IJEP 41(1): 11-24 : Vol. 41 Issue. 1 (January 2021)
K. Arouya1,2, H. Tabyaoui2, H. Taouil1, J. Naoura2 and S. Ibn Ahmed1*
1. University Ibn-Tofail, Laboratory Materials, Electrochemistry and Environment, Faculty of Sciences, Morocco
2. University Sidi Mohamed Ben Abdellah, Laboratory Natural Resources and Environment, Faculty Polydisciplinary of Taza, Route of Oujda, Taza Station, Morocco
This study is part of the characterization of surface water chemistry and the determination of the origin of chemical elements present in the waters of the Taza region of Morocco. To carry out this investigation, 60 samples were collected in July 2017 and January 2018 (30 samples per month). The principal component analysis (PCA) applied to the data sets resulted in three significant factors accounting for 89.46% of the total variance. The F1 factor expresses 53.51% of the total information, called the factor of salinization, water pollution by nitrogen compounds and seasonality. Factors F2 and F3 can be called anthropogenic pollution and seasonality factors. In addition, the stations are well typed and therefore, well structured by their physico-chemical data. In addition, hierarchical cluster analysis (CA) grouped the twenty-five physico-chemical variables studied into five distinct groups related to water-rock interaction, agriculture and anthropogenic sources. Therefore, this work indicates that multivariate statistical methods are an excellent exploratory tool for interpreting a complex set of water quality data and for understanding spatial variations that are useful and effective for water quality management.
Multivariate analysis, Surface water, Physico-chemical quality, Northern Morocco
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