A variety of technologies for reducing residential irrigation water use are available to homeowners. These "Smart Irrigation" technologies include evapotranspiration (ET)-based controllers and soil moisture sensor (SMS) controllers. The purpose of this research was to evaluate the effectiveness of these technologies, along with rain sensors, based on irrigation applied and turfgrass quality measurements on St. Augustinegrass (Stenotaphrum secundatum (Walter) Kuntze). Testing was performed on two types of SMS controllers (LawnLogic LL1004 and Acclima Digital TDT RS500) at three soil moisture threshold settings. Mini-Clik rain sensors (RS) comprised six treatments at two rainfall thresholds (3mm and 6mm) and three different irrigation frequencies (1, 2, and 7d/wk). Two ET controllers were also tested, the Toro Intelli-Sense controller and the Rain Bird ET Manager. A time-based treatment with 2 days of irrigation per week without any type of sensor (WOS) to bypass irrigation was established as a comparison. All irrigation controller programming represented settings that might be used in residential/commercial landscapes. Even though three of the four testing periods were relatively dry, all of the technologies tested managed to reduce water application compared to the WOS treatment, with most treatments also producing acceptable turf quality. Reductions in irrigation applied were as follows: 7-30% for RS-based treatments, 0-74% for SMS-based treatments, and 25-62% for ET-based treatments. The SMS treatments at low threshold settings resulted in high water savings, but reduced turf quality to unacceptable levels. The medium threshold setting (approximately field capacity) SMS-based treatment produced good turfgrass quality while reducing irrigation water use compared to WOS by 11-53%. ET controllers with comparable settings and good turf quality had -20% to 59% savings. Reducing the irrigation schedule (treatment DWRS) by 40% and using a rain sensor produced water savings between 36% and 53% similar to smart controllers. Proper installation and programming of each of the technologies was essential element to balancing water conservation and acceptable turf quality. Water savings with the SMS controllers could have been increased with a reduced time-based irrigation schedule. Efficiency settings of 100% (DWRS) and 95% (TORO) did not reduce turf quality below acceptable limits and resulted in substantial irrigation savings, indicating that efficiency values need not be low in well designed and maintained irrigation systems. For most conditions in Florida, the DWRS schedule (60% of schedule used for SMS treatments) can be used with either rain sensors or soil moisture sensors in bypass control mode as long as the irrigation system has good coverage and is in good repair.
[1]
I. A. Walter,et al.
The ASCE standardized reference evapotranspiration equation
,
2005
.
[2]
Terry A. Howell,et al.
Encyclopedia of water science.
,
2003
.
[3]
Michael D. Dukes,et al.
Sensor-Based Automation of Irrigation on Bermudagrass during Dry Weather Conditions
,
2008
.
[4]
H. Vereecken,et al.
Soil-Water-Solute-Process Characterization
,
2006
.
[5]
M. Dukes,et al.
Evaluation and Demonstration of Evapotranspiration-Based Irrigation Controllers
,
2007
.
[6]
Kati W. Migliaccio,et al.
Plant response to evapotranspiration and soil water sensor irrigation scheduling methods for papaya production in south Florida
,
2010
.
[7]
Michael D. Dukes.
Residential Irrigation Water Use and Control
,
2007
.
[8]
Melissa B. Haley,et al.
Residential Irrigation Water Use in Central Florida
,
2007
.
[9]
William B. DeOreo,et al.
SOIL MOISTURE SENSORS FOR URBAN LANDSCAPE IRRIGATION: EFFECTIVENESS AND RELIABILITY 1
,
2001
.
[10]
Michael D. Dukes,et al.
Bahiagrass crop coefficients from eddy correlation measurements in central Florida
,
2009,
Irrigation Science.
[11]
Michael D. Dukes,et al.
Evaluation of Sensor Based Residential Irrigation Water Application
,
2007
.
[12]
Michael D. Dukes,et al.
Precision of soil moisture sensor irrigation controllers under field conditions
,
2010
.
[13]
Michael D. Dukes,et al.
Expanding Disk Rain Sensor Performance and Potential Irrigation Water Savings
,
2008
.
[14]
D. A. Devitt,et al.
Residential Water Savings Associated with Satellite-Based ET Irrigation Controllers
,
2008
.
[15]
David D. Bosch,et al.
Field Methods for Monitoring Soil Water Status
,
2005
.
[16]
G. Gee,et al.
Particle-size Analysis
,
2018,
SSSA Book Series.
[17]
L. S. Pereira,et al.
Crop evapotranspiration : guidelines for computing crop water requirements
,
1998
.
[18]
Dani Or,et al.
Nonlinear Parameter Estimation Using Spreadsheet Software
,
1998
.