Estimating the amount of evapotranspiration in the area affected by flood spreading using METRIC algorithm

Evapotranspiration (ET) is one of the most important factors in the hydrological cycle and is a key determinant of energy equations on the earth’s surface. evapotranspiration estimates are important for hydrology, irrigation, forest and rangeland, and water resources management. The evapotranspiration drives the soil water-energy balance which is largely used in general circulation models and climate modelling. Consequently, river water flow forecasting, crop yield forecasting, irrigation management systems, river/lake water quality are all dependent on evapotranspiration levels. For this reason, it is essential to accurately estimate the water budget. Numerous models have been developed to estimate evapotranspiration using remote sensing methods. The review of recent research shows that remote sensing and the use of satellite images have a high ability to estimate the amount of actual evapotranspiration.

The aim of this study is calibrating the METRIC algorithm in estimating evapotranspiration in the Sohrin-Qaracheryan Plain, which is affected by flood spreading. This method has been used by many researchers around the world to estimate evapotranspiration. On the other hand, estimating the actual evapotranspiration is of great importance in the plains affected by the flood, especially in the Sohrin-Qaracherian Plain’s flood spreading. Therefore, in this research was conducted to estimate evapotranspiration using the metric algorithm in the Sohrin-Qaracherian Plain, for the optimization management of water resources in the region and regions with similar conditions. In this research, were used of the daily and hourly meteorological data of Zanjan Airport synoptic station from 2020 to 2021. These the data included minimum and maximum temperature, minimum and maximum humidity, wind speed average, sunshine hours and air pressure. To check the application of metric algorithm, were downloaded Landsat 8 images for 2020-2021 years and were done necessary corrections and preprocessing on them. Landsat images are available at 16-day intervals with a spatial resolution of 30 m and were obtained from the United States Geological Survey website (http://glovis.usgs.gov). After the images processing, is obtained the albedo, surface emissivity, land surface temperature, plant indicators, incoming-outgoing radiation fluxes, net radiation flux and the soil heat flux. Next, the sensible heat flux is calculated by determining the hot and cold pixels. Finally, evapotranspiration maps are plotted. In addition, for a better comparison of the results, were compared of the layers related to vegetation index include soil heat flux and land surface temperature in the different stages of the growth period. After extracting these indices, the evapotranspiration map was extracted using ENVI software.

Results show that daily evapotranspiration increases is directly related with increase in vegetation density. at the initial of the growth period, the range of evapotranspiration is estimated between 0.08 and 4.97 mm.d-1, while this value in the middle and late of the growing season is estimated in the range of 0.086 to 5.56 and 0.59 to 9.57 mm.d-1 respectively. Based on the results of this research evapotranspiration obtained from the soil water balance model and METRIC model were estimated as 24115 and 25648 m3, respectively. The results validation of evapotranspiration obtained from the metric model was compared with the actual evaporation and transpiration obtained from the soil water balance model, and the error coefficient was obtained equal to 5.97%.

According to the results of this research, it was determined that the use of energy balance models using the science of remote sensing provides the possibility of estimating evaporation and transpiration regionally. On the other hand, the calculation error percentage shows that the metric algorithm is accurate enough to estimate ET in the studied area.