Modeling nitrous oxide emissions from rough fescue grassland soils subjected to long-term grazing of different intensities using the Soil and Water Assessment Tool (SWAT)
Shrestha, N.K., Thomas, B.W., Du, X., Hao, X., Wang, J. (2018). Modeling nitrous oxide emissions from rough fescue grassland soils subjected to long-term grazing of different intensities using the Soil and Water Assessment Tool (SWAT), 25(27), 27362-27377. http://dx.doi.org/10.1007/s11356-018-2719-2
© 2018, Springer-Verlag GmbH Germany, part of Springer Nature. Given the rising nitrous oxide (N2O) concentration in the atmosphere, it has become increasingly important to identify hot spots and hot moments of N2O emissions. With field measurements often failing to capture the spatiotemporal dynamics of N2O emissions, estimating them with modeling tools has become an attractive alternative. Therefore, we incorporated several semi-empirical equations to estimate N2O emissions with the Soil and Water Assessment Tool from nitrification and denitrification processes in soil. We then used the model to simulate soil moisture and the N2O flux from grassland soils subjected to long-term grazing (> 60 years) at different intensities in Alberta, Canada. Sensitivity analysis showed that parameters controlling the N2O flux from nitrification were most sensitive. On average, the accuracy of N2O emission simulations were found to be satisfactory, as indicated by the selected goodness-of-fit statistics and predictive uncertainty band, while the model simulated the soil moisture with slightly higher accuracy. As expected, emissions were higher from the plots with greater grazing intensity. Scenario analysis showed that the N2O emissions with the recommended fertilizer rate would dominate the emissions from the projected wetter and warmer future. The combined effects of fertilization and wetter and warmer climate scenarios would increase the current N2O emission levels by more than sixfold, which would be comparable to current emission levels from agricultural soils in similar regions.
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