Assessment of water quality parameters using multivariate analysis for Klang River basin, Malaysia

被引:54
|
作者
Mohamed, Ibrahim [1 ]
Othman, Faridah [2 ]
Ibrahim, Adriana I. N. [1 ]
Alaa-Eldin, M. E. [2 ]
Yunus, Rossita M. [1 ]
机构
[1] Univ Malaya, Fac Sci, Inst Math Sci, Kuala Lumpur 50603, Malaysia
[2] Univ Malaya, Fac Engn, Dept Civil Engn, Kuala Lumpur 50603, Malaysia
关键词
Klang River; Water quality; Factor analysis; Principal component; Biplot; STATISTICAL TECHNIQUES; INDEX;
D O I
10.1007/s10661-014-4182-y
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This case study uses several univariate and multivariate statistical techniques to evaluate and interpret a water quality data set obtained from the Klang River basin located within the state of Selangor and the Federal Territory of Kuala Lumpur, Malaysia. The river drains an area of 1,288 km(2), from the steep mountain rainforests of the main Central Range along Peninsular Malaysia to the river mouth in Port Klang, into the Straits of Malacca. Water quality was monitored at 20 stations, nine of which are situated along the main river and 11 along six tributaries. Data was collected from 1997 to 2007 for seven parameters used to evaluate the status of the water quality, namely dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, suspended solids, ammoniacal nitrogen, pH, and temperature. The data were first investigated using descriptive statistical tools, followed by two practical multivariate analyses that reduced the data dimensions for better interpretation. The analyses employed were factor analysis and principal component analysis, which explain 60 and 81.6% of the total variation in the data, respectively. We found that the resulting latent variables from the factor analysis are interpretable and beneficial for describing the water quality in the Klang River. This study presents the usefulness of several statistical methods in evaluating and interpreting water quality data for the purpose of monitoring the effectiveness of water resource management. The results should provide more straightforward data interpretation as well as valuable insight for managers to conceive optimum action plans for controlling pollution in river water.
引用
收藏
页码:1 / 12
页数:12
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