Application of Multivariate Statistical Analysis to Define Water Quality in Jajrud River
The copious prevalence of water deficiency and the geographical location of Iran (arid and semi-arid zone) make acquiring enough accurate data of water quantity and quality for water management vital. However, merely having sufficient data without proper interpretation is rather worthless too when it comes to effective water management and thus, there are several techniques for analyzing water quantity and quality. In this work, statistical method was used to analyze the data collected from the catchment area under study i.e. Jajrud River, located in the North West of Tehran Province. The multivariate time series method was employed to analyze water quality parameters in the river. Box-Jenkins time series model was also applied to the factor data resulted from the Multivariate time series. The results showed that the water quality parameters are not independent having a correlation coefficient larger than 0.3. The study also shows that ground water is the first effective factor, which causes increasing total dissolved solid (TDS) in the river. Domestic waste water pollution is the second-most important factor. Agricultural fertilizers and industrial waste may rank as the third and fourth pollution factors, respectively. Prediction of factor data using Box-Jenkins model was accurate and suitable which may be applicable to other place to model the factors data instead of many water quality parameters.
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