Application of Multivariate Statistical Modelling in Temporal Patterns of Water Chemistry in Haraz River (Mazandaran Province)

Principal component analysis (PCA) was used to extract the factors associated with the physico-chemical variables in the Haraz River during four seasons in 2004-05. Using the results which were analyzed using PCA, a data matrix was produced. From the annually correlation matrix, seven principal components (PC) were extracted which explain 81.49% of the total variance of the raw data. PC1 (21.31% of the variance) is associated with the nitrogen compounds in terms of nitrate, DIN and DON and also CFU. PC2 (14.49% of the variance) is characterized by TA, TH and EC (physical parameters). PC3 (11.16% of the variance) is mainly contributed by the phosphorous compounds (DIP and DOP) and TSS. PC4 which explains 10.44% of the variance is associated with temperature and BOD5, while, PC5, PC6 and PC7 explain 10.39%, 7.25% and 6.89% of total variance are contributed by NH4+, DOP and pH and DO respectively. This study highlights the advantage of combining simple but powerful statistics with water quality monitoring.

Keywords:

Multivariate Statistical , Physico-chemical , Haraz River , Mazandaran , Iran