Location: Coastal Plain Soil, Water and Plant Conservation Research
2023 Annual Report
Objectives
1. Develop effective irrigation and water management techniques to improve water and nutrient use efficiency and increase water reuse for conservation.
1a. Improve site-specific/variable-rate irrigation management using decision support systems to improve water and nutrient use efficiency.
1b. Enhance multiscale prediction of water pathways under climate variability using Machine Learning (ML) with hydrological models.
1c. Evaluate the impact of advanced treatment technologies for livestock wastewater reuse.
2. Develop innovative cropping systems and rotations to improve water and nutrient use efficiency, profitability, climatic resiliency, and reduce environmental impacts.
2a. Quantify the impact of tillage and crop rotation interactions on optimizing water availability and crop productivity in rainfed agriculture with or without cover crops.
2b. Identify and develop novel cover and row crop systems that provide double cropping benefits, while improving soil and water conservation in the Southeastern United States.
2c. Evaluate available novel row and cover crop genetic resources for productivity and water-use in drought-prone soils.
2d. Evaluate how water availability and microbial population dynamics are influenced by soil management practices.
Approach
Water availability is essential to maintain and increase agricultural production to meet the new century’s growing food and fiber demands. Increasing demand for water for recreational, industrial, and ecosystem services is competing with agriculture for available water resources. Therefore, agriculture must be more efficient with its available water resources. The overall goal of this project is to improve water and nutrient management in humid regions. The research focuses on two main objectives. The first objective is to develop effective irrigation and water management techniques to improve water and nutrient use efficiency and increase water reuse. In this objective, we will evaluate and refine a decision support system for variable-rate irrigation management to improve water and nutrient use efficiency. Using hydrologic models and machine learning, we will improve the prediction of multiscale water and nutrient pathways under climatic variability. We will investigate the feasibility of reusing livestock wastewater for supplemental irrigation from improved treatment technologies. The second objective is to develop innovative cropping systems and rotations to improve water and nutrient use efficiency, profitability, climatic resiliency, and reduce environmental impacts. Much of the Southeastern Coastal Plain’s agriculture is in rainfed production. To address this, we will investigate and quantify the impact of tillage and novel crop rotations to optimize water availability and crop productivity and improve overall soil and water conservation. We will also investigate novel cover crops and their genetic resources to provide potential double-cropping benefits and improve soil and water conservation in the region’s drought-prone soils. Overall, this research will identify water and nutrient management practices that conserve water, sustain production, and enhance environmental quality. Conservation and protection of the nation’s water resources will ensure food and fiber production for current and future populations in an economically viable and environmentally sustainable manner.
Progress Report
In Sub-objective 1a, we continued the second year of an experiment using the ARS Irrigation Scheduling Supervisory Control and Data Acquisition (ISSCADA) system to evaluate its ability to manage both corn and soybean production under one center pivot. The corn and soybean are rotated each year. Each crop will contain three irrigation treatments using: 1) the standard ISSCADA treatment using canopy temperatures, 2) the hybrid-ISSCADA treatment using both soil feedback with canopy temperatures, and 3) a uniform irrigation treatment.
In Subobjective 1.B, a collaborative effort is conducted with a scientist at Clemson University to evaluate the connection between drought and yield loss using a joint-probabilistic approach. Precisely, copula-based models were separately applied to time-series of Standard Precipitation and Evaporation Index (SPEI) and annual yield of corn, cotton, peanuts, and soybean at the county-level. Analyses were extended to all counties in North Carolina, South Carolina, and Georgia, then partial results were presented at two conferences including the 2023 World Environmental and Water Resources Congress, and the 2022 South Carolina Water Resources Conference.
In Subobjective 1.C, we are collaborating with scientists from the USDA-ARS Rangeland Resources and Systems Research Unit in Fort Collins, CO and the McGill University, Canada. The Root Zone Water Quality Model version 2 (RZWQM2) is being calibrated to simulate bermudagrass forage production, nitrogen, and water uptake under an irrigated condition. During the process, the RZWQM2 scripts were modified to integrate bermudagrass water-nutrients management specificities. High model uncertainties are noted, and the modeling effort is undergoing to address the uncertainties during the calibration. Ultimately, the calibrated model will be used to evaluate swine lagoon water reuse potential in the Coastal Plain region.
In Sub-objective 2a, the cotton and soybean from the 2022 season were harvested, with yield data compiled and analyzed during winter 2022-23. Soil moisture data was also compiled and organized during winter 2022-23. Carinata was initially planted in the plots in December 2022 as a double crop, but extreme cold (-9.4°C) 3-wks after planting resulted in 80% stand kill. Due to this and lack of time to replant carinata, we implemented the established contingency, where the 4-species cover crop mix was replanted in January 2023. Cover crop data was collected, along with soil fertility data in spring 2023. Cotton and soybean crops were rotated into respective plots in May 2023, alternating from their plots the prior field season. Lysimeters were also installed at two depths (30 and 90 cm) in each plot during the cover cropping season and following cotton and soybean emergence. Soil leachates were collected after major rain events during the cover crop season. All collected soil leachate were processed and stored in freezers and are currently awaiting analysis. Collection of soil leachate will continue throughout the cash crop season. Soil moisture will be monitored with Time Domain Reflectometers (TDR) probes that will be installed following cotton fertilization in June 2023.
In Subobjective 2b, the first year of the pilot-scale study involving perennial groundcover crops was completed and analyzed. The second year of the pilot-scale study was conducted, and all respective cover crop and cotton agronomic data was collected and analyzed. A peer-reviewed journal article relating to perennial groundcover weed suppression was submitted and published in Crop Science. Two more manuscripts are in process related to the perennial groundcover water-use and effects on cotton morphology and physiology. Data were presented at several stakeholder meetings.
In Subobjective 2c, the first year of the drought tolerant cotton and soybean germplasm trial was completed. Frequent hot temperatures (>30°C) and minimal rainfall created ideal drought stress conditions. Notable physiological and moisture stress differences were detected between drought tolerant cotton and soybean compared to unimproved commercial varieties. Data were compiled and analyzed and will be presented at stakeholder meetings in fiscal year 2024. The second year of the trial is awaiting establishment, with the corn intercrop being shifted to fallow to minimize incidence of volunteer corn emerging after harvest. Drought tolerant cover crops will be planted into plots in August 2023, followed by data collection, compiling and analyses in fall and winter 2023.
In Subobjective 2d, plots were re-established for a second year. Sensors to monitor moisture were calibrated and were inserted at 5 and 30 cm depths to monitor plant available water. Soil samples are pending collection to monitor early season microbial activity prior to start of the drought stress portion of the study.
Accomplishments
1. Using crop canopy feedback to manage variable rate cotton irrigation. Irrigation scheduling is crucial to providing high-yielding cotton grown on low water-holding capacity soils of the southeastern U.S. Coastal Plain. ARS researchers in Florence, South Carolina, used sensor technologies to reduce irrigation inputs, match the irrigation inputs with crop needs in real time, and aligned irrigation events with critical physiological stages in Coastal Plain cotton production. Variable rate irrigation prescriptions using the normalized difference vegetative indices (NDVI) were as effective as uniformly irrigating, resulting in less seasonal irrigation depths than a uniform method without reducing lint yields. These findings from this work validated the use of new technologies for the cotton industry to reduce crop production’s water use footprint. Variable rate irrigation technologies are critical to maximizing plant water use efficiency, and this research provides the industry with additional knowledge of the efficacy of NDVI prescription irrigation tools. This tool can be used to enhance further and develop efficient irrigation systems that maximize crop water use efficiency.
Review Publications
Stone, K.C., Billman, E.D., Bauer, P.J., Sigua, G.C. 2022. Using NDVI for variable rate cotton irrigation prescriptions. Applied Engineering in Agriculture. 38(5):787-795. https://doi.org/10.13031/aea.15071.
Billman, E.D., Campbell, B.T., Reay-Jones, F. 2023. Using perennial groundcover crops to suppress weeds and thrips in the Southeast Cotton Belt. Crop Science. 63(5):3037-3050. https://doi.org/10.1002/csc2.21048.
Sohoulande Djebou, D.C., Szogi, A.A., Novak, J.M., Stone, K.C., Martin, J.H., Watts, D.W. 2023. Instream constructed wetland capacity at controlling phosphorus outflow under a long-term nutrient loading scenario. Modeling Earth Systems and Environment. https://doi.org/10.1007/s40808-023-01763-w.
Sohoulande Djebou, D.C., Szogi, A.A., Stone, K.C., Sigua, G.C., Martin, J.H., Shumaker, P.D., Bauer, P.J. 2022. Evaluation of phosphorus runoff from sandy soils under conservation tillage with surface broadcasted recovered phosphates. Journal of Environmental Management. 328:117005. https://doi.org/10.1016/j.jenvman.2022.117005.
Epie, K., Bauer, P., Stone, K.C., Locke, A.M. 2023. Density, not tillage, increases soybean protein concentration in some southeastern US environments. Agronomy Journal. 115(4):1867–1876. https://doi.org/10.1002/agj2.21371.
