Application of chemometric techniques in the assessment of groundwater quality in a urban area of Isfahan city, Iran

Chemometric techniques, such as discriminant analysis (DA), cluster analysis (CA), and factor analysis (FA)/principal component analysis (PCA) and regression analysis (RA) were applied for the evaluation of temporal variation and correlation of water quality parameters, also for the interpretation of water quality data for the Kaptazh well adjacent Zayanderood river during the years 2014-2016 by measuring 18 water quality parameters (WQPs) at ten different periods. The DA and CA classified ten temporal observations into three groups, reflecting varying water quality levels including moderate hardness, high hardness, and very high hardness under the similarity of water quality parameters, and 18 water quality parameters into three clusters.The RA was used to identify correlation between various parameters. The obtained correlation values of regression analysis suggest a significant linear relationship between various WQPs. FA / PCA was applied to the chemical parameters of well with the aim of classification and data sets summation as well as segmentation of large heterogeneous data sets into smaller homogeneous subsets. Five principle components explained about 80.40 % of the total variance of the water data sets from eigenvalue > 1. This study successfully illustrates that chemometric methods provide useful information for further monitoring strategies

کلیدواژه ها:

Cluster Analysis ، Discriminant Analysis ، Temporal Variations ، Water Quality