Estimating selected cultivated crop water requirement-based surface energy balance algorithm.

The main purpose of this study is to estimate the water requirement of crops such as wheat, barley, alfalfa, lentils, and chickpeas in the northern half of Ardabil province, Iran. For this purpose, remote sensing methods such as SEBAL (Surface Energy Balance Algorithm for Land) and SEBS (Surface Energy Balance System) were used, and the results were compared with Penman-Monteith, Hargreaves-Samani, and pan evaporation methods. The results showed that wheat yield at 2018.11.30 with numerical values of 1.52 in SEBAL method and 1.09 mm/day in SEBS method had the lowest and lentil product at 2013.7.3 with numerical values of 7.86 and 8.14 mm/day had the highest water requirement among the studied products. Also, based on the results, the SEBAL method has the lowest error with RMSE of 0.893 and MAD of 0.843 compared to Penman-Monteith and Hargreaves-Samani methods; it has the highest error rate with RMSE of 1.112 and MAD of 1.215. The SEBS method also has the lowest error rate with RMSE of 0.930 and MAD of 0.833 compared to Hargreaves and the highest error rate with RMSE of 1.691 and MAD of 1.49 compared to the Penman-Monteith method. [ABSTRACT FROM AUTHOR]