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洪湖水质与气象因子对叶绿素a浓度的相互作用:基于分段结构方程模型-广义相加模型耦合模型

The interaction between water quality and meteorological factors on chlorophyll-a concentration in Honghu Lake: based on PiecewiseSEM-generalized additive model coupling model.

作者信息

Chen Yanfei, Ding Jiawei, He Chao, Wang Qing, Zhu Wenlong, Xu Shubang

机构信息

Hubei Key Laboratory of Petroleum Geochemistry and Environment, Yangtze University, Wuhan, 430100, China.

出版信息

Environ Monit Assess. 2024 Sep 27;196(10):984. doi: 10.1007/s10661-024-13136-6.

Abstract

In order to explore the interactive effects of environmental factors on the chlorophyll-a (Chl-a) concentration variation in Honghu Lake, this study was based on the monitoring data of Chl-a mass concentration and water quality factors (water temperature, pH, dissolved oxygen, permanganate index, total nitrogen, total phosphorus) and meteorological factors (evaporation, precipitation, sunshine hours, average wind speed) at three research sites (Dakou, Chatan Island, Lantian) in Honghu Lake from January 2010 to December 2019. Time series analysis, piecewise structural equation model (PiecewiseSEM), and generalized additive model (GAM) were used to quantitatively study the spatial and temporal changes of different environmental factors and their interaction with chlorophyll-a concentration in Honghu Lake. The results showed that the effects of TN and DO on Chl-a at Dakou and Chatan Island were more significant than other environmental meteorological factors, while the effects of DO and COD on Chl-a at Lantian were more obvious. At the same time, it was found that Chl-a had a non-linear relationship with TN and DO at Dakou and Chatan Island, a non-linear relationship with DO at Lantian, and a linear relationship with COD. The interaction effect of dominant environmental meteorological factors on Chl-a was significantly higher than that of a single factor, and the explanation rates were 80.6%, 72.8%, and 64.6%, respectively. In conclusion, based on the Piecewise SEM and GAM model, it not only can reveal the influence of the interaction of influencing factors on the change of Chl-a concentration, but also has important significance for the early warning and control of lake eutrophication.

摘要

为探究环境因子对洪湖叶绿素-a(Chl-a)浓度变化的交互作用,本研究基于2010年1月至2019年12月洪湖大口、茶坛岛、蓝田3个研究站点的Chl-a质量浓度及水质因子(水温、pH值、溶解氧、高锰酸盐指数、总氮、总磷)和气象因子(蒸发量、降水量、日照时数、平均风速)的监测数据。采用时间序列分析、分段结构方程模型(PiecewiseSEM)和广义相加模型(GAM)定量研究洪湖不同环境因子的时空变化及其与叶绿素-a浓度的相互作用。结果表明,大口和茶坛岛TN和DO对Chl-a的影响比其他环境气象因子更显著,而蓝田DO和COD对Chl-a的影响更明显。同时发现,大口和茶坛岛Chl-a与TN和DO呈非线性关系,蓝田Chl-a与DO呈非线性关系,与COD呈线性关系。主导环境气象因子对Chl-a的交互作用显著高于单一因子,解释率分别为80.6%、72.8%和64.6%。综上,基于分段结构方程模型和广义相加模型,不仅能揭示影响因子交互作用对Chl-a浓度变化的影响,而且对湖泊富营养化预警与控制具有重要意义。

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