Location: Sustainable Water Management Research2021 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.
Significant progress was made towards completing this project. In Sub-objective 1.1, the test of Variable Rate Irrigation (VRI) management continued. Soybean crops were planted in a field covered by the VRI center pivot irrigation system, uniform rate irrigation (URI), and rainfed irrigation. The VRI prescription was created based on soil electrical conductivity. An upgraded AgSense device was employed for VRI irrigation control. TDR (time domain reflectometer) soil water sensors were installed in the fields to monitor soil water status for irrigation scheduling. VRI irrigation events were triggered as the soil water content dropped to 50% depletion of available water. The grain yield in the management zones, were analyzed for water productivity. The corn phase of the corn-soybean rotation in Sub-objective 1.3 was established in a farm-scale plot with furrow irrigation facilities. Whenever plant-available water in the soil fell below 65% of total plant available water the crops were irrigated at 100%, 50%, and 0% (rainfed) irrigation levels. Growth and development responses of the corn crops to the applied irrigations were collected. Corn water use under full irrigation, half irrigation, and rainfed systems were quantified using Eddy Covariance (EC) techniques for developing corn responses to irrigations and climate variabilities. Potential crop evapotranspiration (ET) quantified using the EC and energy balance methods from the data collected in the experiments were used to calibrate and improve corn growth simulations in the Root Zone Water Quality Model (RZWQM2). The calibrated model was further integrated with the experiments and climate-change scenarios for the Mississippi Delta region, and impacts of climate change on soybean production were investigated. In Sub-objective 1.4, sensors were installed for measuring canopy temperatures, normalized difference vegetation index (NDVI), and photochemical reflectance indices in corn fields maintained at 100, 50, and 0% irrigation levels. The irrigation was initiated based on the plant-available water in the 50 cm root zone of the crop. The data were continuously collected during the season. Corn, soybean, and rice crops in farmer fields also were monitored for similar data. As in the previous years, there was no significant drought (water stress) adversely affecting the crop. However, a few flood-storm events were causing crop-stand loss and instrument damages and failures. This rendered it nearly impossible to evaluate water stress indices as a standalone tool for irrigation decision support. The data collected were used to evaluate stress indices calculated in the cropping system model. Three UAS (unmanned aircraft system)-based sensing systems were set up and two of them have been used in field studies (Sub-objective 2.1 and Objective 8). Images of crops and soils in various wavebands were acquired using the UAS-based sensing systems. Preliminary image analyses were performed to estimate crop water stress status and predict the relationships between spectral reflectance characteristics of the soils and the soil texture. Crop water stress index and soil texture can be used for crop water management. In Sub-objective 2.2, experiments were conducted in farm-scale plots and in 500-ac irrigated soybean fields in collaboration with a local rice producer. An open-path infrared gas analyzer and a sonic anemometer were used in the EC system for estimating evapotranspiration. The quantified ET was used from calculating crop coefficient for alfalfa and grass reference crops. Agricultural-weather monitoring systems coupled with EC systems were installed in farmers’ rice fields for collecting real-time data on crop water use and greenhouse gas emissions. The data collected will be useful for developing research information for developing management practices that help reduce greenhouse gas emissions and develop sustainable water management practices in response to climate variability and extremes. In Sub-objective 2.3, we continued the experiments on the impact of cover crop on runoff, soil water, and crop yield in corn production system. Twelve farm-strip scale plots were used for the tests with two rates of nitrogen (N) and either cover crop or no cover crop. Cover crop (tillage radish) was planted in the fall of 2020 followed by corn as a cash crop in April of 2021. Irrigations were scheduled based on in-situ sensor-measured soil water contents and applied using a center-pivot irrigation system. Storm water monitoring systems were used for continuous data collection from the plots for runoff water quantity and quality. One lysimeter was installed in each plot to collect underground water samples for quality of the underground water. Corn grain yield was obtained. All data collected will be analyzed to determine the effect of cover crop and N rates on corn yield. Related to Sub-objectives 3.1 and 3.2, runoff water sampling was conducted in Stoneville, MS and the data is being analyzed. Soil moisture and temperature probes have been used for collecting data. All plots were conventionally tilled and planted for the “reset” term to capture the effects of the transition and introduction of conservation measures over the next few years. Irrigation access for each plot was installed in preparation for irrigation experiments during this transition time. An experiment was set up in two fields with cover crops and without cover crops in crop rotation of corn-soybean to quantify the water use and conservation by the cover crops. The comparative analysis will help to assess the impacts of cover crop on soil moisture of the succeeding main crop. Concurrent measurement of carbon and water fluxes will be useful in estimating the water use efficiency of two different cropping systems. In Objective 4, the experiment was established in collaboration with a rice farmer in two fields. Crops were planted under alternate wetting drying (AWD) and continuous flood (CF) systems. EC systems with sensors for measuring water, carbon dioxide, and methane fluxes were installed in the middle of the fields. Soil samples were collected for soil texture and characterizing water holding capacities and available nutrients. Second-year data on crop growth, development/phenology, and grain yield were collected. Methane emissions from the two systems were compared and informed the farmer. AWD had less methane emissions than the CF system with similar grain yield returns. Data collection in tillage radish cover crop study was continued in corn plots for runoff water quantity and quality. In Objective 5, soybean under no-tillage with residue retention (NT) and conventional tillage (CT) systems were established in farm-scale plots. Soil, water, C, and N data under NT and CT were collected. Air temperature and relative humidity, soil temperatures, net solar radiation, wind speed, and soybean canopy temperature were also collected for quantifying crop water use using an energy balance model. Collected weather and crop management data were used to calibrate the RZWQM2 for the NT and CT experiment simulations. Long-term climate data (1960-2020) at Stoneville, Mississippi were collected for integration with the calibrated model for simulating production risk associated with the two soil tillage systems in the region. For Objective 6, the data from the cotton and corn years were analyzed and the data from the soybean years is being analyzed. Effects of different tillage methods, cover crops, and different edge-of-field buffer strips on runoff water quantity and quality in cotton and corn were investigated. While there were no differences in yield in either crop, conservation practices that increased residue cover on the field and that provided an edge-of-field barrier reduced sediment loss in runoff in cotton and corn. Also, nutrients that were associated with sediment were reduced, nitrogen and phosphorus in cotton and phosphorus in corn. However, nutrient loss associated with the runoff tended to increase 50-75% under conservation management in cotton and 80-110% in corn. The analyses of the routine and seasonal grab data and the storm event water quality data (nutrients and sediment) from the tailwater recovery system (TWR) has been completed, as has the pesticide data from the routine and seasonal grab schemes in accordance with Objective 7. Water quality and quantity data from a ditch and pond TWR system were measured from a farm in Sunflower County, Mississippi. This is the last report for this project. Novel technologies and tools for sustainable water management were developed. VRI prescriptions were generated based on soil properties, canopy temperature, and sensor-measured soil water content. Water was applied site-specifically according to the VRI prescriptions. Results indicated VRI management saved up to 11-30% irrigation water. Low-cost tools for real-time monitoring of field conditions via the cellular network was accomplished by accessing the internet via smartphone apps and web browsers on mobile devices. These inexpensive sensing devices will enable researchers and producers to collect field data at low cost. This project also quantified crop ecosystem water use efficiencies using the EC and residual energy balance methods. Results of this investigation can be used for irrigation scheduling and help in adopting crop mixtures that are environmentally and economically sustainable while conserving water resources in the region. Tailwater recovery systems in Mississippi were evaluated. The investigation showed total solids, phosphate, ammonium, and nitrate contents in the ditch water were much higher than that in the reservoir water. These results suggested the reservoir serves an important function to process nutrients and sediments and emphasize the importance of a closed TWR system in reducing water quality impairment by the runoff from farms.
1. Cover crop increased rainwater use in cotton production. Appropriate use of cover crops can improve soil health and water holding capacity in cotton production system. ARS researchers in Stoneville, Mississippi, tested the effects of cover crop on soil water and cotton yield. Winter tillage radish was used as the cover crop. Results indicated that the cover crop increased soil water infiltration capacity increasing the ability of the soil to retain higher water content. Use of the cover crop did not affect the cotton yield and had the potential to reduce groundwater withdrawals from the Mississippi River Valley Alluvial Aquifer.
2. Tailwater recovery system improved runoff water quality. Agricultural water pollution has become a serious environmental issue worldwide. The runoff from farms is one of the leading causes of water quality impairment. ARS researchers in Stoneville, Mississippi, evaluated a tailwater recovery system in Mississippi. Total solids were 2 to 4 times higher in the tailwater ditch than in the reservoir. Phosphate was 1.4 times higher in the ditch in spring compared to the reservoir, while ammonium and nitrate were two to four times higher in the ditch during the summer. These results suggest the reservoir serves an important function to process nutrients and sediments and emphasize the importance of a closed tailwater recovery system when trying to prevent nutrients and sediments from getting to the Gulf of Mexico.
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