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Spatio-temporal variations in water quality of Nullah Aik-tributary of the river Chenab, Pakistan

机译:巴基斯坦Chenab的纳拉艾克支流水质时空变化

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This study reports the spatio-temporal changes in water quality of Nullah Aik, tributary of the Chenab River, Pakistan. Stream water samples were collected at seven sampling sites on seasonal basis from September 2004 to April 2006 and were analyzed for 24 water quality parameters. Most significant parameters which contributed in spatio-temporal variations were assessed by statistical techniques such as Hierarchical Agglomerative Cluster Analysis (HACA), Factor Analysis/Principal Components Analysis (FA/PCA), and Discriminant Function Analysis (DFA). HACA identified three different classes of sites: Relatively Unimpaired, Impaired and Less Impaired Regions on the basis of similarity among different physicochemical characteristics and pollutant level between the sampling sites. DFA produced the best results for identification of main variables for temporal and spatial analysis and separated eight parameters (DO, hardness, sulphides, K, Fe, Pb, Cr and Zn) that accounted 89.7% of total variations of spatial analysis. Temporal analysis using DFA separated six parameters (E.C., TDS, salinity, hardness, chlorides and Pb) that showed more than 84.6% of total temporal variation. FA/PCA identified six significant factors (sources) which were responsible for major variations in water quality dataset of Nullah Aik. The results signify that parameters identified by statistical analyses were responsible for water quality change and suggest the possibility of industrial, municipal and agricultural runoff, parent rock material contamination. The results suggest dire need for proper management measures to restore the water quality of this tributary for a healthy and promising aquatic ecosystem and also highlights its importance for objective ecological policy and decision making process.
机译:这项研究报告了巴基斯坦的Chenab河支流Nullah Aik水质的时空变化。 2004年9月至2006年4月,从七个采样点按季节采集溪流水样,并分析了24个水质参数。通过统计技术,例如分层聚集聚类分析(HACA),因子分析/主成分分析(FA / PCA)和判别函数分析(DFA),对造成时空变化的最重要参数进行了评估。 HACA根据采样地点之间不同理化特性和污染物水平之间的相似性,确定了三类不同的地点:相对未受损,受损和较少受损的区域。 DFA在识别时空分析主要变量方面产生了最佳结果,并分离了八个参数(DO,硬度,硫化物,K,Fe,Pb,Cr和Zn),占空间分析总变化的89.7%。使用DFA进行的时间分析分离了六个参数(E.C.,TDS,盐度,硬度,氯化物和Pb),这些参数显示了总时间变化的84.6%以上。 FA / PCA确定了六个重要因素(来源),它们是Nullah Aik水质数据集主要变化的原因。结果表明,通过统计分析确定的参数是水质变化的原因,并暗示了工业,市政和农业径流,母岩材料污染的可能性。结果表明,迫切需要采取适当的管理措施来恢复该支流的水质,以建立健康有前途的水生生态系统,并强调其对于客观生态政策和决策过程的重要性。

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