ABSTRACT:The DayCent ecosystem model, widely tested in upland agroecosystems, was recently updated to simulate waterlogged soils. We evaluated the new version in a paddy rice experiment in Southern Brazil. DayCent was used to simulate rice yield, soil organic carbon (SOC), and soil CH 4 fluxes. Model calibration was conducted with a multiple-year dataset from the conventional tillage treatment, followed by a validation phase with data from the no-tillage treatment. Model performance was assessed with statistics commonly used in modeling studies: root mean square error (RMSE), model efficiency (EF), and mean difference (M). In general, DayCent slightly underestimated rice yields under no-tillage (by 0.07 Mg ha -1 , or 9.2 %) and slightly overestimated soil C stocks, especially in the first years of the experiment. A comparison of observed and simulated CH 4 daily fluxes showed that DayCent could simulate the general patterns of soil CH 4 fluxes with slight discrepancies. Daily soil CH 4 fluxes were overestimated by 0.43 kg ha -1 day -1 (12 %). Growth-season CH 4 emissions under no-tillage were also somewhat overestimated (11 % or 45.29 kg ha -1). We conclude that DayCent simulated SOC, rice yield, and CH 4 with some inaccuracies, but the overall performance was considered adequate. However, the model failed to represent the observed potential of no-tillage to mitigate CH 4 emissions, possibly because model algorithms could not capture the actual field conditions derived from no-tillage management, such as soil redox potential, plant senescence, and surface placement of plant residue.