An examination of the Kaiser-Meyer-Olkin measure of sampling adequacy suggested that the sample was factorable (Table 2). PCA was carried out to extract the various factors. The varimax rotation was performed to secure increased principal components of chemical/environmental significance. The Eigenvalues for different factors, percentage variance accounted, cumulative percentage variance and component loadings (Varimax rotated) are given in Table 2. Eigenvalues >1 were taken as criterion for the extraction of the principal components required for explaining the sources of variances in the data. This analysis resulted in the explanation of 71.53–79.26 of variances in the data.
The parameter loading for the three components from the PCA of the data set are given in Tables 3, 4, 5 and 6. In order to interpret the results, the high factor load in excess of 0.75 and mean factor load between 0.4 and 0.75 were considered which were optional values (Childs 1970). These values were obtained in studies by different researchers (Miller and Drever 1977; Puckett and Bricker 1992; Evansa et al. 1996).
The investigation of the factors with Eigenvalues >1 for the four seasons demonstrated that three factors affected the chemical composition of the Karoon River water quality. The Scree plot of spring season exhibited in Fig. 3, which also includes the percentage variances explained by each component and gives an idea on how the different principal components were extracted. This figure shows a pronounced change of slope after the 3th Eigenvalue. Therefore, three components were retained, which have Eigenvalues >1 and explain 79.26 % of the variance.
An Eigenvalue gives a measure of the significance of the factor: the factors with the highest Eigenvalues are the most significant. Eigenvalues of 1.0 or greater are considered significant. Liu et al. (2003) classified the factor loadings as ‘strong’, ‘moderate’ and ‘weak’, corresponding to the absolute loading values of >0.75, 0.75e0.50 and 0.50e0.30, respectively. Therefore, we also classified these results in Tables 3, 4, 5 and 6.
All three factors are examined separately as follows:
Autumn season: The results of the analysis discovered that three factors accounted for 74.66 % of the total variance (Table 3). Based on the distribution of the Eigenvalues, factor 1 alone explained 38.87 % of the variance. TDS, conductivity, chloride and sodium were strongly correlated and sulfate, calcium and potassium were moderately correlated with factor 1. Calcium, sulfate, and discharge were strongly correlated with factor 2 and bicarbonate and pH with factor 3.
Winter season: The results of the analysis revealed that three factors account for 76.74 % of the total variance (Table 4). The Eigenvalues also performed that factor 1 alone accounts for 42.54 % of the variance. TDS, conductivity, chloride and sodium were strongly and sulfate, magnesium and discharge were moderately correlated with factor 1. Calcium was strongly correlated; sulfate, pH and discharge were moderately correlated with factor 2; and bicarbonate and potassium with factor 3.
Spring season: The results of the analysis revealed that three factors account for 79.26 % of the total variance (Table 5). The Eigenvalues also showed that factor 1 alone accounts for 33.61 % of the variance. Sulfate, calcium and discharge were strongly and TDS, conductivity, chloride, sodium, magnesium, potassium were moderately correlated with factor 1. Discharge, chloride, sodium were strongly correlated, TDS and conductivity were moderately correlated with factor 2, and bicarbonate and pH with factor 3.
Summer season: The results of the analysis exhibited that three factors account for 71.53 % of the total variance (Table 6). The Eigenvalues also showed that factor 1 alone accounts for 36.20 % of the variance. TDS, conductivity, chloride and sodium were strongly and discharge was moderately correlated with factor 1. Sulfate was strongly correlated and magnesium was moderately correlated with factor 2 and calcium, bicarbonate and pH with factor 3.
Factor 1 have high loading of the ions Na+ and Cl−, and factor 2 have great loading of the ions Ca+ and for all seasons except spring. The concentration of Na, Cl, Ca and SO4 in runoff generated by Gachsaran Formation outcrops is much greater than that in other formations. Factor 3 shows the influence of limestone formations on the Karoon River water quality.
As identified by a plot, the selected parameters showing seasonal trends are given in Fig. 4. The average discharge (Fig. 4) is higher in spring compared to autumn, winter and summer. In the study period, these might have been due to the frequent snow melt and continuously discharge melt water into river network in the basin. Lastly, river water quality is expected to improve in the Karoon River basin by increasing discharge amount. Vary factors obtained from FA indicate that the parameters responsible for water quality variations are mainly related to discharge amount as well as Gachsaran geology and formation. EC is extremely less in the spring season when discharge value increases and tremendously high in the rest of the year. This pollution is significantly natural and point source as nonpoint pollutions like agriculture and orchard plantations did not involve in this basin.
Figure 4 showed that although the lowest flow discharge was observed during the summer season, the highest salinity occurred over the autumn season. In other words, the salinity of the river water increases in the wet season (autumn and winter).
Gachsaran Formation having a high erosion potential, so the generated runoff in wet season passing through this formation, dissolve gypsum and halite, can contaminate the surface or subsurface water resources and the salinity of the river water increases. As regards in the flowing water, the dissolution rates of gypsum is 100 times more than the rate of limestone dissolution, and only about 1/1,000 the rate of salt dissolution (Milanovic 2004), so dissolution of halite of Gachsaran Formation is the first and dissolution of gypsum is the second effective factors on the Karoon River water quality.