Earth System Models (ESMs) and landscape-scale long-term models are often unable to capture ecosystem patterns and dynamics as most ecosystem functions emerge from the underlying complexity of soil/vegetation processes and feedbacks. While incorporation of detailed process models is crucial for a better representation of the soil and land-surface processes across spatial and temporal scales it is still a challenge to identify, prioritize and scale key driving factors and mechanisms. Furthermore, if the underlying nonlinear processes exhibit threshold effects and trigger complex emergent feedbacks, such behavior should find a proper representation in the upscaled models. The aim of this session is to bring together state-of-the-art expertise in soil biogeochemistry, ecology, geomorphology, soil physics, hydrology, and climatology to reveal and address knowledge gaps, encourage knowledge transfer between disciplines, and explore the potential of synthesis and hybrid-modelling approaches towards improving predictions of soil dynamics and vulnerability and resilience under ongoing global change. Cross-disciplinary collaboration and integration in soil science is crucial to inform and guide soil management efforts. We invite theoretical and empirical studies that bridge the gap between scales, from detailed process understanding to emergent landscape-scale behavior. Specifically, we seek model and dataset analyses, as well as scaling methodologies, that will help advance quantitative understanding and multi-scale modelling of soil dynamics for integration in ESMs.
SSS11.6
Upscaling detailed models to landscape for long-term predictions and integration in Earth System Models