分摊
主成分分析
水质
空间变异性
环境科学
碱度
采样(信号处理)
地表水
线性判别分析
浸出(土壤学)
环境工程
统计
化学
土壤科学
数学
土壤水分
计算机科学
法学
生态学
计算机视觉
有机化学
滤波器(信号处理)
生物
政治学
作者
Kunwar Raghvendra Singh,Ajay S. Kalamdhad,Bimlesh Kumar
标识
DOI:10.1080/15275922.2021.1913675
摘要
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-, SO42- 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.
科研通智能强力驱动
Strongly Powered by AbleSci AI