基于东北温带落叶阔叶林通量数据的BEPS 模型参数优化

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41.1 μmol·m^-2·s^-1、J_max 为82.8 μmol·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,R²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.

Parameter optimization of BEPS model based on the flux data of the temperate deciduous broad-leaved forest in Northeast China.

Keeping other parameters as empirical constants, different numerical combinations of the main photosynthetic parameters V_{c max} and J_max were conducted to estimate daily GPP by using the iteration method in this paper. To optimize V_{c max} and J_max in BEPSHourly model at hourly time steps, simulated daily GPP using different numerical combinations of the parameters were compared with the flux tower data obtained from the temperate deciduous broad-leaved forest of the Maoershan Forest Farm in Northeast China. Comparing the simulated daily GPP with the observed flux data in 2011, the results showed that optimal V_{c max} and J_max for the deciduous broad-leaved forest in Northeast China were 41.1 μmol·m^-2·s^-1 and 82.8 μmol·m^-2·s^-1 respectively with the minimal RMSE and the maximum R² of 1.10 g C·m^-2·d^-1 and 0.95. After V_{c max} and J_max optimization, BEPSHourly model simulated the seasonal variation of GPP better.