Simulation of N 2 O emissions from a urine‐affected pasture in New Zealand with the ecosystem model DayCent

We used the trace gas model DayCent to simulate emissions of nitrous oxide (N 2 O) from a urine‐affected pasture in New Zealand. The data set for this site contained year‐round daily emissions of nitrification‐N 2 O (N 2 O nit ) and denitrification‐N 2 O (N 2 O den ), meteorological data, soil moisture, and at least weekly data on soil ammonium (NH 4 + ) and nitrate (NO 3 − ) content. Evapotranspiration, soil temperature, and most of the soil moisture data were reasonably well represented. Observed and simulated soil NH 4 + concentrations agreed well, but DayCent underestimated the NO 3 − concentrations, due possibly to an insufficient nitrification rate. Modeled N 2 O emissions (18.4 kg N 2 O‐N ha −1 yr −1 ) showed a similar pattern but exceeded observed emissions (4.4 kg N 2 O‐N ha −1 yr −1 ) by more than 3 times. Modeled and observed N 2 O emissions were dominated by peaks following N‐application and heavy rainfall events and were favored under high soil temperatures. The contribution of N 2 O den was simulated well except for a 4‐week period when water‐filled pore space was overestimated and caused high N 2 O emissions which accounted for one third of the simulated annual N 2 O emissions. N 2 O nit fluxes were overestimated with DayCent because they are calculated as a fixed proportion of NH 4 + converted to NO 3 − , while the data suggest that significant rates of nitrification can occur without inducing significant N 2 O emissions. The comprehensive data set made it possible to explain discrepancies between modeled and observed values. In‐depth model validations with detailed data sets are essential for a better understanding of the internal model behavior and for deriving possible model improvements.