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引用本文:蒙凌凌,林育青,冯韬,张建云,严晗璐,何术锋,陈求稳.基于GOCI数据的太湖蓝藻垂向迁移特征及关键影响因素.湖泊科学,2024,36(2):353-363. DOI:10.18307/2024.0211
Meng Lingling,Lin Yuqing,Feng Tao,Zhang Jianyun,Yan Hanlu,He Shufeng,Chen Qiuwen.Vertical migration characteristics and key influencing factors of cyanobacteria in Lake Taihu based on GOCI data. J. Lake Sci.2024,36(2):353-363. DOI:10.18307/2024.0211
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基于GOCI数据的太湖蓝藻垂向迁移特征及关键影响因素
蒙凌凌1,2, 林育青3, 冯韬2, 张建云2, 严晗璐2, 何术锋2, 陈求稳2
1.重庆交通大学河海学院, 重庆 400074;2.南京水利科学研究院生态环境研究所, 南京 210029;3.水灾害防御全国重点实验室, 南京 210098
摘要:
蓝藻水华频繁暴发是太湖面临的主要环境问题之一,蓝藻聚集上浮是表层水华形成的前提。为探究蓝藻垂向迁移与水华日变化之间的关系,阐明蓝藻垂向迁移的关键影响因素,基于2015-2020年地球静止海洋彩色成像仪(GOCI)数据,分析了太湖不同湖区蓝藻水华日变化过程,发现太湖蓝藻水华垂向迁移的日变化主要呈现上升、下降、先上升后下降三种类型,且不同湖区存在差异。统计分析和偏最小二乘法结构方程模型(PLS-SEM)结果表明,水环境因子对蓝藻垂向迁移过程影响较小,累积光辐射是驱动蓝藻垂向迁移的主要气象因子。气温升高有利于蓝藻持续维持上浮能力,前一天风速较大且当天风速较小会加速蓝藻上浮。相较于沿岸湖区,湖心区受累积光辐射、风速的影响更大,蓝藻水华日变化过程更剧烈。本研究水环境因子数据为逐月数据,为深入探究水环境因子对蓝藻垂向迁移的影响后续还需进行高频监测研究。本文结果有助于探明浅水湖泊蓝藻水华形成机制,为富营养化湖泊蓝藻水华预测预警及治理提供理论支撑。
关键词:  太湖  GOCI  蓝藻水华  垂向迁移  气象因子  水环境因子
DOI:10.18307/2024.0211
分类号:
基金项目:国家自然科学基金项目(52121006,52209094)和国家重点研发计划项目(2022YFC3202104)联合资助。
Vertical migration characteristics and key influencing factors of cyanobacteria in Lake Taihu based on GOCI data
Meng Lingling1,2, Lin Yuqing3, Feng Tao2, Zhang Jianyun2, Yan Hanlu2, He Shufeng2, Chen Qiuwen2
1.College of River & Ocean Engineering, Chongqing Jiaotong University, Chongqing 400074, P.R. China;2.Eco-Environmental Research Department, Nanjing Hydraulic Research Institute, Nanjing 210029, P.R. China;3.The National Key Laboratory of Water Disaster Prevention, Nanjing 210098, P.R. China
Abstract:
The frequent outbreaks of cyanobacterial blooms are one of the major environmental problems in Lake Taihu, and the accumulation and upwelling of cyanobacteria is a prerequisite for the formation of surface water blooms. In order to investigate the relationship between cyanobacterial vertical migration and the daily variation of water blooms and to elucidate the key influencing factors of cyanobacterial vertical migration, the daily variation of cyanobacterial water blooms in different areas of Lake Taihu was analysed based on the 2015-2020 GOCI data, and it was found that the daily variation of cyanobacterial water blooms in Lake Taihu mainly showed three types: rising, falling, rising and then falling, and there were differences between different lake areas. The daily variation of cyanobacterial bloom migration in Lake Taihu was found to be mainly rising, falling and then declining. The results of the statistical analysis and partial least squares structural equation modelling (PLS-SEM) showed that the water environment factors had less influence on the cyanobacterial vertical migration process, cumulative light radiation was the main driver of cyanobacterial upwelling. Higher temperatures helped cyanobacteria sustain their upwelling ability; wind speed affected the vertical migration, with higher wind speed on the previous day and lower wind speed on the same day accelerating cyanobacterial upwelling. The central zone of the lake was more affected by cumulative light radiation and wind speed than the coastal zone, and the daily variation of cyanobacterial blooms was more dramatic. The data from this study are monthly data, and high frequency monitoring studies are needed to investigate the effect of environmental factors on the vertical migration of cyanobacteria. This study can help to understand the mechanism of cyanobacterial bloom formation in shallow lakes and provide theoretical support for the prediction and early warning of cyanobacterial blooms in eutrophic lakes and their management.
Key words:  Lake Taihu  GOCI  cyanobacterial bloom  vertical migration  meteorological factor  water environment factor
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