Parameter sensitivity study of the biogeochemical model in the China coastal seas
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摘要: 本文基于包含12个生态变量的生态模型,建立了高分辨率三维物理-生物地球化学模型,优化改进了浮游植物死亡过程和浮游动物摄食过程方程,分析了中国近海海洋生态环境变化特征,进行了生态参数敏感性实验。结果表明,生态模型中浮游植物浓度存在4个最敏感生态参数,即浮游动物的吸收率(ZooAE_N),浮游动物的新陈代谢率(ZooBM),浮游动物的最大比生长率(μ20)和叶绿素与浮游植物的最大比率(Chl2C_m),敏感率均超过了90%。进一步讨论和分析了生态模型对不同生态参数值的敏感范围。结果表明浮游动物的最大比生长率、浮游植物吸收硝酸盐的半饱和系数和小型碎屑再矿化率的敏感区间分别为0.1-1.2d-1,0.1-1.5(mmol/m3)-1和0.01-0.1d-1。基于SEATS站点从1998年9月到2000年7月的观测数据,对生态模型模拟结果进行了校验。结果表明基于参数优化后的生态模型可以节省计算资源,也可以有效地再现中国近海海洋生态过程特征。Abstract: In order to develop a coupled basin scale model of ocean circulation and biogeochemical cycling, we present a biogeochemical model including 12 components to study the ecosystem in the China coastal seas (CCS). The formulation of phytoplankton mortality and zooplankton growth are modified according to biological characteristics of CCS.The four sensitivity biological parameters, zooplankton assimilation efficiency rate (ZooAE_N), zooplankton basal metabolism rate (ZooBM), maximum specific growth rate of zooplankton (μ20) and maximum chlorophyll to carbon ratio (Chl2C_m) are obtained in sensitivity experiments for the phytoplankton, and experiments about the parameter μ20, half-saturation for phytoplankton NO3 uptake (KNO3) and remineralization rate of small detritusN (SDeRRN) are conducted. The results demonstrate that the biogeochemical model is quite sensitive to the zooplankton grazing parameter when it ranges from 0.1 to 1.2 d-1. The KNO3 and SDeRRN also play an important role in determining the nitrogen cycle within certain ranges.The sensitive interval of KNO3 is from 0.1 to 1.5(mmol/m3)-1, and interval of SEdRRN is from 0.01 and 0.1 d-1. The observational data from September 1998 to July 2000 obtained at SEATS station are used to validate the performance of biological model after parameters optimization. The results show that the modified model has a good capacity to reveal the biological process features, and the sensitivity analysis can save computational resources greatly during the model simulation.
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Key words:
- China coastal seas /
- biogeochemical model /
- parameter sensitivity
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