Integration of Landsat 8 satellite images and MODIS sensor to estimate the water requirement of maize during the growth period (Case study: Mahidasht, Kermanshah province)

Evapotranspiration is one of the key components of the hydrological cycle and its quantification is essential to understand the processes such as vegetation phenological changes, environmental hazards such as floods and droughts, and, in general, the ecosystem water balance. The use of remote sensing methods based on surface energy balance has been increased to estimate evapotranspiration. The purpose of this study was to estimate the evapotranspiration of corn based on integration of Landsat 8 and MODIS satellite images using the SEBAL algorithm in in Mahidasht, Kermanshah province. Linear with Zero Intercept (LinZi) method was used to integrate satellite images. Also, actual evapotranspiration of corn in 15 farms in the study area was estimated based on ground data. The results of the SEBAL algorithm were compared with ground-based evapotranspiration using MAE, BIAS and RMSE indices. The results indicated that the combination of satellite images has led to an improvement in the accuracy of estimated evapotranspiration compared to Landsat 8 images. The mean absolute error of estimated evapotranspiration during the growth period was determined as 0.44 and 0.42 mm.day -1 respectively based on Landsat 8 and combined images. In general, the results of this study showed that the estimation of evapotranspiration using the SEBAL algorithm and based on the integration of satellite images with different spatial and temporal resolutions could have acceptable results.