Simulation of nitrous oxide emissions at field scale using the SPACSYS model.
Bottom Line: A comprehensive understanding of these processes embodied in an appropriate model can help develop agricultural mitigation strategies to reduce greenhouse gas emissions, and help with estimating emissions at landscape and regional scales.The comparison between the simulated and observed data suggested that the new module can provide a good representation of these processes and improve prediction of N2O emissions.The model provides an opportunity to estimate gaseous N emissions under a wide range of management scenarios in agriculture, and synthesises our understanding of the interaction and regulation of the processes.
Affiliation: Sustainable Soils and Grassland Systems Department, Rothamsted Research, North Wyke, Okehampton EX20 2SB, UK. Electronic address: Lianhai.Wu@rothamsted.ac.uk.Show MeSH
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Mentions: The dynamics of N2O emission for the various treatments demonstrated that in all the treatments, the total error in the simulated values was significantly less than the error inherent in the measured values (Fig. 7). Statistical analysis suggested that the simulations fit measured data reasonably well (Table 8) although there is no significant correlation in the Control treatment. Simulation values follow the same pattern as measured values (significant association) and describe the trend in the measured data better than the mean of the observations (positive value for EF and CD > 1) for the AN and Slurry treatments but not for the Control. Furthermore, RE values were within the 95% confidence interval of the data, indicating no bias. However, another indicator of model bias, MD, showed a slight bias towards over-estimation for the AN and Control treatments and towards under-estimation for the Slurry treatment. As N2O emissions were not simulated in the old version of the model, it is impossible to compare simulation results produced from the two versions.
Affiliation: Sustainable Soils and Grassland Systems Department, Rothamsted Research, North Wyke, Okehampton EX20 2SB, UK. Electronic address: Lianhai.Wu@rothamsted.ac.uk.