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

2024 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. To develop tools to determine the impact of alternate water supplies on aquifer recharge and groundwater levels, a cost-effective sensing system was designed for water level monitoring. This system uses open-source hardware and software ultrasonic sensors and liquid level transmitters that were integrated with a microcontroller and evaluated for water level monitoring. In addition, geospatial technologies were used to create an inventory of on-farm water storage systems over multiple years in the Big Sunflower River Watershed. Geo-referenced datasets with soils, crops, hydrologic, and climate data past 2017 have been acquired from the Mississippi Department of Environmental Quality, CropScape, and United States Geological Survey to help quantify and characterize demand for irrigation water and identify the value of water in competing and complementary agricultural water uses. As part of the effort to model the impact of alternate water supplies on aquifer dynamics, flow meters, rain gauges, runoff auto-samplers, and level loggers have been collecting data from a tailwater recovery system in Sunflower County, Mississippi for the third year. Data for the model, including the relevant land use, soil, and weather data have been compiled. To help develop optimized irrigation scheduling tools for cropping systems, a weather-based calibration approach was developed and implemented for soil and water sensors. The algorithms for irrigation scheduling have been initialized and tests are being conducted to complete the third year of data collection. In addition, eleven on-farm automation sites were evaluated this past year. On-farm sites consist of a farmer controlled well where they irrigated their fields as they chose, and another well equipped with pump controls and automated valves where researchers controlled the irrigation through the automated system. Data was compiled on time used, irrigation amounts applied, and crop yields for both automated and non-automated sites. To help develop new and novel sensor systems, and tools for water resource management, combinations of tension-based irrigation triggers and nitrogen fertilizer rates are being evaluated in sprinkler-irrigated corn on two soil types. Tension-based irrigation triggers are those based on measurements of the tensions between soil particles and water and are one of the most common types of soil moisture sensors, The higher the tension, the less water, allowing researchers to determine tension levels at which irrigation is recommended, Also, electrical resistance sensors and multisensor capacitance probes are being evaluated in two regions of Mississippi. Combining the measurements from these sensors with aerial\satellite images and creating an algorithm allowed for the successful determination of irrigation needs over a larger area. Relationships between soil water, canopy temperature, and crop yield are being analyzed. To evaluate and improve current best management practices on irrigated fields, three sprinkler irrigation systems were in operation, while agronomic, crop, and water use data were measured. Cover crop studies have had three full winters of cover crops planted and three cash crop seasons. Soil, water, nutrient, and agronomic data have been collected for both the cover crop studies and tillage and fertilizer placement treatments. To further engage stakeholders through our university research and extension partners, eleven on-farm automation sites established, plus an additional 30 soil moisture sensors demonstrations were conducted. Meetings with and presentations to stakeholders were conducted. Technical assistance on irrigation management was provided to farmers and extension agents and a stakeholder-oriented annual report was compiled. The response period for the conservation practices survey questionnaire has closed. Additional stakeholder organizations have been consulted to develop approaches to ensure the survey was delivered to a broad sampling of producers across the Mississippi Delta. Data has been tabulated and analysis is ongoing. To develop and validate models using remote sensing and eddy covariance methods to improve the forecasting capabilities of models to address the impacts of climate change, corn experiments were continued in two large farm-scale plots, one rainfed and one irrigated. Eddy covariance stations are used to directly observe the exchanges of gas, energy, and water vapor between ecosystems and the atmosphere. For this research, they were used to monitor water plant use and evaporation, and carbon dioxide for a third year. In addition, the effect of nighttime temperature on cotton growth and physiology was investigated. Data was collected on the critical growth stages for irrigations of soybean.

Accomplishments
1. Master irrigator program teaches practices of irrigation efficiency. The National Center for Alluvial Aquifer Research (NCAAR) in Stoneville, Mississippi, initiated the Master Irrigator Program this year as a way to transfer information on irrigation efficiency directly to producers. To save money and become more efficient with water use, growers must understand and properly implement these tools on their farms. The program presented knowledge and tools to the participants to put into practice on their farms. The program was produced at no cost to participants and included eight hours of online classes and 16 hours of in-person training. The Master Irrigator class will be offered each year by ARS researchers in Stoneville, Mississippi. Producers enrolled in certain Natural Resources Conservation Service programs can meet program requirements by submitting their Master Irrigator certificate. The inaugural class had 38 participants successfully complete the program.

2. Factors affecting farmer adoption of conservation practices. Employing survey data, ARS researchers in Stoneville, Mississippi, were able to identify factors associated with farmer adoption of conservation practice in the context of irrigated agriculture. Only a third of growers believe (or are aware of) groundwater problems at the farm or state level. This lack of awareness was found to be correlated to whether farmers noticed a change in the depth to water distance in their irrigation wells. Perception of a groundwater problem is positively associated with conservation practice adoption. Participation in sponsored conservation programs was found to not affect decision to adopt specific practices but did have a significant positive impact on the number of practices adopted. Engagement with extension agents/programs was found to speed-up adoption of practices such as computerized hole selection in furrow irrigation and sprinkler irrigation, both of which reduce overall groundwater use.

3. Development of optimization tool for agro-hydrologic models. Development of optimization tool for agro-hydrologic models. ARS researchers in Stoneville, Mississippi, created an optimized tool in Python to improve efficiency for sensitivity and uncertainty analyses of hydrological parameters of hydrologic models. Since parameterization requires tens to hundreds of thousands of iterations, researchers have incorporated the capabilities to use high-performance computing facilities directly into the tool to reduce computational expenses. This tool can be used for any hydrological model but was designed especially for an agro-hydrologic model to be integrated with groundwater and economic models. This tool has been used in models looking at water quality runoff under different grazing scenarios in Oklahoma and is currently being used in research in collaboration with University of Texas Arlington to examine the effects of best management practices under future climate scenarios in Mississippi. Paired with the high-performance computing facilities, this tool has reduced the completion time of computing procedures that took multiple days down to hours. It also saves further time and resources by automatically producing visualization products of the results in the forms of graphs and charts.

Review Publications
Nelson, A.M., Maskey, M.L., Northup, B.K., Moriasi, D.N. 2024. Calibrating Agro-Hydrological Model under Grazing Activities: Challenges and Implications. Journal of Hydrology. https://doi.org/10.3390/hydrology11040042.
Rix, J.P., Lo, T., Gholson, D.M., Spencer, D.G., Singh, G. 2023. Effects of conservation practices on rainfed maize yield, furrow water infiltration, and soil moisture for surface sealing loam soils in the Yazoo-Mississippi Delta. Soil Science Society of America Journal. https://doi.org/10.1002/saj2.20595.
Lo, T., Rix, J.P., Pringle, H., Rudnick, D.R., Gholson, D.M., Nakabuye, H.N., Katimbo, A. 2024. Metrics for Evaluating Interreplicate Variability of Irrigation Scheduling Sensors. American Society of Agricultural and Biological Engineers. 67(1):115-126. https://doi.org/10.13031/ja.15513.
Feng, G.G., Anapalli, S.S. 2022. Integrating models with field experiments to enhance research: cover crop, manure, tillage, and climate change impacts on crops in the humid Mississippi Delta. In: Ahuja, L.R., Kersebaum, K.C., Wendroth, O., editors. Advances in Agricultural Systems Modeling. p. 359-391. https://doi.org/10.1002/9780891183860.ch12.
Gitter, A., Boellstorff, D.E., Mena, K.D., Gholson, D.M., Pieper, K.J., Chavarria, C.A., Gentry, T.J. 2023. Quantitative microbial risk assessment for private wells in flood-impacted areas. Water. 15(3):469. https://doi.org/10.3390/w15030469.
Vargas, A., Singh, G., Kaur, G., Lo, T., Spencer, G., Krutz, J.L., Gholson, D.M. 2024. Urea ammonium nitrate placement methods, row patterns, and irrigation effects on corn productivity in a humid subtropical region. Agrosystems, Geosciences & Environment. https://doi.org/10.1002/agg2.20462.
Russell, D., Singh, G., Quintana-Ashwell, N., Kaur, G., Gholson, D.M., Krutz, J.L., Nelson, K.A. 2023. Cover crops and furrow irrigation impacts on soybean production in sub-humid climate. Agricultural Water Management. https://doi.org/10.1016/j.agwat.2023.108347.
Bryand, C.J., Spencer, D.G., Gholson, D.M., Plumbee, M.T., Dodds, D.M., Oakley, G.R., Reynolds, Z.D., Krutz, J. 2023. Development of a soil moisture sensor-based irrigation scheduling program for the mid-southern USA. Crop, Forage & Turfgrass Management. https://doi.org/10.1002/cft2.20217.
Spencer, D.G., Gore, J., Mills, B.E., Gholson, D.M. 2023. On-farm response of inbred and hybrid rice cultivars to furrow irrigation. Agronomy Journal. https://doi.org/10.1002/agj2.21453.
Singh, B., Chastain, D.R., Kaur, G., Snider, J., Stetina, S.R., Bazzer, S. 2023. Reniform nematode impact on cotton growth and management strategies: A review. Agronomy Journal. 2023:1-19. https://doi.org/10.1002/agj2.21368.
Chastain, D.R., Snider, J., Singh, B., Virk, G. 2024. Drought response modeling of leaf photosynthetic parameters in two Gossypium species. Journal of Agronomy and Crop Science. 210(3):12709. https://doi.org/10.1111/jac.12709.
Turner, J.L., Desai, A.R., Thom, J., Lindgren, K., Laudon, H., Peichl, M., Nilsson, M., Campeau, A., Jarveoja, J., Hawman, P. 2023. On the relationship between aquatic CO2 concentration and ecosystem fluxes in some of the world’s key wetland types. Wetlands. 44(1):20. https://doi.org/10.1007/s13157-023-01751-x.
Nelson, A.M., Witthaus, L.M., Moore, M.T., Griffith, M.K., Locke, M.A., Taylor, J.M., Lizotte Jr, R.E. 2023. Seasonal water quality trends in a tailwater recovery system in the Mississippi Delta. Agricultural Water Management. 78(1):26-32. https://doi.org/10.2489/jswc.2023.00090.
Delhom, C.D., Van Der Sluijs, M.J., Bange, M.P., Long, R.L., Nelson, A.M. 2023. Yield, fiber quality and textile outcomes from in-field blending of cotton seed at planting. Journal of Cotton Science. 27:1-11. https://doi.org/10.56454/PHCR9024.
Russell, D., Singh, G., Quintana-Ashwell, N., Kaur, G., Gholson, D., Krutz, J., Nelson, K.A. 2024. Cover crops and irrigation impacts on corn production and economic returns. Agricultural Water Management. https://doi.org/10.1016/j.agwat.2024.108739.
Quintana Ashwell, N.E., Al-Sudani, A., Gholson, D. 2024. The cost of mismanaging crop heat stress with irrigation: Evidence from the mid-south USA. Agricultural Water Management. 300:108907. https://doi.org/10.1016/j.agwat.2024.108907.
Inam, A., Islam, M., Ria, S., Perez, F., Delhom, C.D., Abidi, N., Tabassum, S. 2023. Circular sensing of nitrate levels in water with flexible screen-printed sensors on biodegradable cellulose substrate. IEEE Sensors Letters. 7:9. https://doi.org/10.1109/LSENS.2023.3301834.
Kaur, G., Ashwell,Nicolas, Q.E., Singh, G., Gholson, D., Locke, M.A., Krutz, J., Cooke, T. 2023. Producer perceptions on the value and availability of water for irrigation in the Mississippi Delta. Journal of Contemporary Water Research and Education. 178(1):60-70. https://doi.org/10.1111/j.1936-704X.2023.3393.x.
Gitter, A.C., Boellstorff, D.E., Gholson, D.M., Pieper, K.J., Mena, K.D., Mendez, K.S., Gentry, T.J. 2023. Texas well user stewardship practices three years after Hurricane Harvey. Water. 15(22):3943. https://doi.org/10.3390/w15223943.
Atwill, L.R., Bond, J.A., Gore, J., Gholson, D.M., Walker, T., Spencer, D.G., Oakley, G.R., Reynolds, Z.D., Krutz, J.L. 2023. Barnyardgrass control in conventional and Clearfield rice grown under intermittent flooding. Crop, Forage & Turfgrass Management. 284:108347. https://doi.org/10.1002/cft2.20246.
Singh, G., Quintana Ashwell, N.E., Kaur, G., Gholson, D., Locke, M.A., Krutz, J.L., Cooke, T. 2023. Opinions on irrigation water management tools and alternative irrigation sources by Farmers from the Delta Region of Mississippi. Journal of Contemporary Water Research and Education. 178(1):90-102. https://doi.org/10.1111/j.1936-704X.2023.3395.x.