Abstract Methane （CH4） emissions from paddy rice fields substantially contribute to the dramatic increase of this greenhouse gas in the atmosphere. Due to great concern about climate change, it is necessary to predict the effects of the dramatic increase in atmospheric carbon dioxide （CO2） on CH4 emissions from paddy rice fields. CH4MOD 1.0 is the most widely validated model for simulating CH4 emissions from paddy rice fields exposed to ambient CO2 （hereinafter referred to as aCO2）. We upgraded the model to CH4MOD 2.0 by： （a） modifying the description of the influences of soil Eh and the water regime on CH4 production; （b） adding new features to reflect the regulatory effects of atmospheric CO2 upon methanogenic substrates, soil Eh during drainages, and vascular CH4 transport; and （c） adding a new feature to simulate the influences of nitrogen （N） addition rates on methanogenic substrates under elevated CO2 （hereinafter referred to as eCO2） condition. Validation with 109 observation cases under aC02 condition showed that CHaMOD 2.0 possessed a minor systematic bias in the prediction of seasonally accumulated methane emissions （SAM）. Validation with observations in free-air CO2 enrichment （FACE） experiments in temperate and subtropical climates showed that CH4MOD 2.0 successfully simulated the effects of eCO2 upon SAM from paddy rice fields incorporated with various levels of previous crop residues and/or N fertilizer. Our results imply that CH4MOD 2.0 provides a potential approach for estimating of the effects of elevated atmospheric CO2 upon CHa emissions from regional or global paddy rice fields with various management practices in a changing climate.
In order to numerically simulate daily nitrous oxide （N2O） emission from a rice-winter wheat rotation cropping system, a process-based site model was developed （referred to as IAP-N-GAS） to track the movement and transformation of several forms of nitrogen in the agro-eeosystem, which is affected by climate, soil, crop growth and management practices. The simulation of daily N2O fluxes, along with key daily environmental variables, was validated with three-year observations conducted in East China. The validation demonstrated that the model simulated well daily solar radiation, soil temperature and moisture, and also captured the dynamics and magnitude of accumulated rice aboveground biomass and mineral nitrogen in the soil. The simulated daily N2O emissions over all three years investigated were generally in good agreement with field observations. Particularly well simulated were the peak N2O emissions induced by fertilizations, rainfall events or mid-season drainages. The model simulation also represented closely the inter-annuM variation in N2O emission. These validations imply that the model has the capability to capture the general characteristics of N2O emission from a typical rice-wheat rotation agro-ecosystem. Sensitivity analyses revealed that the simulated N2O emission is most sensitive to the fertilizer application rate and the soil organic matter content, but it is much less sensitive to variations in soil pH and texture, temperature, precipitation and crop residue incorporation rate under local conditions.
