Efficient irrigation management is important to increase agriculture water use efficiency and achieve sustainable crop production under increasing water scarcity and climatic variability. Based on advanced devices and artificial intelligence (AI) algorithms, the irrigation system can be digitalized and transformed from experience-driven decision-making toward data-driven, predictive, and adaptive control. Digital Twins (DTs) enable smart irrigation management through continuous bi-directional data flows, dynamic model updating, intelligent prediction, and closed-loop execution. This paper provides a comprehensive review of the applications of DTs in irrigation management and optimization, covering Internet of Things (IoT), Remote Sensing (RS), and advanced simulation-inspired irrigation systems. Furthermore, we discuss the opportunities and challenges in DTs for irrigation optimization with the development of new techniques, and identify the major technological trends, existing bottlenecks, and future research directions for DT-enabled irrigation.
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Chang et al. (2026) studied this question.
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