Estimating evapotranspiration of pistachio crop based on SEBAL algorithm using Landsat 8 satellite imagery

Abstract

Stationary actual evapotranspiration (ET) estimation methods deal with some issues such as maintenance problems, the point data recording for a particular location, the complex hydrological process calculation, and requiring the expert workers. To solve this, ET estimation methods like Surface Energy Balance Algorithm for Land (SEBAL) method can be used based on the satellite images. However, the efficiency of the SEBAL model varies in ET estimation for different products and environmental conditions. On the other hand, pistachio is an important crop of Iran which little investigation were accomplished to estimate its ET using the presented models. Therefore, the purpose of this study is to investigate the efficiency of SEBAL algorithm in estimating ET of pistachio crop. In this regard, actual ET of a 100 hectares pistachio farm, located in Safaeieh region in the Semnan province, Iran, was selected as the study area. Implementations were performed using 29 Landsat 8 Operational Land Imager (OLI) images during the 2013–2017 period. The results were verified and compared with the results of evapotranspiration in standard condition estimated by the Intelligent Meteorological instrument (iMetos-Pessl) as the ground truth. The results of this study indicate the determination coefficient and Root Mean Square Error (RMSE) of the estimated actual ET for pistachio plant as 0.8 and 2.5 mm, respectively. Moreover, the results indicate the high spatial variability of ET in the pistachio growth period and the need to use a satellite data analysis method, like the SEBAL method, to prepare the ET map. Overall, the results show the good efficiency of the SEBAL model for estimating the actual ET of the pistachio product.