Modeling methane and nitrous oxide emissions from direct-seeded rice systems

©2015. American Geophysical Union. All Rights Reserved. Process-based modeling of CH4 and N2O emissions from rice fields is a practical tool for conducting greenhouse gas inventories and estimating mitigation potentials of alternative practices at the scale of management and policy making. However,...

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Main Authors: Simmonds, M., Li, C., Lee, Juhwan, Six, J., Van Kessel, C., Linquist, B.
Format: Journal Article
Published: 2015
Online Access:http://hdl.handle.net/20.500.11937/75594
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author Simmonds, M.
Li, C.
Lee, Juhwan
Six, J.
Van Kessel, C.
Linquist, B.
author_facet Simmonds, M.
Li, C.
Lee, Juhwan
Six, J.
Van Kessel, C.
Linquist, B.
author_sort Simmonds, M.
building Curtin Institutional Repository
collection Online Access
description ©2015. American Geophysical Union. All Rights Reserved. Process-based modeling of CH4 and N2O emissions from rice fields is a practical tool for conducting greenhouse gas inventories and estimating mitigation potentials of alternative practices at the scale of management and policy making. However, the accuracy of these models in simulating CH4 and N2O emissions in direct-seeded rice systems under various management practices remains a question. We empirically evaluated the denitrification-decomposition model for estimating CH4 and N2O fluxes in California rice systems. Five and nine site-year combinations were used for calibration and validation, respectively. The model was parameterized for two cultivars, M206 and Koshihikari, and able to simulate 30% and 78% of the variation in measured yields, respectively. Overall, modeled and observed seasonal CH4 emissions were similar (R2 = 0.85), but there was poor correspondence in fallow period CH4 emissions and in seasonal and fallow period N2O emissions. Furthermore, management effects on seasonal CH4 emissions were highly variable and not well represented by the model (0.2-465% absolute relative deviation). Specifically, simulated CH4 emissions were oversensitive to fertilizer N rate but lacked sensitivity to the type of seeding system (dry seeding versus water seeding) and prior fallow period straw management. Additionally, N2O emissions were oversensitive to fertilizer N rate and field drainage. Sensitivity analysis showed that CH4 emissions were highly sensitive to changes in the root to total plant biomass ratio, suggesting that it is a significant source of model uncertainty. These findings have implications for model-directed field research that could improve model representation of paddy soils for application at larger spatial scales.
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spelling curtin-20.500.11937-755942019-05-29T07:51:09Z Modeling methane and nitrous oxide emissions from direct-seeded rice systems Simmonds, M. Li, C. Lee, Juhwan Six, J. Van Kessel, C. Linquist, B. ©2015. American Geophysical Union. All Rights Reserved. Process-based modeling of CH4 and N2O emissions from rice fields is a practical tool for conducting greenhouse gas inventories and estimating mitigation potentials of alternative practices at the scale of management and policy making. However, the accuracy of these models in simulating CH4 and N2O emissions in direct-seeded rice systems under various management practices remains a question. We empirically evaluated the denitrification-decomposition model for estimating CH4 and N2O fluxes in California rice systems. Five and nine site-year combinations were used for calibration and validation, respectively. The model was parameterized for two cultivars, M206 and Koshihikari, and able to simulate 30% and 78% of the variation in measured yields, respectively. Overall, modeled and observed seasonal CH4 emissions were similar (R2 = 0.85), but there was poor correspondence in fallow period CH4 emissions and in seasonal and fallow period N2O emissions. Furthermore, management effects on seasonal CH4 emissions were highly variable and not well represented by the model (0.2-465% absolute relative deviation). Specifically, simulated CH4 emissions were oversensitive to fertilizer N rate but lacked sensitivity to the type of seeding system (dry seeding versus water seeding) and prior fallow period straw management. Additionally, N2O emissions were oversensitive to fertilizer N rate and field drainage. Sensitivity analysis showed that CH4 emissions were highly sensitive to changes in the root to total plant biomass ratio, suggesting that it is a significant source of model uncertainty. These findings have implications for model-directed field research that could improve model representation of paddy soils for application at larger spatial scales. 2015 Journal Article http://hdl.handle.net/20.500.11937/75594 10.1002/2015JG002915 fulltext
spellingShingle Simmonds, M.
Li, C.
Lee, Juhwan
Six, J.
Van Kessel, C.
Linquist, B.
Modeling methane and nitrous oxide emissions from direct-seeded rice systems
title Modeling methane and nitrous oxide emissions from direct-seeded rice systems
title_full Modeling methane and nitrous oxide emissions from direct-seeded rice systems
title_fullStr Modeling methane and nitrous oxide emissions from direct-seeded rice systems
title_full_unstemmed Modeling methane and nitrous oxide emissions from direct-seeded rice systems
title_short Modeling methane and nitrous oxide emissions from direct-seeded rice systems
title_sort modeling methane and nitrous oxide emissions from direct-seeded rice systems
url http://hdl.handle.net/20.500.11937/75594