Registration Number
0226U000940,
(0121U109692)
, R & D reports
Title
Development of theoretical bases of decision support systems in irrigation based on a combination of data of different nature
popup.stage_title
Розроблення теоретичних основ систем підтримки прийняття рішень у зрошенні на основі поєднання даних різної природи
Head
Matiash Tetiana V., Кандидат технічних наук
Registration Date
19-01-2026
Organization
Institute of Water Problems and Land Reclamation of National Academy of Agrarian Sciences of Ukraine
popup.description1
The aim of the project is to develop and study the effectiveness of application in advisory systems to support decision-making in irrigation process models in the system "soil-plant-air", combining data of different nature. The methodology underlying the integrated irrigation management system, which is based on the modeling of soil moisture transfer to ensure optimal moisture of the root system of plants and minimize its losses due to infiltration into deeper soil layers
popup.description2
Report: 55 p., 24 fig., 4 tabl., 48 references.
Keywords: optimization algorithms, agriculture, information-analytical system, decision support, IAS specification, sustainable land use. Object of research – decision support systems in agriculture.
Project Purpose – to develop and study the effectiveness of applying models of processes in the “soil–plant–air” system within advisory decision support systems for irrigation that integrate data of various origins. Research methods – systems analysis, optimization, computer modeling, data collection and primary processing, programming methods, languages. The report presents the results of research on crop evapotranspiration under various climatic conditions and levels of moisture supply. Methods and models for calculating evapotranspiration are substantiated, taking into account soil moisture and suction pressure index, irrigation regimes parameters. Databases of crop growth stages and irrigation water requirements for regions of Ukraine were developed, considering years with different levels of moisture deficit and allowing correction using remote sensing data. A GIS architecture of the irrigation DSS was developed using the cloud computing platforms Google Earth Engine, with integration of satellite (Landsat, Sentinel, MODIS), meteorological, and soil data. Within this technology, indices NDVI, NDMI, and Gross Primary Productivity were calculated, and geospatial maps of evapotranspiration and water deficit were generated. Testing on pilot sites confirmed the effectiveness of irrigation scheduling and increase in crop productivity. The economic effect is determined by reducing losses from unjustified decisions, saving resources, and achieving ecological benefits from sustainable irrigation. The projected implementation potential covers 500–700 thous. ha. The results form the basis of the monograph “Theoretical Foundations of Decision Support Systems in Irrigation Based on the Integration of Multi-Source Data”
Product Description
popup.authors
Чорна Катерина Іванівна
Volodymyr P. Kovalchuk
Тetiana V. Matiash
Салюк Алла Федорівна
Vsevolod O. Bohaienko
Krucheniuk Anatolyi V.
Vladyslav Knysh
Сорока Наталія Володимирівна
Romashchenko Mykhailo I.
Svitlana I. Burykina
Butenko Yaryna O
Oleksandr P. Voitovych
Anton M. Smirnov
popup.nrat_date
2026-01-19
