Research Project: Development of Best Management Practices, Tools, and Technologies to Optimize Water Use Efficiency and Improve Water Distribution in the Lower Mississippi River Basin

Location: Sustainable Water Management Research

2023 Annual Report

Objectives
1. Develop robust datasets, models, and data visualization tools to determine the impact of alternate water supplies on aquifer recharge and groundwater levels in the LMRB. 1.A. Implement sensing device to monitor ground water and surface water level in the Mississippi Delta. 1.B. Monitor status of surface water storage using remote sensing technology. 1.C. Quantify and characterize demand for irrigation water and identify the value of water in competing and complementary agricultural water uses. 1.D. Modeling the impact of alternate water supplies on aquifer dynamics. 2. Develop optimized irrigation scheduling tools for cropping systems in the LMRB that account for crop water requirements, impacts of water stress, and economic and environmental sustainability while minimizing water usage. 2.A. Develop and evaluate improved sensor-based irrigation scheduling methods. 2.B. Implement and evaluate, automation and other advanced technologies and methods for optimal irrigation management. 3. Develop new and novel sensor systems and that include optimized telemetry and efficiently integrate with decision support models and tools for prescription irrigation and water resource management. 3.A. Integrating ground-based sensor and remote sensing systems and cloud-based data acquisition, develop and evaluate decision support systems for site-specific irrigation and nutrient management. 3.B. Develop new sensing and monitoring systems to provide measurements of soil- and surface-water status and plant response and stress for continuous, site-specific water and crop management. 4. Evaluate and improve current best management practices or develop new practices based on new and novel approaches that stochastically account for interaction effects of irrigation, planting, fertility and pest management, and implementation of conservation practices including cover crops, tillage methods, edge-of-field buffers, surface water storage/use, and soil health. 4.A. Evaluate the effects of irrigation water sources, application techniques, and scheduling methods on crop production, environmental outcomes, and farm profitability. 4.B. Determine the water-related effects of crop management strategies such as crop/variety selection, and cover crops on crop production, environmental outcomes, and farm profitability. (See postplan for subobjective 4.C.) 5. Engage LMRB stakeholders through our MSU research and Extension partners to characterize producer behavior and attitudes with respect to irrigation and water conservation management and introducing them to cutting edge digital tools, technologies, and best management practices. (See postplan for subobjectives 5.A and 5.B.) 6. Develop and validate algorithms/models using remote sensing and eddy covariance methods to improve evapotranspiration (ET) estimates and water productivity at field and regional scales to improve the predictability and forecasting capabilities of the LMRB cropping systems models to more robustly address the impacts of climate change. (See postplan for subobjectives 6.A. and 6.B.)

Approach
New sensing systems for the automated monitoring of surface water using ultrasonic and LiDAR distance sensors will be developed. Field experiments will be conducted to monitor surface water storage bodies across the Mississippi Delta region using novel sensors as well as UAV and/or satellite imagery. Economic studies will be carried out to identify the factors which influence groundwater pumping decisions in addition to the cost of pumping water. Groundwater and economic studies will combine to examine the impact of alternate water supplies, such as tailwater recovery systems, on aquifer dynamics and agricultural productivity. Variable rate irrigation (VRI) experiments will be conducted to examine options for reducing withdrawals from the aquifer without negatively impacting agricultural productivity. VRI management will be conducted by integrating sensor data with crop yield and water efficiency data. Crops will be grown in fields equipped with eddy covariance (EC) system for measuring water vapor and CO2 fluxes, and instrumentation for monitoring ET using a residual energy balance (REB) approach. Relevant data will be collected and analyzed to predict impacts of climate change and variability on production and water requirements in cropping systems. Sensors to monitor canopy temperature and reflectance will be deployed and used to develop vegetation indices. Plant physiological and morphological responses will be monitored. Water stress indices based on canopy temperature, NDVI, PRI, ET, and soil water will be developed and related to the crop physiological responses. Sensor development will be integrated into the agricultural production trials to develop improve irrigation prescriptions and decision support models. Additional field exeperiments will be conducted to examine the impact of irrigation application technique, row spacing and production techniques and methods. Additional studies will quantify changes in water use and water quality based on cover crops and fertilizer management practices. Site-specific and one-on-one learning opportunities will be employed to familiarize producers who are interested in adopting the newly developed techniques. Diverse technology transfer materials and extension programming materials will be developed and delivered to target audiences through a wide array of outlets to maxmizie technology awareness and adoption. A combination of interviews, focus groups, and survey instruments will be developed to understand current attitudes towards conservation and best management practices. The target population for this study is all permit holders, landowners, and operators who withdraw water for agricultural irrigation in the Bootheel of Missouri and the Delta regions of Arkansas, Mississippi, and Louisiana. This approach allows for intuitive and explicit modeling of non-economic factors that influence economic decisions and behaviors. The findings will inform and guide our research and promotions efforts in relation to developing best management practices for the region.

Progress Report
Significant progress was made in this project. A cost-effective sensing system was designed for water level monitoring using open-source hardware and software for Subobjective 1.A. Ultrasonic sensors and liquid level transmitters were integrated into Arduino and evaluated for water level monitoring in the lab. A stand-alone system with Raspberry Pi for field testing is in progress in preparation for sensor deployment. Geospatial technologies such as ERDAS IMAGINE image analysis software and high-resolution imagery were used to create an inventory and analysis of on-farm water storage systems for multiple years to evaluate their rate of construction in the Big Sunflower River Watershed for Subobjective 1.B. Sensor integration on a stationary sensor platform is in progress and UAV images were collected weekly at West Farm experimental fields for validation and optimization for flight pattern and image quality. The geo-referenced dataset with soils, crops, hydrologic, and climate data up to 2017 has been acquired from the Mississippi Department of Environmental Quality, CropScape, and USGS for Subobjective 1.C. The GIS data has been processed for uniformity and completeness. For Subobjective 1.D., flow meters, rain gauges, runoff auto-samplers, and level loggers have been collecting data from a tailwater recovery system in Sunflower County, near Inverness, MS. Flow, rain, and levels are being recorded and sample collection has begun. The hydrologic model for the tailwater system is being built. For Subobjective 2.A, a weather-based calibration approach was developed and implemented for the Sentek Drill & Drop soil water sensor. Year-2 data were processed, and year-3 data were collected. Soil water sensors have been tested and installed. The algorithms for irrigation scheduling have been initialized and tests are being conducted to complete the second year of data collection. Ten on-farm automation sites were evaluated this past year for Subobjective 2.B. On-farm sites consist of a farmer control well where they irrigated their fields as they normally would. Another well was equipped with pump controls and automated valves where researchers controlled the irrigation. Automation will continue to be compared to non-automated on-farm sites. For Subobjective 3.A., factorial combinations of tension-based irrigation triggers and nitrogen fertilizer rates are being evaluated in sprinkler-irrigated corn on two soil types. Data relevant to site-specific irrigation and nutrient management are being collected and analyzed for year 2. Two types of soil water sensors are being evaluated in two regions of Mississippi for Subobjective 3.B. Open-source software was developed and tested for UAV\satellite images with algorithm development of geo-referenced image transformation, clipping, and target delineation and successfully delivered grid-based metrics. Airborne imagery was collected weekly on corn, soy, and cotton fields for seasonal profile of plant responses to stress and agronomic variations for year 2. For Subobjective 4.A., three sprinkler irrigation systems and a tile drainage system were operating for year 2. Cover crop studies have had two full winters of cover crops planted and two cash crop seasons for Subobjective 4.B. Data has been collected and future yield data will be combined with current data. For Subobjective 4.C., tillage and fertilizer placement treatments were conducted for year 2, and yield data will be collected and analyzed. Ten on-farm automation sites established plus an additional 30 soil moisture sensors demonstrations were conducted for Subobjective 5.A. Meetings with and presentations to stakeholders were conducted. Technical assistance on irrigation management was provided to LMRB farmers and Extension agents. A stakeholder-oriented annual report was compiled. For Subobjective 5.B., A survey questionnaire has been deployed to producers suggested by Delta FARM and producer groups. Additional stakeholder organizations have been consulted to develop approaches to ensure the survey is delivered to a broad sampling of producers across the Mississippi Delta. Data has been tabulated and analysis is ongoing. Corn experiments were established in two large farm-scale plots (about 23 acres each) for Subobjective 6.A. One plot was maintained under rainfed and the other irrigated. After harvesting the crop this season, one of the plots will be continued under reduced tillage (RT) and the other as conventional tillage (CT). Eddy covariance stations for monitoring water (crop water use, ET) and CO2 were established, and second-year data was collected. Concurrently, in another parallel study, the whole experiment was repeated with soybean as the main crop planted in place of corn, and similar data were collected. For Subobjective 6.B, the effect of nighttime temperature on cotton growth and physiology at 400 ppm carbon dioxide was investigated.

Accomplishments
1. Irrigation, row pattern and nitrogen placement effects on corn grain yield in the Mississippi Delta. Early nitrogen applications in the spring are prone to nitrogen losses due to extended periods of rainfall events. Nitrogen losses such as runoff, volatilization, denitrification, and leaching can be mitigated by following the 4R nutrient stewardship system (right source, right rate, right timing, and right place). Different nitrogen placement methods and row patterns (single and double) in irrigated and rainfed corn systems were evaluated by ARS researchers in Stoneville, Mississippi. Corn grain yield was higher in all nitrogen placement methods compared to the control. Row pattern had no effect in corn grain yield. However, results indicate that one knife-coulter applicator is more efficient than surface dribble and two knives methods in either single or twin row pattern corn.

2. On-farm training and demonstration farms to improve extension. To empower producers to integrate soil moisture sensors and irrigation automation fully into their farming operations, ARS researchers in Stoneville, Mississippi, launched a multi-year on-farm education program. Ten automation sites were established in 2022, along with 30 soil moisture demonstrations. With support from commodity promotion boards, researchers provided telemetry-enabled soil moisture monitoring systems and technical support to interested Mississippi State University Extension county agents. From this research, three extension publications have been produced. The first explained how to calculate irrigation pumping cost using NCAAR’s MITOOL web app. The second explained how to interpret data from the Sentek Drill & Drop soil water sensor. The third explained how to compute irrigation water volume and depth based on flow meter totalizer readings using NCAAR’s Flow Meter Calculator web app. This program is helping Mississippi producers gain the skills and confidence necessary to adopt soil moisture sensors and automation on their own, allowing them to optimize their irrigation practices.

3. Characterizing surface water use for irrigation in the Mississippi Delta. A conservation practice known as on-farm water storage (OFWS) systems, captures irrigation and rainfall runoff in tailwater recovery ditches that then convey water to a pond for storage and reuse. OFWS systems are one of the many practices being used to prevent the increased depletion of the Mississippi River Valley alluvial aquifer due to excess pumping for irrigation. By employing geospatial technologies such as ERDAS IMAGINE image analysis software and high-resolution imagery, ARS researchers in Stoneville, Mississippi, conducted an inventory and analysis of on-farm water storage systems for multiple years to evaluate their rate of construction in the Big Sunflower River Watershed (HUC 08030207). An interpolated map of groundwater levels for the same years was being created, using groundwater level data from USGS gauge stations. The groundwater data was used in conjunction with the OFWS system analysis to assess trends in construction and the impacts on groundwater levels. The results of this study provides a functional inventory of OFWS systems and quantifies the effects of these systems on water resources in the Mississippi Delta.

Review Publications
Sehgal, A., Reddy, R., Walne, C.H., Barickman, C., Brazel, S., Chastain, D.R., Gao, W. 2022. Effects of UV-B, elevated CO2 and high temperature on morphological and biochemical aspects of two brassica species. Life. 12(10):1546. https://doi.org/10.3390/life12101546.
Nelson, A.M., Moore, M.T., Witthaus, L.M. 2022. Pesticide trends in a tailwater recovery system in the Mississippi Delta. Agrosystems, Geosciences & Environment. 2(4):e20325. https://doi.org/10.1002/agg2.20325.
Singh, B., Chastain, D.R., Stetina, S.R., Gardiner, E.S., Snider, J.L. 2022. Early-season growth responses of resistant and susceptible cotton genotypes to reniform nematode and soil potassium application. Agronomy. 12(11):2895. https://doi.org/10.3390/agronomy12112895.
Nelson, A.M., Quintana Ashwell, N.E., Delhom, C.D., Gholson, D.M. 2022. Leveraging big data to preserve the Mississippi River Valley Alluvial Aquifer: A blueprint for the National Center for Alluvial Aquifer Research. Land. 11(11):1925. https://doi.org/10.3390/land11111925.
Anapalli, S.S., Pinnamaneni, S.R., Reddy, K.N., Wagle, P., Ashworth, A.J. 2023. Eddy covariance assessment of alternate wetting and drying floodwater management on rice methane emissions. Heliyon. 9(4):e14696. https://doi.org/10.1016/j.heliyon.2023.e14696.
Anapalli, S.S., Pinnamaneni, S.R., Chastain, D.R., Reddy, K.N., Simmons, C.D. 2023. Eddy covariance quantification of carbon and water dynamics in twin-row vs. single-row planted corn. Agricultural Water Management. 281:108235. https://doi.org/10.1016/j.agwat.2023.108235.
Chatterjee, A., Anapalli, S.S. 2022. Comparing eddy covariance-based cotton evapotranspiration with CSM-CROPGRO and APSIM-OzCot simulations in Mississippi. Water. 14(24):4022. https://doi.org/10.3390/w14244022.
Pinnamaneni, S.R., Saseendran, A., Molin, W.T., Reddy, K.N. 2022. Effect of cereal rye cover crop on weed control, soybean yield and profitability. Frontiers in Agronomy. https://doi.org/10.3389/fagro.2022.907507.
Pinnamaneni, S.R., Anapalli, S.S., Reddy, K.N. 2023. Effect of irrigation regimes and planting patterns on corn (Zea mays L.,) water use efficiency and on-farm profitability in humid climates. Agronomy Journal. https://doi.org/10.1002/agj2.21221.
Srinivasa, P.R., Anapalli, S., Reddy, K.N. 2022. Photosynthetic response of soybean and cotton to different irrigation regimes and planting geometries. Frontiers in Plant Science. https://doi.org/10.3389/fpls.2022.894706.
Pinnamaneni, S.R., Mubvumba, P., Anapalli, S., Reddy, K.N. 2022. Cereal rye cover crop impacts on soybean (Glycine max L.) root growth and soil properties. Frontiers in Soil Science. https://doi.org/10.3389/fsoil.2022.970380.
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.
Quintana-Ashwell, N., Gholson, D., Kaur, G., Krutz, L., Henry, C.G., Cooke, III, T., Massey, J., Reba, M.L., Locke, M.A. 2022. Irrigation water management tools and alternative irrigation sources trends and perceptions by farmers from the Delta regions of the Lower Mississippi River Basin in South Central USA. Agronomy. 12(4):894. https://doi.org/10.3390/agronomy12040894.
Volk, J.M., Huntington, J.L., Melton, F., Minor, B., Wang, T., Anapalli, S.S., Anderson, R.G., Evett, S.R., French, A.N., Jasoni, R., Bambach, N., Kustas, W.P., Alfieri, J.G., Prueger, J.H., Hipps, L., McKee, L.G., Castro, S.J., Alsina, M.M., McElrone, A.J., Reba, M.L., Runkle, B., Saber, M., Sanchez, C., Tajfar, E., Allen, R., Anderson, M.C. 2023. Post-processed data and graphical tools for a CONUS-wide eddy flux evapotranspiration dataset. Data in Brief. 48. Article 109274. https://doi.org/10.1016/j.dib.2023.109274.
Nakabuye, H.N., Rudnick, D., DeJonge, K.C., Lo, T.H., Heeren, D., Qiao, X., Franz, T.E., Katimbo, A., Duan, J. 2022. Real-time irrigation scheduling of maize using Degrees Above Non-Stressed (DANS) index in semi-arid environment. Agricultural Water Management. 279. Article e107957. https://doi.org/10.1016/j.agwat.2022.107957.
Katimbo, A., Rudnick, D.R., Liang, W., DeJonge, K.C., Lo, T.H., Franz, T., Ge, Y., Qiao, X., Kabenge, I., Nakabuye, H., Duan, J. 2022. Two source energy balance maize evapotranspiration estimates using close-canopy mobile infrared sensors and upscaling methods under variable water stress conditions. Agricultural Water Management. 274. Article e107972. https://doi.org/10.1016/j.agwat.2022.107972.
Roberts, C., Gholson, D., Quintana-Ashwell, N., Kaur, G., Singh, G., Krutz, L.J., Cooke, T. 2022. Perceptions of irrigation water management practices in the Mississippi Delta. Agronomy. 12(1):186. https://doi.org/10.3390/agronomy12010186.
Spencer, D., Krutz, J.L., Locke, M.A., Gholson, D.M., Bryant, C.J., Henry, B.W., Golden, B.R. 2022. Runoff, erosion, and nutrient transport arising from furrow irrigation in a corn conservation production system. Agrosystems, Geosciences & Environment. 5(2). Article e20259. https://doi.org/10.1002/agg2.20259.
Spencer, D., Krutz, J.L., Locke, M.A., Gholson, D.M., Bryant, C.J., Mills, B.E., Henry, B.W., Golden, B.R. 2021. Corn productivity and profitability in raised, stale seedbed systems with and without cover crops. Crop, Forage & Turfgrass Management. 8(1). Article e20142. https://doi.org/10.1002/cft2.20142.
Brock, M.L., Tagert, M.M., Paz, J.O., Krutz, J.L. 2023. Evaluation of on-farm water capture and groundwater decline in the Big Sunflower Watershed, Mississippi River Basin. Journal of Hydrology: Regional Studies. 48:101479. https://doi.org/10.1016/j.ejrh.2023.101479.
Quintana Ashwell, N.E., Gholson, D.M. 2022. Optimal management of irrigation water from aquifer and surface sources. Journal of Agricultural and Applied Economics. 54(3):496-514. https://doi.org/10.1017/aae.2022.23.
Singh, B., Kaur, G., Quintana Ashwell, N.E., Singh, G., Lo, T.H. 2023. Row spacing and irrigation management affect soybean yield, water use efficiency and economics. Agricultural Water Management. 277:108087. https://doi.org/10.1016/j.agwat.2022.108087.
Rix, J.P., Lo, T.H., Gholson, D., Pringle, H.L., Spencer, D.G., Singh, G. 2022. Effects of low-till parabolic subsoiling frequency and furrow irrigation frequency on maize in the Yazoo-Mississippi Delta. Agricultural Water Management. 274:107945. https://doi.org/10.1016/j.agwat.2022.107945.
Katimbo, A., Rudnick, D.R., DeJonge, K.C., Lo, T.H., Qiao, X., Franz, T., Nakabuye, H.N., Duan, J. 2022. Crop water stress index computation approaches and their sensitivity to soil water dynamics. Agricultural Water Management. 266. Article e107575. https://doi.org/10.1016/j.agwat.2022.107575.