Sustainable soil and land management is a key challenge in the context of climate change. The complexity arises from the high spatial heterogeneity of soils and landscapes, as well as from differences in spatial and temporal scales of the processes driving soil functions and (agro)ecosystem dynamics. To address these challenges, integrated modelling approaches are needed that bridge scales, disciplines, and data sources.
This session invites contributions presenting and discussing innovative modelling strategies and data analyses for sustainable soil management and landscapes evolution. Topics include multi-scale modelling approaches, the integration of machine learning with mechanistic models, the direct assimilation of monitoring data into models (e.g. digital twin concepts), and the coupling of different models to represent interactions between soil, microbes, plants and the atmosphere. We especially welcome studies that highlight the potential and limitations of integrated approaches, exploring their application across various systems, from agroecosystems to natural ecosystems. The session aims to provide a platform for exchange on methods, experiences, and visions to advance soil and land management towards sustainability and resilience.