Development of a PCA-derived water quality index model for monitoring the urban river systems in Dhaka City, Bangladesh
Mohiuddin Ahmed Bhuiyan, Hridoy Roy, Kazi Saidur Rahman, Bimol Nath Roy, Md.Al Amin Kabir Bhuyan, Md. Rezaul Maksud Jahedi, Md. Shahinoor Islam
Abstract
In this study, a Water Quality Index (WQI) model was developed to assess the water quality of the major rivers in Dhaka city, including Buriganga, Balu, Turag, and Sitalakhya, based on a comprehensive dataset collected across four seasons (dry, pre-monsoon, monsoon, post-monsoon) in 2024. A total of 144 water samples were analyzed for 16 water quality parameters, and principal component analysis (PCA) combined with correlation analysis was applied to identify eight key parameters: pH, dissolved oxygen (DO), total solids (TS), chemical oxygen demand (COD), chloride, ammonia–nitrogen, E. coli, and total coliform. Sub-indexing was performed using quality rating curves provided by NSF-WQI and a linear interpolation function to transform parameter values into standardized scores. PCA was used again to assign weights based on eigenvalues, a data-driven approach to parameter weighting, with TS (0.215) and ammonia–nitrogen (0.199) contributing most to pollution levels. The final WQI, calculated using a weighted aggregation function, ranged from 29.78 to 77.96, with Buriganga exhibiting the poorest water quality (mean WQI: 46.85) and Sitalakhya the best (mean WQI: 57.10). Seasonal variations revealed that the dry season WQI reached as low as 29.78, while dilution during the monsoon season improved water quality to a maximum of 74.29. Statistical analysis confirmed significant temporal ( p < 0.001) and spatial ( p < 0.001) variations in water quality. Sensitivity analysis identified TS, COD, and chloride as the most influential parameters. This study presents a robust, data-driven WQI model for efficient monitoring and management of water quality in Dhaka.