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 Cropping Systems and Water Quality Research: Columbia, MO
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ARS Home Midwest Area Columbia, Missouri Cropping Systems and Water Quality Research Research





- Baffaut, Claire
- Schreiner-Mcgraw, Adam
- Sudduth, Kenneth - Ken
- Veum, Kristen
- Ransom, Curtis
- Abendroth, Lori
- 2023
- 2022
- Publications
- Water Availability and Watershed Management (211)
- Soil and Air (212)
- Sustainable Agricultural Systems Research (216)

Research Project: Linkages Between Crop Production Management and Sustainability in the Central Mississippi River Basin **Location:
                            Cropping Systems and Water Quality Research** 2023 Annual Report **Objectives**
                                

Objective 1: Determine linkages between plant available water, evapotranspiration, and crop yields. 1a: Determine the relationship between crop yields and available soil water. 1b: Develop spatially explicit field-scale water budgets using remote sensing. 1c: Determine the ability of the APEX model to simulate the spatial variability of crop yields and soil moisture. 

Objective 2: Characterize and quantify the sub-daily variability in water quality and identify the drivers of that change. 2a: Identify and quantify stream sub-daily water quality variability. 2b: Identify the drivers for phosphorus sub-daily variability. 

Objective 3: Determine and characterize the effects of management on water use efficiency, nutrient use efficiency, GHG emissions, productivity, and ecology. 3a: Compare WUE and water budget components of different crops and cropping systems. 3b: Integrate corn incremental N use efficiency (NUE) into fertilizer recommendations. 3c: Determine the effects of conservation practices and crop rotations on greenhouse gas and productivity, and the potential trade-offs. 3d: Determine how conservation practices and crop rotations affect above ground biomass and ecology. 

Objective 4: Evaluate ASP (aspirational) and BAU (business-as-usual) production systems for water quantity, water quality, soil, biological, production and profitability outcomes. 4a: Investigate trade-offs between productivity and environmental metrics for more diverse cropping systems. 4b: Create publicly accessible data holdings for publishing CMRB production and environmental data. 4c: Extrapolate the BAU and ASP water budgets developed at field scale to larger scales. **Approach**
                                

The overall purpose of the project is to identify how conservation practices affect outcomes, what cropping systems improve short- and long-term sustainability, and the trade-offs between environmental and production outcomes; and provide that information to producers to help them move toward more sustainable agricultural systems. Objective 1 focuses on the relationship between crop yields, soil moisture content, and evapotranspiration within the context of these soils. Objective 3 compares multiple outcomes of different agricultural systems. The conclusions of these two objectives will help identify important processes that improve agricultural sustainability, provide the information necessary to develop metrics that describe this sustainability, and evaluate trade-offs between environmental and production outcomes of agricultural systems. Objective 4 connects to these two objectives by bringing the information to stakeholders. It will also scale results related to water availability and movement to a larger scale. The research in Objective 2 is needed to incorporate issues of phosphorus transport when scaling phosphorus losses from the edge-of-field to the watershed scale and evaluate environmental impacts. The project will conduct experiments at multiple scales ranging from small plots to watersheds, adding measurements and continuing those already underway. The project builds upon the research infrastructure developed in collaboration with the University of Missouri at our research farm in Centralia and elsewhere, which was enhanced for the Central Mississippi River Basin (CMRB) site of the Long-Term Agroecosystem Research Network (LTAR) starting in 2015. This infrastructure includes small plots, large plots, and fields on which the Common Experiment—a coordinated experiment across LTAR—has been implemented, and the observatory, which provides long-term data of weather and stream flow quantity and quality in multiple nested watersheds. The proposed research focuses on surface and soil water in row crop production systems in the CMRB, with simultaneous consideration of productivity, nitrogen use, greenhouse gas emissions, soil health, and biodiversity. Specifically, research will address the immediate and long-term relationships between row-crop production practices and water budgets, surface water quality, hazardous algae blooms, GHG emissions, ecology, and aboveground and soil biodiversity. The project will result in information that producers and policy makers can use to incite changes in cropping systems. **Progress Report**
                                

Progress was made on all four objectives, all of which fall under the four components of National Program 211. 
In support of Sub-objective 1A, which falls under Component 1 (Effective water management in agriculture) we have used historical crop yields in one experimental field to identify 12 sites to install soil moisture sensors and defined how to install them in a manner that allows disturbance from field operations. We installed soil moisture sensors at four depths at each of these sites. Three depths are below the depth at which field operations could damage the sensor. The top sensor is installed in a manner that we can easily remove and reinstall it before and after field operations. These installations were successful and soil moisture data are coming in through dataloggers and telemetry.

In support of Sub-objective 1B, the collaboration with ARS scientists in Beltsville, Maryland, has resulted in remote sensed evapotranspiration (ET) images validated with water budget numbers at watershed scale. We have processed and completed the analysis of 2016-2020 eddy flux data in two fields to produce estimates of daily ET along with their uncertainty. A paper was developed and published, which details the uncertainty calculation method. Analysis of field 2016-2020 daily ET estimated from remote sensed images and eddy-flux data for these two fields showed a good match in one field, which gives confidence that the two sets of data are correct. However, the match between remote sensed and eddy flux data was poor for the second field and we need to understand the cause. We have also validated water budgets for these two fields based on the 2016-2020 data. 

In support of Sub-objective 1C, which addresses Problem 1E (Develop and Improve Simulation Modeling, Data, and Decision Support Tools for Water Management), we have used the Agricultural Policy Environmental Extender (APEX) to simulate spatial and temporal variations of soil water content in two plots and compared them with discrete measurements of soil water content. We were encouraged by the facts that the ranges of measured and simulated soil water contents were similar, and the simulated water contents for different management systems made sense given what we know about how these systems behave. Results were presented in a poster presentation at the 2022 fall meeting of the American Geophysical Union. We have also validated the parameterization of the model for all the cropping systems based on 2017-2021 flow and production data. At field-scale, we developed 2016-2020 monthly water budgets for the two fields that use prevailing and alternative practices. We used the soil water contents that were measured at the eddy flux tower, the ET data from the eddy flux measurements, and the discharge data. The water budget uncertainty was large, which indicates greater interaction with groundwater than represented.

In support of Objective 2 (Erosion, Sedimentation, and Water Quality Protection), we have installed the equipment necessary to collect high-frequency water quality data at one of our stream gage stations. This supports Problem Statement 2B, which aims to Determine In-Stream Processes Affecting Contaminant Fate, Transport, and Biological Elements. We have tested and calibrated a dissolved phosphorus sonde and a water quality probe that measures pH, dissolved oxygen, electrical conductivity, and turbidity. Once testing results were satisfactory, we installed these two sondes at the stream gage station, along with data communication equipment to send the data. We also started to collect monthly water samples at that location and send them to our Oxford, Mississippi, collaborators for algal content determination.   

Progress was made in all sub-objectives of Objective 3, which evaluates Conservation Practices in Agricultural Watersheds (Component 3).  The four sub-objectives all aim to improve our Understanding of Chemical, Physical, and Biological Processes That Affect Implementation of Conservation Practices (Problem Statement 3A) and Assess and Implement Conservation Practices in Agricultural Landscapes (Problem Statement 3B). In support of Sub-objective 3A, we collaborated on a review and trade-off analysis of different water use efficiency (WUE) indicators at different scales and for different agricultural systems. This resulted in a manuscript, which was published. We developed the relationship between annual precipitation and production, which was crop yield for cropping systems or above-ground net primary production (ANPP) for range land and grazing systems. This relationship is one of the possible definitions of water use efficiency. In addition, we are collaborating on the determination of these relationships for all the sites in the Long-Term Agroecosystem Research (LTAR) Network. In support of Sub-objective 3A2, all the code necessary to process eddy flux data was written and is working. In addition, we have continued to collect eddy flux data, which are now going to the Ameriflux site. The soil moisture sensors installed in the field also support this objective so we can relate soil water content and ET under different crop covers. 

In support of Sub-objective 3B, we continued to present the results of the analysis published in FY22 to colleagues (professional society meetings) and to producers (e.g., a group of Canadian Farmers) explaining the need to expand nitrogen management decision making to include the Nitrogen use Efficiency. Data collection in support of Sub-objective 3C continued in FY23. The FY22 plot crop yields and records of farm operations were certified. In support of Sub-objective 3D1, data collection continued in the plots that have prevailing and alternative management practices with the FY22 crop for the late crop stages and with the FY23 crop. In support of Sub-objective 3D2, we started measuring biodiversity in the native prairie and in the cropping systems that use prevailing and alternative practices. A graduate student was hired and is collecting data every other week for eight weeks over the summer. Many samples are collected so that we can determine the spatial and temporal frequency of the measurements for a meaningful comparison of the systems. 

Objective 4 is directly related to Long-Term Agroecosystem Research Network (LTAR) objectives of evaluating the cropping systems with prevailing and alternative practices for a suite of indicators. In support of Sub-objective 4A, we have established regular meetings with our stakeholders to develop the relationship needed to ask for input on the metrics and indicators that matter to them to evaluate the cropping systems. Meanwhile, we have contributed to the development of the LTAR indicator framework. In collaboration with several LTAR working groups, we have developed guidelines for the measurement, quality assurance, and quality control procedures for the metrics needed to evaluate these agricultural systems. These guidelines are summarized in documents that are currently under LTAR internal review, and available to all LTAR scientists. In support of Sub-objectives 4A and 4B, data collection is continuing, and scientists have certified the 2020 and 2021 data on production, all water quantity variables, and all water quality variables. The backlog of water quality samples is going down thanks to the purchase of new ion chromatography equipment. Total nutrients (nitrogen and phosphorus) from FY19 and later are now processed. Eddy flux data were uploaded to the Ameriflux website up to December 2022 and we have planned a virtual visit of our site by the Ameriflux scientists to review and audit our data collection and processing. The data citation, which refers to the Ameriflux site, and the procedures to calculate eddy flux data uncertainties are included in a paper that was published in FY23.  

We have summarized our quality assurance procedures for water quantity and water quality monitoring, which gives a list of tasks to do during field visits and allows the technicians to indicate which ones were performed. Quality control procedures include setting minimum and maximum values, comparisons with a secondary sensor, and for the plots, comparison with replicate plots and with rainfall depth. The rules give an objective, quantifiable, and repeatable mechanism to reject the data, or to assign a quality grade. A carbon budget was developed, which uses eddy flux data from the prevailing and alternative practices fields, crop removal based on yields, and soil samples. **Accomplishments**
                                

1. The sites of the Long-Term Agroecosystem Research Network (LTAR) describe well the variability of U.S. agricultural environments. The USDA LTAR network coordinates agricultural research in the United States across multiple research sites. It is important to understand how well these sites represent the varied environmental characteristics of agricultural working land in the continental United States. ARS 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 of the current network based on 15 soil and climate variables. Representativeness is a 0 to 1 number that quantifies the combined differences in these 15 variables between a U.S. location and an LTAR site; it shows how well environmental conditions at any U.S. location are represented by the closest LTAR site in terms of the 15 variables. LTAR representativeness was good across most of the country, but there were regions not as well represented. For those, borrowing an existing site from the Long-Term Ecological Research (LTER) Network and the National Ecological Observatory Network (NEON) would be beneficial. The results of this study are useful to identify future site locations so that LTAR findings are more broadly applicable to U.S. agriculture. 2. Alternative cropping systems are more resilient to extreme weather. Climate change is resulting in an increase in extreme heat events and changing rainfall patterns so that rain is generally less frequent, but more intense. This makes agricultural production challenging. ARS scientists in Columbia, Missouri, in collaboration with researchers from the University of Missouri, compared measurements of carbon fluxes to quantify plant growth under a variety of weather and soil moisture conditions within prevailing and alternative cropping systems and a native prairie. The native prairie, with over 100 different plant species, maintained carbon uptake and evapotranspiration during sub-optimal weather conditions. The alternative system, which has a four-year crop rotation was able to mimic some of the resilience seen in the prairie while the prevailing system was the least resilient to sub-optimal weather. This approach will be used to examine the resilience of alternative cropping systems across the Long-Term Agroecosystem Research network. These results are critical for informing climate smart agricultural practices for producers to maintain resilient crop yields during weather extremes. 3. Complex groundwater recharge routes challenge the effectiveness of nitrogen reduction strategies. The transport of nitrogen to streams is a concern in the U.S. Midwest, including for soils with layers that restrict infiltration, such as claypan soils. Claypan cracks and soil profile heterogeneities provide conduits for the transport of nutrients and herbicides from the surface to shallow and deep groundwater, especially during dry periods. Determining how contaminants reach deep groundwater is important to develop strategies to mitigate water contamination. ARS scientists at Columbia, Missouri, in collaboration with Lincoln University of Missouri and Michigan Technological University, determined that only 13-41% of deep groundwater came from above the claypan, and that amount varied in space and time due to variable hydraulic characteristics of the claypan. There was no evidence of transformation of nitrate-nitrogen into nitrogen gas (denitrification) in deep groundwater, and the concentrations were controlled by only the mixing of different water sources. Because little deep groundwater originated from shallower depths, nitrates accumulate in deep groundwater, which then provides a major source of nitrates to streams. These results imply that 1) groundwater nitrate concentrations are not likely to change rapidly in response to crop nitrogen management strategies, and 2) the effectiveness of claypan-soil nutrient management strategies would vary spatially and temporally. Nevertheless, it is important to improve crop nitrogen management strategies to reduce additional accumulation of nitrates in deep groundwater. This information can help water managers and water resource agencies evaluate the effectiveness of nutrient management and mitigation practices and develop new practices that account for this type of soils. 4. Developed a water use efficiency framework for network level science. Agriculture has the highest demand for water globally and understanding the relationship between water use and production is essential because water resources are limited. Water use efficiency (WUE), or drop-per-crop, can be applied across spatial scales from the leaf to the farm to the dinner table, and temporal scales from seconds to months to years. However, the measurement and interpretation of WUE vary across these scales and among disciplines, making cross-regional or cross-crop comparisons difficult. ARS researchers at Columbia, Missouri, collaborated with researchers across the Long-Term Agroecosystem Research (LTAR) network to review common WUE indicators, establish a common language, and link WUE across scales and agricultural systems. Awareness of the points of inconsistency between scales of WUE measurement is critical for avoiding misunderstandings and extrapolating experimental results to larger regions. For example, the specificity of leaf- or plant-specific measurements is a strength but the assessment of a community of plants captured through remote-sensing is critical. WUE is a simplistic idea but gets complicated when used for networks such as LTAR; this research has advanced the science of WUE in relation to highly variable farming practices across the United States. 5. Uncertainty in cropland phosphorus inputs and outputs impairs phosphorus management. Phosphorus (P) is a critical nutrient for crop growth and optimal productivity, but when lost from agricultural fields it can result in eutrophication and harmful algal blooms in downstream water bodies. Measuring P inputs and outputs is necessary to determine if P management is appropriate. ARS scientists in Columbia, Missouri, collaborated on research to analyze the P inputs and outputs across 56 cropping systems in 22 U.S. states and two Canadian provinces. In 39% of cases, the uncertainties in the phosphorus contained in applied manure and fertilizers and in crops removed were too large to determine whether P lost to the environment was changing. Thus, better measures of the application rate, the P concentration of manures and fertilizers, and crop yield and the P content of harvested material are needed to improve the assessment of P management. Measuring other P fluxes, such as the change of soil P, may also be important to assess the full impacts of management practices. These recommendations will provide the data needed to improve phosphorus use efficiency and develop conservation practices that mitigate environmental impacts of agricultural systems. **Review Publications**
                            *Schreiner-McGraw, A.P., Wood, J.D., Metz, M.E., Sadler, E.J., Sudduth, K.A. 2023. Agriculture accentuates interannual variability in water fluxes but not carbon fluxes, relative to native prairie, in the U.S. Corn Belt. Agricultural and Forest Meteorology. 333. Article 109420. https://doi.org/10.1016/j.agrformet.2023.109420.*
                                *Moody, A.H., Lerch, R.N., Goyne, K.W., Anderson, S.H., Mendoza-Cozatl, D.G., Alvarez, D.A. 2022. Vegetative buffer strips show limited effectiveness for reducing antibiotic transport in surface runoff. Journal of Environmental Quality. 52(1):137-148. https://doi.org/10.1002/jeq2.20441.*
                                *Youssef, M., Strock, J., Bagheri, E., Reinhart, B.D., Abendroth, L.J., Chighladze, G., Ghane, E., Shedekar, V., Fausey, N., Frankenberger, J., Helmers, M.J., Jaynes, D.B., Kladivko, E., Negm, L., Nelson, K., Pease, L. 2022. Impact of controlled drainage on corn yield under varying precipitation patterns: A synthesis of studies across the U.S. Midwest and Southeast. Agricultural Water Management. 275. Article 107993. https://doi.org/10.1016/j.agwat.2022.107993*
                                *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.*
                                *Hofmeister, K., Lerch, R., Baffaut, C., Yang, J., Liu, F. 2022. Characterizing groundwater chemistry and recharge in the critical zone of an agricultural claypan watershed. Water Resources Research. 58(10). Article e2021WR031797. https://doi.org/10.1029/2021WR031797.*
                                *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.*
                                *Mire, M., Kim, C., Baffaut, C., Liu, F., Wuliji, T., Zheng, G. 2022. Escherichia cryptic clade II through clade VIII: Rapid detection and prevalence in feces and surface water. Science of the Total Environment. 848. Article 157741. https://doi.org/10.1016/j.scitotenv.2022.157741.*
                                *Baffaut, C., Costello, C., Gautam, S., Phung, Q., Thompson, A. 2022. Soil water management and climate fluctuations: modelling approach. In: Blanco, H., Kumar, S., and Anderson, S.H., editors. Soil Hydrology in a Changing Climate. Clayton South, Australia: CSIRO Publishing. p. 233-250.*
                                *Johnson, F.E., Lerch, R.N., Motavalli, P.P., Veum, K.S., Scharf, P.C. 2022. Spatial variability of denitrification enzyme activity and actual denitrification emissions on Missouri claypan soils. Soil Science Society of America Journal. 86(6):1582-1596. https://doi.org/10.1002/saj2.20457.*
                                *Hatch, K.M., Lerch, R.N., Kremer, R.J., Willett, C.D., Roberts, C.A., Goyne, K.W. 2022. Evaluating phytochemical and microbial contributions to atrazine degradation. Journal of Environmental Management. 321. Article 115840. https://doi.org/10.1016/j.jenvman.2022.115840.*
                                *Conway, L.S., Sudduth, K.A., Kitchen, N.R., Anderson, S.H., Veum, K.S., Myers, B.D. 2022. Soil organic matter prediction with benchtop and implement-mounted optical reflectance sensing approaches. Soil Science Society of America Journal. 86(6):1652-1664. https://doi.org/10.1002/saj2.20475.*
                                *Feng, A., Vong, C., Zhou, J., Conway, L., Zhou, J., Vories, E.D., Sudduth, K.A., Kitchen, N.R. 2023. Developing an image processing pipeline to improve the position accuracy of single UAV images. Computers and Electronics in Agriculture. 206. Article 107650. https://doi.org/10.1016/j.compag.2023.107650*
                                *Rieke, E.L., Bagnall, D.K., Morgan, C., Greub, K., Bean, G.M., Cappellazzi, S.B., Cope, M., Liptzin, D., Norris, C.E., Tracy, P.W., Ashworth, A.J., Baumhardt, R.L., Dell, C.J., Derner, J.D., Ducey, T.F., Fortuna, A., Kautz, M.A., Kitchen, N.R., Leytem, A.B., Liebig, M.A., Moore Jr., P.A., Osborne, S.L., Owens, P.R., Sainju, U.M., Sherrod, L.A., Watts, D.B., et al. 2022. Evaluation of aggregate stability methods for soil health. Geoderma. 428. Article 116156. https://doi.org/10.1016/j.geoderma.2022.116156.*
                                *Liptzin, D., Norris, C.E., Cappellazzi, S.B., Bean, G.M., Cope, M., Greub, K.L., Rieke, E.L., Tracy, P.W., Aberle, E., Ashworth, A.J., Baumhardt, R.L., Dell, C.J., Derner, J.D., Ducey, T.F., Novak, J.M., Dungan, R.S., Fortuna, A., Kautz, M.A., Kitchen, N.R., Leytem, A.B., Liebig, M.A., Moore Jr., P.A., Osborne, S.L., Owens, P.R., Sainju, U.M., Sherrod, L.A., Watts, D.B. 2022. An evaluation of carbon indicators of soil health in long-term agricultural experiments. Soil Biology and Biochemistry. 172. Article 108708. https://doi.org/10.1016/j.soilbio.2022.108708.*
                                *Svedin, J., Kitchen, N.R., Ransom, C.J., Veum, K.S., Myers, R. 2022. A tale of two fields: Management legacy, soil health, and productivity. Agricultural and Environmental Letters. 7(2). Article e20090. https://doi.org/10.1002/ael2.20090.*
                                *Svedin, J., Kitchen, N.R., Ransom, C.J., Veum, K.S., Anderson, S. 2022. Can soil biology tests improve phosphorus and potassium corn fertilizer recommendations? Agronomy Journal. 114(6):3457-3472. https://doi.org/10.1002/agj2.21180.*
                                *Veum, K.S., Zuber, S.M., Ransom, C.J., Myers, R.L., Kitchen, N.R., Anderson, S.H. 2022. Reduced tillage and rotational diversity improve soil health in Missouri. Agronomy Journal. 114(5):3027-3029. https://doi.org/10.1002/agj2.21156.*
                                *Crookston, B.S., Yost, M.A., Bowman, M.S., Veum, K.S. 2022. Relationships of on-farm soil health scores with corn and soybean yield in the midwestern United States. Soil Science Society of America Journal. 86(1):91-105. https://doi.org/10.1002/saj2.20355.*
                                *Kaur, H., Nelson, K.A., Singh, G., Veum, K.S., Davis, M.P., Udawatta, R.P., Kaur, G. 2023. Drainage water management impacts soil properties in floodplain soils in the midwestern, USA. Agricultural Water Management. 279. Article 108193. https://doi.org/10.1016/j.agwat.2023.108193.*
                                *Svedin, J., Veum, K.S., Ransom, C.J., Kitchen, N.R., Anderson, S.H. 2022. An identified agronomic interpretation for potassium permanganate oxidizable carbon. Soil Science Society of America Journal. 87(2):291-308. https://doi.org/10.1002/saj2.20499.*


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