Location: Sustainable Water Management Research2019 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.
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.
The corn-soybean rotation, with starting corn, was established in an 80 ac field with furrow irrigation facilities in the CPSRU farm in 2017. In 2018, the experiment was rotated to soybean, and in 2019 rotated back to corn under conservation tillage management. The crop-field after harvest of soybean was rebedded (reshape the beds) with light tillage for easy drainage of fall and spring rain-water out of the field and make furrow irrigation possible. Poor water drainage from the field due to excessive rain and floods were noticed during all the three-years (2017, 2018, and 2019), making it difficult to access the crops by foot or motorized vehicle to collect data on crop physiological response to different water levels/irrigations. Whenever, plant available soil water in the cropped-field fell below 65% of total plant available water, irrigations were provided at 100 (full irrigations in which alternate furrows were irrigated), 50 (half irrigations in which, every fourth row was irrigated), and 0 (rainfed with no added irrigation) % of the irrigation demands in excess of the rainfall received. Eddy covariance (EC) measuring system redesigned to monitor both water (evapotranspiration, ET) and CO2 fluxes and land-surface energy balance were reestablished in the full, half, and rainfed irrigation fields planted to corn. Crop growth and development, and physiological responses of corn to irrigations are being collected. Methods for computing ET using both eddy covariance and residual energy balance approach was developed, and three articles based on this work were published and another one submitted to a journal. Based on the data collected in corn, soybean, and cotton in 2018, a talk entitled “contrasting water requirements of staple crops in the MS Delta region” was presented at the MS Water Resources Research Institute conference at Jackson, Mississippi, April 2019, and a paper based on this work was published in the journal Science of Total Environment. The Infrared thermometer sensors for measuring canopy temperatures (Tc), NDVI (normalized difference vegetation index), and PRI (photochemical reflectance indices) sensors were installed in the corn fields maintained under 100, 50, and 0% irrigation levels. The sensors were installed on height adjustable towers and constantly positioned at 1m above the crop canopies. The Tc, NDVI, and PRI data are being continuously monitored this crop season. Due to above-normal rainfall and consequent flood that was adequate for stress-free crop growth during the corn season in 2017-18, there were no significant water stress periods. This year there were extensive crop-stand and instrument loss due to flood events. Therefore, it was not possible to test water stress indices with the 2017-18 data. Data collected during 2019 is being analyzed for water stress periods in which waters stress indices can be calculated. New multispectral reflectance sensors were evaluated under greenhouse and field conditions to determine suitability for field monitoring. The multispectral sensors integrate with microcontroller-based, GPS-equipped monitoring systems to allow fixed-location and mobile, whole-field mapping of reflectance characteristics. Multispectral measurements have shown promise for agronomic applications, and inexpensive mapping systems will aid in expanding the use and acceptance of advanced instrumentation. The sensors have been evaluated under limited conditions, and continued testing will help determine appropriate conditions under which the sensors can be of value. Two EC systems installed in Stoneville and Arcola, Mississippi, were maintained for normal operation and have been collecting the year-3 data. However, one EC system in rice field in Arcola was hit by lighting in a big storm this summer. The major electronic circuits and sensors with that system were seriously damaged. It has been requested to repair that system. Another three EC and REB systems continued to measure the ET and REB with soybean and cotton crops for estimating water stress of crops under different irrigation levels. EC and Energy Balance ET data collected during 2016-18 were used to calibrate and improve crop growth simulations of the Agricultural System Model RZWQM2 and a paper prepared based on this was submitted to the Journal, ‘Agricultural Water Management’. The calibrated model was further integrated with climate-change scenarios for the MS Delta region, and we are investigating impacts of climate change and prescribe adaptation and mitigation measures. Cotton was planted in the experimental plots and field managed as describe in the experimental design. Runoff water monitoring systems were maintained and calibrated for the data collection from the 12 plots. The wireless data transmission devices with the runoff water monitoring systems were upgraded to meet the data transmission requirement by the wireless network. Runoff water samples were collected for water quality analysis. Soil moisture in each plot was continuously measured using soil water content sensors installed last year. Soil samples of the plots were collected for soil properties before cotton was planted. Data collected in the previous two years were analyzed. Due to the cold weather in the winter and late planting caused by wet weather, cover crop tillage radish did not grow well resulting in no significant biomass production in 2019 season. The 6001-13000-001-00D and 6001-13000-002-00D projects have been merged into 6066-13000-005-00D but no “research” has been initiated in the added projects due to vacant research positions. So, there is no progress report for objectives 3-7.
1. Variable rate irrigation (VRI) technology. Due to overuse of ground water from the Mississippi Alluvial Aquifer for irrigation, ongoing depletion of the Aquifer becomes a big threat to agriculture sustainability in the Lower Mississippi River Basin. It is necessary to use advanced irrigation technologies to save water in crop production. Soil properties and plant characteristics can vary considerably within a single field resulting in variability of water need for plant to reach its yield potential. ARS researchers in Stoneville, Mississippi, developed VRI technology to site-specifically apply irrigation water within a field to account for the temporal and spatial variability in soil and plant characteristics. VRI prescriptions were created based on soil electrical conductivity and irrigation was scheduled according to the sensor-measured soil moisture content. Desired amount of water was applied site-specifically according to the VRI prescriptions. The field tests showed that use of this VRI technology saved 25% irrigation water.
2. Open source electronic systems. Open source Arduino platforms, coupled with new and inexpensive sensing devices has enabled the development of low-cost tools for a variety of applications related to agricultural and environmental monitoring, and irrigation. ARS researchers in Stoneville, Mississippi, developed and deployed open-source electronic monitoring systems to monitor agronomic and meteorological variables in remote locations. Real-time monitoring of field conditions via the new cellular network was accomplished by accessing the internet-available data via smartphone apps and web browsers on computers and mobile devices. These inexpensive sensing devices could enable researchers and producers collecting field data with a low cost.
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