilation to extract soil moisture information from SMAP observations. Remote Sensing. 9(11):1179. https://doi.org/10.3390/rs9111179.

Reichle, R., De Lannoy, G., Liu, Q., Ardizonne, J., Colliander, A., Conaty, A., Crow, W.T., Jackson, T.J., Jones, L., Kimball, J., Koster, R., Mahanama, S., Smith, E., Berg, A., Bircher, S., Bosch, D.D., Caldwell, T., Cosh, M.H., Gonzalez-Zanora, A., Holifield Collins, C.D., Livingston, S.J., Lopez-Baeza, E., Martinez-Fernandez, J., McNairn, H., Moghaddam, M., Pacheco, A., Pellarin, T., Prueger, J.H., Rowlandson, T., Seyfried, M.S., Starks, P.J., Su, Z., Thibeault, M., Uldall, F., van der Velde, R., Walker, J., Wu, X., Zeng, Y. 2017. Assessment of the SMAP Level-4 surface and root-zone soil moisture product using in situ measurements. Journal of Hydrometeorology. 18(10):2621-2645. https://doi.org/10.1175/JHM-D-17-0063.1.

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. https://doi.org/10.1016/j.agrformet.2017.01.018.

Bajgain, R., Xiao, X., Basara, J., Wagle, P., Zhou, Y., Mahan, H., Gowda, P., Mccarthy, H., Northup, B.K., Neel, J.P., Steiner, J.L. 2018. Carbon dioxide and water vapor fluxes in winter wheat and tallgrass prairie in central Oklahoma. Science of the Total Environment. 644: 1511-1524. https://doi.org/10.1016/j.scitotenv.2018.07.010.

Doughty, R., Xiao, X., Wu, X., Zhang, Y., Bajgain, R., Zhou, Y., Qin, Y., Zou, Z., Mccarthy, H., Friedman, J., Wagle, P., Basara, J., Steiner, J.L. 2018. Responses of gross primary production of grasslands and croplands under drought, pluvial, and irrigation conditions during 2010-2016, Oklahoma, USA. Agricultural Water Management. 204:47-59. https://doi.org/10.1016/j.agwat.2018.04.001.

Spiegal, S.A., Bestelmeyer, B.T., Archer, D.W., Augustine, D.J., Boughton, E., Boughton, R., Clark, P., Derner, J.D., Duncan, E.W., Cavigelli, M.A., Hapeman, C.J., Harmel, R.D., Heilman, P., Holly, M.A., Huggins, D.R., King, K.W., Kleinman, P.J., Liebig, M.A., Locke, M.A., McCarty, G.W., Millar, N., Mirsky, S.B., Moorman, T.B., Pierson Jr, F.B., Rigby Jr, J.R., Robertson, G., Steiner, J.L., Strickland, T.C., Swain, H., Wienhold, B.J., Wulfhorts, J., Yost, M., Walthall, C.L. 2018. Evaluating strategies for sustainable intensification of U.S. agriculture through the Long-Term Agroecosystem Research network. Environmental Research Letters. 13(3):034031. https://doi.org/10.1088/1748-9326/aaa779.

Moriasi, D.N., Steiner, J.L., Duke, S.E., Starks, P.J., Verser, J.A. 2018. Reservoir sedimentation rates in the Little Washita River experimental watershed, Oklahoma: measurement and controlling factors. Journal of the American Water Resources Association. 1-13. https://doi.org/10.1111/1752-1688.12658.

Guzman, J.A., Chu, M.L., Steiner, J.L., Starks, P.J. 2018. Assessing and quantifying changes in precipitation patterns using event-driven analysis. Journal of Hydrology. 15: 1-15. https://doi.org/10.1016/j.ejrh.2017.11.006.

Avila-Carrasco, R., Junez-Ferreira, H.E., Gowda, P., Steiner, J.L., Moriasi, D.N., Starks, P.J., Gonzalez, T.J., Villalobos, A.A., Bautista-Capetillo, C. 2018. Evaluation of satellite-derived rainfall data for multiple physio-climatic regions in the Santiago River Basin, Mexico. Journal of the American Water Resources Association. 54(5):1-19. https://doi.org/10.1111/1752-1688.12672.

Petrie, M., Peters, D.C., Yao, J., Blair, J.M., Burruss, N., Collins, S., Derner, J.D., Gherardi, L.A., Hendrickson, J.R., Sala, O., Starks, P.J., Steiner, J.L. 2018. Regional grassland productivity responses to precipitation during multiyear above- and below-average rainfall periods. Global Change Biology. 24:1935-1951. https://doi.org/10.1111/gcb.14024.