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Jeff B. Million and T.H. Yeager

’s traditional irrigation practice. Using results from the trial, we also evaluated the benefit of adopting a weather-based irrigation management program that adjusts run times daily compared with a periodically adjusted irrigation management practice. Materials

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Jeff B. Million and Thomas H. Yeager

intermittent adjustments to irrigation, there is potential to further improve irrigation efficiency by making real-time adjustments to irrigation based on real-time weather collected on-site. We developed a web-based irrigation scheduling program called CIRRIG

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Janet S. Hartin, David W. Fujino, Lorence R. Oki, S. Karrie Reid, Charles A. Ingels, and Darren Haver

. More work on the use of smart irrigation controllers based on ET o and soil moisture depletion under dry California conditions is also important. Although several studies measuring the potential water savings of smart controller technology have shown

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Dennis R. Pittenger, David A. Shaw, and William E. Richie

We conducted an evaluation of three commercial weather-sensing irrigation controllers to determine the climatic data they use, how easy they are to set up and operate, and how closely their irrigation regimes match landscape irrigation needs established by previous field research. The devices virtually controlled an existing reference irrigation system and used its system performance data as required in their initial setup. Reference standard treatments for cool-season turfgrass, trees/shrubs and annual flowers were calculated using onsite, real-time reference evapotranspiration (ETo) data and plant factors developed primarily from previous research. The reference irrigation system applied the correct amount of water to an actual tall fescue turfgrass planting whose water needs served as the reference standard treatment comparison for the cool-season turfgrass treatment. Virtual applied water was recorded for other plant materials and it was compared to the corresponding calculated reference standard amount. Results show each controller adjusted its irrigation schedules through the year roughly in concert with weather and ETo changes, but the magnitudes of adjustments were not consistently in proportion to changes in ETo. No product produced highly accurate irrigation schedules consistently for every landscape setting when compared to research-based reference comparison treatments. Greater complexity and technicality of required setup information did not always result in more accurate, water-conserving irrigation schedules. Use of a weather-sensing controller does not assure landscape water conservation or acceptable landscape plant performance, and it does not eliminate human interaction in landscape irrigation management.

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Shane R. Evans, Kelly Kopp, Paul G. Johnson, Bryan G. Hopkins, Xin Dai, and Candace Schaible

models ( U.S. Environmental Protection Agency, 2018 ). WaterSense-labeled smart irrigation controllers adjust irrigation scheduling based on climate data and/or feedback from a soil moisture sensor, and evaluations of smart irrigation controller rebate

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Maria C. Morera, Paul F. Monaghan, Michael D. Dukes, Ondine Wells, and Stacia L. Davis

, G.L. 2008 Sensor-based automation of irrigation on bermudagrass, during wet weather conditions J. Irrig. Drain. Eng. 134 120 128 10.1061/(ASCE)0733-9437(2008)134:2(120) Davis, S.L. 2014 Effectiveness of smart controllers for water conservation in

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Jeff B. Million and Thomas H. Yeager

, C.D. Albano, J.P. 2011 CCROP - Simulation model for container-grown nursery plant production Scientia Hort. 130 874 886 Million, J.B. Yeager, T.H. 2015 CIRRIG: Weather-based irrigation management program for container nurseries HortTechnology 25 528

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Alberto Pardossi and Luca Incrocci

ensure that all irrigation water is used by the crop. A schedule to maximize net economic return, which depends also on water price, is less common. Conventional methods for IS rely on determination of soil water balance (weather-based method) or on the

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Matthew Chappell, Sue K. Dove, Marc W. van Iersel, Paul A. Thomas, and John Ruter

[Moisture Clik IL200-MC; Dynamax, Houston, TX ( Fig. 1 )] were deployed to compare MNI irrigation practices to soil-moisture-based irrigation control. Moisture Clik irrigation controllers were used initially because Decagon Devices (Pullman, WA) had yet to

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Pascal Nzokou, Nicholas J. Gooch, and Bert M. Cregg

tensiometers placed in each irrigation treatment, (4) an instrument box containing data logging equipment, and (5) a relay controller able to activate the solenoids. The principle of the system was based on a simple feedback loop with the soil matric potential