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首页> 美国卫生研究院文献>International Journal of Environmental Research and Public Health >Analyses on the Temporal and Spatial Characteristics of Water Quality in a Seagoing River Using Multivariate Statistical Techniques: A Case Study in the Duliujian River China
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Analyses on the Temporal and Spatial Characteristics of Water Quality in a Seagoing River Using Multivariate Statistical Techniques: A Case Study in the Duliujian River China

机译：多元统计技术在海河水质时空特征分析中的应用-以中国多留uji河为例

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摘要

In the Duliujian River, 12 water environmental parameters corresponding to 45 sampling sites were analyzed over four seasons. With a statistics test (Spearman correlation coefficient) and multivariate statistical methods, including cluster analysis (CA) and principal components analysis (PCA), the river water quality temporal and spatial patterns were analyzed to evaluate the pollution status and identify the potential pollution sources along the river. CA and PCA results on spatial scale revealed that the upstream was slightly polluted by domestic sewage, while the upper-middle reach was highly polluted due to the sewage from feed mills, furniture and pharmaceutical factories. The middle-lower reach, moderately polluted by sewage from textile, pharmaceutical, petroleum and oil refinery factories as well as fisheries and livestock activities, demonstrated the water purification role of wetland reserves. Seawater intrusion caused serious water pollution in the estuary. Through temporal CA, the four seasons were grouped into three clusters consistent with the hydrological mean, high and low flow periods. The temporal PCA results suggested that nutrient control was the primary task in mean flow period and the monitoring of effluents from feed mills, petrochemical and pharmaceutical factories is more important in the high flow period, while the wastewater from domestic and livestock should be monitored carefully in low flow periods. The results may provide some guidance or inspiration for environmental management.
机译：在多留江，在四个季节中分析了对应于45个采样点的12个水环境参数。利用统计检验（斯皮尔曼相关系数）和多元统计方法，包括聚类分析（CA）和主成分分析（PCA），分析了河流水质的时空格局，以评估污染状况并确定沿线潜在污染源。河流。 CA和PCA在空间尺度上的结果显示，上游部分受到生活污水的污染，而中上游部分由于饲料厂，家具和制药厂的污水而受到高度污染。中下游地区受到纺织，制药，石油和炼油厂以及渔业和畜牧业活动的污水的中等污染，证明了湿地保护区的净水作用。海水入侵在河口造成了严重的水污染。通过时间CA，将四个季节分为与水文平均，高和低流量时段一致的三个群集。 PCA的时间结果表明，养分控制是平均流量时期的首要任务，在高流量时期，对饲料厂，石化和制药厂的废水进行监测尤为重要，而在此期间应仔细监测家庭和牲畜的废水。低流量期。结果可能为环境管理提供一些指导或启发。

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