Butenko Y. Improving irrigation management via using remote sensing data

The thesis provides a scientific substantiation for the use of space imagery data to improve irrigation management in the areas of large farms in the south of Ukraine. To develop methods to improve irrigation management on large farms, long-term comprehensive studies were conducted using space imagery data and ground-based observations. To achieve this goal, field, statistical and computational methods were used in the research. Field research was performed during 2012-2017 in a large number of production fields on three farms in Kherson and Zaporizhia regions in a total area of 7236.7 hectares, where the Information System "GIS Polyv" was implemented. The main result of the work is proving the necessity of taking into account the spatial unevenness of biomass growth and evapotranspiration of crops (according to remote sensing data) in the information systems of operational irrigation schedule, which improves the accuracy of calculations and, accordingly, the effectiveness of management decisions. For this purpose, a special algorithm for the use of remote sensing methods in the IS "GIS Polyv" has been developed and tested, which best enables to take into account the actual condition of crops development in real production due to: - determining correction factors to crop coefficients of total water consumption of crops in conditions of atmospheric drought; - identifying fields with unsatisfactory condition of crops for control the measurements of soil moisture and, if necessary, clarifying the irrigation plans and forecast for total water consumption of crops for the next calculation period. The developed algorithm was tested during the implementation of IS "GIS Polyv" in LLC "Freedom Farm Terra" in Zaporizhia region during 2017-2019. In the fields of the farm, the effect of the implementation of remote sensing methods averaged 3056 UAH/ha, due to the increase in soybean yield and due to the difference between the costs of irrigation compared to the reference crop rotation of the neighboring farm. Keywords: operational irrigation schedule, information system, remote sensing, irrigation management, sprinkling, soybean