A remote sensing approach to estimate variable crop coefficient and evapotranspiration for improved water productivity in the Ethiopian highlands

Abstract

Proper and reasonable estimation of actual evapotranspiration is critical for the design, operation, and management of irrigation systems. However, the density of climatic stations is low in many parts of Ethiopia to estimate spatially reasonable reference evapotranspiration (ETo), and the lack of spatial variability of crop coefficient (Kc) is clear barrier to the proper management of irrigation water. Therefore, the main objective of this study was to estimate reasonable crop evapotranspiration (ETc) by deriving spatially and temporally varying crop coefficients using remote sensing products in 10 wheat plots at the Koga irrigation scheme. The moderate-resolution imaging spectroradiometer (MODIS) potential evapotranspiration was calibrated at two class-I climate stations (Bahir Dar and Dangila) based on Penman–Monteith estimates and Normalized Difference Vegetation Index (NDVI) was derived from Sentinel 2B, which was later used to derive Kc. The correlation between reference evapotranspiration from MODIS Penman Monteith was acceptable for both Dangila (R2 = 0.64) and Bahir Dar (R2 = 0.74) stations. The MODIS calibration constant for Koga irrigation schemes was 0.27 and 1.99 (regression slope and constant) on an 8-day basis. Similarly, a strong correlation (R2 = 0.95) was found between Sentinel-based NDVI and FAO crop coefficient, which indicated an alternative pathway for estimating crop coefficient. The value of Kc varies in space (across the 10 plots) from 0.16 to 0.42 at the initial stage and from 1.20 to 1.32 at the mid-stage. Similarly, the mean value of Kc varies in time from 0.29 at the initial stage to 1.26 at the mid-stage. On the other hand, evaluation of MODIS and WaPOR ETc found a significant difference (p < 0.05) with the calibrated MODIS-Sentinel 2B derived ETc. This indicated the need to calibrate both MODIS and WaPOR for the proper estimation of crop water needs. Underestimation of ET was observed from MODIS, and the reverse is true for WaPOR. Our findings showed that calibrating and integrating MODIS with Sentinel 2B would be a feasible approach to estimate Kc and hence ETc that varies in time and space. This would assist water managers in estimating crop water needs for better productivity in the region.