The System of Rice Intensification (SRI) is known as a climate-smart agricultural practice that increases rice production by changing the management of plants, soil, water, and nutrients. SRI water management relies on intermittent irrigation rather than on the continuous flooding of conventionally managed rice production. Different water table levels affect the soil conditions which contribute to different fluxes of greenhouse gas (GHG) emissions. This study estimated the impact on global warming potential (GWP) of GHG emissions from rice paddies when an SRI crop is managed with different water table levels. In this study, CO2 equivalence was assessed using a Simple Greenhouse Gas model, and an artificial neural network model for assessing CH4 and N2O. SRI paddy rice was grown in experimental pots under varying water table treatments, with the water table controlled by using Mariotte tubes set at + 2, 0, − 3, − 5, − 7, and − 12 cm from the soil surface. GHG emissions, which could be monitored more closely in pot trials than in fields, are a composite of the plants’ respiration, soil respiration (which is a result primarily of microbial activity), and the respiration that results from root exudates. With SRI practices, rice paddies can serve as a sink rather than a source for CH4 as seen from the negative values for CH4 emissions at all water table treatments. While there were N2O emissions with SRI practice, they were much less in terms of CO2 equivalence than the GWP reduction achieved by reducing CH4. Overall, under the experimental conditions the best water table level for SRI cultivation, with the most rice produced relative to GHG emissions, was − 5 cm from the soil surface. For each kg of grain produced, there were 0.80 kg CO2 eq of GHG emissions. By comparison, a normally flooded paddy field with usual crop management methods emits 1.97 kg CO2 eq per kg of grain produced, almost 150% more. This finding that a water table of − 5 cm is optimal will not necessarily apply for all field conditions, but the research addresses the desirability of seeking to optimize between GHG reductions and increased yield when growing paddy rice, and of developing appropriate methodology for achieving this composite objective.
ANN model Greenhouse gas emissions Paddy production SG model System of Rice Intensification
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This work was supported by a grant under PMDSU research project “Automation of Irrigation and Drainage to Improve the Productivity of Land and Water and Reduce Greenhouse Gas Emissions Factor” from the Ministry of Research, Technology and Higher Education, Indonesia. This work was further supported by UII through international conference travel grants 2018.
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