Advancing distributed ecohydrological modeling of catchment-scale carbon and nutrient fluxes

Spatial heterogeneity in water and energy fluxes drives patterns of vegetation productivity and soil carbon and nutrient cycling across landscapes. However, most ecohydrological models either neglect lateral transfers or treat biogeochemical processes in a spatially decoupled manner, limiting their ability to reproduce observed catchment-scale patterns. We address this gap by extending the mechanistic ecohydrological model Tethys–Chloris–Biogeochemistry (T&C-BG) to a fully distributed configuration (T&C-BG-2D) that explicitly represents lateral routing of soil carbon and nutrients. The model is evaluated against long-term hydrological and biogeochemical observations from the Hafren catchment (UK) and the Erlenbach catchment (Swiss pre-Alps), where it successfully reproduces observed dynamics of several river solutes, including dissolved organic carbon, ammonia, and nitrate. To overcome the computational bottleneck of distributed model initialization, we further introduce a hybrid spin-up framework combining flux-tracking one-dimensional simulations with a random forest–based spatial extrapolation. This approach efficiently generates spatially heterogeneous and topography-informed initial conditions while reducing computational costs by up to 90%. Together, these advances enable efficient, spatially explicit ecohydrological–biogeochemical modeling across complex landscapes.