Location: Sustainable Water Management Research2022 Annual Report
1. Quantify water requirements of cotton, corn, and soybean cropping systems and develop crop coefficients for irrigation scheduling in humid regions, and develop and evaluate irrigation scheduling and variable-rate irrigation technologies to improve water use efficiency in cotton, corn, and soybean. 1.1. Develop sensor technologies and algorithms for variable rate irrigation (VRI) scheduling, prescription development, and automation, and quantify the impacts of VRI technology on water-use efficiency and crop yield. 1.2. Develop new and/or improved sensing technologies to automatically monitor crop responses, and develop improved irrigation scheduling methods based on weather data and numerical models incorporating internet-based data access to provide real-time information access. 1.3. Predict the impacts of climate change and variability on production and water requirements in cropping systems in the Mississippi Delta to develop adaptation strategies for sustainable production. 1.4. Quantify and evaluate water stress indices and crop physiological responses for irrigation scheduling to enhance water productivity under drought conditions in humid regions. 2. Develop conservation management practices to improve water management and enhance environmental sustainability. 2.1. Develop and evaluate mobile remote sensing applications including ground- and UAV-based sensing systems to monitor crop conditions for managing irrigation water and nutrient applications. 2.2. Use eddy covariance (EC) and residual energy balance (REB) methods to determine ET and crop coefficients for irrigation scheduling, and monitor emission of CO2 and CH4 from agricultural fields for assessing the impact of climate change on agroecosystems in the Mississippi Delta. 2.3. Study impact of tillage radish cover crops on runoff water quantity and quality and crop production. 3. Develop integrated conservation management cropping systems that improve soil health, water availability, water quality, and productivity. 4. Develop integrated irrigation and crop management systems that increase profitability, conserve water, and protect water quality in the Mid-South. 5. Assess the profitability and risks associated with integrated production agriculture and conservation systems in the Mid-South. 6. Assess surface and subsurface hydrology, surface runoff, and contaminant transport in conservation crop production systems at plot and field scales. 7. Improve knowledge and understanding of the hydrological and climate variability processes governing the movement, storage, quantity and quality of water in the Lower Mississippi River Basin (LMRB), and develop tools/technologies to enhance the sustainability of water resources for agriculture. 8. Utilize UAS and multi-scale geospatial technologies to assess and improve the long-term sustainability of water resources in agroecosystems. 9. Develop robust datasets, models, and data visualization tools to determine the impact of alternate water supplies on aquifer recharge and groundwater levels in the Lower Mississippi River Basin.
Variable rate irrigation (VRI) experiments will be conducted. Experiments will consist of two irrigation management treatments, VRI management and ISSCADA (Irrigation Scheduling and Supervisory Control and Data Acquisition System) management. Sensors will be used to detect soil water content. An algorithm to calculate crop water requirements will be developed using soil water content, soil electrical conductivity, yield, and crop water stress index. VRI events will be scheduled according to the VRI prescriptions. Crop yield and irrigation water efficiency in VRI treatment will be compared to that in ISSCADA treatment. Wireless electronic sensing and monitoring systems will be developed to measure properties of interest for agronomic, water-management, and irrigation-scheduling applications. Advance and distribution of irrigation water across the field will be monitored to improve uniformity and reduce runoff. Weather-based water-balance and crop models will be compared for use in scheduling irrigations. Smartphone apps will be developed to provide capabilities to configure system operating parameters and download 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. Four-row datalogging systems, measuring plant height, canopy temperature, canopy spectral reflectance, and GPS information, will be developed for mounting on the front of agricultural equipment. Unmanned aerial vehicles will be tested for suitability as mobile sensing platforms to detect problem areas in the field, assess vegetation and changes, and collect sensor measurements. Four EC systems consisting of CH4 analyzer, CO2/H2O analyzer, 3D sonic anemometer, and biomet system will be deployed in Mississippi Delta to monitor long-term agroecosystem and collect data for ET and crop coefficients estimates. We will participate in the Lower Mississippi River Basin (LMRB) Delta Flux Network to share the resources and data appropriate to the USDA-ARS Long-Term Agroecosystem Research (LTAR) project. Tillage radish cover crop will be applied in 12 large plots of cotton field. One storm water monitoring system will be installed in each plot to measure the runoff. The runoff samples will be collected and analyzed for water quality. Soil water content, soil properties, and cotton plant characteristics and yield will be determined. In comparison with conventional cultivation, effects of the cover crop on soil water content, runoff water quantity and quality, and cotton yield will be analyzed. Please refer to related docs for 6001-13000-001/002-00D for remaining approach.
This is the final annual report for this project. New project number is 6066-13000-006-00D titled Development of Best Management Practices, Tools, and Technologies to Optimize Water Use Efficiency and Improve Water Distribution in the Lower Mississippi River Basin. Significant progress was made on the objectives of this project throughout the performance period. In Objective 1, the water requirements for cotton, corn, and soybean crops in humid regions were determined and crop coefficients were developed. Inexpensive wireless monitoring systems were deployed into fields to monitor the movement and location of advancing water during irrigation events. This technology allows real-time monitoring of field conditions through smartphone technology. As part of Objective 2, crop coefficients were developed by examining water productivity and crop stress responses under small and large-scale production environments. The results from Objective 2 were employed in models to assist in determining optimum irrigation scheduling for variable rate irrigation systems, particularly with a focus on automated irrigation as part of Objective 1. Accomplishing Objective 3, required monitoring the spread of irrigation water across crop fields for uniformity as well as monitoring runoff quality and quantity to ensure minimal loss of soil and excess application of irrigation water. Eddy covariance (EC) systems were deployed in the fields to monitor crop responses to new irrigation schemes. Researchers in Stoneville, Mississippi, examined corn/soybean rotations over multiple years at field-scale while using EC systems to monitor crop stress and response to variation irrigation systems. This data was used to accomplish Objective 4 and 5 to provide recommendations to producers on the impact of new crop management and production systems. Alternative irrigation schemes, such as alternate furrow irrigation and variable rate irrigation, were demonstrated to reduce water usage without negatively impacting crop yield or producer profitability. Runoff was monitored from various research trials executed at large-scale for the accomplishment of multiple objectives. The runoff was quantified for quantity, soil content, and chemical content to understand the role of various conservation crop production systems, such as cover crops, no tillage, and minimal tillage, in reducing soil loss and minimizing chemical leaching in the runoff (Objective 6). Models of water flow throughout the Lower Mississippi River Basin (LMRB) were developed to understand the role of various hydrologic and climate variables in governing the movement of water throughout the aquifer system of the LMRB (Objectives 7 and 8). These models will enable future research to understand the ability of the LMRB to recharge the aquifer through reduce irrigation withdrawal and capture of precipitation. These models provide the ability to demonstrate the positive impact irrigation practices can have on aquifer levels, thus increasing adoption of more efficient irrigation practices. Objective 9 built upon the results of Objectives 7 and 8 to demonstrate the impact of alternate water supplies on water availability throughout the LMRB. To accomplish this, an on-farm water storage study was initiated in collaboration with a commercial producer in Sunflower County, Mississippi. This research project is quantifying the reduction in groundwater withdrawal from the LMRB through the use of an alternate water supply. During the course of the project, numerous components of the project were brought together to develop an irrigation scheduling model using water data and a soil-water balance method. A version of this model was developed which downloads weather data automatically from internet-based weather-data services. The limited special coverage of these weather-data services was sufficient to provide temperature measurements but the highly variable rainfall patterns across the LMRB necessitated the collection of individual farm rainfall data. This work highlighted the need to incorporate locally measured rainfall data into irrigation scheduling applications for wide-spread adoption and utility.