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首页> 外文期刊>Journal of limnology >Using integrated multivariate statistics to assess the hydrochemistry of surface water quality, Lake Taihu basin, China
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Using integrated multivariate statistics to assess the hydrochemistry of surface water quality, Lake Taihu basin, China

机译:利用综合多元统计数据评估太湖流域地表水水质

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摘要

We investigated the hydrochemical setting of Lake Taihu (eastern China) to determine how different land use types influence the variability of surface water chemistry in different water sources to the lake. Major water types within the watershed range from caclium-magnesium bicaxrbonate water, typical of relatively pristine water, highly ocntaminated water characterized by more sulfate, sodium, chloride and nutrients. Principal components analysis produced three principal components that explained 78% of the variance in the water quality and reflect three major types of water chemistry. Agricultural land use is associated with greater concentrations of nutrients; urban areas with high concentrations of sodium, chloride, sulfate, fluoride and potassium; and natural weathering with calcium, magnesium and bicarbonate. Discriminant analysis and hierarchical cluster analysis produce complementary and similar results. Broadly speaking, future remediation to reduce nutrient loadings to the lake or industrial contamination can now be focused on specific land use practices, which are readily identifiable by using statistics in conjunction with GIS.
机译:我们调查了太湖(中国东部)的水化学环境,以确定不同土地利用类型如何影响到湖的不同水源中地表水化学的变化性。该流域内的主要水类型包括钙镁双碳酸钠水(典型的相对纯净水),高浓度被高硫酸盐,钠,氯和养分含量高的水。主成分分析产生了三个主成分,这些主成分解释了78%的水质差异并反映了水化学的三种主要类型。农业土地利用与养分含量更高有关;钠,氯化物,硫酸盐,氟化物和钾含量高的城市地区;以及钙,镁和碳酸氢盐的自然风化。判别分析和层次聚类分析产生互补和相似的结果。广义上讲,将来为减少湖泊中的养分含量或工业污染而采取的补救措施现在可以集中在特定的土地利用方法上,这些方法可以很容易地通过与GIS结合使用统计数据来确定。

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