Crop coefficient (K_c)-based estimation of crop water consumption is one of the most commonly used methods for irrigation management. In this study, cotton evapotranspiration was measured in the field during two seasons using the eddy covariance method. K_c was estimated as the ratio between reference evapotranspiration and the measured cotton evapotranspiration. In addition, a time series of Sentinel-2 imagery was processed to produce 21 vegetation indices (VIs) based on the sensor's unique spectral bands. The results suggest that most VIs that are based on Sentinel-2 bands are suitable predictors for cotton K_c, and that those based on the red and red-edge spectral bands are the best ones. Consequently, this work sets the scene for near-real-time irrigation decision support systems. © Wageningen Academic Publishers 2019