Location: Cropping Systems and Water Quality Research
2017 Annual Report
Accomplishments
1. New tools to detect degraded sensors. Automated weather stations and other installations require substantial labor for care and maintenance to ensure high quality data are collected. Some installations use a second sensor to provide a check on the primary one. Even so, it is difficult to detect the onset of sensor problems that although small, degrade the quality of the data products. Using datalogger and post-processing approaches (i.e., no additional equipment), ARS researchers and cooperators at Columbia, Missouri, produced tools that inform the quality assurance process for both single- and dual-sensor installations. Implementing these tools can assist researchers in producing higher-quality weather and other sensor-based data for use in empirical and model-based research to solve agricultural problems.
2. A regional parameter set for the Agricultural and Policy Environmental Extender (APEX). APEX is capable of estimating edge-of-field water, nutrient, and sediment transport and is used to assess the environmental impacts of agricultural management practices. The program requires hundreds of input parameters, some of which need to be adjusted (i.e., calibrated) based on the comparison of simulated flow and water quality. Since flow and water quality data are not always available measured data, ARS researchers in Columbia, Missouri and university cooperators developed and validated a regionally calibrated model using data from twelve sites with restricted-layer soils of Iowa, Missouri, and Kansas. Use of APEX with this parameter set can produce very good estimates of event runoff but total phosphorus loss estimates should be used with caution due to poor simulation of sediment loss. Availability of this parameterization strategy is important for researchers and water resource managers who need runoff estimates on soils with restrictive layers but do not have the data or resources to calibrate the model.
3. Computer simulation models should be calibrated with data from several management systems. Computer simulation models are being used to evaluate the effects of management practices on water quality. For this purpose, they are often calibrated (i.e., input parameters are adjusted so that simulated results match monitoring data) with data specific to one management practice, and then used to evaluate alternative management systems. ARS researchers in Columbia, Missouri and university cooperators calibrated the APEX model and tested its accuracy with the management used for calibration and with different managements. Models were also developed by using data from all the managements together. When applied outside the calibration management, the models were accurate only in 1/3 of the tests. Models developed with data from multiple managements were more accurate. For maximum confidence, models should only be applied within the managements used for calibration. Using data from multiple management systems for model calibration should increase result reliability. These results are important model limitations that researchers and water resource managers need to be aware of for improved confidence in model results.
4. Vegetative buffer strips reduce herbicides in runoff. Vegetative buffer strips have been shown to be effective for reducing sediment and nutrient transport from fields, but they had not been tested for reducing herbicides from high runoff potential soils. This study evaluated the effects of different grasses, buffer width, and season on the movement of three commonly used herbicides - atrazine, metolachlor, and glyphosate– in runoff from a claypan soil. All grass treatments were shown to be similarly effective at reducing herbicide and sediment losses in runoff, and reductions in contaminant load were mainly related to buffer width. Using equations developed from this study, herbicide load reductions can be estimated for any combination of source drainage area and buffer width. These models provide conservation agencies and landowners a simple tool for effectively implementing buffer strips to control herbicide losses from cropped fields.
Review Publications
Delgado, J.A., Weyers, S.L., Dell, C.J., Harmel, R.D., Kleinman, P.J., Sistani, K.R., Leytem, A.B., Huggins, D.R., Strickland, T.C., Kitchen, N.R., Meisinger, J.J., Del Grosso, S.J., Johnson, J.M., Balkcom, K.S., Finley, J.W., Fukagawa, N.K., Powell, J.M., Van Pelt, R.S. 2016. USDA Agricultural Research Service creates Nutrient Uptake and Outcome Network (NUOnet) Journal of Soil and Water Conservation. 71(6):147A-148A. https://doi.org/10.2489/jswc.71.6.147A.
Baffaut, C., Nelson, N.O., Lory, J.A., Senaviratne, G., Bhandari, A.B., Udawatta, R.P., Sweeney, D.W., Helmers, M.J., Van Liew, M.W., Mallarino, A.P., Wortmann, C.S. 2017. Multisite evaluation of APEX for water quality: 1. Best professional judgement parameterization. Journal of Environmental Quality. doi: 10.2134/jeq2016.06.0226.
Bhandari, A.B., Nelson, N.O., Sweeney, D.W., Baffaut, C., Lory, J.A., Senaviratne, G., Pierzynski, G.M., Janssen, K.A., Barnes, P.L. 2016. Calibration of the APEX model to simulate management practice effects on runoff, sediment, and phosphorus loss. Journal of Environmental Quality. doi: 10.2134/jeq2016.07.0272.
Sadler, E.J., Sudduth, K.A., Drummond, S.T., Thompson, A.L., Chen, J., Nash, P.R. 2016. Inferring random component distributions from environmental measurements for quality assurance. Agricultural and Forest Meteorology. 237:362-370. doi: 10.1016/j.agrformet.2017.02.021.
Lerch, R.N., Lin, C.H., Goyne, K.W., Kremer, R.J., Anderson, S.H. 2017. Vegetative buffer strips for reducing herbicide transport in runoff: effects of buffer width, vegetation, and season. Journal of the American Water Resources Association. 53(3):667-683. doi: 10.1111/1752-1688.12526.
Nelson, N.O., Baffaut, C., Lory, J.A., Senaviratne, G., Bhandari, A.B., Udawatta, R.P., Sweeney, D.W., Helmers, M.J., Van Liew, M.W., Mallarino, A.P., Wortmann, C.S. 2017. Multisite evaluation of APEX for water quality: II. Regional parameterization. Journal of Environmental Quality. 56(5):2663-2674. doi: 10.2134/jeq2016.07.0254.
