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Landscape irrigation scheduling efficiency and adequacy by various control technologies

Author

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  • McCready, M.S.
  • Dukes, M.D.

Abstract

Automated residential irrigation systems tend to result in higher water use than non-automated systems. Increasing the scheduling efficiency of an automated irrigation system provides the opportunity to conserve water resources while maintaining good landscape quality. Control technologies available for reducing over-irrigation include evapotranspiration (ET) based controllers, soil moisture sensor (SMS) controllers, and rain sensors (RS). The purpose of this research was to evaluate the capability of these control technologies to schedule irrigation compared to a soil water balance model based on the Irrigation Association (IA) Smart Water Application Technologies (SWAT) testing protocol. Irrigation adequacy and scheduling efficiency were calculated in 30-day running totals to determine the amount of over- or under-irrigation for each control technology based on the IA SWAT testing protocol. A time-based treatment with irrigation 2 days/week and no rain sensor (NRS) was established as a comparison. In general, the irrigation adequacy ratings (measure of under-irrigation) for the treatments were higher during the fall months of testing than the spring months due to lower ET resulting in lower irrigation demand. Scheduling efficiency values (measure of over-irrigation) decreased for all treatments when rainfall increased. During the rainy period of this testing, total rainfall was almost double reference evapotranspiration (ETo) while in the remaining three testing periods the opposite was true. The 30-day irrigation adequacy values, considering all treatments, varied during the testing periods by 0-68 percentile points. Looking at only one 30-day testing period, as is done in the IA SWAT testing protocol, will not fully capture the performance of an irrigation controller. Scheduling efficiency alone was not a good indicator of controller performance. The amount of water applied and the timing of application were both important to maintaining acceptable turfgrass quality and receiving good irrigation adequacy and scheduling efficiency scores.

Suggested Citation

  • McCready, M.S. & Dukes, M.D., 2011. "Landscape irrigation scheduling efficiency and adequacy by various control technologies," Agricultural Water Management, Elsevier, vol. 98(4), pages 697-704, February.
    • Handle: RePEc:eee:agiwat:v:98:y:2011:i:4:p:697-704
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    References listed on IDEAS

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    1. McCready, M.S. & Dukes, M.D. & Miller, G.L., 2009. "Water conservation potential of smart irrigation controllers on St. Augustinegrass," Agricultural Water Management, Elsevier, vol. 96(11), pages 1623-1632, November.
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    Cited by:

    1. Fan, Yubing & McCann, Laura E., 2015. "Households' Adoption of Drought Tolerant Plants: An Adaptation to Climate Change?," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205544, Agricultural and Applied Economics Association.
    2. Wanjiru, Evan M. & Xia, Xiaohua, 2015. "Energy-water optimization model incorporating rooftop water harvesting for lawn irrigation," Applied Energy, Elsevier, vol. 160(C), pages 521-531.
    3. Snyder, R.L. & Pedras, C. & Montazar, A. & Henry, J.M. & Ackley, D., 2015. "Advances in ET-based landscape irrigation management," Agricultural Water Management, Elsevier, vol. 147(C), pages 187-197.
    4. Marjan Aziz & Madeeha Khan & Naveeda Anjum & Muhammad Sultan & Redmond R. Shamshiri & Sobhy M. Ibrahim & Siva K. Balasundram & Muhammad Aleem, 2022. "Scientific Irrigation Scheduling for Sustainable Production in Olive Groves," Agriculture, MDPI, vol. 12(4), pages 1-14, April.
    5. Barton, Louise & Flottmann, Samuel J. & Stefanovia, Katia T. & Colmer, Timothy D., 2020. "Approaches to scheduling water allocations to kikuyugrass grown on a water repellent soil in a drying-climate," Agricultural Water Management, Elsevier, vol. 230(C).
    6. Khachatryan, Hayk & Suh, Dong Hee & Xu, Wan & Useche, Pilar & Dukes, Michael D., 2019. "Towards sustainable water management: Preferences and willingness to pay for smart landscape irrigation technologies," Land Use Policy, Elsevier, vol. 85(C), pages 33-41.
    7. Sara Komenda & Martha C. Monroe, 2023. "Clues in the Data: The Role of Education in Adopting Technology That Enhances Sustainable Lifestyle Choices," Sustainability, MDPI, vol. 15(11), pages 1-15, May.

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