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李婷婷, 黄耀, 张稳, 宋长春. 自然湿地甲烷排放模拟研究——模型的修正与验证[J]. 气候与环境研究, 2010, 15(3): 246-256. DOI: 10.3878/j.issn.1006-9585.2010.03.04
引用本文: 李婷婷, 黄耀, 张稳, 宋长春. 自然湿地甲烷排放模拟研究——模型的修正与验证[J]. 气候与环境研究, 2010, 15(3): 246-256. DOI: 10.3878/j.issn.1006-9585.2010.03.04
LI Tingting, HUANG Yao, ZHANG Wen, SONG Changchun. Modeling CH4 Emissions from Natural Wetlands—Model Modification and Validation[J]. Climatic and Environmental Research, 2010, 15(3): 246-256. DOI: 10.3878/j.issn.1006-9585.2010.03.04
Citation: LI Tingting, HUANG Yao, ZHANG Wen, SONG Changchun. Modeling CH4 Emissions from Natural Wetlands—Model Modification and Validation[J]. Climatic and Environmental Research, 2010, 15(3): 246-256. DOI: 10.3878/j.issn.1006-9585.2010.03.04

自然湿地甲烷排放模拟研究——模型的修正与验证

Modeling CH4 Emissions from Natural Wetlands—Model Modification and Validation

  • 摘要: 以稻田甲烷排放模型(CH4MOD)框架为基础,基于稻田同自然湿地产甲烷底物、植物生长过程以及土壤氧化还原电位变化过程之间的差异,对模型进行了修改,建立自然湿地甲烷排放模型(CH4MODwetland)。利用三江平原淡水沼泽和若尔盖高原泥炭沼泽的甲烷排放观测数据对模型进行了验证。结果表明:模型可以有效地模拟三江平原沼泽甲烷排放的季节和年际变化特征,但是在若尔盖高原模拟效果欠佳;模拟和观测的甲烷排放季节总量在两地均有良好的一致性,线性相关系数R2为0.96(n=7,显著性水平p<0.001);模拟值和实测值之间的均方根误差,平均偏差和模型效率分别为14.1%, -6.7%和0.95。

     

    Abstract: Wetlands are one of the most important sources of atmospheric CH4, but the quantity of this source is still highly uncertain. We developed a biogeophysical model called CH4MODwetland to simulate CH4 emissions from natural wetlands based on CH4MOD that simulates CH4 emissions from irrigated rice paddies. The development of CH4MODwetland focused on the supply of methanogenic substrates, the process of vegetation growth, and the variation of soil redox potential that differ from the rice paddy. CH4MODwetland was validated against independent datasets from Sanjiang Plain and Zoigê Plateau. Model validation showed that the observed seasonal and interannual variations of CH4 emissions from marshland in northeastern China were well captured, but that from peatland in southwest plateau of China were less well; Nevertheless, modeled seasonal amount of CH4 emissions agreed observed well in the two places, yielding an R2 of 0.96 (n=7, p<0.001); The root-mean-squared error, mean deviation, and model efficiency between modeled and observed values are 14.1%, -6.7%, and 0.95, respectively.

     

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