Actual Crop Evapotranspiration Estimation of Wheat Crop Using SEBAL Algorithm and Remotely Sensed Data

Abstract

Estimation of evapotranspiration is imperative for effective forest, irrigation and water resources management as well as to increase yields and for better crop management. This study aims to evaluate the effectiveness of the Surface Energy Balance Algorithm for Land (SEBAL) in estimating actual evapotranspiration for 15 years of wheat crop in the 2A distributary of Mahanadi canal Command which is situated in Dhamtari district of Chhattisgarh state of India. The Landsat 7 and 8 satellite images from February – March (2007 -2021) were used to acquire the coefficients of the respective bands. To validate the outcomes from the SEBAL algorithm, FAO Penman-Monteith methods were employed to calculate the evapotranspiration values and evaluated using suitable performance metrics. The evaluation using SEBAL, along with the FAO-Penman–Monteith method, showed that SEBAL has a sufficient accuracy for estimating ET. The results showed that the SEBAL generated evapotranspiration values are in high agreement with the FAO Penman-Monteith method registering the highest correlation value (R2 = 0.826) and the corresponding Root Mean Square Error was (RSME =0.4386), Normalized Root Mean Square, (NRMSE= 0.386), Mean Absolute Error (MAE=1.17) and Nash Sutcliffe Efficiency( ENS = 0.843) for wheat crop.  In 2010 maximum ETc  and in 2021 minimum ETc of wheat crop in the study area. The outcomes show that since the performance of the SEBAL algorithm in estimating the actual evapotranspiration using Landsat 7 and 8 satellite images is acceptable, the SEBAL algorithm could be a very convenient method. Moreover, it could easily be assimilated into farming management systems and precision agriculture for better decision-making and higher yield.