This is an empirical study on small urban water bodies in Chittagong Metropolitan City, Bangladesh. The ultimate objective was to explore the alternative source of fresh water supply for the city dwellers- the urban poor. To determine the level of drinking water, a suitability analysis was performed in conjunction with the construction and calculation of a Water Quality Index (WQI) for two distinct seasons: Rainy and Winter. The IBM Statistical Package for the Social Sciences (SPSS) Statistics version: 20 and CAP: version: 5.0.0.465 was used as a mean to an end. The study reveals that water quality in sampled UWBs of CMC was found unsuitable (WQI value 237.11) for drinking in the Rainy season and very poor (WQI value 99.62) in the Winter. The eight (8) parameters that crossed the maximum permissible limit in the Rainy and Winter seasons include EC, BOD, COD, Turbidity and Nitrate. The two biological parameters i.e. Total Coliform (TC) and Fecal Coliform (FC) that stood alone in crossing the admissible limit, detected measured values 1100+ MPN- 100 ml−1 in Rainy and Winter seasons, against unit recommended vale 50. Awareness building on water pollutants in both public and private sectors is required to improve public health service delivery.

This is empirical research that focuses on the urban water ecosystems in the humid tropics of South Asia. The purpose of the study was to evaluate the quality of drinking water in the urban water bodies (UWBs) of Chittagong Metropolitan City (CMC), Bangladesh. The field data was centered on the analysis and depiction of twenty-three (23) water quality parameters, collected from twenty-one (21) spatial observation units. Analytic tools include suitability analysis, correlation matrix, principal component analysis (PCA), and cluster analysis (CA) as a means to an end. The data were analyzed using SPSS. The analysis reveals that drinking water quality in studied UWBs was inappropriate during the monsoon season. Parameters that crossed the extreme permissible concentration incorporate EC, BOD, COD, Turbidity, Nitrate, Total coliform, and Fecal coliform. The PCA extracted four factors (PC1–4) with an eigenvalue of 10.23, explaining 73.1% of the total variation in the dataset in cumulative terms. The CA recognized three (3) broad groups of the sampling stations. Group A represents nine cases, suffering the most from pollution concentration in CMC. Awareness building at all levels is advocated to improve clean water sources, increase service provision, and ensure public health safeguards.