Using the ecosys mathematical model to simulate temporal variability of nitrous oxide emissions from a fertilized agricultural soil

Abstract

Large temporal variability of N₂O emissions complicates calculation of emission factors (EFs) needed for N₂O inventories. To contribute towards improving these inventories, a process-based, 3-dimensional mathematical model, ecosys, was used to model N₂O emissions from a canola crop. The objective of this study was to test the hypothesis in ecosys that large temporal variability of N₂O is due to transition among alternative reduction reactions in nitrification/denitrification caused by small changes in soil water-filled pore space (WFPS) following a threshold response, which controls diffusivity (D_g) and solubility of O₂. We simulated emissions at field scale, using a 20 × 20 matrix of 36 m × 36 m grid cells rendered in ArcGIS from a digital elevation model of the fertilized agricultural field. Modelled results were compared to measured N₂O fluxes using the flux-gradient technique from a micrometeorological tower equipped with a tunable diode laser, to assess temporal N₂O variability. Grid cell simulations were performed using original, earlier and later planting and fertilizer dates, to show the influence of changing precipitation and temperature on EFs. Fertilizer application (112 kg N ha⁻¹), precipitation and temperature were the main factors responsible for N₂O emissions. Ecosys represented the temporal variation of N₂O emissions measured at the tower by modelling significant emissions at WFPS > 60% which reduced the oxygen diffusivity, causing a rising need for alternative electron acceptors, thus greater N₂O production via nitrification/denitrification. Small changes in WFPS above a threshold value caused comparatively large changes in N₂O flux not directly predictable from soil temperature and WFPS. In ecosys, little N₂O production occurred at WFPS < 60% because the oxygen diffusivity was large enough to meet microbial demand. Coefficients of diurnal temporal variation in N₂O fluxes were high, ranging from 25–51% (modelled) and 24–63% (measured), during emission periods (0–0.8 mg N₂O–N m² h⁻¹). This variation was shown to rise strongly with temperature during nitrification of N fertilizer so that EFs were affected by timing of fertilizer application. EFs almost quadrupled when fertilizer applications were delayed (average: 1.67% (fertilizer-induced emissions), causing nitrification to occur in warmer soils (18 °C), compared to earlier applications (average: 0.45%) when nitrification occurred in cooler soils (12 °C). Large temporal variation caused biases in seasonal emissions if calculated from infrequent (daily and weekly) measurements. These results show the importance of the use of models that include climate impact on N₂O, with appropriate time-steps that capture its temporal variation.