2 research outputs found

    Mitigation Potential and Yield-Scaled Global Warming Potential of Early-Season Drainage from a Rice Paddy in Tamil Nadu, India

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    Water-intensive systems of rice cultivation are facing major challenges to increase rice grain yield under conditions of water scarcity while also reducing greenhouse gas (GHG) emissions. The adoption of effective irrigation strategies in the paddy rice system is one of the most promising options for mitigating GHG emissions while maintaining high crop yields. To evaluate the effect of different alternate wetting and drying (AWD) irrigation strategies on GHG emissions from paddy rice in dry and wet seasons, a field experiment was conducted at the Tamil Nadu Rice Research Institute (TRRI), Aduthurai, Tamil Nadu, India. Four irrigation treatments were included: One-AWD (one early drying period), Two-AWD (two early drying periods), Full-AWD (wetting and drying cycles throughout the rice season), and CF (continuous flooding). Different rice varieties were also tested in the experiment. In this study, we emphasized one factor (irrigation effect) that affects the dependent variable. The results show that early AWD treatments reduced methane (CH4) emissions by 35.7 to 51.5% in dry season and 18.5 to 20.1% in wet season, while full-AWD practice reduced CH4 emissions by 52.8 to 61.4% compared with CF. Full-AWD in dry season not only significantly reduced CH4 emission during that season, it also resulted in the decline of the early season emission in the succeeding wet season. Global warming potential (GWP) and yield-scaled GWP were reduced by early or full season AWD in both rice seasons. The GWP value from nitrous oxide (N2O) was relatively low compared to that from CH4 in both rice seasons. Rice yield was not affected by irrigation treatments although varietal differences in grain and straw yields were observed in both rice seasons. This study demonstrated that early season water managements are also effective in reducing CH4 and total GHG emissions without affecting rice yield

    Field Validation of the DNDC-Rice Model for Methane and Nitrous Oxide Emissions from Double-Cropping Paddy Rice under Different Irrigation Practices in Tamil Nadu, India

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    Two-year field experiments were conducted at Tamil Nadu Rice Research Institute, Aduthurai, Tamil Nadu, India, to evaluate the effect of continuous flooding (CF) and alternate wetting and drying (AWD) irrigation strategies on rice grain yield and greenhouse gas emissions from double-cropping paddy rice. Field observation results showed that AWD irrigation was found to reduce the total seasonal methane (CH4) emission by 22.3% to 56.2% compared with CF while maintaining rice yield. By using the observed two-year field data, validation of the DNDC-Rice model was conducted for CF and AWD practices. The model overestimated rice grain yield by 24% and 29% in CF and AWD, respectively, averaged over the rice-growing seasons compared to observed values. The simulated seasonal CH4 emissions for CF were 6.4% lower and 4.2% higher than observed values and for AWD were 9.3% and 12.7% lower in the summer and monsoon season, respectively. The relative deviation of simulated seasonal nitrous oxide (N2O) emissions from observed emissions in CF were 27% and −35% and in AWD were 267% and 234% in the summer and monsoon season, respectively. Although the DNDC-Rice model reasonably estimated the total CH4 emission in CF and reproduced the mitigation effect of AWD treatment on CH4 emissions well, the model did not adequately predict the total N2O emission under water-saving irrigation. In terms of global warming potential (GWP), nevertheless there was a good agreement between the simulated and observed values for both CF and AWD irrigations due to smaller contributions of N2O to the GWP compared with that of CH4. This study showed that the DNDC-Rice model could be used for the estimation of CH4 emissions, the primary source of GWP from double-cropping paddy rice under different water management conditions in the tropical regions.Peer Reviewe
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