Combining FAO-56 model and ground-based remote sensing to estimate water consumptions of wheat crops in a semi-arid region

Abstract

This study was performed to test three methods based on the FAO-56 “dual” crop coefficient approach to estimate actual evapotranspiration (AET) for winter wheat under different irrigation treatments in the semi-arid region of Tensift Al Haouz, Marrakech (center of Morocco). The three methods differ in the calculation of the basal crop coefficient ( K cb) and the fraction of soil surface covered by vegetation ( f c). The first approach strictly follows the FAO-56 procedure, with K cb given in the FAO-56 tables and f c calculated from K cb (No-Calibration method). The second method uses local K cb and f c values estimated from field measurements (Local-Calibration method) and the last approach uses a remotely-sensed vegetation index to estimate K cb and f c (NDVI-Calibration method). The analysis was performed on three fields using actual (AET) measured by Eddy Correlation systems. It was shown that the Local-Calibration approach gave best results. Accurate estimates of K cb and f c were necessary for FAO-56 “dual” crop coefficient application. The locally derived K cb for winter wheat taken at initial, mid-season, and maturity crop growth were 0.15, 0.90 and 0.23, respectively. The K cb value at the mid-season stage was found to be considerably less than that suggested by the FAO-56. Similarity between the seasonal pattern of normalized difference vegetation index (NDVI) and K cb showed potential for modelling NDVI into a K cb. The obtained relationships between K cb and NDVI, and between f c and NDVI could be easily incorporated within the FAO-56 “dual” crop coefficient model and, thereby, provide a means to apply remotely sensed observation for real-time wheat irrigation scheduling. The results obtained were very acceptable especially when the soil evaporation is negligible. Therefore, the K cb–NDVI relationship employed in the FAO-56 “dual” crop coefficient model holds great potential for estimating crop water requirements on an operational basis and consumption at a regional scale.