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引用本文:唐海滨,郑志伟,胡莲,潘晓洁,史方,邹曦,万成炎.2008—2020年三峡库区小江叶绿素a的时空演变特征及驱动因子.湖泊科学,2023,35(5):1529-1537. DOI:10.18307/2023.0512
Tang Haibin,Zheng Zhiwei,Hu Lian,Pan Xiaojie,Shi Fang,Zou Xi,Wan Chengyan.Spatiotemporal characteristics and driver analysis of chlorophyll-a in Xiaojiang River of the Three Gorges Reservoir from 2008 to 2020. J. Lake Sci.2023,35(5):1529-1537. DOI:10.18307/2023.0512
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2008—2020年三峡库区小江叶绿素a的时空演变特征及驱动因子
唐海滨, 郑志伟, 胡莲, 潘晓洁, 史方, 邹曦, 万成炎
水利部中国科学院水工程生态研究所, 水利部水工程生态效应与生态修复重点实验室, 武汉 430072
摘要:
2008年至2020年期间,对三峡水库小江5个监测断面的叶绿素a(Chl.a)及主要环境因子进行季度监测,分析小江Chl.a的时空变化特征,探讨水体Chl.a与环境因子的相关关系,解析影响小江Chl.a变化的主要环境因子。结果表明,小江Chl.a年平均浓度为(20.69±9.41) μg/L,变幅为5.96~33.90 μg/L。Chl.a浓度季节差异较大,总体呈现出春、夏、秋3个季节明显高于冬季的变化特征,且春季Chl.a浓度最高,为34.48 μg/L;空间分布上,Chl.a浓度呈现倒“N”型分布规律,黄石断面最高(29.55 μg/L),养鹿断面最低(15.23 μg/L)。Pearson相关性分析结果显示,小江Chl.a浓度与CODMn、电导率、pH、溶解氧呈显著正相关关系,与NO-3-N、PO3-4-P、透明度呈显著负相关关系。通过逐步回归分析,筛选得到对小江Chl.a影响最重要的5个环境因子。通径分析表明,各环境因子对水体Chl.a浓度的作用大小在时空上存在一定差异。不同季节中对水体Chl.a影响最显著的环境因子分别为:浊度(春季)、溶解氧(夏季)、NH3-N(秋季)、水温(冬季);不同断面中对Chl.a影响最显著的环境因子由上游到下游依次为:电导率(渠口)、CODMn(养鹿)、PO3-4-P(高阳)、电导率(黄石)、溶解氧(双江)。溶解氧、CODMn是影响小江全段Chl.a最主要的环境因子,其中,溶解氧对Chl.a浓度的直接作用最大,其直接通径系数为0.451,CODMn对Chl.a浓度的间接作用最大,其间接通径系数为0.204。拟合分析结果显示,Chl.a与溶解氧、Chl.a与CODMn均表现为指数函数的拟合效果最好,其次为幂函数,最后为线性函数。本研究对小江及三峡库区其他支流富营养化防控具有借鉴意义。
关键词:  叶绿素a  三峡库区  小江  时空变化  理化因子  逐步回归分析  通径分析
DOI:10.18307/2023.0512
分类号:
基金项目:国家重点研发计划项目(2022YFC3203905)、水利部重大科技项目(SKR-2022015)和国家自然科学基金项目(51779157,51679153)联合资助。
Spatiotemporal characteristics and driver analysis of chlorophyll-a in Xiaojiang River of the Three Gorges Reservoir from 2008 to 2020
Tang Haibin, Zheng Zhiwei, Hu Lian, Pan Xiaojie, Shi Fang, Zou Xi, Wan Chengyan
Key Laboratory of Ecological Impacts of Hydraulic-Projects and Restoration of Aquatic Ecosystem of Ministry of Water Resources, Institute of Hydroecology, Ministry of Water Resources and Chinese Academy of Sciences, Wuhan 430079, P.R. China
Abstract:
From 2008 to 2020, we measured chlorophyll-a (Chl.a) and major environmental factors at five monitoring sites in Xiaojiang River, Three Gorges Reservoir, on a quarterly basis, analysed the spatial and temporal variation characteristics of Chl.a, explored the correlation between Chl.a and environmental factors in water bodies, and analysed the major environmental factors affecting the change of Chl.a in Xiaojiang River. The results showed that the annual average concentration of Chl.a was (20.69±9.41) μg/L with a variation of 5.96-33.90 μg/L. The Chl.a concentration varied seasonally, and the overall characteristics showed that the Chl.a concentration was significantly higher in spring, summer and autumn than in winter, and peaked at 34.48 μg/L in spring. The spatial distribution of Chl.a concentration showed an inverted “N” type distribution pattern, with the highest in the Huangshi section (29.5 μg/L) and the lowest in the Yanglu section (15.23 μg/L). Pearson correlation analysis showed that Chl.a concentration in Xiaojiang was significantly and positively correlated with CODMn, conductivity, pH and DO, and significantly and negatively correlated with NO-3-N, PO3-4-P and Secchi depth. Stepwise regression analysis was used to screen the five most important environmental factors affecting Chl.a. Temporally, the most important environmental factors affecting Chl.a in different seasons were turbidity in spring, DO in summer, NH3-N in autumn, water temperature in winter. Spatially, the most important factors influencing Chl.a from upstream to downstream in different reaches were conductivity in Qukou, CODMn in Yanglu, PO3-4-P in Goyang, conductivity in Huangshi, DO in Shuangjiang. DO and CODMn were the most important environmental factors affecting Chl.a in Xiaojiang River, where DO had the largest direct effect on Chl.a concentration with a direct path coefficient of 0.451, and CODMn had the largest indirect effect on Chl.a concentration with an indirect path coefficient of 0.204. Fitting analysis showed that Chl.a and DO, Chl.a and CODMn were best fitted with an exponential function, followed by a power function and finally a linear function. This study is important for the in-depth understanding of the spatial and temporal variation patterns and the main influencing factors of chlorophyll-a, and for the management of eutrophication in Xiaojiang River and other tributaries in the Three Gorges Reservoir area.
Key words:  Chlorophyll-a  Three Gorges Reservoir  Xiaojiang River  spatial-temporal variation  environmental factors  stepwise regression analysis  path analysis
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