Тhe purpose of the study is to improve the management of systemic water use, ensuring an increase in the effectiveness of control actions, which is especially critical in conditions of limited natural resources and financing of operational measures. The research materials were publications, stock materials; information on the operation of inter-farm irrigation systems, technologies for their purpose and criteria for evaluating the effectiveness of management decisions; rules for water distribution and other materials necessary to achieve the purpose of the study. In the course of the research, mathematical modeling and forecasting methods based on probabilistic approaches, as well as methods of mathematical and genetic programming, neural network modeling, machine learning and big data processing were used to optimize technological processes of water use. An intelligent information and advisory computer decision support system for managing systemic water use has been developed, combining multi-criteria optimization modeling with artificial intelligence methods and modern geoinformation technologies. It combines several key subsystems: Water distribution management, Technical operation, GIS integration, Forecasting, Digital twin of water management organization, Administration. Automated planning of water distribution in conditions of water scarcity is carried out on the basis of economic and mathematical modeling. The process uses a multi-criteria function and a genetic optimization algorithm, which allows for maximum efficiency. A discrete mathematical model is used to optimize the planning procedures for technical operation, which is a special case of the general transport task of mathematical optimization. The results of testing automated control systems on the materials of the meliorative water management complex operation service showed a significant increase in water use efficiency and reliability of irrigation system structures. This became possible due to the development of information and technological support for management decisions of water management organizations. Thus, the efficiency of water distribution planning in difficult meteorological conditions, when there is a shortage of water, increases by 10 % compared to the traditional method, which involves reducing water supply depending on the level of water availability of the irrigation system. The implementation of multi-criteria economic and mathematical modeling and artificial intelligence in the selection of priority repair and restoration facilities reduced possible damage by 10–15 % compared to singlecriteria solutions that are based on maximizing the area of irrigated land, profitability of a water management organization or reducing irrigation water losses.
Dmitry A. Rogachev (Sat,) studied this question.