Toward automated irrigation management with integrated crop water stress index and spatial soil water balance
نویسندگان
چکیده
Abstract Decision support systems intended for precision irrigation aim at reducing applications while optimizing crop yield to achieve maximum water productivity (CWP). These incorporate on-site sensor data, remote sensing inputs, and advanced algorithms with spatial temporal characteristics compute precise needs. The availability of variable rate (VRI) enables a sub-field scale. combination an appropriate VRI system along decision would be ideal improved CWP. objective this study was compare evaluate two in terms seasonal applied irrigation, yield, This implemented the Spatial EvapoTranspiration Modeling Interface (SETMI) model Irrigation Scheduling Supervisory Control Data Acquisition (ISSCADA) management center pivot 58-ha maize-soybean field during 2020 2021 growing seasons. scheduling methods included: ISSCADA plant feedback, hybrid, common practice, SETMI. were levels 0, 50, 100, 150% full prescribed by respective method. from infrared thermometers (IRTs), soil sensors, weather stations, satellites used methods. Mean different among 2 years. feedback least majority cases. practice largest depth three crop-year maize rainfed found significantly lower than irrigated since dry year. No significant differences observed both CWP ranged between 2.72 3.15 kg m −3 maize, 1.03 1.13 soybean, 3.57 4.24 1.19 1.48 soybean. Deficit level (50%) had all cases study. SETMI reduce as compared maintaining yield. first implement newly developed integrated stress index (iCWSI) thresholds site-specific soybean Nebraska.
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ژورنال
عنوان ژورنال: Precision Agriculture
سال: 2023
ISSN: ['1385-2256', '1573-1618']
DOI: https://doi.org/10.1007/s11119-023-10038-4