Importance of ET Controller Program Settings on Water Conservation Potential

Abstract

In unincorporated Orange County, Florida, 57% to 62% of single-family residential homes were found to regularly over-irrigate, resulting in the need to find better ways to schedule automatic irrigation. The objective of this research was to evaluate the effects of programming for identical virtual landscapes to further explore the water savings potential of evapotranspiration (ET) controllers. As a virtual test, three Rain Bird ET controllers were studied: the ESP-SMT controller with two firmware options (original and an updated), and the ESP-SMTe, a replacement product for the ESP-SMT. Irrigation was scheduled for a virtual central Florida landscape by altering possible program settings of plant type, microclimate, soil type, and density that relate directly to parameters used in the soil water balance. The ESP-SMTe consistently applied similar amounts of irrigation to the ESP-SMT with updated firmware, indicating that controller updates were minor between the two models. The settings were optimized for Florida landscapes by selecting a heavier soil type, increasing the shade, and selecting a medium stand for a custom plant type, resulting in reductions in irrigation application. The ESP-SMTe and ESP-SMT with updated firmware were different from the ESP-SMT with original firmware, where newer models applied more water despite identical settings, averaging 12 to 21 mm more per month than the original firmware. Additionally, all of the controllers were unable to fully account for rainfall throughout the test resulting in a minimum of 51% in over-irrigation compared to the gross irrigation requirement (GIR). Increasing the accuracy of rainfall accounting would be extremely beneficial to overall water conservation and efficiency. In a separate, independent ET controller study, there was a large discrepancy in irrigation application among multiple brands programmed to irrigate the same virtual landscape. This further shows the importance of understanding the algorithms behind the program settings.