Developing an ensembled machine learning model for predicting water quality index in Johor River Basin

• Main Authors: Sidek L.M., Mohiyaden H.A., Marufuzzaman M., Noh N.S.M., Heddam S., Ehteram M., Kisi O., Sammen S.S.
• Other Authors: 35070506500
• Format: Article
• Published: Springer 2025
• Subjects: Johor; Johor Basin; Malaysia; West Malaysia; Biochemical oxygen demand; Decision making; Dissolved oxygen; Escherichia coli; Forecasting; Forestry; Machine learning; Mathematical operators; Numerical methods; Quality assurance; Quality control; Regression analysis; Water quality; Watersheds; Gradient boosting; Gradient boosting regression; Index models; Johor river; Machine learning models; Random forests; River basins; Study areas; Surface water quality; Water quality indexes; decision making; hydrological modeling; machine learning; prediction; regression analysis; river basin; water quality; Rivers

Currently, the Water Quality Index (WQI) model becomes a widely used tool to evaluate surface water quality for agriculture, domestic and industrial. WQI is one of the simplest mathematical tools that can assist water operator in decision making in assessing the quality of water and it is widely use...