Bridging Carbon and Water Dynamics: Insights from Process-Based Modeling in Agricultural Ecosystems Under Global Change Drivers

Global change drivers, such as climate change and land-use intensification, pose imminent threats to the functioning of agricultural ecosystems, by disrupting vital ecosystem processes. In this context, understanding the interplay between carbon cycling and ecohydrological processes becomes important for the development of adaptive strategies that enhance the resilience of agricultural ecosystems in response to the dynamic challenges imposed by global change drivers. Process-based simulation models are a powerful tool to disentangle the complex interactions of microbiota-plant-soil interactions and provide a basis for long-term predictions and scenario simulations. Our study focuses on the "Global Change Experimental Facility (GCEF)" (https://www.ufz.de/index.php?en=42385), where comprehensive data on plant physiology, soil nutrients, soil microbes, fauna, soil structure and moisture were collected across various agricultural land-use types. These include conventional and organic cropping systems, intensively and extensively farmed meadows, and extensively grazed sheep pastures, all under ambient and simulated future-climate conditions. Here we present an extended version of the process-based soil model BODIUM, which captures the dynamics of soil functions, responding to soil management or changes in climatic conditions. The model was parametrized for different land-use types on the GCEF. First simulation results, compared with measured data for validation, reveal promising agreement in carbon data for cropland systems. However, an overestimation of water content within the soil profile after the vegetation phase needs further investigation. Additional simulations, alongside experimental findings are employed to discuss the impact of climate-change and land-use types on carbon and water dynamics and their potential interactions. The successful validation of the model across varied treatments provides the foundation for a potential application of the model to other boundary conditions that are not covered by the GCEF experiment.