Toward automated irrigation management with integrated crop water stress index and spatial soil water balance
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Published:2023-07-03
Issue:6
Volume:24
Page:2223-2247
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ISSN:1385-2256
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Container-title:Precision Agriculture
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language:en
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Short-container-title:Precision Agric
Author:
Bhatti Sandeep, Heeren Derek M.ORCID, O’Shaughnessy Susan A., Neale Christopher M. U., LaRue Jacob, Melvin Steve, Wilkening Eric, Bai Geng
Abstract
AbstractDecision 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 applied 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: ISSCADA plant feedback, ISSCADA hybrid, common practice, and SETMI. These methods were applied at irrigation levels of 0, 50, 100, and 150% of the full irrigation prescribed by the respective irrigation scheduling method. 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 the irrigation levels and methods for the 2 years. The ISSCADA plant feedback prescribed the least irrigation among the methods for majority of the cases. The common practice prescribed the largest seasonal irrigation depth among the methods for three 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 2.72 and 3.15 kg m−3 for 2020 maize, 1.03 and 1.13 kg m−3 for 2020 soybean, 3.57 and 4.24 kg m−3 for 2021 maize, and 1.19 and 1.48 kg m−3 for 2021 soybean. Deficit level (50%) had the largest irrigation water productivity 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.
Funder
Irrigation Innovation Consortium Valmont Industries Water for Food Daugherty Global Institute
Publisher
Springer Science and Business Media LLC
Subject
General Agricultural and Biological Sciences
Reference42 articles.
1. Allen, R. G., Pereira, L. S., Raes, D., Smith, M., (1998). Crop evapotranspiration: Guidelines for computing crop water requirements, Irrigation and drainage paper 56, Food and Agriculture Organization of the United Nations. 2. Andrade, M. A., Shaughnessy, S. A. O., & Evett, S. R. (2020). ARSPIVOT, a sensor-based decision support software for variable-rate irrigation center pivot sytems: Part A. Development. Transactions of the ASABE, 63, 1521–1533. https://doi.org/10.13031/trans.13907 3. Barker, J. B., Bhatti, S., Heeren, D. M., Neale, C. M. U., & Rudnick, D. R. (2019). Variable rate irrigation of maize and soybean in west-central nebraska under full and deficit irrigation. Frontiers in Big Data, 2, 1–15. https://doi.org/10.3389/fdata.2019.00034 4. Barker, J. B., Heeren, D. M., Neale, C. M. U., & Rudnick, D. R. (2018). Evaluation of variable rate irrigation using a remote-sensing-based model. Agricultural Water Management, 203, 63–74. https://doi.org/10.1016/j.agwat.2018.02.022 5. Bhatti, S., Heeren, D. M., Barker, J. B., Neale, C. M. U., Woldt, W. E., Maguire, M. S., & Rudnick, D. R. (2020). Site-specific irrigation management in a sub-humid climate using a spatial evapotranspiration model with satellite and airborne imagery. Agricultural Water Management, 230, 105950. https://doi.org/10.1016/j.agwat.2019.105950
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