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Modeling methane and nitrous oxide emissions from direct‐seeded rice systems
Author(s) -
Simmonds Maegen B.,
Li Changsheng,
Lee Juhwan,
Six Johan,
Kessel Chris,
Linquist Bruce A.
Publication year - 2015
Publication title -
journal of geophysical research: biogeosciences
Language(s) - English
Resource type - Journals
eISSN - 2169-8961
pISSN - 2169-8953
DOI - 10.1002/2015jg002915
Subject(s) - seeding , environmental science , greenhouse gas , nitrous oxide , paddy field , fertilizer , methane , biomass (ecology) , agronomy , straw , drainage , atmospheric sciences , environmental engineering , chemistry , ecology , organic chemistry , biology , geology
Process‐based modeling of CH 4 and N 2 O 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 CH 4 and N 2 O emissions in direct‐seeded rice systems under various management practices remains a question. We empirically evaluated the denitrification‐decomposition model for estimating CH 4 and N 2 O 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 CH 4 emissions were similar ( R 2 = 0.85), but there was poor correspondence in fallow period CH 4 emissions and in seasonal and fallow period N 2 O emissions. Furthermore, management effects on seasonal CH 4 emissions were highly variable and not well represented by the model (0.2–465% absolute relative deviation). Specifically, simulated CH 4 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, N 2 O emissions were oversensitive to fertilizer N rate and field drainage. Sensitivity analysis showed that CH 4 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.