Temporal and spatial variations of water quality in the Jinshui River of the South Qinling Mts., China
Temporal and spatial variations of water quality in the Jinshui River of the South Qinling Mts., China
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DOI：
10.1016/j.ecoenv.2009.11.007
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发表时间：
2010-07-01
影响因子：
6.8
通讯作者：
Zhang, Quanfa
中科院分区：
文献类型：
--
作者：
Bu, Hongmei;Tan, Xiang;Zhang, Quanfa
近几十年来，水污染对人类社会和自然生态系统的威胁越来越大，因此需要更好地了解水系统中污染物的时空变化。本研究于2006年10月至2008年8月对南秦岭金水河12个采样点的水质进行了监测，中国采用多元统计技术和网格化方法，研究了水质的时空变化，确定了主要污染因子和污染源。双向方差分析（ANOVA）表明，25个研究的水质变量具有显着的时间差异（p < 0.01）和空间变异性（p < 0.01）。利用聚类分析，12个采样点分为3个污染水平组（无污染，中度污染，高污染）的基础上的水质变量的相似性。因子分析表明，盐度、营养性、有机污染、氧化物相关过程和侵蚀作用5个因子可解释总方差的80.4%。网格化方法表明，水质从上游到下游逐渐恶化。分析结果表明，南秦岭山区小流域水污染主要来源于生活污水和农业径流，为山区小流域水资源保护提供了重要信息。中国(C)2009 Elsevier Inc. All rights reserved.
Water pollution has become a growing threat to human society and natural ecosystems in recent decades, increasing the need to better understand the spatial and temporal variabilities of pollutants within aquatic systems. This study sampled water quality at 12 sampling sites from October 2006 to August 2008 in the Jinshui River of the South Qinling Mts., China. Multivariate statistical techniques and gridding methods were used to investigate the temporal and spatial variations of water quality and identify the main pollution factors and sources. Two-way analysis of variance (ANOVA) showed that 25 studied water quality variables had significant temporal differences (p < 0.01) and spatial variability (p < 0.01). Using cluster analysis, the 12 sampling sites were classified into three pollution level groups (no pollution, moderate pollution, and high pollution) based on similarity of water quality variables. Factor analysis determined that 80.4% of the total variance was explained by five factors, that is, salinity, trophicity, organic pollution, oxide-related process, and erosion. The gridding methods illustrated that water quality progressively deteriorated from headwater to downstream areas. The analytical results suggested that the water pollution primarily resulted from domestic wastewater and agricultural runoff, and provided critical information for water resource conservation in mountainous watersheds of the South Qinling Mts., China. (C) 2009 Elsevier Inc. All rights reserved.