Water Conservation Potential of Smart Irrigation Technologies in the Catawba-Wateree River Basin
Publication: Journal of Irrigation and Drainage Engineering
Volume 143, Issue 2
Abstract
A 3-year study was conducted in the Catawba-Wateree River Basin during the spring and summer months of 2009–2011 to evaluate the water savings potential of three smart irrigation controllers compared with standard timer-based irrigation controllers. Thirty-six residential sites, 12 on each of three Duke Energy lakes (Lake Norman, Lake Hickory, and Lake Wylie), were selected for the study. Each site had an automated, underground irrigation system that directly drew water from the Duke Energy lake that the property bordered. None of the systems had previously been metered and there was no charge to homeowners for withdrawing water from the bordering lake. All sites were instrumented with water meters in 2009 to monitor irrigation water withdrawals, and irrigation system audits were performed before installation of smart technologies. After collecting baseline water-use data in 2009, existing controllers were replaced with one of three smart controllers at 27 of the study sites in 2010, and irrigation was monitored through the end of the 2011 irrigation season. Irrigation treatments included a standard irrigation controller with an add-on soil moisture sensor system (SMS), an evapotranspiration (ET) based controller that received daily reference evapotranspiration estimates from a third-party provider (ET1), an evapotranspiration-based controller with an on-site weather sensor (ET2), and a comparison group that used the existing irrigation controller with no intervention (COMP). Weekly water withdrawals were monitored with on-site data loggers, and turf quality was visually rated and characterized with a normalized difference vegetation index (NDVI) meter. The SMS treatment applied the most irrigation per week (mean of ), compared with for the ET1 treatment, and the COMP and ET2 treatments that applied 20.9 and , respectively. Although applying the most irrigation, the SMS treatment had the greatest effect on water-use behavior for sites receiving technologies, reducing irrigation by compared with the baseline year in which the SMS group applied the most water. There was no evidence of a change in water-use behavior in the COMP treatment, but collectively the smart treatments reduced irrigation from 60% more than the gross irrigation requirement (GIR) in 2009 to only 10% more than GIR in 2010 and 2011, without adversely affecting the turf quality. Visual turf quality ratings in the COMP treatment were slightly less than the minimally acceptable level, which may have resulted from underirrigation during high water demand periods. Several challenges to retrofitting existing systems and issues with smart controllers were observed, including poorly designed and maintained existing irrigation systems, incompatibility between existing controllers and SMS sensor modules, failure of all nine soil-moisture sensors, communication failures in ET-based controllers, and manual overrides of smart technologies by study participants. This study emphasizes the importance of proper installation, programming, and maintenance of smart technologies on suitable irrigation systems if they are to function correctly. To maximize water savings, smart irrigation retrofits should be targeted toward systems that historically overirrigate.
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Acknowledgments
The authors thank Phil Fragapane of Duke Energy for coordinating communication and efforts among Duke Energy, North Carolina State University, and the study cooperators. Gratitude is expressed to each of the study participants, to Duke Energy, and numerous municipal and county agencies in the Catawba River Basin that provided GIS information used in the study, and to Duke Energy and the Catawba-Wateree Water Management Group for providing funding toward this project.
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Published In
Journal of Irrigation and Drainage Engineering
Volume 143 • Issue 2 • February 2017
Copyright
©2016 American Society of Civil Engineers.
History
Received: Jan 7, 2016
Accepted: Aug 22, 2016
Published online: Oct 10, 2016
Published in print: Feb 1, 2017
Discussion open until: Mar 10, 2017
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