Location: Southeast Watershed Research
2023 Annual Report
Objectives
1. Quantify and assess the patterns, trends, and interactions among agroecosystems and landscape components and their impacts on water supply and water quality within the Little River Experimental Watershed (LREW) and in agricultural watersheds of the southeastern U.S.
1.A. Quantify the differences between water use and storage capacity among differing land use types in agricultural watersheds of the Georgia Coastal Plain.
1.B. Quantify differences in water quality as a function of land use in LREW sub-watersheds.
2. As part of the Long-Term Agroecosystem Research (LTAR) Network and a participant in the Conservation Effect Assessment Project (CEAP) effort, use GACP and other LTAR sites to quantify contrasting agroecosystem responses to “Business-As-Usual” and “Aspirational” treatments, among others, at plot, field, and farm scales.
2.A. Quantify the plot-level biophysical and hydrological responses to ASP practices as compared with BAU, that are characteristic of the GACP LTAR Network site.
2.B. Characterize and quantify the contaminants and dissolved trace gases transported from agroecosystems by surface and subsurface flow.
3. Quantitatively assess the effects of agricultural conservation practices on ecosystem services at field, landscape, and regional scales in agricultural watersheds of the southeastern US.
3.A. Characterize field level spatial and temporal variability of biophysical parameters on three farms within the LREW.
3.B. Quantify meteorological and phenological characteristics from crops under differing management practices.
4. Utilize landscape and watershed scale assessment models to improve understanding of tradeoffs among ecosystem services and evaluate the long-term sustainability of agricultural watersheds.
4.A. Estimate ecosystem services provided by GACP agricultural landscapes.
4.B. Quantify the impacts of regional cropping patterns, conservation practices and winter covers on hydrology and water quality in GACP watersheds.
4.C. Evaluate uncertainties in the regional water balance and scenarios of long-term water quality as a response to intensifying seasonal climatic extremes.
4.D. Evaluate tradeoffs in ecosystem services related to scenarios of conservation practice implementation for enhancing long-term sustainability of agricultural watersheds in the GACP region.
Approach
The goal of this project is to leverage our knowledge about the tradeoffs in ecosystem services to support stakeholder decisions about the balance of costs and benefits of conservation practice implementation. An additional goal includes contributions to the LTAR Network’s Strategic Plan by considering agroecosystem responses to sustainable intensification strategies. We do so by accounting for uncertainties in the regional water balance due to intensifying seasonal climatic extremes in order to more effectively manage ecosystem services through proper placement of conservation practices in the landscape.
The proposed research uses plot, field, landscape, and watershed observations from multiple locations in the 334 km2 Little River Experimental Watershed (LREW; centered at N31°36', W83°37') that are the basis for our long-term hydrology and natural resources research at SEWRL. Experiments are designed to evaluate processes at plot-to-landscape levels using the LREW as the basis for validating modeled outcomes from practice implementation. Each objective and sub-objective is designed to address selected spatial and temporal processes, provide information for extrapolations across scales, and/or explore novel technical approaches for characterizing ecosystems services within the LREW. Research is conducted on large plots (0.08 – 0.12 ha) at several farms in partnership with the University of Georgia, private producers’ fields (50 – 72 ha) within the LREW, and multiple collaborators.
We will compare historical observations in flow, ET, land cover, and groundwater withdrawal practices to better understand trends in the watershed. We will compare annual and seasonal means of discharge using appropriate parametric and non-parametric tests for analysis of watershed data. Rates of ET will be compared where quantifiable. Geospatial statistics and simulation models offer innovative methods for quantifying the relationships between land-use change, its driving factors and downstream effects on hydrology, nutrient loading, dissolved organic carbon chemistries, and effects of agricultural versus urban associations with water quality. As part of the LTAR Network, aspirational cropping scenarios that include biofuel feedstock production and winter cover crops will be compared to traditional (business-as-usual) systems with respect to impacts on ecosystem services (primarily C and nutrient stocks, water holding capacity, and stream flow and water quality), and profitability for producers. A long-term approach is necessary to fully evaluate the potential magnitudes of change as well as the stability of these changes. A combined approach using remote sensing and physical sampling will be used to measure changes to vegetation and crop production in relation to soil and weather conditions as affected by management practices. Regular image collection using multispectral UAS-borne sensors will occur throughout the year with flights timed to capture phenological stages in crop development. Inferences between the implemented conservation practices and the hydrologic and water quality impacts will be assessed via modeling.
Progress Report
Flow data and water quality collection and analysis efforts on the Little River Experimental (LREW), University of Georgia (UGA) Gibbs Farm, and New River (NR) watersheds (urban) continue. Data collection from the NR urban watersheds has been completed and a manuscript summarizing those results is being developed. Due to the completion of this collection, and the increasing challenges of maintaining the weirs in this urban environment, we are decommissioning the NR weirs in August 2023, and will no longer collect new data at those sites. Spatial databases of soils, hydrography, land-cover, and land-management across the LREW have been updated. Historical land-cover data were assembled in a geodatabase and are being updated regularly. Water samples are being collected at all sites in the LREW to relate dissolved nutrient loads and dissolved organic matter (DOM) to land-use. Bi-weekly water samples from the LREW, UGA Animal Science Farm (ASF), and UGA Gibbs and UGA Ponder farms are being analyzed for DOM optical characteristics. The resulting optical data are being processed using parallel factor (PARAFAC) analysis.
Existing sites at the ASF, LREW O3 sub-watershed, and LREW O sub-watershed, along with new sites at the Sumner Cooperator Farm (SCF) are being used to evaluate livestock impacts at the watershed scale. Automated flow monitoring, sample collection, and water quality analysis at existing LREW sites continues. Installation of hydrologic measurement and sampling equipment was completed at the TyTy Cooperator Farm (TCF). Pond bathymetry measurements at both TCF and SCF were modeled to obtain information on pond storage for more accurate water balance calculations and a manuscript is in progress. Data continue to be collected from the meteorological station installed at the SCF. Soil cores from ASF were collected in Oct 2022 and from the SCF in April 2023. Cores are in cold storage until processing can be completed.
Re-design of field scale plots at the UGA Gibbs (GFRP) and UGA Ponder (PFRP) farms has been completed. LTAR common experiment (CE) procedures were implemented at PFRP in Oct 2022, and baseline data are being collected at GFRP with initiation of CE procedures anticipated in Oct 2024. Baseline hydrologic data has been collected from the PFRP plots. Electricity and flumes were installed in late fall 2022 on the GFRP plots to enable baseline hydrology of those areas. Both PFRP and GFRP are fully operational. Additional groundwater wells were installed surrounding GFRP and PFRP plots to better document shallow water table depths. Imagery, both RGB and multi-spectral, is being collected regularly over the plots to document baseline surface conditions and plot development. Baseline soil cores were collected at the PFRP plots in fall 2022, and biomass samples from the plots were collected in summer 2023.
Data collection continues at the SEWRL LTAR meteorological and phenology stations. Eddy covariance data are being collected at two sites for quantifying the exchange rates of trace gases over natural ecosystems. This year, we have been unable to continue our data collection of very high resolution RGB and multispectral imagery throughout the growing season at three cooperator farms due to the failure of aging non-compliant drones and our inability to repair them. As of November 2022, our single drone which “semi-compliant” drone (a Terraview RangePro X8) was grounded due to needed repairs, which were delayed due to the process of receiving AAR approvals. To cover this period of data collection, the ARS location at Morris, Minnesota, lent us their drone, and we were able to proceed with plot-level multispectral data collection. However, due to the wear and tear caused by flights of entire farms, we did not accomplish our usual periodic flights of cooperator farms, leaving a data gap for this work, described in sub-objective 3A.
Accomplishments
1. Validation of remotely sensed soil-water. Estimates of soil moisture across the globe are critical for prediction of climate, water balance, and crop production. The Little River Experimental Watershed (LREW) managed by ARS researchers at Tifton, Georgia, is part of a nation-wide network of core validation sites collecting continuous in-situ soil-water across large spatial areas. This network has played a crucial role in the calibration and validation of satellite based remotely sensed soil-water. Tremendous improvements have been made in accuracy and resolution of these remotely sensed data, documented through scientific publications utilizing data collected at the LREW and other locations within the core validation network. The credibility of the remotely sensed data has been greatly enhanced by the testing provided by this nation-wide in-situ network. The LREW provides a unique data set for the diverse Coastal Plain landscape.
2. Importance of Long-term data in understanding soil moisture. Validation of soil moisture utilizing data collected from satellites and simulated by numerical models use ground based measurements for verification purposes. A global study including researchers from several ARS watershed locations was able to improve remotely sensed estimates of soil moisture by refining the estimation methods using the ground based measurements.
3. Agricultural environments in the conterminous U.S. are well-represented by the USDA Long-Term Agroecosystem Research Network. The USDA Long-Term Agroecosystem Research (LTAR) Network coordinates agricultural research in the United States across multiple research sites. Research outcomes have the potential for very high impact, but only if the Network represents the totality of agricultural working lands in the conterminous United States. Scientists at Tifton, Georgia; Columbia, Missouri; and Oxford, Mississippi, in collaboration with Oak Ridge National Laboratory; the University of Arizona; and the U.S. Forest Service, defined and mapped representativeness and constituency of the current LTAR network based on an analysis of 15 global environmental variables. Representativeness shows how well environmental conditions are represented by one of the LTAR sites, while constituency shows which LTAR site is the closest match for each location. LTAR representativeness was good across most of the country, but there were regions not as well represented. For those, targeted collaborations with existing sites from the Long-Term Ecological Research (LTER) Network and the National Ecological Observatory Network (NEON) would be beneficial. While this analysis considered environmental characteristics related to production on working lands, a similar process could be applied to variables that describe the primary agronomic systems or the socio-economic context. These are important aspects of socio-agroecosystems that, if considered in future analyses, could lead to a deeper understanding of how well the LTAR Network represents working lands of the continental USA, and help research leaders identify future sites’ locations.
Review Publications
Farmer, M.A., Klick, S.A., Cullen, D.W., Stevens, B.G. 2023. Eastern Oysters, Crassostrea virginica, settle near inlets in a lagoonal estuary: spatial and temporal distribution of recruitment in Mid-Atlantic Coastal Bays (Maryland, USA). PeerJ. 11:e15114. https://doi.org/10.7717/peerj.15114.
Colliander, A., Kerr, Y., Wigneron, J., Al-Yaari, A., Rodriguez-Fernandez, N., Li, X., Chaubell, J., Richaume, P., Mialon, A., Asanuma, J., Berg, A., Bosch, D.D., Caldwell, T., Cosh, M.H., Holifield Collins, C.D., Martinez-Fernandez, J., Mcnaim, H., Seyfried, M.S., Starks, P.J., Su, Z., Thibeault, M., Walker, J. 2023. Performance of SMOS soil moisture products over core validation sites. IEEE Geoscience and Remote Sensing Magazine. 20:1-5. https://doi.org/10.1109/LGRS.2023.3272878.
Welikhe, P., Williams, M.R., King, K.W., Bos, J.H., Akland, M., Baffaut, C., Beck, G., Bierer, A.M., Bosch, D.D., Brooks, E., Buda, A.R., Cavigelli, M.A., Faulkner, J., Feyereisen, G.W., Fortuna, A., Gamble, J.D., Hanrahan, B.R., Hussain, M., Kovar, J.L., Lee, B., Leytem, A.B., Liebig, M.A., Line, D., Macrae, M., Moorman, T.B., Moriasi, D.N., Mumbi, R., Nelson, N., Ortega-Pieck, A., Osmond, D., Penn, C.J., Pisani, O., Reba, M.L., Smith, D.R., Unrine, J., Webb, P., White, K.E., Wilson, H., Witthaus, L.M. 2023. Uncertainty in phosphorus fluxes and budgets across the U.S. long-term agroecosystem research network. Journal of Environmental Quality. 52(4):837-885. https://doi.org/10.1002/jeq2.20485.
Chaubell, J., Yueh, S., Dunbar, S., Andreas, C., Entekhabi, D., Chan, S., Chen, F., Xu, A., Bindlish, R., O'Neill, P., Asanuma, J., Berg, A., Bosch, D.D., Caldwell, T., Cosh, M.H., Holifield Collins, C.D., Jensen, K., Martinez-Fern, J., Mcnarin, H., Seyfried, M.S., Starks, P.J., Su, Z., Thibeault, M., Walker, J. 2022. Regularized dual-channel algorithm for the retrieval of soil moisture and vegetation optical depth for SMAP. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 15(2022):102-114. https://doi.org/10.1109/JSTARS.2021.3123932.
Elias, E.H., Tsegaye, T.D., Hapeman, C.J., Mankin, K.R., Kleinman, P.J., Cosh, M.H., Peck, D.E., Coffin, A.W., Archer, D.W., Alfieri, J.G., Anderson, M.C., Baffaut, C., Baker, J.M., Bingner, R.L., Bjorneberg, D.L., Bryant, R.B., Gao, F.N., Gao, S., Heilman, P., Knipper, K.R., Kustas, W.P., Leytem, A.B., Locke, M.A., McCarty, G.W., McElrone, A.J., Moglen, G.E., Moriasi, D.N., O'Shaughnessy, S.A., Reba, M.L., Rice, P.J., Silber-Coats, N., Wang, D., White, M.J., Dobrowolski, J.P. 2023. A vision for integrated, collaborative solutions to critical water and food challenges. Journal of Soil and Water Conservation. 78(3):63A-68A. https://doi.org/10.2489/jswc.2023.1220A.
Hoover, D.L., Abendroth, L.J., Browning, D.M., Saha, A., Snyder, K.A., Wagle, P., Witthaus, L.M., Baffaut, C., Biederman, J.A., Bosch, D.D., Bracho, R., Busch, D., Clark, P., Ellsworth, P.Z., Fay, P.A., Flerchinger, G.N., Kearney, S.P., Levers, L.R., Saliendra, N.Z., Schmer, M.R., Schomberg, H.H., Scott, R.L. 2022. Indicators of water use efficiency across diverse agroecosystems and spatiotemporal scales. Science of the Total Environment. 864. Article e160992. https://doi.org/10.1016/j.scitotenv.2022.160992.
Jones, G.M., Frosi, B., Evans, J.M., Gottlieb, I., Lox, X., Nunez-Regueiro, M.M., Ober, H.K., Pienaar, E., Pillay, R., Pisarello, K., Smith, L.L., Fletcher, R.J. 2021. Conserving alpha- and beta-diversity in wood production landscapes. Conservation Biology. https://doi.org/10.1111/cobi.13872.
Klick, S.A., Bryant, R.B., Collick, A.S., May, E.B., Pisani, O. 2023. Urea-nitrogen concentration is influenced by humic-like dissolved organic matter in agricultural drainage ditches adjacent to corn fields. Journal of Environmental Quality. 00:1-15. http://doi.org/10.1002/jeq2.20498.
Kumar, J., Coffin, A.W., Baffaut, C., Ponce-Campos, G., Witthaus, L., Hargrove, W. 2023. Quantitative representativeness and constituency of the long-term agroecosystem research network and analysis of complementarity with existing ecological networks. Environmental Management. 72:705-726. https://doi.org/10.1007/s00267-023-01834-9.
Phung, Q., Thompson, A., Baffaut, C., Witthaus, L.M., Aloysius, N., Veith, T.L., Bosch, D.D., McCarty, G.W., Lee, S. 2023. Assessing soil vulnerability index classification with respect to rainfall characteristics. Journal of Soil and Water Conservation. 78(3):209-221. https://doi.org/10.2489/jswc.2023.00065.
Sapkota, S., Harris-Shultz, K.R., Strickland, T.C., Anderson, W.F. 2022. Identification of cultured and diazotrophic bacterial endophytes in warm-season grasses. PhytoFrontiers. 3(2):411-419. https://doi.org/10.1094/PHYTOFR-10-22-0110-R.