DNDC-Rice model is a process-based model which can estimate CH₄ emissions from paddy fields. However, there are few studies evaluating CH₄ emission using the model where rice cultivation is possible two or three times a year. We aimed to investigate the effect of model parameters on the estimation of CH₄ emission from the paddy field in Tamil Nadu, southern India and to evaluate the impact of CH₄ emission from the region on global CH₄ emission. We used long term measurement of CH₄ flux using the eddy covariance technique in the field from 2016 to 2021 for the model analysis. Our study showed that calibration of the cultivar-specific parameters improved model CH₄ emission estimate. The magnitude of overestimation of CH₄ emission was decreased by reproducing the heterogeneity of the soil trivalent iron content. Simulated cumulative CH₄ emission in each cropping season varied −2.4%-+63.95% compared to the measured CH₄ flux. Our results suggest that simulated CH₄ flux tends to underestimate CH₄ emission from the paddy field of the region because the model could not well simulate burst CH₄ emission in the intercropping period.