陈晨　　　　　　　沃文伟　　　　　范文义

(东北林业大学，哈尔滨，150040)　　　　(黑龙江省水文水资源勘测局)　　　　(东北林业大学)



森林生态系统碳循环模型参数优化1)

陈晨沃文伟范文义

(东北林业大学，哈尔滨，150040)(黑龙江省水文水资源勘测局)(东北林业大学)

摘要以2011年帽儿山生态站通量塔观测的二氧化碳通量(总初级生产力和显热通量)数据为基础，使用集合卡尔曼滤波的顺序同化技术，对北方生态系统生产力(BEPS)模型的关键参数进行优化。结果表明：参数在季节尺度上变化显著，通常在展叶期迅速增大，夏季达到稳定，秋季落叶期降低。根据优化的参数，模型的总初级生产力、生态系统呼吸的模拟值精度显著提高，精度分别达到91%、96%，比优化之前的模拟值精度提高了8%和11%。说明集合卡尔曼滤波的参数优化可以明显改善模型模拟碳水通量的能力。

关键词BEPS模型；通量数据；集合卡尔曼滤波；数据同化；季节变化

分类号S715.3

Optimization of Ecosystem Carbon Cycle Model Parameters//

Chen Chen

(Northeast Forestry University, Harbin 150040, P. R. China); Wo Wenwei(Hydrology and Water Resources Survey Bureau of Heilongjiang Province); Fan Wenyi(Northeast Forestry University)//

Journal of Northeast Forestry University，2016,44(5)：15-19.

With CO2flux observation data (gross primary productivity (GPP) and sensible heat flux (LE)) from Maoershan Ecosystem Station flux tower in 2011, we used sequential data assimilation and ensemble Kalman filter technique to optimize some of the key parameters of the Boreal Ecosystem Productivity Simulator (BEPS) model by taking into account the errors in inputs, parameters, and observations. We optimized the parameters by data assimilation including maximum photosynthetic carboxylation rate (Vcmax), and the slope of stomatal conductance and net photosynthetic rate (M). Parameters were optimized in daily steps. The parameters varied significantly at seasonal scales, was with usually rapid increase in leaf expansion period, and in summer would reach a steady and decline in senescence of leaves. According to optimized parameters, model simulated value of GPP and RE flux were significantly increased. GPP and RE simulated accuracy reached 91% and 96%, and the precision values of the simulated values before optimization were increased by 8% and 11%, respectively. Ensemble Kalman filter parameter optimization could significantly improve model capacity in simulating the carbon and water fluxes.

KeywordsBEPS model； Flux data； Ensemble Kalman filter； Data assimilation； Seasonal variability

森林生态系统是陆地生态系统的主体，在维持全球碳平衡、减缓全球气候变化等方面起到重要的作用[1-2]，而生态系统和大气之间的碳、水和能量交换对地球气候影响显著[3]。关于森林生态系统的碳水能量循环及其驱动机制的研究已经成为当今全球气候变化研究的重点问题[4]。

陆地生态系统模型已经广泛应用于模拟生态系统生产力、水分消耗以及温室气体的排放。由于生态过程的复杂性及其时空变异的特征，模型参数值通常存在空间和时间的异质性，在应用到大区域的时候，这些参数通常是不能直接测量的(如冠层级别的参数)，但又显著地影响模型模拟碳、水和能量通量的能力。……