Stable Isotope and AI supported model development for high frequency, cross scale water partitioning (ISO SCALE)
2 Bioclimatology, Faculty of Forest Sciences and Forest Ecology, University of Göttingen, Göttingen, Germany
3 IGB Leibniz Institute of Freshwater Ecology and Inland Fisheries, Berlin, Germany
P 2.4 in Climate Change and Physiology
Changing climate conditions and accelerating human demands on agricultural systems and ecosystem services increase the importance and urgency of understanding water movement in the soil-plant-atmosphere continuum (SPAC) and developing sustainable water management strategies for croplands. Non-linear dependencies among SPAC processes require dynamic and high-resolution monitoring to identify the spatio-temporal variability of water movement along SPAC interfaces. Recent technological advances have made water isotopes more affordable and widely applicable tracers. They are commonly used in natural systems for monitoring water movement and integrating process knowledge but are rarely applied to cropland. High-resolution data are needed to successfully predict the long-term effects of climate change-related disturbances and associated legacy effects on ecosystem resilience and crop water use strategies. Thus, in the ISO-SCALE project, we aim to achieve a novel integrated, cross-compartmental and cross-scale understanding of water partitioning and its spatio-temporal dynamics through high temporal resolution data. We will use in situ isotopic monitoring techniques to characterize the spatio-temporal patterns of water movement along the SPAC interfaces in a cropland. Particularly, we will investigate the temporal and spatial variability of ecosystem evapotranspiration, soil evaporation, plant transpiration, and soil water partitioning.