Improving WISE Crop Evapotranspiration Estimates Using Crop Coefficients Derived from Remote-Sensing Algorithms

Abstract

Sustainable irrigation water management is achievable only when irrigation scheduling is optimized to conserve water and soil resources in an agricultural setting. This study evaluated the use of remote sensing–based algorithms for determining actual crop evapotranspiration (ETa) mapping to update crop coefficients (kc) of an irrigation scheduler software (WISE). The scheduler’s kc values are based on the FAO-56 approach for crop evapotranspiration (ETc) determination. A surface-irrigated (furrow) maize (Zea mays L.) field in Fort Collins, Colorado, was used from July to September 2020 and 2021. An eddy covariance energy balance system (ECSEBS) installed on a tower at 3.5 m above the ground surface was used to determine hourly and daily maize ETa data. These EC-based ETa data were used to evaluate the performance of three approaches for maize ETa estimation and the FAO-56–based ETc predictions from WISE. Microsatellite PlanetScope multispectral imagery, at a 3-m-pixel spatial resolution, provided surface reflectance in the red and near-infrared bands for input in the remote sensing of ETa algorithms. On-site micrometeorological data were measured at the exact location of the ECSEBS tower. Optimization of kc values was done using an ordinary least-squares regression approach. The optimized kc values were calculated for the maize midseason growth stage. Results indicated that using remote sensing of ETa algorithms has excellent potential to improve irrigation scheduling by integrating optimized crop coefficients. WISE overestimated daily maize ETc predictions by as much as 26%. When remote sensing-based optimized kc values were introduced, the overestimation of daily maize ETc was reduced significantly, by 18% to 75%, depending on the remote sensing of the ETa algorithm used. The research findings support the combined use of remote sensing data and the FAO-56 approach for irrigation scheduling to improve agricultural water management at the farm level.