Synergizing grassland and soil system model expertise by coupling GRASSMIND (v2.0) and BODIUM (v1.2)

Abstract. Ecological models often have a specific focus, simplifying other system components. In the context of landscapes under climate change, it is increasingly important to include all relevant components and their interactions in detail in the models. Grassland models, advising management strategies for this important vegetation type of European landscapes, often lack detailed and reliable hydrological and soil resource dynamics that influence plant growth in grasslands. This study investigates the potential to overcome this issue by coupling an existing grassland with a soil system model, making use of their expertise in a specialized area. Here, the individual- and process-based grassland model GRASSMIND is coupled to the systemic soil model BODIUM using the coupling framework FINAM. The influence of soil water on grassland dynamics is shown to be more reliable with the coupled models than with GRASSMIND alone. In addition, the coupling offers the potential to tackle shortcomings in the representation of other plant processes such as root growth. However, the most urgent challenge is to overcome the ambiguity in the parametrization of GRASSMIND itself. Our experience suggests that maintaining the native models as independent components provides flexibility for future improvements but also complicates updating parametrizations in the combined system as the individual models evolve.