Assessing the performance of three frequently used biogeochemical models when simulating N 2 O emissions from a range of soil types and fertiliser treatments

Biogeochemical models have the potential to provide insights into the key drivers of greenhouse gas (GHG) dynamics, and may be used in Tier 2 and 3 GHG emission reporting. Modelling nitrous oxide (N2O) emissions from agriculture, however, is still subject to large uncertainties. In the present study we analysed the performance of the three semi-mechanistic models, DailyDayCent (DayCent), DeNitrification-DeComposition (DNDC 9.4 and 9.5), and ECOSSE when simulating N2O fluxes from two different land uses (simulated grazing and spring barley) under a range of fertiliser types and application rates. Model performance was assessed using linear regression analysis, root mean square error (RMSE), and relative error. Monte Carlo analysis was carried out to assess the sensitivity of DayCent and ECOSSE to changes in the timing of management events.