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基于植被生理生态过程的模型包含较多参数,合理的参数取值能够极大地提高模型的模拟能力.参数敏感性分析可以全面分析模型参数对模拟结果的影响程度,在筛选模型敏感参数过程中起到重要作用.本研究以模拟吉林省汪清林业局长白落叶松林净初级生产力(NPP)为例,分析了BIOME-BGC模型的参数敏感性.首先利用样地实测NPP数据与模拟值进行对比分析,检验模型对长白落叶松林NPP的模拟能力;然后利用Morris法和EFAST法筛选出BIOME-BGC模型中对长白落叶松林NPP影响较大的敏感参数.在此基础上,通过EFAST法对所有筛选出的参数进行定量的敏感性分析,计算了敏感参数的全局敏感性指数、一阶敏感性指数和二阶敏感性指数.结果表明:BIOME-BGC模型能够较好地模拟研究区内长白落叶松林NPP的变化趋势;Morris法可以在样本量较少的情况下实现对BIOME-BGC模型敏感参数的筛选,而EFAST法可以定量分析BIOME-BGC模型中单个参数以及不同参数之间交互作用对模拟结果的影响程度;BIOME-BGC模型中对长白落叶松林NPP影响较大的敏感参数为新生茎与叶片的碳分配比和叶片碳氮比,且二者之间的交互作用明显大于其他参数之间的交互作用.
The model based on the physiological and ecological processes of vegetation contains more parameters, and reasonable parameter values can greatly improve the simulation ability of the model.Parametric sensitivity analysis can comprehensively analyze the impact of model parameters on the simulation results, and plays an important role in screening sensitive parameters of the model To an important role.This study analyzed the parameter sensitivity of the BIOME-BGC model by taking the net primary productivity (NPP) of the Larix olgensis plantation of Wangqing Forestry Bureau of Jilin Province as an example.Firstly, using the NPP data of the sample plots and the simulated values for comparative analysis, Then the Morris method and EFAST method were used to select the most sensitive parameters in the BIOME-BGC model which affected the NPP of Larix olgensis.According to the results of EFAST, The sensitivity of the parameter was evaluated and the global sensitivity index, first-order sensitivity index and second-order sensitivity index were calculated.The results showed that the BIOME-BGC model could well simulate the NPP The Morris method can be used to screen the sensitive parameters of BIOME-BGC model with a small sample size, while EFAST The single parameter in BIOME-BGC model and the effect of interaction between different parameters on the simulation results can be quantitatively analyzed. The sensitive parameters in BIOME-BGC model which have greater influence on NPP of Larix olgensis are the carbon allocation ratio of new stem and leaf and Leaf carbon and nitrogen ratio, and the interaction between the two is significantly greater than the interaction between other parameters.