Integration of digital technologies into water distribution management in irrigation systems

Abstract

Abstract
Background and Aim. Climate change, growing pressure on water resources, and increasing agricultural demand for water require more efficient irrigation management. The digital transformation of water management improves water-use efficiency and strengthens the resilience of irrigation systems.
This study evaluates water distribution efficiency in the Almaty region and substantiates the use of digital technologies for water resources management under stochastic variability in water availability.
Materials and methods. The study was based on statistical data on water use in the Almaty region for 2010–2024, hydrological records of the Ili River basin, and official data from Kazakhstan's authorized water management agencies. Systems analysis, comparative assessment, statistical analysis, correlation analysis, and regression modeling were applied. The coefficients of variation, correlation, and determination were calculated to evaluate water distribution efficiency. The applicability of GIS, IoT,
SCADA systems, digital twins, and artificial intelligence toirrigation management was also assessed.
Results. The results indicate an improvement in the efficiency of water resources management. Water withdrawal increased by 20.8%, while the water distribution efficiency coefficient rose from 0.62 to 0.77 and water losses decreased from 38% to 25%. Irrigation water consumption per unit area declined by 22%, resulting in estimated annual water savings of approximately 640 million m³. A strong
negative correlation was found between water losses and system efficiency (r = –0.89). The regression model demonstrated high explanatory power (R² = 0.86), confirming the robustness of the results. The implementation of digital technologies contributes to more efficient water allocation, reduces water losses, and greater resilience of irrigation systems.
Conclusion. Digital technologies enhance the efficiency and sustainability of water resources management by improving water distribution, reducing losses, and the adaptability of irrigation systemsto hydrological variability. The proposed digital–stochastic framework provides a scientific and methodological basis for developing digital water management platforms and decision-support systems, as well as for the practical implementation of adaptive water allocation technologies in irrigation
management.