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作 者:王玮 张明涛 程杰 陈建文 杨阳 Wang Wei;Zhang Mingtao;Cheng Jie;Chen Jianwen;Yang Yang(Jingzhou Ecological Environment Monitoring Center,Department of Ecology and Environment of Hubei Province,Jingzhou 434000,Hubei,China)
机构地区:[1]湖北省生态环境厅荆州生态环境监测中心,湖北荆州434000
出 处:《绿色科技》2025年第4期117-122,共6页Journal of Green Science and Technology
基 金:荆州市科技创新智库2023年度立项课题(编号:JZCXZK202313)。
摘 要:本文以2018-2023年洪湖的水质监测数据为切入点,分析洪湖水体叶绿素a浓度与环境因子之间的相关性,找到水华暴发的驱动因子。相关性分析的结果显示:湖区总体的水华驱动因子主要为COD Mn、TP、BOD 5、透明度;因子分析结果显示:环境温度(水温、气温)、透明度、风速对洪湖水华暴发的影响作用最显著,COD Mn、TP等环境因子也共同推动促进藻类的生长和聚集。多元回归分析模型能够快速且较准确地预测叶绿素a浓度的动态变化趋势,同时对湖区显著的影响因子进行筛选,为洪湖水华暴发作出有效的半定量预测,降低水华暴发风险。同时,建议引进卫星遥感技术,增加洪湖监测频次,强化数据支撑;加大洪湖生态修复保护力度,恢复水体生态调节和水体自净能力。This paper takes the water quality monitoring data of Honghu Lake from 2018 to 2023 as the starting point,analyzes the correlation between chlorophyll-a concentration in Honghu Lake water and environmental factors,and identifies the driving factors for the outbreak of algal bloom.The results of correlation analysis show that the main driving factors of algal bloom in the lake area are COD Mn,TP,BOD 5,and transparency;the results of factor analysis show that the environmental temperature(water temperature and air temperature),transparency,and wind speed are the most significant impact on the outbreak of algal bloom in Honghu Lake.Environmental factors such as COD Mn and TP also jointly promote the growth and aggregation of algae.The multiple regression analysis model can quickly and accurately predict the dynamic trend of chlorophyll-a concentration,and screen for significant influencing factors in the lake area,making effective semi quantitative predictions for the outbreak of algal blooms in Honghu Lake,and reducing the risk of algal bloom.Meanwhile,it is recommended to introduce satellite remote sensing technology to increase monitoring frequency in Honghu Lake and strengthen data support;efforts in ecological restoration and protection of Honghu should be intensified Lake to rehabilitate its ecological regulation functions and enhance water self-purification capacity.
分 类 号:X703[环境科学与工程—环境工程]
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