Irrigated agriculture, while critical for food security, is the largest consumer of freshwater resources worldwide. Timely, detailed knowledge on irrigation is fundamental for growers, policymakers, and water managers to assess water demands, resolve conflicts, and implement effective management strategies. Recent advances in data availability, Earth observation foundation models, AI, and computing capacity have greatly improved our ability to characterize irrigation practices and evaluate impacts with unprecedented spatial and temporal detail. This session invites contributions that leverage these data infrastructure and technological developments to advance understanding of irrigation systems and their impacts from field to global scales. Topics of interest include, but are not limited to, mapping irrigation practices; estimating irrigation water use, efficiency, sources, and withdrawals; and improving representation of irrigation in climate, food, and water system models. Submissions addressing challenges such as data scarcity, model generalization, cross-region scalability, and the development of open-access datasets and tools are particularly encouraged.

• H - Hydrology
• IN - Informatics