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

Abstract

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.

Greenhouse gas mitigation potential under different rice-crop rotation systems: from site experiment to model evaluation

“…The crop growth sub-model in the DNDC model predicts the crop phenological period, water and N demand/uptake, biomass accumulation and allocation, respiration, and litter production at a daily time step. Sensitivity tests from previous studies showed that CH 4 emissions are more sensitive to the ratio of root and plant C (Simmonds et al 2015). Increased rice growth slightly stimulates CH 4 emissions (Chen et al 2016).…”

Assessing the impacts of tillage and fertilization management on nitrous oxide emissions in a cornfield using the DNDC model

“… Deng et al, 2015]. However, the impacts of these management practices on N 2 O release form croplands remain controversial [ Venterea et al, ; Uzoma et al, ; Simmonds et al, ]. Consequently, a better assessment of N 2 O emission from croplands and associated management potential are essential for the development of sustainable agriculture and climate change mitigation.…”

Greenhouse Gas Emissions and Management Practices that Affect Emissions in US Rice Systems

“…This is a particular concern when quantifying the effects of mitigation options, as the various processes affecting emissions need to be fully understood in order for these models to provide reliable emissions estimates. Some examples of these modeling efforts for rice production include Simmonds et al (2015b) for DNDC, Kraus et al (2015) for Landscape DNDC, and Cheng et al (2013) for DAYCENT. To improve these models, Kraus et al (2015) suggested that they be coupled to more complex hydrological models to integrate the complex interactions between the soil, atmosphere, and hydrosphere.…”