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A process-based biogeochemistry model, DNDC-Rice, was modified to simulate rice growth and CH4 emission under elevated atmospheric CO2 concentration, [CO2]. It simulates the effect of [CO2] on the photosynthetic rate by an empirical parameter (β-factor), which is calibrated based on observed biomass under varied [CO2]. Rice growth is linked to CH4 emission through rhizodeposition of C and the rice plant’s conductance of CH4, which depend on the root biomass and tiller density, respectively. DNDC-Rice was tested using five years of rice growth data and four years of CH4 emission data from a free-air CO2 enrichment (FACE) experiment in a Japanese rice field, in which [CO2] was controlled at 200 ppm above ambient. In the experiment, FACE increased the average final aboveground biomass by 11% and seasonal CH4 emission by 22%. By calibrating the β-factor of photosynthesis calculation, DNDC-Rice successfully predicted the final aboveground biomass across the years and the [CO2] treatments. However, it underestimated the enhancement of CH4 emission by FACE, to be only 9% as the average over the four years. We found this discrepancy to be attributed to the modeling of photosynthesis, root growth and exudation, and rice tiller conductance of CH4 under elevated [CO2]. These results indicate that DNDC-Rice needs to be further refined using detailed data on these plant processes in order to simulate future CH4 emission under elevated [CO2].

Application of a process-based biogeochemistry model, DNDC-Rice, to a rice field under free-air CO2 enrichment (FACE)