Mitigation of greenhouse gas emissions from agriculture requires an understanding of spatial-temporal dynamics of nitrous oxide (N2O) emissions. Process-based models can quantify N2O emissions from agricultural soils but have rarely been applied to regions with highly diverse agriculture. In this study, a process-based biogeochemical model, DeNitrification-DeComposition (DNDC), was applied to quantify spatial-temporal dynamics of direct N2O emissions from California cropland employing a wide range of cropping systems. DNDC simulated direct N2O emissions from nitrogen (N) inputs through applications of synthetic fertilizers and crop residues during 2000-2015 by linking the model with a spatial-temporal differentiated database containing data on weather, crop areas, soil properties, and management. Simulated direct N2O emissions ranged from 3,830 to 7,875 tonnes N2O-N yr-1, representing 0.73%-1.21% of the N inputs. N2O emission rates were higher for hay and field crops and lower for orchard and vineyard. State cropland total N2O emissions showed a decreasing trend primarily driven by reductions of cropland area and N inputs, the trend toward growing more orchard, and changes in irrigation. Annual direct N2O emissions declined by 47% from 2000 to 2015. Simulations showed N2O emission variations could be explained not only by cropland area and N fertilizer inputs but also climate, soil properties, and management besides N fertilization. The detailed spatial-temporal emission dynamics and driving factors provide knowledge toward effective N2O mitigation and highlight the importance of coupling process-based models with high-resolution data for characterizing the spatial-temporal variability of N2O emissions in regions with diverse croplands.
Keywords: California; biogeochemical modeling; direct N2O emission; diverse agricultural ecosystems; spatial‐temporal variations.
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