articleEnvironmental Sciences EuropeMar 3, 2025GOLD OA

Comparative analysis of machine learning models for predicting water quality index in Dhaka’s rivers of Bangladesh

Islamic University of Technology · Bangladesh University of Engineering and Technology · +3 more institutions

Indexed incrossrefdoaj

Abstract

The pollution in Dhaka's navigable waterways, including the Buriganga, Balu, Tongi Khal, and Turag rivers, is a significant concern due to rapid industrial and urban expansion. Industrial discharges, domestic sewage and inadequate waste management are the primary sources of this pollution, degrading water quality and threatening aquatic ecosystems. This study aimed to predict the Water Quality Index (WQI) of these rivers using fourteen machine learning (ML) models: Decision Tree Regression, Linear Regression, Ridge Regression, Stochastic Gradient Descent (SGD) Regressor, Extreme Gradient Boosting (XGB) Regressor, Light Gradient Boosting Machine (GBM) Regressor, Elastic Net Regressor, Support Vector Regression…

Citation impact

51
total citations
FWCI
32.44
Percentile
100%
References
107
Citations per year

Authors

9

Topics & keywords

Keywords
  • Water quality
  • Index (typography)
  • Ecotoxicology
  • Environmental science
  • Statistics
  • Mathematics
  • Toxicology
  • Ecology
UN Sustainable Development Goals
  • Clean water and sanitation
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