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Application of the Denitrification-Decomposition Model to Predict Carbon Dioxide Emissions under Alternative Straw Retention Methods
Straw retention has been shown to reduce carbon dioxide (CO(2)) emission from agricultural soils. But it remains a big challenge for models to effectively predict CO(2) emission fluxes under different straw retention methods. We used maize season data in the Griffith region, Australia, to test wheth...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3886247/ https://www.ncbi.nlm.nih.gov/pubmed/24453915 http://dx.doi.org/10.1155/2013/851901 |
Sumario: | Straw retention has been shown to reduce carbon dioxide (CO(2)) emission from agricultural soils. But it remains a big challenge for models to effectively predict CO(2) emission fluxes under different straw retention methods. We used maize season data in the Griffith region, Australia, to test whether the denitrification-decomposition (DNDC) model could simulate annual CO(2) emission. We also identified driving factors of CO(2) emission by correlation analysis and path analysis. We show that the DNDC model was able to simulate CO(2) emission under alternative straw retention scenarios. The correlation coefficients between simulated and observed daily values for treatments of straw burn and straw incorporation were 0.74 and 0.82, respectively, in the straw retention period and 0.72 and 0.83, respectively, in the crop growth period. The results also show that simulated values of annual CO(2) emission for straw burn and straw incorporation were 3.45 t C ha(−1) y(−1) and 2.13 t C ha(−1) y(−1), respectively. In addition the DNDC model was found to be more suitable in simulating CO(2) mission fluxes under straw incorporation. Finally the standard multiple regression describing the relationship between CO(2) emissions and factors found that soil mean temperature (SMT), daily mean temperature (T (mean)), and water-filled pore space (WFPS) were significant. |
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