Spatiotemporal Assessment of River Water Quality and Pollution Status in Dhaka, Bangladesh

Abstract

Rapid urbanization, industrial expansion, and seasonal hydroclimatic variability have placed increasing pressure on river systems in Dhaka, Bangladesh, making integrated assessment of water quality essential for effective environmental management. This study investigated the spatiotemporal variability of river water quality and pollution status using physicochemical, hydroclimatic, and multivariate statistical approaches. A total of 1,495 observations collected from multiple rivers and streams between 2017 and 2021 were evaluated for temperature, pH, dissolved oxygen, chemical oxygen demand, nitrate, turbidity, phosphate, rainfall, and Water Quality Index (WQI). Spearman correlation, principal component analysis, multivariate analysis of variance, hierarchical clustering, and robust multiple linear regression were applied. WQI was most strongly positively associated with pH (ρ = 0.705) and phosphate (ρ = 0.468), while dissolved oxygen showed a negative association (ρ = −0.325). The first three principal components explained 54.46% of total variance and represented hydroclimatic–oxygenation, organic-pollution, and nutrient-related gradients. Significant seasonal differences were observed, particularly between monsoon and winter conditions. Hierarchical clustering classified the monitored rivers into three distinct environmental groups. The regression model explained 16.6% of WQI variability, with dissolved oxygen emerging as the strongest independent correlate. These findings highlight the need for river-specific and season-sensitive monitoring and management strategies in Dhaka.