Abstract
Variety approaches are being used to interpret the concealed variables that determine the variance of observed water quality of various source points. A considerable proportion of these approaches are statistical methods, multivariate statistical techniques in particular. The use of multivariate statistical technique(s) is/are required when the number of variables is large and greater than two for easy and robust evaluation. By means of multivariate statistics of principal components analysis (PCA) and cluster analysis (CA), this study attempted to determine major factors responsible for the variations in the quality of 30 surface ponds used for domestic purposes in six (6) selected communities of Akoko Northeast LGA, Ondo State, Nigeria. The samples’ locations were classified into mutually exclusive unknown groups that share similar characteristics/properties. The laboratory results of 20 parameters comprising 6 physicals, 8 chemicals, 4 heavy metals and 2 microbial from the sampled springs were subjected to PCA and CA for further interpretation. The result shows that 5 components account for 97.52% of total variance of the surface spring quality while 2 cluster groups were identified for the locations. Based on the parameters concentrations and the land uses impacts, it was concluded that domestic and agricultural waste strongly influenced the variation and the quality of ponds in the area. Key words: Multivariate statistics, surface water, quality, interpretation.
Highlights
The complexity of water quality as a subject is reflected in various types of measurements
dissolved oxygen (DO) is generally lower when compared with their mean except Arae, Igbarake, Omi-Alagoke, OmiOlokungboye, Asanmo, Ogbogi and Arae at Ikare, Ajagun at Ise, Otuu at Iboropa and, OtunadumI and Gonga Obane at Akunnu, which are above the regulatory limits
This study presents the usefulness of multivariate statistical techniques of large and complex dataset in order to obtain better information and interpretation concerning surface water quality
Summary
The complexity of water quality as a subject is reflected in various types of measurements These measurements include simple (in situ), basic and more complex parameters (Laboratory). Relationship between two parameters may lead to increases or decrease in the concentration of others This relationship or association is usually achieved using multivariate statistical techniques (Ifabiyi, 1997; Mazlum et al, 1999; Jaji et al, 2007). This is because some analysis is primarily concerned with relationships between samples, while others trepidation are largely with relationships between variables
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