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基于多元统计分析的独流减河水质时空特征 被引量:7

Assessment of spatio-temporal features of water quality via multivariate statistical analysis of Duliujian River basin
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摘要 为了解独流减河流域水质时空特征及污染物排放结构情况,准确掌握污染来源和防控重点,达到改善流域水质的目的,基于2017年独流减河流域9个监测断面的8个水质指标的监测数据,采用综合水质标识指数法进行水质评价,运用多元统计分析方法中的聚类分析和主成分分析开展水质时空分布特征及污染物来源解析研究。结果表明:独流减河流域水质时空特征差异显著,干流水质优于支流水质;时间维度划分为2个时段T_(1)(1—3月)和T_(2)(4—12月),T_(2)时段水质优于T_(1)时段,氨氮、总磷和阴离子表面活性剂是各时段的主要污染因子,畜禽养殖、农村居民生活为主要污染源,氟离子和COD_(Cr)分别是T_(1)和T_(2)时段的另外主要污染因子,代表工业电镀行业废水污染和耗氧有机污染。空间分布划为G_(1)组和G_(2)组,其中G_(1)组主要位于中上游,主要污染因子为氨氮、总磷及阴离子表面活性剂,代表畜禽养殖和居民生活污染;G_(2)组位于中下游,主要污染因子为化学需氧量、总磷和氟化物,代表城镇居民生活污染和工业电镀行业废水污染,G_(2)组水体水质优于G_(1)组。 The paper intends to make a comprehensive water quality assessment of the water quality of Duliujian River basin near Tianjin Municipality. For the said purpose,we have adopted the multivariate statistical approach,including the cluster analysis and the principal component analysis methods to analyze the status-in-situ of the water quality of the river basin so as to identify its spatio-temporal variations and the potential pollution sources. And,then,we have taken into account in the given paper the 8 water quality parameters we have collected in 2017 at the 9 water quality monitoring sites of the river. The results of our investigation help us to make out that the main water quality of the river belongs to regular Class Ⅱ to poor Class Ⅴ with a significant spatio-temporal variation. And,furthermore,from the viewpoint of the hierarchical cluster analysis in the 12 months of the water conservation and monitoring period,it can be divided into 2 periods of conservation,that is,the period one,i. e. T_(1),from January to March whereas the period T_(2) from April to December,with the 9 monitoring sites being into 2 groups as G_(1) and G_(2). On the other hand,the major water quality of period T_(1) belongs to Class Ⅴ and the poor Class Ⅴ with the accounting rate being 88. 9%. At the same time,NH_(3)-N,TP,F-and anionic surfactant have been disclosed as the main pollution factors in period T_(1),mainly from the domestic farming sewage,with the livestock breeding and electroplating pollutants. And,in contrast,the water quality of period T_(2) belongs to Class Ⅳ and ClassⅤ with the accounting rate of 79. 0%. NH_(3)-N,COD_(Cr),TP,Hg and Anionic surfactant have also been proven as the main pollution factors in this period,which are mainly derived from the farming domestic sewage,the farming process and the live stock breeding. As to the group G_(1),it ought to be located in the upper-mid reaches of the Duliujian River basin with the major water quality of group G_(1) belonging to Class Ⅴ and poor Class Ⅴwith the accounting rate of 93. 8%. Besides,NH_(3)-N,TP and the Anionic surfactant have been proven to be the main pollutant factors in group G_(1),mainly from the domestic food-processing sewage,including that of farming and livestock breeding. And,in similar ways,group G_(2) has been found in the mid-lower reaches of the Duliujian River basin. The major water quality of the group G_(2) belongs to Class Ⅳ and Class Ⅴ at the rate of 76. 6%.And,last of all,COD_(Cr),TP and F-have to be the principal pollutant factors in group G_(2),which can mainly derived from the urban domestic sewage and electroplating industry. Thus,in summary,the groups G_(1) and G_(2) belong to the pollutants by NH_(3)-N,COD_(Cr) and TP,that is,the principal pollution-control indicators in the said river basin. Hence,the investigation results of ours can be said qualified enough to provide a scientific basis for the water environment management of the Duliujian River basin.
作者 徐媛 赵吉睿 马楠 展先辉 魏代艳 荚秀艳 孙猛 XU Yuan;ZHAO Ji-rui;MA Nan;ZHAN Xian-hui;WEI Dai-yan;JIA Xiu-yan;SUN Meng(Tianjin Eco-Environmental Monitoring Center,Tianjin 300191,China;Tianjin Tianbin Ruicheng Environmental Technology Engineering Co.,Ltd.,Tianjin 300191,China;Tianjin Water Engineering Co.,Ltd.,Tianjin 300222,China)
出处 《安全与环境学报》 CAS CSCD 北大核心 2021年第3期1342-1351,共10页 Journal of Safety and Environment
基金 天津市科技重大专项与工程项目(18ZXSZSF00130)。
关键词 环境工程学 多元统计分析 水质评价 时空特征 污染源 独流减河流域 environmental engineering multivariate statistical techniques water quality evaluation spatio-temporal variations pollution source Duliujian River basin
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