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ARS Home » Plains Area » Bushland, Texas » Conservation and Production Research Laboratory » Soil and Water Management Research » Research » Publications at this Location » Publication #394192

Research Project: Dryland and Irrigated Crop Management Under Limited Water Availability and Drought

Location: Soil and Water Management Research

Title: Toward automated irrigation management with integrated crop water stress index and spatial soil water balance

Author
item BHATTI, SANDEEP - University Of Nebraska
item HEEREN, DEREK - University Of Nebraska
item Oshaughnessy, Susan
item NEALE, C M U - University Of Nebraska
item LARUE, JAKE - University Of Nebraska
item MELVIN, STEVE - University Of Nebraska
item WILKENING, ERIC - University Of Nebraska
item BAI, GENG - University Of Nebraska

Submitted to: Precision Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/25/2023
Publication Date: 7/3/2023
Citation: Bhatti, S., Heeren, D., O'Shaughnessy, S.A., Neale, C., Larue, J., Melvin, S., Wilkening, E., Bai, G. 2023. Toward automated irrigation management with integrated crop water stress index and spatial soil water balance. Precision Agriculture. 24(4). https://doi.org/10.1007/s11119-023-10038-4.
DOI: https://doi.org/10.1007/s11119-023-10038-4

Interpretive Summary: Limited groundwater resources for agriculture on the Great Plains require that farmers maximize crop water productivity by maintaining grain yield and reducing water inputs. In this study, scientists from ARS (Bushland, Texas), University of Nebraska Lincoln and Valmont Industries did side by side comparison of two precision irrigation methods to schedule irrigations for corn and soybean planted under a variable rate irrigation center pivot sprinkler in Nebraska. One irrigation scheduling method involved the Irrigation Scheduling Supervisory Control and Data Acquisition (ISSCADA) system developed and patented by ARS scientists in Bushland, Texas. This system uses ground based thermal sensors and soil water sensing feedback to recommend irrigation timing and amount. The second method, named the Spatial EvapoTranspiration Modeling Interface (SETMI), used satellite information to estimate spatially variable crop water use. Both precision irrigation scheduling methods were compared with the irrigation method commonly used by farmers in Nebraska. Irrigation amounts, grain yield and crop water productivity were similar between precision irrigation methods in both years and prescribed less water than the method commonly used by farmers.

Technical Abstract: Decision support systems intended for precision irrigation aim at reducing irrigation applications while optimizing crop yield to achieve maximum crop water productivity (CWP). These systems incorporate on-site sensor data, remote sensing inputs, and advanced algorithms with spatial and temporal characteristics to compute precise crop water needs. The availability of variable rate irrigation (VRI) systems enables irrigation applications at a sub-field scale. The combination of an appropriate VRI system along with a precise decision support system would be ideal for improved CWP. The objective of this study was to compare and evaluate two decision support systems in terms of seasonal irrigation, crop yield, and CWP. This study implemented the Spatial EvapoTranspiration Modeling Interface (SETMI) model and the Irrigation Scheduling Supervisory Control and Data Acquisition (ISSCADA) system for management of a center pivot irrigation system in a 58-ha maize-soybean field during the 2020 and 2021 growing seasons. The irrigation scheduling methods included: plant feedback ISSCADA, hybrid ISSCADA, common practice, and SETMI. These methods were applied at irrigation levels of 0, 50, 100, and 150%. Data from infrared thermometers (IRTs), soil water sensors, weather stations, and satellites were used in the irrigation methods. Mean seasonal irrigation prescribed was different among irrigation levels and methods for the two years. The plant feedback ISSCADA prescribed the least irrigation among the methods except in 2021 soybean. The common practice prescribed the largest seasonal irrigation depth among the methods for the majority of crop-year cases. The maize yield in rainfed was found to be significantly lower than the irrigated levels in 2020 since 2020 was a dry year. No significant differences were observed in crop yield among the different irrigation methods for both years. The CWP among the different irrigation methods ranged between 3.24 to 3.84 kg m-3 for 2020 maize, 1.1 to 1.32 kg m-3 for 2020 soybean, 3.81 to 4.42 kg m-3 for 2021 maize, and 1.32 to 1.38 kg m-3 for 2021 soybean. Deficit level (50%) had the largest CWP in all crop-year cases in this study. The ISSCADA and SETMI systems were found to reduce irrigation applications as compared to the common practice while maintaining crop yield. This study was the first to implement the newly developed integrated crop water stress index (iCWSI) thresholds and the ISSCADA system for site-specific irrigation of maize and soybean in Nebraska.