Evaluation of SEBS and SEBAL algorithms for estimating wheat evapotranspiration (case study: central areas of Khuzestan province)

Abstract This study aimed to accurately estimate daily wheat evapotranspiration using two remote sensing algorithms, Surface Energy Balance System (SEBS) and Algorithm for Land (SEBAL), in central Khuzestan province during 2019–2020. The results of algorithms were compared with lysimeter (as a direct method), FAO-Penman–Monteith (FAO-PM), temperature-based methods (Hargreaves-Samani Blaney-Criddle), radiation-based (Priestley–Taylor Doorenbos–Pruitt), mass transfer-based (Mahringer World Meteorology Organization) indirect methods). Coefficient Determination ( R 2 ), Root-Mean-Square Error (RMSE), Percentage Bias (PBIAS), Mean Error, Absolute Nash–Sutcliffe indicators used comparing the results. According results, both SEBAL SEBS showed highest compatibility data = 0.92 0.96, RMSE 2.15 1.53 mm/day, respectively). Comparing FAO-PM method, resulted 2.42 mm/day 0.87 3.14 0.79 SEBAL. Hargreaves-Samani method 0.72, 16.4 mm/day) 0.8, 10.4 among methods, Doorenbos–Pruitt 0.71, 3.33 0.79, 2.63 Mahringer 0.6, 6.8 0.68, 5.51 yielded better estimations than respectively. Owing high accuracy estimating amount area close actual values field, energy balance is recommended province.