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Interpretation of seasonal water quality variation in the Yeongsan Reservoir, Korea using multivariate statistical analyses

机译:利用多元统计分析解释韩国龙山水库的季节性水质变化

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The Yeongsan (YS) Reservoir is an estuarine reservoir which provides surrounding areas with public goods, such as water supply for agricultural and industrial areas and flood control. Beneficial uses of the YS Reservoir, however, are recently threatened by enriched non-point and point source inputs. A series of multivariate statistical approaches including principal component analysis (PCA) were applied to extract significant characteristics contained in a large suite of water quality data (18 variables monthly recorded for 5 years); thereby to provide the important phenomenal information for establishing effective water resource management plans for the YS Reservoir. The PCA results identified the most important five principal components (PCs), explaining 71% of total variance of the original data set. The five PCs were interpreted as hydro-meteorological effect, nitrogen loading, phosphorus loading, primary production of phytoplankton, and fecal indicator bacteria (FIB) loading. Furthermore, hydro-meteorological effect and nitrogen loading could be characterized by a yearly periodicity whereas FIB loading showed an increasing trend with respect to time. The study results presented here might be useful to establish preliminary strategies for abating water quality degradation in the YS Reservoir.
机译:龙头山水库是一个河口水库,为周边地区提供公共物品,例如农业和工业区的供水以及防洪。然而,YS水库的有益用途最近受到非点和点源输入的丰富威胁。应用了包括主成分分析(PCA)在内的一系列多元统计方法,以提取大量水质数据中包含的重要特征(每月记录18个变量,连续5年)。从而为建立YS水库有效的水资源管理计划提供重要的重要信息。 PCA结果确定了最重要的五个主要成分(PC),解释了原始数据集的71%的总方差。这五台PC被解释为水文气象效应,氮负荷,磷负荷,浮游植物的初级生产以及粪便指示菌(FIB)负荷。此外,水文气象效应和氮负荷可以以每年的周期为特征,而FIB负荷则表现出随时间增加的趋势。此处介绍的研究结果可能对建立减轻YS水库水质退化的初步策略很有帮助。

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