Adaptive Irrigation Management Model under Climate Change Based on Yield Forecasting and Scenario Analysis

Анотація

The increasing impact of climate change on agricultural systems necessitates the development of adaptive irrigation management approaches capable of ensuring stable yields under growing environmental uncertainty. The aim of this study is to analyze and demonstrate the effectiveness of an adaptive irrigation management model based on yield forecasting and scenario analysis to improve the economic efficiency and sustainability of agricultural production.

Methods: analysis of the scientific literature was applied to examine current developments in this field; generalization and systematization were used to present the research findings.

Results. The study synthesizes contemporary theoretical and methodological approaches to irrigation management and integrates them with predictive and analytical tools to form a comprehensive decision support system. The structural framework of the adaptive model is substantiated, combining climatic, agronomic, and economic parameters into a unified system of dynamic interaction. Key sources of uncertainty affecting irrigation efficiency are identified, namely climatic variability, water resource availability, and technological constraints, and their influence on yield is established. The methodological foundations of yield forecasting and their integration into managerial decision-making processes are examined, enabling the timely, data-driven adjustment of irrigation strategies. The role of scenario modeling is analyzed as a tool for evaluating alternative development trajectories of irrigation systems under varying climatic and economic conditions, which makes it possible to determine optimal strategies under risk and uncertainty. The economic feasibility of implementing the adaptive model is substantiated through its comparison with traditional irrigation approaches, demonstrating its advantages in resource efficiency, yield stability, and profitability. The model’s sensitivity to changes in external parameters is assessed, and the limits of its adaptability under extreme conditions are determined.

Conclusions. The proposed model enhances the resilience and economic viability of irrigated agriculture by improving the quality of decision-making, reducing risks, and ensuring more efficient use of water resources under climate change.