Evaluation of irrigation scheduling approaches within sand‐capped turfgrass systems

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‐yr 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 (a) wireless soil moisture sensor (SMS), (b) on‐site reference evapotranspiration (ETo), (c) National Oceanic and Atmospheric Administration forecasted reference evapotranspiration, and (d) visual‐wilt‐based treatment. The turfgrass used was ‘Latitude 36’ hybrid bermudagrass [Cynodon dactylon (L.) Pers. ×C. transvaalensis Burtt‐Davy] planted atop a 17.8‐cm medium‐coarse textured sand cap. Results demonstrated that all approaches produced similar levels of acceptable turfgrass quality and percentage green cover with no apparent differences in root development. Forecasted reference evapotranspiration was found to be a good predictor of on‐site ETo (R2 = .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 scheduling. Finally, seasonal water use was 23% lower for the on‐site ETo–based approach compared with 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. Core Ideas All scheduling approaches produced acceptable turfgrass quality during both growing seasons. Forecasted reference ETo was a reliable indicator of seasonal turfgrass water needs. On‐site ETo irrigation scheduling reduced water use compared with soil moisture sensor‐based approaches.