Comparing four irrigation scheduling methods on maize growth, yield, and water productivity

Efficient irrigation scheduling is critical for optimizing water use and sustaining crop productivity, especially under water-limited conditions. This three-year field study (2022–2024) at USDA-ARS Limited Irrigation Research Farm, Greeley Colorado evaluated the performance of four irrigation scheduling methods: a standardized crop-coefficient method (FAO56); a model‑ and remote sensing-assimilated method (RZRS); and two soil-water-balance methods (SWB1, which used measured soil water depletion to trigger irrigation, and SWB2, which used a regional Kcb curve and daily water balance calculations). Each method was tested under full (F) and/or deficit (D, intentional application of less than 100% of crop water demand) irrigation regimes in a maize cropping system. Despite potential irrigation events occurring on fixed days of each week (Tuesday and Friday), treatments differed in both total water applied and irrigation frequency. Under full irrigation, the irrigation method had no significant effect on either grain yield or water productivity (WP). Under deficit irrigation, RZRS-D consistently achieved higher yield and WP than the soil-water-based irrigation scheduling methods (SWB1-D and SWB2-D). These findings highlight the benefits of an adaptive, RZWQM2 model-based irrigation scheduling method for high-frequency application to maximize yield and improve crop water productivity under limited‑water conditions.