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控制其他参数为经验常数,利用迭代方法对主要光合作用参数最大羧化速率(V_(c max))及最大电子传递速率(J_(max))进行不同数值组合,将得到的多组模拟结果的逐日总初级生产力(GPP)分别与东北帽儿山落叶阔叶林的通量观测数据进行比较,实现对小时步长BEPSHourly模型V_(c max)和J_(max)的参数优化.结果表明:对于东北温带落叶阔叶林,当V_(c max)为41.1μmol·m~(-2)·s~(-1)、J_(max)为82.8μmol·m~(-2)·s~(-1)时,模拟的2011年逐日GPP与观测数据比较的均方根误差(RMSE)最小,为1.10 g C·m~(-2)·d~(-1),R~2最高,为0.95.经过光合作用参数V_(c max)和J_(max)优化后,BEPSHourly模型能更好地模拟GPP的季节变化.
Controlling other parameters as empirical constants, the maximum carboxylation rate (V_ (c max)) and the maximum electron transfer rate (J_ (max)) of the main photosynthesis parameters were numerically combined by iterative methods. Daily total primary productivity (GPP) was compared with flux observation data of the deciduous broad-leaved forest in Maoershan, northeast China respectively to optimize the parameters of V cmax and J max of the hourly step BEPSHourly model.The results showed that for the In the temperate deciduous broad-leaved forest in northeastern China, when V cmax is 41.1 μmol · m -2 · s -1 and J max is 82.8 μmol · m -2 · s ~ (- 1), the simulated root mean square error (RMSE) of daily GPP and observed data in 2011 was the lowest, which was 1.10 g C m -2 d -1 and the highest R 2 was 0.95 After optimization of the photosynthesis parameters V cmax and J max, the BEPSHourly model can better simulate the seasonal variation of GPP.