In-situ N$_2$O and N$_2$ data improved N budget simulation with APSIM and LandscapeDNDC in tropical sugarcane systems

Denitrification is a key process in the global nitrogen (N) cycle, causing nitrous oxide (N$_2$O) and dinitrogen (N$_2$) emissions. Biogeochemical models allow field-scale estimates of N$_2$O and N$_2$, extrapolating important yet often limited experimental results. However, such predictions rely mostly on N$_2$O data, and the lack of N$_2$ data hinders validating total denitrification, which remain a major uncertainty for N budgets. This study investigated denitrification losses and N budgets in two tropical sugarcane systems using the Agricultural Production Systems sIMulator (APSIM) and the LandscapeDNDC (LDNDC) simulation framework using a unique dataset of both N$_2$O and N$_2$ emissions measured in the field over a complete growing season. Key soil N parameters influencing N$_2$O and N$_2$ emissions in APSIM and LDNDC were identified via global sensitivity analysis, followed by generalised likelihood uncertainty estimation to determine their posterior distributions using (i) N$_2$O data only and (ii) both N$_2$O and N$_2$ data. The simulation of N$_2$O emissions in APSIM and LDNDC were improved in both calibration approaches, resulting in 0.7–1.3 kg N ha$^{−1}$ of RMSE. ... mehrHowever, simulated N$_2$ emissions increased and agreed better with the observed values only when calibrated with both N$_2$O and N$_2$ (RMSE 30.1–45.0 kg N ha$^{−1}$ before calibration and 19.3–19.9 kg N ha$^{−1}$ after). The simulated N loss pathway shifted from leaching to N$_2$ emissions after calibration including N$_2$. The simulated N balance was larger when sugarcane residues were retained as compared to burning consistently across the different soil N parameter configurations. These findings indicate that biogeochemical models, when used with default soil N parameters or calibration limited to N$_2$O data, are likely to underestimate denitrification losses (>50 %), leading to a bias in N budgets simulation. Accurate N loss estimates are essential for understanding the long-term management impacts on soil organic matter dynamics, as demonstrated by the improved N budgets from both simulation models denote N mining when sugarcane is burnt, and the potential to sequester N when cane residues are retained. These outcomes emphasise the importance of integrating in-situ measurements of N$_2$O and N$_2$ in simulation exercises, ensuring more accurate N budget estimates across scales.