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Water quality assessment of a tropical coastal lake system using multivariate cluster, principal component and factor analysis

机译:基于多元聚类,主成分和因子分析的热带沿海湖泊系统水质评估

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摘要

Statistical techniques represent a reliable tool for classifying, modelling and interpreting surface water quality monitoring data, particularly for lakes. The complexity associated with the analysis of a large number of measured variables, however, is a major problem in water quality assessments. Multivariate analysis, such as cluster analysis and factor analysis (FA), was utilized in this study for the analysis of water quality data (including water discharges and 28 water quality parameters) for Akkulam-Veli Lake, a tropical coastal lake system in Kerala, India. This lake is partially divided into two sub-systems, namely Veli Lake and Akkulam Lake. Akkulam Lake exhibits freshwater characteristics, in contrast to Veli Lake, which exhibits saline water characteristics because of its close proximity to the sea. Thus, studying this lake provides insights into water quality variations in both a freshwater and saline water lake in a tropical region. Water quality patterns and variations in Akkulam-Vela Lake over three seasons, including pre-monsoon (PRM), monsoon (MON) and post-monsoon (POM), also were studied, utilizing multivariate techniques. The organic pollution factor played a significant role on lake water quality during PRM. The influence of organic pollution tends to decrease during MON and POM, a particular situation faced by urban lakes in tropical regions. Polluted stretches in a lake system during different seasons can easily be ascertained by hierarchical cluster analysis. Further, the factors affecting a lake system as a whole, as well as for a particular sampling site, can easily be identified by FA. Improved water quality can be observed during POM. Akkulam and Vela lakes exhibit a wide variation in water quality during all seasons, a finding that corroborates a water flow obstruction from Akkulam Lake to Veli Lake because of the bund existing between the two lakes. The location of the bund is identified as the major reason for different hydrochemical processes in A-V Lake.
机译:统计技术是一种可靠的工具,可用于对地表水质量监测数据进行分类,建模和解释,特别是对于湖泊。但是,与大量测量变量的分析相关的复杂性是水质评估中的主要问题。本研究利用多变量分析(例如聚类分析和因子分析(FA))分析了喀拉拉邦热带沿海湖泊系统Akkulam-Veli湖的水质数据(包括排水量和28个水质参数),印度。该湖部分分为两个子系统,即Veli湖和Akkulam湖。阿克库拉姆湖表现出淡水特征,而韦里湖则因其靠近大海而表现出咸水特征。因此,对这个湖泊的研究为深入研究热带地区的淡水湖和盐水湖提供了见识。还利用多变量技术研究了季风前(PRM),季风(MON)和季风后(POM)三个季节的阿克库拉姆-维拉湖水质模式及其变化。在PRM过程中,有机污染因子对湖泊水质起着重要作用。在MON和POM期间,有机污染的影响趋于减少,热带地区城市湖泊面临的一种特殊情况。通过分层聚类分析,可以轻松地确定不同季节湖泊系统中的污染伸展带。此外,FA可以轻松地确定影响整个湖泊系统以及特定采样点的因素。在POM期间可以观察到水质的改善。 Akkulam湖和Vela湖在所有季节的水质都有很大差异,这一发现证实了从Akkulam湖到Veli湖的水流阻塞是由于两个湖之间存在外滩。外滩的位置被确定为A-V湖不同水化学过程的主要原因。

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  • 来源
    《Lakes & Reservoirs》 |2012年第2期|p.143-159|共17页
  • 作者单位

    Directorate of Environment and Climate Change, Thiruvananthapuram, University of Kerala, Kerala, India;

    Directorate of Technical Education,Thiruvananthapuram,University of Kerala, Kerala, India;

    Department of Environment Sciences, University of Kerala, University of Kerala, Kerala, India;

    Department of Statistics,University of Kerala, University of Kerala, Kerala, India;

    Department of Future Studies, University of Kerala, Kerala, India;

    Department of Environment Sciences, University of Kerala, University of Kerala, Kerala, India;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    akkulam-veli lake; cluster analysis; factor analysis; multivariate analysis; water quality;

    机译:akkulam-veli湖;聚类分析;因子分析;多元分析水质;

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