The traditional calibration approach for process-based models, such as DayCent, consists of the iterative adjustment of model parameters and comparison of the simulated total N2O flux to measured observations. However, the contributions of individual production pathways, namely nitrification and denitrification, are uncertain. Here, N2O emissions from the soil of sugar beet plots with control (Null) and mineral (NPK) fertilizer treatments were measured by a static chamber technique. The isotopic composition of emitted N2O was analyzed to identify the N2O production pathways. The latter showed that denitrification was the predominant source of N2O emissions at this site. The model’s default settings strongly overestimated the contributions of nitrification. This incorrect allocation of N2O emissions to nitrification could partly be explained by the model’s tendency to underestimate the soil water content during the growing season. DayCent model parameters were also manually adjusted to better represent the observation derived contributions of nitrification and denitrification. Although, this “expert-informed approach”, showed a slightly lower performance concerning the cumulative N2O flux (Null: RMSE = 0.37 kg N ha−1 yr−1, NPK: RMSE = 0.50 kg N ha−1 yr−1) than the traditional calibration (Null: RMSE = 0.15 kg N ha−1 yr−1, NPK: RMSE = 0.10 kg N ha−1 yr−1), it may be considered as more representative because it better reflected the higher contribution from denitrification shown by the isotope data. This study demonstrates that the inclusion of observational methods, such as isotope measurements, can provide important insight into model function and improve pathway-specific estimation of N2O emissions in DayCent.