An irrigation optimization tool developed by Stanford University's Weiyu Li and Daniel Tartakovsky can estimate water loss from soil caused by evapotranspiration 100 times faster than state-of-the-art methods while preserving accuracy.
The tool can significantly cut time from formulating strategic, efficient irrigation schedules that optimally position watering and sensing equipment farm-wide; it also can process data quickly enough to adjust irrigation in near-real time amid changing weather conditions.
The researchers combined enhanced Kalman filter and maximum likelihood estimation algorithms, and applied the approach to drip irrigation, according to Li.
They calculated the evapotranspiration rate of an approximately 5-foot x 33-foot plot of land in roughly 10 minutes, which would have taken nearly 17 hours with enhanced Kalman filter alone.
From Stanford News Service
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