| 引用本文: | 夏威,张萌,周慜,吴俊伟,姚娜,冯兵,欧阳涛,刘足根,张秋根.大型深水湖库溶解氧时空变化及驱动因素:以江西仙女湖为例.湖泊科学,2023,35(3):874-885. DOI:10.18307/2023.0330 |
| Xia Wei,Zhang Meng,Zhou Min,Wu Junwei,Yao Na,Feng Bing,Ouyang Tao,Liu Zugen,Zhang Qiugen.Spatio-temporal dynamics of dissolved oxygen and its influencing factors in Lake Xiannv Jiangxi, China. J. Lake Sci.2023,35(3):874-885. DOI:10.18307/2023.0330 |
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| 大型深水湖库溶解氧时空变化及驱动因素:以江西仙女湖为例 |
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夏威1,2,3, 张萌1,2,3, 周慜2,3, 吴俊伟2,3, 姚娜2,3, 冯兵2,3, 欧阳涛4, 刘足根2,3, 张秋根1
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1.南昌航空大学环境与化学工程学院, 南昌 330063;2.江西省生态环境科学研究与规划院, 南昌 330039;3.江西省环境保护工程技术研究中心, 南昌 330039;4.江西省新余市生态环境监测中心, 新余 336500
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| 摘要: |
| 为探究深水湖库溶解氧的时空分布规律及其主控因素，本文以南方亚热带大型深水湖库——江西省仙女湖为研究对象，基于2008—2021年仙女湖4个国控站点溶解氧的历史数据分析其年际变化的规律及原因；另于2016年水污染事件发生前（2014年5月-2015年4月）及水污染事件结束后（2018年1月-2018年12月）对仙女湖进行加密逐月监测，采用结构方程模型（SEM）分析仙女湖溶解氧的主要驱动因素。研究结果表明，2008—2021年仙女湖水体溶解氧浓度先下降后上升，变化范围为5.1~18.7 mg/L，季节均值为春季>冬季>秋季>夏季。水污染事件发生前高溶解氧区域多出现在舞龙湖湖心区及湖出口位置，水温、叶绿素a浓度和浊度是溶解氧浓度变化的主要驱动因素；水污染事件结束后高溶解氧区域多出现在钤阳湖及舞龙湖枝杈状湖湾位置，叶绿素a浓度及营养盐浓度成为溶解氧浓度变化的主要驱动因素；而pH与溶解氧主要是协同变化的关系。根据对仙女湖最深点（江口）的垂向监测结果，溶解氧的垂向差异为夏季>秋季>春季>冬季，夏、秋季在5 m以下出现低溶解氧（DO<5 mg/L）区域，且夏季观察到明显的温跃层及温跃层内溶解氧的极小值现象。总体来说，水污染事件使得仙女湖水体营养平衡被打破，营养盐浓度大幅上升导致的浮游植物数量增多是仙女湖水体表层溶解氧浓度升高的主要原因，而深水溶解氧浓度变化则与水温、水深密切相关。 |
| 关键词: 仙女湖 溶解氧 深水水库 驱动因素 富营养化 结构方程模型 |
| DOI：10.18307/2023.0330 |
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| 基金项目:江西省重点研发计划项目（20203BBG72W007）、江西省主要学科学术和技术带头人资助项目（20182BCB22016）和江西省科技计划项目（20161BBG70098）联合资助。 |
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| Spatio-temporal dynamics of dissolved oxygen and its influencing factors in Lake Xiannv Jiangxi, China |
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Xia Wei1,2,3, Zhang Meng1,2,3, Zhou Min2,3, Wu Junwei2,3, Yao Na2,3, Feng Bing2,3, Ouyang Tao4, Liu Zugen2,3, Zhang Qiugen1
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1.School of Environmental & Chemical Engineering, Nanchang Hangkong University, Nanchang 330063, P. R. China;2.Jiangxi Academy of Eco-Environmental Sciences & Planning, Nanchang 330039, P. R. China;3.Environmental Pollution Engineering Center of Jiangxi, Nanchang 330039, P. R. China;4.Xinyu Municipal Eco-Environmental Monitoring Center of Jiangxi, Xinyu 336500, P. R. China
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| Abstract: |
| To systematically explore the spatial-temporal distribution and main controlling factors of dissolved oxygen (DO) in deep lakes, we take Lake Xiannv, a large subtropical reservoir in south China, as the research object. By collecting the historical data of DO at four state-controlled points in Lake Xiannv from 2008 to 2021 to analyze its interannual changes. We also conducted intensive monthly monitoring of Lake Xiannv from May 2014 to April 2015 and from January 2018 to December 2018, which were before and after the water pollution accident in 2016. The factors influencing DO in Lake Xiannv were quantitatively analyzed by the structural equation model (SEM). Results showed that from 2008 to 2021, the DO concentration of Lake Xiannv first decreased and then increased, with a range of 5.1-18.7 mg/L, and the seasonal means were spring>winter>autumn>summer. Before the water pollution accident, the DO concentration in the central area and the outlet of Lake Wulong was higher and water temperature, chlorophyll-a and turbidity were the main driving factors for the change of DO. After the accident, the DO concentration in Lake Qianyang and the bays of Lake Wulong was higher and chlorophyll-a and water nutrition were the main driving factors for the change of DO. There are common changes between pH and DO. The vertical monitoring results of the deepest point (Jiangkou) showed that the vertical changes of water temperature and DO in Lake Xiannv were summer>autumn>spring>winter. We found that there were low DO (DO<5 mg/L) zones below 5 m of the lake in summer and autumn, thermocline and metalimnetic oxygen minimum (MOM) were observed in summer. In general, the water pollution accident broke the nutrient balance of Lake Xiannv, and the large increase in nutrient concentration led to an increase of phytoplankton, which was the main reason for the increase in DO concentration on the surface of Lake Xiannv, and the changing of deep-water DO concentration is closely related to water temperature and water depth. |
| Key words: Lake Xiannv dissolved oxygen deep reservoirs influencing factor eutrophication structural equation model |
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