Full TGIF Record # 310859
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Web URL(s):https://archive.lib.msu.edu/tic/ressum/2019/2019.pdf#page=255
    Last checked: 04/23/2020
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Publication Type:
i
Report
Author(s):Haghverdi, Amir
Author Affiliation:Department of Environmental Sciences, University of California Riverside
Title:Enhancing site-specific turf irrigation management and developing turf deficit irrigation strategies using soil moisture sensors, smart ET-based irrigation controllers, and remote sensing
Section:Integrated turfgrass management
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Ecophysiology: Water
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Source:Turfgrass and Environmental Research Program: 2019 Research Summaries. 2019, p. 247-260.
# of Pages:14
Publishing Information:[New York, New York]: The United States Golf Association Green Section
Language:English
References:0
See Also:Other Reports from this USGA research project: 2018-06-656
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USGA Summary Points:An irrigation research trial was conducted in 2018 and 2019 at UCR Agricultural Experiment Station in inland Southern California to study the response of tall fescue (Festuca arundinacea), and bermudagrass (Cynodon dactylon) turfgrass species to multiple irrigation treatments. The irrigation treatments were autonomously regulated by Weathermatic smart irrigation controller, which showed a promising agreement with ET data collected from a nearby CIMIS data. The catch can test estimation of the precipitation rate was substantially lower than the precipitation rate measured with a precise flow meter. This finding suggests that in irrigation research projects the precipitation rate should not be scheduled based on a catch can test. Our results (three years; 2017-2019) indicate an irrigation application of approximately 110% ETref and 80% ETref for tall fescue and bermudagrass species as a minimum to maintain an accepted turf quality over summer months in inland Southern California. Assuming the irrigation efficiency of 80% for the sprinkler system, the estimated minimum plant factor for the tall fescue and bermudagrass species, therefore, are 0.88 and 0.64 for the study area.
ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Haghverdi, A. 2019. Enhancing site-specific turf irrigation management and developing turf deficit irrigation strategies using soil moisture sensors, smart ET-based irrigation controllers, and remote sensing. USGA Turfgrass Environ. Res. Summ. p. 247-260.
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https://archive.lib.msu.edu/tic/ressum/2019/2019.pdf#page=255
    Last checked: 04/23/2020
    Requires: PDF Reader
    Notes: Item is within a single large file
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