PCA Interrelations Through New Standardization Method for Langat River

Water quality assessment is critical for environmental management and public health, particularly in the face of increasing anthropogenic pressures and climate change. Traditional water quality indices (WQIs) often rely on empirical methods or standardized parameters that may not fully capture the complex interrelationships within diverse aquatic ecosystems. This study introduces a novel standardization method for Principal Component Analysis (PCA) to develop a more robust and reliable water quality model, specifically applied to the Langat River in Malaysia. Utilizing a comprehensive dataset from 2015–2020, we demonstrate that standardizing water quality parameters based on the National Water Quality Standards for Malaysia (NWQSM) ranges, rather than conventional normalization techniques, significantly enhances the accuracy and consistency of PCA-derived WQIs. Through rigorous correlation, crosstabulation, biplot, and regression analyses, our proposed method consistently outperforms existing approaches, yielding a higher concordance with Department of Environment (DOE) WQI classifications and revealing clearer, independent contributions of key water quality parameters. This research provides a scientifically sound and ecologically relevant framework for water quality assessment, offering a powerful tool for environmental authorities to make informed decisions and implement effective pollution control strategies in riverine environments globally.