Author/Authors :
Davarzani ، Vahid Department of Watershed Management Engineering - Faculty of Natural Resources - Tarbiat Modares University , Vafakhah ، Mehdi Department of Watershed Management Engineering - Faculty of Natural Resources - Tarbiat Modares University , Moradi ، Hamidreza Department of Watershed Management Engineering - Faculty of Natural Resources - Tarbiat Modares University
Abstract :
Estimation of actual evapotranspiration (ET) in large areas is an important part of water resources management. In recent years, remote sensing has been successfully used in ET estimation, which is supposed to be more accurate for estimating ET on regional and agricultural scales. The main aim of this investigation is to evaluate the efficiency of two algorithms namely Surface Energy Balance Algorithms for Land (SEBAL) and Mapping ET at high Resolution with Internalized Calibration (METRIC) algorithms for estimating actual ET from agricultural lands in Davarsen County, Iran. Accordingly, six Landsat 8 OLI/TIR satellite images and Lysimeter data installed in these lands were used. The amounts of actual ET were estimated using two algorithms and the obtained results were compared with Lysimeter data. Based on the results of evaluation, Root Mean Square Error (RMSE) of 0.54 and 0.64 mm day^-1 , Nash-Sutcliffe Efficiency (NSE) criteria of 0.85 and 0.79, Mean Bias Error (MBE) of 0.04 and 0.02 mm day^-1 , Mean Absolute Error (MAE) of 0.42 and 0.48 mm day^-1 and coefficient of determination (R²) of 0.86 and 0.82 were estimated for SEBAL and METRIC algorithms, respectively. These statistical indices show that these algorithms have a high accuracy for estimating actual ET in the study area. The executive applications of this study can be used to determine the exact amount of evapotranspiration in irrigated lands for water allocation planning, optimization of crop production, irrigation management and assessment of land use change on water efficiency.
Keywords :
Actual evapotranspiration , Energy balance algorithm , Remote sensing , Water management