Reducing N2O emissions while maintaining yield in a wheat–maize rotation system modelled by APSIM

Modelling approaches have already been used to quantitatively assess the trade-offs between crop yield and N 2 O emissions as impacted by management practices. However, the model's performance in terms of predicting N 2 O emissions was mainly assessed against total emissions per growing season or year, which may reduce accuracy in modelling due to the uncertainties in total emissions estimated using the manual (static) chamber method. Here, a comparison between optimizations for Agricultural Production Systems sIMulator (APSIM) with total N 2 O emissions and daily N 2 O emissions was conducted. We further used the validated model to develop simple surrogate models for estimating total N 2 O emissions in different years and target potential opportunities to reduce N 2 O emissions while still maintaining the grain yield under long-term climatic conditions. Five parameters relating to denitrification and nitrification were optimized using differential evolution algorithm for global optimization based on two-year field experimental data at Huantai site in North China Plain, and comprehensive simulation experiments were further conducted under long-term climate variability in an irrigated wheat–maize rotation system. The method of Levenberg-Marquardt was implemented to fit simple surrogate models for estimating total N 2 O emissions in different years, and Analysis of Variance was used for model comparison. APSIM model optimized with daily N 2 O emissions could better simulate soil N 2 O and nitrate dynamics than that optimized with total N 2 O emissions. We obtained the posterior distributions of five key parameters to which N 2 O emissions are sensitive, and demonstrated that original model using default parameters could underestimate the rate of nitrification and denitrification and the subsequent N 2 O emissions. Total N 2 O emissions increased exponentially with nitrogen application rate and mean temperature, and IPCC (1% emission factor) could underestimate whole-year N 2 O emissions when N rate was higher than the optimized nitrogen rate for crop production. We also found that there was potential to optimize nitrogen fertiliser rate to reduce N 2 O emissions while still maintaining crop yield in the irrigated wheat–maize rotation system. This study demonstrated the necessity of optimization with daily N 2 O emissions in improving model accuracy, and the posterior distributions of five parameters relating to N 2 O emissions offered reference range for future model improvement and applications. • Crop yield and soil N 2 O emissions were studied using a modelling approach. • APSIM could more accurately model soil N 2 O and nitrate dynamics when five related parameters were optimized with daily N 2 O emissions. • Posterior distributions of five parameters controlling N 2 O dynamics were obtained. • Total N 2 O emissions increased exponentially with N rate and mean temperature. • N rate could be reduced by 19% without sacrificing crop yield, which in turn led to a reduction of N 2 O emissions by 34%.