چکیده مقاله
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
کلیدواژهها
نویسندگان
Hasan Nasrollahzadeh Saravi
Ecological Aquatic Center of the Caspian Sea EACCS
Seyed Ebrahim Varedi
Hasan Nasrollahzadeh Saravi Ecological Aquatic Center of the Caspian Sea (EACCS)Seyed Rasol VarediReza Safari
Seyed Rasol Varedi
Hasan Nasrollahzadeh Saravi Ecological Aquatic Center of the Caspian Sea (EACCS)Seyed Ebrahim VarediReza Safari
Reza Safari
Hasan Nasrollahzadeh Saravi Ecological Aquatic Center of the Caspian Sea (EACCS)Seyed Ebrahim VarediSeyed Rasol Varedi
شیوه ارجاع
Nasrollahzadeh Saravi, Hasan and Varedi, Seyed Ebrahim and Varedi, Seyed Rasol and Safari, Reza,1388,Application of Multivariate Statistical Modelling in Temporal Patterns of Water Chemistry in Haraz River (Mazandaran Province),08th International River Engineering Conference ,Ahvaz
ارائهشده در
مجموعه مقالات هشتمین سمینار بین المللی مهندسی رودخانه6 بهمن 1388 · اهواز