水华过程水质参数与浮游植物定量关系的研究——以太湖梅梁湾为例

考虑到太湖水华暴发过程中水质参数（如营养盐或水体理化参数）对浮游植物增殖的滞后效应，利用有滞后变量参与的格兰杰因果关系检验和向量自回归模型，分析了太湖梅梁湾湖区2000年~2012年的监测数据，探讨了湖泊水质参数对于水华暴发的影响和定量关系.结果发现，表征浮游植物生物量的叶绿素a（Chl-a）浓度与总磷（TP）、氮磷比（N/P）、水温（WT）之间存在长期的均衡关系，格兰杰因果关系模型和向量自回归模型（VAR）的结果显示，水体中TP浓度、N/P和WT是Chl-a含量变化的格兰杰原因，上述结果提供了湖泊水质参数与蓝藻生物量的定量关系，在其他水质参数保持不变的情况下，约1%湖泊TP含量、N/P和水温的变化分别造成0.97%、0.078%和0.55%的浮游植物生物量的变化.本研究为水华暴发研究过程中水质参数的定量化影响提供一个新颖的视角，考虑了时间滞后变量的时间序列分析方法也可以加深对水华暴发过程的理解.

The quantitative relation of aquatic parameters and phytoplankton biomass in the process of algal blooms-the case of Meiliang Bay in Taihu Lake

Considering the lag effects of various aquatic variables (nutrients, physical or chemical parameters) to proliferation of phytoplankton in algal blooms, time series analysis was applied in this study to analyze the influence and quantitative relation of aquatic variables to algal blooms by using monitoring data of Meiliang Bay in Taihu Lake (Ch:Taihu) from 2000 to 2012. The results showed that there was a long-run equilibrium relationship between concentration of Chl-a and total phosphorus (TP), N/P, water temperature (WT). The results of Granger causality models and vector autoregression model demonstrated that concentration of TP, N/P and WT were the Granger causes of Chl-a. The results also provided an accurate quantitative equation of these variables. Assuming that other variables remain constant, if concentration of TP, N/P and WT were increased by 1%, concentration of Chl-a would increase by 0.97%, 0.078% and 0.55% respectively. This study provided a new, alternative method to explore the influence of aquatic parameters to algal blooms and could advance the understanding of process of algal blooms by taking lagged variables of time series into account.