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18 September 2018 Simulation of methane emissions from double-rice cropping system in southern China during the past 50 years by DNDC model
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Abstract
Paddy field is a major source of methane (CH4) emission. Methane emission in paddy fields accounts for 31.5% of agricultural methane emissions in China. Double-rice cropping system is a part of the major paddy systems in China for rice production, accounting for only 27% of the national rice planting area while CH4 emission accounting for 60% of the national CH4 emission. Given the importance of reducing CH4 emission from double rice to mitigate climate warming, it is necessary to investigate the impact of climate change on CH4 emission of double cropping paddy field in the future. In this study, the denitrification–decomposition (DNDC-a process-based biogeochemistry model) model is employed to simulate the CH4 emission from double-rice cropping system in southern China based on the historical meteorological data of the past 50 years (1966-2015) and the observational data of rice agricultural stations in the study area. Then we combined the outputs with Geographic Information System (GIS) technology to analyze the impact of climate change on CH4 emissions from the double rice paddy. The results indicate that change of the average temperature is associated with the change of CH4 emission across the growing period of double rice paddy. Methane has increased by 8.4% in the main producing provinces of double cropping rice in southern China. Zhejiang has increased by up to 20.8%. Anhui, Hubei, Hunan has increased by 10.6%, 10.2% and 11.4%. The relatively small increase in Fujian and Yunnan is only 5%. However, in the low latitudes of Guangxi, and Guangdong province, there was a slight reduction in CH4 emission.
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Xiangyi Wang, Zhan Tian, Dongli Fan, Meifang Hou, Yilong Niu, Hanqing Xu, Biao Hu, Runhe Shi, and Maosi Chen "Simulation of methane emissions from double-rice cropping system in southern China during the past 50 years by DNDC model", Proc. SPIE 10767, Remote Sensing and Modeling of Ecosystems for Sustainability XV, 1076716 (18 September 2018); https://doi.org/10.1117/12.2320158
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