Kannel Prakash Raj, Lee Seockheon, Kanel Sushil Raj, Khan Siddhi Pratap
Water Environment & Remediation Research Center, Korea Institute of Science and Technology, Cheongryang, Seoul 130-650, Republic of Korea.
Anal Chim Acta. 2007 Jan 23;582(2):390-9. doi: 10.1016/j.aca.2006.09.006. Epub 2006 Sep 8.
The study presents the application of selected chemometric techniques: cluster analysis, principal component analysis, factor analysis and discriminant analysis, to classify a river water quality and evaluation of the pollution data. Seventeen stations, monitored for 16 physical and chemical parameters in 4 seasons during the period 1999-2003, located at the Bagmati river basin in Kathmandu Valley, Nepal were selected for the purpose of this study. The results allowed, determining natural clusters of monitoring stations with similar pollution characteristics and identifying main discriminant variables that are important for regional water quality variation and possible pollution sources affecting the river water quality. The analysis enabled to group 17 monitoring sites into 3 regions with 5 major discriminating variables: EC, DO, CL, NO(2)N and BOD. Results revealed that some locations were under the high influence of municipal contamination and some others under the influence of minerals. This study demonstrated that chemometric method is effective for river water classification, and for rapid assessment of water qualities, using the representative sites; it could serve to optimize cost and time without losing any significance of the outcome.
聚类分析、主成分分析、因子分析和判别分析,用于对河流水质进行分类以及对污染数据进行评估。为了本研究的目的,选取了位于尼泊尔加德满都谷地巴格马蒂河流域的17个监测站,这些监测站在1999 - 2003年期间的4个季节对16个理化参数进行了监测。结果能够确定具有相似污染特征的监测站自然聚类,并识别出对区域水质变化和影响河流水质的可能污染源具有重要意义的主要判别变量。该分析能够将17个监测点分为3个区域,有5个主要判别变量:电导率(EC)、溶解氧(DO)、氯化物(CL)、亚硝酸盐氮(NO₂N)和生化需氧量(BOD)。结果表明,一些地点受城市污染影响较大,而其他一些地点受矿物质影响较大。这项研究表明,化学计量学方法对于河流水质分类以及利用代表性站点快速评估水质是有效的;它可以在不损失任何结果重要性的情况下优化成本和时间。