基于主成分分析修正水质指数的华北平原黄壁庄地下水水质评价

Shuang Gan, M. Zhang, Kaining Yu, Yahong Zhou, Bai-zhong Yan
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引用次数: 0

摘要

摘要以石家庄市和北京市重要水源地黄壁庄镇为研究对象,开展了地下水水质评价研究。2018年7月至9月,从抽水和监测井中收集了56个地理参考水样。研究了专家加权法和主成分分析加权法两种加权方法在水质评价中的适用性,采用化学分析指标和多元统计方法对水质状况和地下水污染的主要原因进行了评价。结果表明,研究区地下水水质总体较好,浅层和深层地下水基本适合饮用和灌溉。专家加权法的WQI结果显示,74.36%的浅层地下水和58.82%的深层地下水为优。浅层地下水与地表水有密切的水力联系,浅层地下水水质优于深层地下水。与专家加权法相比,主成分加权的自然因子权重更大,WQI值更高。由于不涉及主观因素,PCA加权法更客观,更适合研究区域。此外,多元统计计算结果表明,地下水污染既有点源污染、工业活动污染,也有非点源污染,如农业活动污染。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Groundwater quality assessment using principal component analysis modified water quality index in the Huangbizhuang, Northern China Plain
Abstract This study was carried out to evaluate the groundwater quality in Huangbizhuang town, which is an important water source for Shijiazhuang and Beijing, China. Fifty-six geo-referenced water samples were collected from pumping and monitoring wells from July to September 2018. The study investigated the applicability of two weighting methods, the expert weighting method, and the principal component analysis weighting method, to water quality assessment and evaluated the water quality status and the leading causes of groundwater pollution by chemical analysis index and multivariate statistical methods. The results show that the overall quality is good, and shallow and deep groundwater in the study area is generally suitable for drinking and irrigation. The WQI of the expert weighting method reveals that 74.36% of the shallow groundwater and 58.82% of the deep groundwater is excellent. Shallow groundwater has a close hydraulic connection with surface water, and the water quality of shallow groundwater is superior to that of deep groundwater. Compared with the expert weighting method, the weight of natural factors is larger, and the WQI value is higher in PCA weighting. Since no subjective factor is involved, the PCA weighting method is more objective and more suitable for the study area. In addition, multivariate statistical calculation results show groundwater pollution is due to both point source pollution, industrial activities, and non-point source pollution, such as agricultural activities.
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