Agricultural systems are increasingly exposed to droughts, heatwaves, floods, and compound extremes, with impacts that can cascade across water resources, crops production, and rural livelihoods. Addressing such challenges requires better hazard monitoring or sensing technologies. A stronger link between observation, prediction, and the practical adaptation decisions is also needed that allow agricultural systems to anticipate, cope with, and recover from natural hazards.
This session brings together research that connects these different steps, from monitoring and prediction to adaptation and decision-making in agriculture under hydro-climatic extremes. Although hazard monitoring and precision agriculture technologies have advanced rapidly, turning these developments into tangible improvements in resilience remains challenging. This requires closer integration of hydrology, agriculture, remote sensing, climate science, and decision-support approaches.
We welcome contributions covering the full chain from observation to action, including Earth Observation and in situ monitoring of agricultural exposure and impacts; AI, machine learning, and hybrid modelling for impact prediction and early warning; agro-hydrological and land surface modelling under changing and compound climate conditions; and the use of monitoring and prediction to support adaptation, such as smart irrigation, precision water management, nature-based solutions, and climate-resilient cropping systems.
We particularly encourage studies that show how advances in observation and modelling can be translated into practical decision-support and adaptation. Contributions addressing compound and cascading hazards, especially those linking monitoring and modelling with agricultural impacts and management responses, are also welcome.