温室气体排放量空间尺度扩展方法的误差来源分析——以CH4MOD模型为例
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国家自然科学基金创新群体项目(40621001)资助


Sources of errors in spatial upscaling of greenhouse gas emission from soil—a case study of CH4MOD model
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    摘要:

    在估算区域温室气体排放量时往往需要利用模型,从可验证的点的排放量扩展至区域排放总量,这一尺度扩展过程中会产生误差。为比较不同扩展方法的误差大小,本研究收集江苏省内稻麦轮作体系水稻田59个样点的与CH4排放相关的信息,以CH4MOD模型模拟了CH4排放,比较了以下种尺度扩展方法的结果: 1)取区域内多个点的模型输入参数平均值,计算区域平均排放量;2)以区域内一个代表样点的参数输入模型,计算区域平均排放量。3)根据区域内各模型参数的统计学特征,随机生成100个虚拟点,以其输出结果的平均值为区域平均排放量,此为蒙特卡罗法。研究发现,以真实参数模拟计算的59个样点CH4排放量均值作为基准,则第一和第二种方法的相对误差分别为-19.60%和-19.74%,采用多点代面的蒙特卡罗法可将误差降低至3.29%。对第一和第二种方法的误差来源进行了分析。

    Abstract:

    Models are often used to estimate regional greenhouse gas emissions by scaling up verified point data to a region, and errors may arise in this spatial up-scaling process. To compare the error sizes of different up-scaling methods, we collected input data of 59 sites required by CH4MOD in Jiangsu Province of China to simulate CH4 emission from rice paddies, and applied three upscalling methods: 1) Take the average of all input parameters of 59 sites as the input parameters to model, then calculate the regional CH4 emission, which is average-parameter method; 2) Apply the parameters of one representative sample site to the model, and extend the estimation directly to the regional scale, which is typical-point method; 3) Generate 100 virtual sites randomly according to the statistical characteristics of the parameters of 59 samples, then input them to run the model 100 times and get the average of simulated results as the regional CH4 emission, which is the Monte Carlo method. The results showed that, when compared with the average of simulated results of the 59 individual sites, the average-parameter method and the typical-point method have a relative error of -19.60% and -19.74%, respectively, whereas the Monte Carlo method can effectively reduce the relative error to 3.29%. We also analyzed the error sources of average-parameter method and the typical-point method.

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郭 淼,遆超普,蔡祖聪,颜晓元.温室气体排放量空间尺度扩展方法的误差来源分析——以CH4MOD模型为例[J].土壤学报,2012,49(5):916-923. DOI:10.11766/trxb201109230360 Guo Miao, Ti Chaopu, Cai Zucong, Yan Xiaoyuan. Sources of errors in spatial upscaling of greenhouse gas emission from soil—a case study of CH4MOD model[J]. Acta Pedologica Sinica,2012,49(5):916-923.

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  • 收稿日期:2011-09-23
  • 最后修改日期:2011-12-15
  • 录用日期:2012-03-31
  • 在线发布日期: 2012-07-02
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