Estimation of actual evapotranspiration using remote sensing data for improved water management

Spatial quantification of actual evapotranspiration (ET) is crucial for water resource management and planning in arid regions. This research focuses on the investigation and estimation of evapotranspiration using Py_SEBAL and METRIC algorithms, as well as the WaPOR model and MOD16 product, during the years 2021 and 2022 in the Moghan Plain located in Ardabil Province. The results of each model are compared with the FAO-56 method, which is a standard approach for estimating evapotranspiration in different areas. The results indicate that the Py_SEBAL algorithm shows the highest correlation with the FAO-56 method, with an R value of 0.97 and an RMSE (mm/month) of 1.88. Next, the METRIC algorithm demonstrates the highest correlation with an R value of 0.89 and an RMSE (mm/month) of 1.5. To further validate the performance of the estimation models in different areas, the WaPOR database is also utilized. The obtained outputs indicate that among the irrigated lands covered by the water network, the Py_SEBAL algorithm exhibits the highest correlation with the values derived from WaPOR, with an R2 value of 0.77. After Py_SEBAL, METRIC demonstrates a relatively suitable correlation with an R2 value of 0.55. Considering the land use map of the region, more than 60% of the area is covered by the irrigation network. Since Py_SEBAL yields the best results in the conducted investigations for these lands, the estimation of evapotranspiration volume is focused on the entire region. The results indicate that the volume of evapotranspiration is approximately 4/5 times higher per hectare in irrigated lands compared to drylands.