Abstract

Research-based information regarding the accuracy and reliability of smart irrigation controllers for autonomous landscape irrigation water conservation is limited in central California. A two-year irrigation research trial (2018–2019) was conducted in Parlier, California, to study the response of hybrid bermudagrass and tall fescue to varying irrigation scenarios (irrigation levels and irrigation frequency) autonomously applied using a Weathermatic ET-based smart controller. The response of turfgrass species to the irrigation treatments was visually assessed and rated. In addition, turfgrass water response functions (TWRFs) were developed to estimate the impact of irrigation scenarios on the turfgrass species based on long-term mean reference evapotranspiration (ETo) data. The Weathermatic controller overestimated ETo between 5% and 7% in 2018 and between 5% and 8% in 2019 compared with California Irrigation Management Information System values. The controller closely followed programmed watering-days restrictions across treatments in 2018 and 2019 and adjusted the watering-days based on ETo demand when no restriction was applied. The low half distribution uniformity and precipitation rate of the irrigation system were 0.78 and 28 mm h−1, respectively. The catch-cans method substantially underestimated the precipitation rate of the irrigation system and caused over-irrigation by the smart controller. No water-saving and turfgrass quality improvement was observed owing to restricting irrigation frequency (watering days). For the hybrid bermudagrass, the visual rating (VR) for 101% ETo treatment stayed above the minimum acceptable value of six during the trial. For tall fescue, the 108% ETo level with 3 d wk−1 frequency kept the VR values in the acceptable range in 2018 except for a short period in mid-trial. The TWRF provided a good fit to experimental data with r values of 0.79 and 0.75 for tall fescue and hybrid bermudagrass, respectively. The estimated VR values by TWRF suggested 70–80% ETo as the minimum irrigation application to maintain the acceptable hybrid bermudagrass quality in central California during the high water demand months (i.e., May to August) based on long-term mean ETo data. The TWRF estimations suggest that 100% ETo would be sufficient to maintain the tall fescue quality for only 55 days. This might be an overestimation impacted by the relatively small tall fescue VR data in 2019 owing to minimal fertilizer applications and should be further investigated in the future.

Highlights

  • The state of California, and in general the U.S west, has some of the largest cities across the nation, making urban water demand a vital component of any integrated water resources management plan

  • In a recently published study [7], we introduced the turfgrass water response function (TWRF) as an empirical statistical model to estimate the response of turfgrass species to varying irrigation scenarios and ETo demand

  • Our results suggest that applying typically recommended values of 60% ETo for hybrid bermudagrass and 80% ETo for tall fescue is insufficient to maintain the acceptable quality over high ETo demand months in Central California

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Summary

Introduction

The state of California, and in general the U.S west, has some of the largest cities across the nation, making urban water demand a vital component of any integrated water resources management plan. In the future, competition for water and land resources among urban, environmental, and agricultural uses will intensify as a result of increased population, coupled with changes in land use and climate [2]. Irrigation demand is a significant component of total water use in the urban sector in California [4]; improving irrigation water use efficiency is a crucial water conservation strategy. Considerable water savings have been reported as a result of implementing emerging technologies for landscape irrigation management [5,6,7]. Soil moisture sensor-based and evapotranspiration (ET)-based smart irrigation controllers can help increase irrigation water use efficiency by maintaining the root zone soil moisture status within a programmed desired range and scheduling irrigation based on crop coefficient and reference ET (ETo) data, respectively

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