Assessment of surface water quality by using multivariate statistical techniques
Keywords:
water quality, multivariate analysis of variance, factor analysis, cluster analysis, Sourani-dam lake, comprehensive pollution index (CPI)Abstract
This study included evaluation and interpretation of multiple measurements data for surface water quality parameters and pollution sources in the Sourani dam lake - Tartous- Syria, which allowing us to obtain advanced information about water quality, evaluation and design of monitoring network. Nowadays, assessment and forecasting techniques have spread, in order to conserve and sustainably water resources management.
In this study, multivariate statistical techniques, including multivariate analysis of variance (MANOVA), hierarchical cluster analysis (CA), principal components analysis (PCA) and Factor analysis (FA) were applied to assess the water quality of the lake. The study focused on the analysis of 21 physical, chemical and bacteriological parameters in water samples collected monthly over a period of three years (2018-2020) from 7 different sampling sites located around and within the lake. Exploratory analysis of laboratory data included the use of (PCA and CA) as an attempt to distinguish between different sources of variance in samples.
The hierarchical cluster analysis (CA) classified the approved sampling sites for identical water quality into two clusters. The first cluster (Cluster 1) included two groups consisting of five monitoring stations from the northern side of the lake, the first group is (S1, S2, S3) and the second group is (S4, S6), this cluster is severely polluted according to the comprehensive quality index (CPI) which calculated in the seven monitoring stations for all measurements during January 2018 and December 2020, as the source of this pollution results from villages sewage water, industrial and tourist facilities adjacent to the lake. While the second cluster (Cluster 2) included one group consisting of two monitoring stations (S5, S7). This cluster can also be classified as highly polluted, as its pollution results from some villages sewage and agricultural located near the lake, which generally indicates that the water quality in the lake is highly polluted. Factor analysis (FA) was used to reduce the lake pollution variables and include them in six basic components, which indicates up to 69% of the total temporal and spatial changes.
These technologies help and provide water management authorities with knowledge related to the use, modification or determination of a water quality index, and contribute to the future planning studies of drinking water.
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