Abstract

In this study, chemometric techniques have been used in source apportionment for spatial variation of surface water quality of seven rivers (Baralia, Puthimari, Pagladia, Beki, Manas, Kolong and Kameng River) of Assam (India). The study was carried out in two phases. The first phase included the survey of the study area and the collection and analysis of water samples. In the second phase, cluster analysis (CA), discriminant analysis (DA) and principal component analysis (PCA) were applied to the observed water quality data-sets. CA grouped all the sampling sites into three clusters based on the similarities of the characteristics they possess. The result from CA was verified using DA, which helped in determining the variables that distinguish the observed groups. DA resulted in eight water quality parameters (DO, total alkalinity, K⁺, Ca²⁺, Mg²⁺, Cl^-, SO₄^2- and Mn) affording 100% correct assignations in spatial analysis of rivers. PCA applied to the three separate datasets obtained from CA indicated that soil leaching, organic waste and fertilizer were the major sources of water quality variation. Therefore, the present study illustrates the requisiteness and efficacy of chemometric techniques in source apportionment for variation of water quality and effective management of water resources.

摘要

在这项研究中，化学计量学技术已用于阿萨姆邦（印度）七条河流（Baralia、Puthimari、Pagladia、Beki、Manas、Kolong 和 Kameng 河）地表水水质空间变化的源解析。该研究分两个阶段进行。第一阶段包括研究区域的调查以及水样的收集和分析。在第二阶段，将聚类分析 (CA)、判别分析 (DA) 和主成分分析 (PCA) 应用于观察到的水质数据集。CA 根据所有采样点所具有的特征的相似性将其分为三个集群。CA 的结果使用 DA 进行了验证，这有助于确定区分观察组的变量。DA 产生八个水质参数（DO、总碱度、K⁺ , Ca ²⁺ , Mg ²⁺ , Cl ^- , SO ₄ ^2-和 Mn) 在河流的空间分析中提供 100% 正确的分配。应用于从 CA 获得的三个独立数据集的 PCA 表明土壤淋溶、有机废物和肥料是水质变化的主要来源。因此，本研究说明了化学计量学技术在源解析中对水质变化和水资源有效管理的必要性和有效性。