Evaluation of irrigation scheduling approaches within sand-capped turfgrass systems

Authors: Hejl, Reagan; WHERLEY, BENJAMIN - Texas A&M University; MCINNES, KEVIN - Texas A&M University; STRAW, CHASE - Texas A&M University; FONTANIER, CHARLES - Oklahoma State University

Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/7/2022
Publication Date: 5/14/2022
Citation: Hejl, R.W., Wherley, B.G., McInnes, K.J., Straw, C.M., Fontanier, C.H. 2022. Evaluation of irrigation scheduling approaches within sand-capped turfgrass systems. Agronomy Journal. 114(3):1694-1704. https://doi.org/10.1002/agj2.21059.
DOI: https://doi.org/10.1002/agj2.21059

Interpretive Summary: The process of adding a layer of sand over a native soil system is known as sand-capping. This practice is being adopted on turfgrass systems, such as golf course fairways and sports fields, with the goal of improving drainage and reducing the harsh effects of irrigating with poor-quality water. Considering current strains on fresh water supplies, development of efficient irrigation management practices for sand-capped systems is essential. A 2-year field study was conducted in College Station, Texas to evaluate the effect of different irrigation scheduling methods on turfgrass quality, soil characteristics, and water use in sand-capped systems. Four irrigation scheduling approaches were tested: 1) using wireless soil moisture sensors, 2) based on evapotranspiration estimates, with the reference evapotranspiration measured on-site; 3) based on evapotranspiration estimates, but using NOAA-forecasted reference evapotranspiration, and 4) irrigating at the onset of wilt (visual wilt-based). All irrigation scheduling approaches produced acceptable turfgrass quality during both growing seasons. The on-site measured evapotranspiration approach reduced water consumption in comparison with wireless soil moisture sensor-based irrigation, without negatively impacting turfgrass quality or soil salinity levels. These results suggest that water use can be further reduced with soil moisture sensor-based irrigation by refining the soil water content value used to trigger an irrigation. Under the conditions of the experiment, the forecasted reference evapotranspiration matched well with the on-site measured values throughout the season. Thus, in the absence of local measurements, forecasts can be used reliably for irrigation scheduling. The findings are of interest to managers of sand-capped turfgrass systems, as they provide guidance for implementing data-driven irrigation scheduling.

Technical Abstract: In an effort to improve performance of turfgrass irrigated with poor quality water, the practice of sand-capping is increasing. Given current strains on water supplies, evaluation of various methods of irrigation scheduling approaches for these systems is needed. The objectives of this 2-year field study were to evaluate turfgrass performance, temporal and spatial soil moisture and salinity dynamics, and comparative water use among four irrigation scheduling approaches including: 1) wireless soil moisture sensor (SMS), 2) on-site reference evapotranspiration (ETo), 3) National Oceanic and Atmospheric Administration (NOAA) Forecasted Reference Evapotranspiration (FRET) and 4) visual wilt-based. The turfgrass used in this study was 'Latitude' 36 [Cynodon dactylon (L.) Pers. x C. transvaalensis Burtt-Davy] planted atop a 17.8 cm medium-coarse textured sand-cap. Results of the study demonstrated all irrigation scheduling approaches produced similar levels of acceptable turfgrass quality and percent green cover with no apparent differences in root development. Forecasted Reference Evapotranspiration was found to be a good predictor of on-site ETo (R2= 0.97) when comparing daily values across two growing seasons. Under wilt-based irrigation, the volumetric water content (7.6 cm sand-cap depth) at which wilt occurred was highest mid-summer (4.1 – 4.7%), but declined during early and late summer months (1.8 – 2.2%), suggesting different thresholds may be needed throughout the season when using SMS-based irrigation scheduling. Finally, seasonal water use was 23% lower for the on-site ETo based approach compared to SMS-based scheduling, although this did not result in elevated electrical conductivity within the sand-cap. The results provide important information to guide adoption of data-driven approaches to irrigation scheduling.