Modeling process-based biogeochemical dynamics in surface freshwaters of large watersheds with the IMAGE-DGNM framework

Over the last centuries, human activities have exerted increasing pressures on the environment, leading to drastic alterations in the functioning of freshwater bodies (e.g., eutrophication). Global biogeochemical models have proven crucial to investigate interactions between humans, hydrology, and water quality of surface fresh waters. However, most do not account for high‐resolution spatial and temporal variability within watersheds, and they typically lack any representation of benthic dynamics that can drive pollution legacy effects. We present here the Integrated Model to Assess the Global Environment‐Dynamic Global Nutrient Model (IMAGE‐DGNM), which couples global, spatially explicit hydrology and integrated assessment models with process‐based biogeochemistry in surface fresh waters. The new Dynamic In‐Stream Chemistry (DISC) module calculates advective transport from headwaters to estuaries, processes in the water column and in bed sediments, as well as the exchanges between these two compartments. As application examples of IMAGE‐DGNM, we simulate sediment dynamics and nitrogen cycling in two large river basins. We assess in‐stream concentration time series at specific locations, and identify governing processes in transfers along the aquatic continuum. Results highlight the importance of benthic dynamics in watersheds highly perturbed by damming. The implementation of such dynamics within IMAGE‐DGNM allows for including the temporal effect of pollution legacies in large scale water quality studies and shifts in pollutant speciation along river continua. This new framework therefore incorporates new features for large basin to global scale studies that are crucial to better predict the effects on receiving ecosystems and evaluate future environmental management pathways.