How do soil-plant-atmosphere interactions shape hydrological and vegetation responses to climate extremes? How do antecedent soil-water and vegetation conditions influence the pathways through which droughts, heatwaves and floods affect agricultural and natural systems? Which approaches can explain contrasting responses and improve predictions?
This session explores soil-plant-atmosphere processes and hydrological pathways during the onset and development of climate extremes and subsequent recovery. We examine links between meteorological forcing, antecedent system states, plant water use, land-atmosphere exchanges and hydrological responses, from field to catchment scales. We welcome studies of contrasting responses under dry and wet conditions, drought-heat interactions and transitions between extremes.
Topics of interest:
1. Soil-plant-atmosphere responses and feedbacks. Root water uptake, plant water regulation, evapotranspiration, canopy energy balance and vegetation stress during droughts, heatwaves and excess water, including soil-water supply and atmospheric demand interactions.
2. Antecedent conditions and hydrological pathways. How soil moisture, root-zone water storage, vegetation condition and groundwater connectivity shape responses to extremes; how water storage and partitioning among evapotranspiration, drainage, recharge and runoff link plant water availability to broader hydrological behaviour.
3. Contrasting extremes, event sequences and recovery. Contrasting responses under different initial conditions; drought-to-flood transitions; compound hot-dry conditions; and hydrological and vegetation recovery: timing, thresholds and legacy effects.
4. Observation-informed process understanding and prediction. Combining observations and models to identify response pathways, test process explanations, link spatial scales and assess predictive performance across events and environmental conditions.
We welcome research using satellite and uncrewed aircraft system (UAS) remote sensing, field experiments, process-based models, data assimilation and interpretable or hybrid machine learning, especially integrating soil-water, vegetation, surface-flux and hydrological observations.
Studies may examine single extremes or processes or compare events and systems. We link soil-plant-atmosphere and hydrological extremes research to explain how initial conditions and interacting processes shape responses and recovery.