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ARS Home » Southeast Area » Stoneville, Mississippi » Sustainable Water Management Research » Research » Research Project #441615

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

2022 Annual Report

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.)

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
This project replaces expired project 6066-13000-005-000D, "Development of Sustainable Water Management Technologies for Humid Regions"; refer to expired project for additional information. Significant progress was made in initiating this project. A cost-effective sensing system was designed for water level monitoring using open-source hardware (e.g., Arduino and Raspberry Pi) and software (e.g., Python) 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. Ultrasonic range finders and pressure-based water level sensors were evaluated in the lab with reference measurement 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 appropriate data has been acquired from the Mississippi Department of Environmental Quality, CropScape, and USGS for Subobjective 1.C. The GIS data is being processed for uniformity and completeness. For Subobjective 1.D., flow meters, rain gauges, runoff auto-samplers, and level loggers have been installed in a tailwater recovery system in Sunflower County, near Inverness, MS. Flow, rain, and levels are being recorded and samples collection has begun. The hydrologic model for the tailwater system is being built. The soybean crop has been planted for Subobjective 2.A. Soil water sensors have been tested and installed. However, the weather station and runoff monitoring systems have been delayed due to the retirement of an SY. The algorithms for irrigation scheduling have been initialized and tests are being conducted to complete the first year of data collection. On-farm comparisons of irrigation automation against conventional management are being performed for Subobjective 2.B. 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. Two types of soil water sensors are being evaluated in two regions of Mississippi for Subobjective 3.B. Water level sensors were identified and evaluated for surface water measurement. 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 Subobjective 4.A., three sprinkler irrigation systems and a tile drainage system were installed and are operating. Cover crop studies have had a full winter of cover crops planted and a cash crop season for Subobjective 4.B. Data has been collected and future yield data will be combined with current data. For Subobjective 4.C., studies were initiated with the planting of the cash crop. Tillage and fertilizer placement treatments were conducted. Yield data will be collected and analyzed. Meetings with stakeholders were conducted for Subobjective 5.A. Technical assistance on soil moisture monitoring systems was provided to Extension agents and a stakeholder-oriented annual report was compiled. For Subobjective 5.B., producer and stakeholder focus groups were organized. A survey questionnaire has been developed, tested, and validated and is being prepared for deployment to producers suggested by Delta FARM and producer groups. 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 first-year data was collected. Crop canopy micrometeorological data was also collected for developing and improving system models for predicting the impacts of climate change on corn production in the MS Delta.

1. Revisiting recommendations for sensor-based soybean furrow irrigation scheduling on clay soils. Over the past decade, Mississippi State University on-station and on-farm research on irrigation scheduling has focused on the use of Watermark soil moisture sensors and established recommendations for irrigation whenever the average sensor value across the soil profile reaches somewhere between 70 and 100 centibars. ARS researchers in Stoneville, Mississippi, re-evaluated these guidelines and found that triggering at 100 centibars rather than 70 centibars delayed irrigation by approximately four days per drying cycle. This extra time to catch rain eliminated three irrigation applications per year and reduced groundwater pumping by about 30%. By following these locally proven recommendations, farmers can conserve the groundwater resources of the Mississippi Delta while maximizing their likelihood of producing a profitable and high-yielding soybean crop.

2. Tailwater recovery and reservoir storage benefits for farm profits and aquifer sustainability emerge when considering field-aquifer interaction in long planning horizons. Tailwater recovery and storage reservoir systems include a large tailwater ditch which captures all runoff later to be used for irrigation. ARS researchers in Stoneville, Mississippi, conducted a cost-benefit analysis of such systems. Expansion of on-farm water storage systems can result in large gains derived from taking advantage of off-season precipitation and keeping pumping lift distances low (i.e., high water table in the aquifer). Additional benefits of the practice that affect the quality of receiving streams and the hypoxic zone justify aggressive incentives to encourage growers to develop these structures which provide them with complete control of an important source of water for irrigation.

3. Soil moisture monitoring showcase. Soil moisture sensors provide science-based information about the amount of soil water available to the crop, which can help farmers forecast and finalize decisions about irrigation scheduling. The National Center for Alluvial Aquifer Research (NCAAR) Soil Moisture Monitoring Showcase was launched in 2020 to address this important need. In 2021, the showcase partnered with seven Mid-South vendors who provided 12 distinct soil moisture monitoring systems, all of which were installed in the same 2-acre field in Stoneville, Mississippi, and presented on the NCAAR website. ARS researchers in Stoneville, Mississippi, will incorporated these findings into Mississippi State University Extension recommendations on sensor selection and interpretation to increase farmer success with scheduling irrigation using soil moisture sensors.

4. Advancing adoption of soil moisture sensors through on-farm training and demonstration. To empower producers to integrate soil moisture sensors fully into their farming operations, ARS researchers in Stoneville, Mississippi, launched a multi-year on-farm education program. 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. These agents recruited more than 20 soybean, corn, cotton, and rice producers from their respective counties in 2021 and provided participants with hands-on training and assistance in troubleshooting and data interpretation until the participants become active and capable independent users of soil moisture sensors. This program is helping Mississippi producers gain the skills and confidence necessary to adopt soil moisture sensors on their own, allowing them to optimize their irrigation practices.

Review Publications
Snider, J., Pilon, C., Hu, W., Wang, H., Tishchenko, V., Slaton, W., Chastain, D.R., Parkash, V. 2022. Net photosynthesis acclimates to low growth temperature in cotton seedlings by shifting temperature thresholds for photosynthetic component processes and respiration. Environmental and Experimental Botany. 196:104816.
Quintana-Ashwell, N., Kaur, G., Singh, G., Gholson, D., Delhom, C.D., Krutz, J., Hedge, S. 2021. Positive mathematical programming to model regional or basin-wide implications of producer adoption of practices emerging from plot-based research. Agronomy Journal. 11(11):2204.
Li, Z., Chen, Z., Cheng, Q., Duan, F., Sui, R., Huang, X., Xu, H. 2022. UAV-based hyperspectral and ensemble machine learning for predicting yield in winter wheat. Agronomy. 12(1):202.
Lo, T., Pringle, H. 2021. A quantitative review of irrigation development in the Yazoo–Mississippi Delta from 1991 to 2020. Agronomy. 11(12):2548.
Huang, Y., Ma, W., Fisher, D.K. 2021. Development and evaluation of an optical sensing system for detection of herbicide spray droplets. Advances in Internet of Things. 11:1-9.
Quintana-Ashwell, N., Anapalli, S.S., Pinnamaneni, S.R., Kaur, G., Reddy, K.N., Fisher, D.K. 2021. Profitability of twin-row planting and skip-row irrigations in a humid climate. Agronomy Journal. 114(2):1209-1219.
Sui, R., Anapalli, S.S. 2021. Effects of nitrogen rate and cover crop on cotton (Gossypium hirsutum L.) yield and soil water content. Agriculture. 11(7):650.
Bellaloui, N., Smith, J.R., Ray, J.D., Mengistu, A., Gillen, A.M., Fisher, D.K., Singh, G. 2022. Responses of seed yield, quality, and composition to the harvest-aid paraquat in soybean grown in Mississippi. Agrosystems, Geosciences & Environment. 5(2):e20262.
Dhakal, M., Huang, Y., Locke, M.A., Reddy, K.N., Moore, M.T., Krutz, J., Gholson, D., Bajgain, R. 2022. Assessment of cotton and sorghum stand establishment using UAV-based multispectral and DSLR-based RGB imagery. Agrosystems, Geosciences & Environment. 5(2):e20247.
Singh, G., Dhakal, M., Sharma, A., Schoonover, J.E., Williard, K.J., Kaur, G. 2022. Cover crops and landscape positions mediate corn–soybean production. Agrosystems, Geosciences & Environment. 5(2):e20249.
Pinnamaneni, S., Anapalli, S.S. 2021. Assessing the effects of agronomic management practices on soybean (Glycine max L.,) residue quality in the lower Mississippi Delta. Plants.
Anapalli, S.S., Pinnamaneni, S., Reddy, K.N., Sui, R., Singh, G. 2022. Investigating soybean (Glycine max L.) responses to irrigation on a large-scale farm in the humid climate of the Mississippi Delta region. Agricultural Water Management. 262:107432.