ASSESSMENT OF THE EVAPOTRANSPIRATION COMPONENTS DYNAMICS IN DIFFERENT AGRO-CLIMATIC ZONES OF UKRAINE USING THE PENMAN-MONTEITH-LEUNING MODEL
Abstract
The results of the assessment of evapotranspiration (ET) and its components based on remote sensing data are presented in the paper. To obtain this assessment, a special software was developed, namely the scripts using the JavaScript programming language for remote data processing in the Google Earth Engine (GEE) cloud software environment. This software allows to adjust the Penman-Monteith-Leuning (PML) model for the conditions of Ukraine and visualize the spatial distribution of ET. The usage of the cloud capabilities of the service made it possible to access the collection of images and carry out their remote processing using the Penman-Monteith-Leuning algorithm calibrated according to the data of the global network of eddy covariance monitoring stations. The result of such an assessment was a composite mosaic - a spatially distributed generalized image of evapotranspiration and its three main components: transpiration from vegetation (Ec), evaporation from the soil (Es) and evaporation of precipitation intercepted by vegetation cover (Ei) on the territory of Ukraine for the 2020 growing season. Understanding the dynamics of these components helps to optimize the water resources use and develop effective irrigation schemes, especially in the climate change conditions. As a result of the analysis of the evapotranspiration components’ dynamics during the growing season, the most important component of evapotranspiration for different agro-climatic zones was determined.
However, the models, which are using remote data to estimate evapotranspiration dynamics, require additional validation and comparison with field measurements to improve their accuracy. Quantitative indicators obtained through modeling should be consistent with the data from ground-based greenhouse gas flows monitoring stations, which will contribute to the improvement of the methodology and its adaptation to the conditions of different agricultural regions. In addition, the use of the maps of geospatial distributed evapotranspiration allows to identify regions with increased transpiration and potential shortage of water resources. Such maps become a valuable tool for planning and forecasting water resources, which is critically important for the agricultural sector.
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