RETRIEVAL OF KC FROM SEBAL AND COMPARISON AMONG NDVI AND LAI BASED KC

In present study spatial crop coefficient (Kc) estimated from Surface Energy Balance Algorithms for Land (SEBAL) model was compared with simulated spatial Kc based on Normalized Difference Vegetation Index (NDVI) and Leaf Area Index (LAI). For selection and comparison of optimal model statistical tests were applied. Statistical tests have revealed that LAI based spatial Kc (LAI-Kc) model has best performances (R2=0.976) in context of spatial Kc compared to NDVI-Kc model with respect to SEBAL-Kc. Further, results show that LAI based simulated spatial Kc has good coefficient of determination (R2, second order polynomial) of 0.976 (at 95%), Multiple R=0.94, and Standard error= 0.11) with SEBAL-Kc rather than NDVI-Kc. The procedure for spatial LAI-Kc presented in this paper should be useful in other regions of the globe to understand crop water requirement studies based on evapotranspiration.