State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process, School of Resource and Environmental Engineering, East China University of Science and Technology, Shanghai 200237, China; Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China.
State Environmental Protection Key Laboratory of Environmental Risk Assessment and Control on Chemical Process, School of Resource and Environmental Engineering, East China University of Science and Technology, Shanghai 200237, China.
Sci Total Environ. 2020 Feb 25;705:135993. doi: 10.1016/j.scitotenv.2019.135993. Epub 2019 Dec 7.
In this study, the generalized additive model (GAM) was used to analyze seasonal monitoring data from Lake Taihu, collected from 2010 to 2014, with the aim to explore the correlation between chlorophyll a (Chla) and other water quality parameters. The selected optimal multivariable GAM could effectively explain the concentration variation of Chla occurring during each season, and the interpretation degree followed the order: summer > autumn > spring > winter. The fitting results indicated that the concentration variation of Chla could reflect that of biochemical oxygen demand and chemical oxygen demand in all seasons. In addition, the total phosphorus showed strong ability to explain the concentration change of Chla in spring and summer, as the growth of algae would be affected when the concentration of phosphorus shifted high or low. Nitrogen showed strong ability to explain the variations in Chla concentration in autumn. The conclusions of the optimal multivariable GAM could provide decision basis for the eutrophication control. In other words, the prevention of eutrophication outbreaks could be carried out via the targeted control of key water pollutants. According to these results, the concentration of Chla was higher in northern and western lake during summer and autumn, the management should focus on nutrient input of adjacent rivers.
本研究采用广义加性模型（GAM）分析了 2010 年至 2014 年太湖逐月监测数据，旨在探讨叶绿素 a（Chla）与其他水质参数之间的相关性。选择的最优多变量 GAM 可以有效地解释每个季节 Chla 浓度的变化，解释程度的顺序为：夏季>秋季>春季>冬季。拟合结果表明，Chla 的浓度变化可以反映生化需氧量和化学需氧量在各个季节的变化。此外，总磷在春季和夏季对 Chla 浓度的变化具有很强的解释能力，因为当磷浓度升高或降低时，藻类的生长会受到影响。氮在秋季对 Chla 浓度变化具有很强的解释能力。最优多变量 GAM 的结论可为富营养化控制提供决策依据。换句话说，可以通过对关键水污染物的有针对性控制来防止富营养化的爆发。根据这些结果，夏季和秋季太湖北部和西部的 Chla 浓度较高，管理部门应重点关注相邻河流的养分输入。
