A novel computer-aided multivariate water quality index

Environmental Monitoring and Assessment
Siong Fong SimMohd Zuli Jaafar

Abstract

A computer-aided multivariate water quality index is developed based on partial least squares (PLS) regression. The index is termed as the partial least squares water quality index (PLS-WQI). Briefly, a training set was computationally generated based on the guideline of National Water Quality Standards for Malaysia (NWQS) to predict the water quality. The index is benchmarked with the well-established index developed by the Department of Environment, Malaysia (DOE-WQI). The PLS-WQI is a continuous variable with the value closer to I indicating good water quality and closer to V indicating poor water quality. Unlike other conventional indexing methods, the algorithm calculates the index in a multivariate manner. The algorithm allows rapid processing of a large dataset without tedious calculation; it can be an efficient tool for spatial and temporal routine monitoring of water quality. Although the algorithm is designed based on the guideline of NWQS, it can be easily adapted to accommodate other guidelines. The algorithm was evaluated and demonstrated on the simulated and real datasets. Results indicate that the algorithm is robust and reliable. Based on six parameters, the overall ratings derived are inversely correlated to DO...Continue Reading

References

Jun 8, 2001·Water Research·S B Jonnalagadda, G Mhere
Feb 25, 2003·Water Research·Shiow-Mey LiouChing-Yao Hu
Aug 26, 2004·Environmental Monitoring and Assessment·Shiow-Mey LiouShan-Hsien Wang
Jan 25, 2013·Water Environment Research : a Research Publication of the Water Environment Federation·Edward Ming-Yang Wu, Shu-Lung Kuo
Mar 19, 2013·Analytica Chimica Acta·Alisa RudnitskayaAndrey Legin

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