Technological advances are central to improving our understanding of agricultural systems and strengthening global food security under increasing climate variability and change. This session focuses on the growing role of artificial intelligence (AI) and Earth observation (EO) in transforming agricultural science, with an emphasis on integrating large-scale data streams and advanced modeling approaches. We invite contributions that leverage EO data, EO foundation models, and AI/ML techniques - alongside process-based crop and ecosystem models and emerging digital twin frameworks - to improve predictive capability, scalability, and real-time monitoring of agricultural systems. Topics of interest include, but are not limited to: innovations in water and nutrient management; enhanced representation of plant physiological processes and soil properties; climate change impacts, extreme and compound events (e.g., droughts, heatwaves, floods) and their cascading effects on agroecosystems; and improved estimation and mitigation of greenhouse gas emissions.

• GC - Global Environmental Change
• H - Hydrology