• Introduced a high spatial resolution HYPE model in a nested boreal catchment. • Krycklan-HYPE reproduced streamflow and DOC across 14 sub-catchments. • A trade-off was observed between streamflow and DOC simulation performance. • Spatial analysis revealed declining DOC performance in downstream subcatchments. Understanding the spatiotemporal dynamics of dissolved organic carbon (DOC) is essential for predicting aquatic carbon fluxes and managing water quality in boreal catchments. Traditional DOC modelling approaches exhibit limitations in representing seasonal dynamics, event-driven responses, and riparian-zone contributions. Here, we evaluate the performance of the Krycklan-HYPE model in simulating streamflow and DOC concentrations across the Krycklan catchment in northern Sweden. The model was calibrated and validated at 14 sub-catchments using the Kling-Gupta Efficiency (KGE) metric. Results showed consistently good to very good performance for streamflow (calibration KGE = 0.50–0.82; validation = 0.35–0.71), with low uncertainty and strong spatial transferability. In contrast, DOC simulations were more varied, with KGE values of 0.11–0.59 in calibration and 0.05–0.58 in validation (excluding one negative value). A negative correlation between streamflow and DOC performance was observed, indicating a trade-off between hydrological and biogeochemical simulation accuracy. Seasonal analysis showed that streamflow and DOC were best captured during spring and autumn, while DOC dynamics during summer and high-flow events were not well simulated. This pointed to the model structure limitation with missing representations of corresponding processes. Scenario-based analysis highlighted the trade-off: streamflow was best simulated under high flows, while DOC performance was better under low flow conditions. These results demonstrate the Krycklan-HYPE model’s strengths in streamflow simulation but also highlight limitations in representing DOC mobilization and transport. Future study should focus on developing model structures that incorporate relevant processes, and considering calibration strategies that take the spatially heterogeneous parameterizations into account
Guo et al. (Thu,) studied this question.