Water Quality Assessment of Karrnaphuli River, Bangladesh Using Multivariate Analysis and Pollution Indices
Mahmudul Karim *
Department of Applied Chemistry and Chemical Engineering, Noakhali Science and Technology University, Noakhali-3814, Bangladesh
Sujan Kanti Das
Bangladesh Council of Scientific and Industrial Research, Chittagong, Bangladesh
Shujit Chandra Paul
Department of Applied Chemistry and Chemical Engineering, Noakhali Science and Technology University, Noakhali-3814, Bangladesh
Mohammad Farhan Islam
Department of Applied Chemistry and Chemical Engineering, Noakhali Science and Technology University, Noakhali-3814, Bangladesh
Md. Shahadat Hossain
Department of Applied Chemistry and Chemical Engineering, Noakhali Science and Technology University, Noakhali-3814, Bangladesh
*Author to whom correspondence should be addressed.
Abstract
The Karrnaphuli river is one of the polluted river of Chittagong originating from the Lushai Hills in India which is being polluted recently by various industries located around it. The primary objective of this study was to determine the water quality status of the most polluted area of Karrnaphuli river along with the root causes of pollution. The study involved the determination of physical parameters like temperature, color, electrical conductivity, odor, turbidity and other chemical parameters like potential of hydrogen (pH), dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD) etc. of the most polluted zone of Karrnaphuli river. From the parameters investigated, evaluation of water quality was done on the basis of standard Water Quality Index (WQI) and Comprehensive Pollution Index (CPI). Principal Component Analysis (PCA) was used to extract the parameters that were most important in assessing variation in water quality. The WQI value indicates that around 40% of the sampled stations water quality is of bad grade, about 40% of water quality is of low grade and 20% water quality was ranged from moderate to good quality. However, CPI values indicate that all of the sampling station water is severely polluted. Four Principal Components were identified to be responsible for the data structure explaining 94% of the total variance of the dataset. The sample sites were highly polluted with different wastes generated from various industries situated in the bank of Karrnaphuli River.
Keywords: Karrnaphuli River, WQI, CPI, geostatistical analysis