Partial least squares integrated national water quality standards (NWQS) for indexing of water quality from industrial effluent

Emmanuel, Freda (2015) Partial least squares integrated national water quality standards (NWQS) for indexing of water quality from industrial effluent. Masters thesis, University Malaysia Sarawak, UNIMAS.

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PARTIAL LEAST SQUARES INTEGRATED NATIONAL WATER QUALITY STANDARDS (NWQS) FOR INDEXING OF WATER QUALITY FROM INDUSTRIAL EFFLUENT (24 pages).pdf

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Abstract

This study attempts to provide a better classification of water quality that is of accurate representation of the actual health of river water and is achieved by applying existing water quality evaluation method used in our country, namely DOE-WQI and average NWQS as well as a newly developed model based on Partial Least Squares (PLS) regression and the guideline of NWQS, called PLS-WQI in the indexing process. Indexing with DOE-WQI equation method using six (6) pre-determined DOE-WQI parameters revealed that all stations falls under Class III with a slightly polluted status. PLS-WQI and average NWQS corresponds well with DOE-WQI method and it is also observed that average NWQS often provides better classification of water quality among all methods studied. Further indexing with PLS-WQI using the algorithm programmed in Matlab R2009b which allows for the consideration of only parameters that impart the greatest influence on water quality has resulted in a better presentation of the actual water quality at each station. PLS-WQI predicted Stations WS1 and WS2 to be of Class 3.66 with parameters pH, DO, BOD and COD at Station WS1 and pH, DO and COD at Station WS2. Meanwhile, Station WS3 is predicted to be of Class 4.45 when indexing was carried out with variables pH, DO, BOD, COD, TSS, AN, OG and Mn. Therefore, PLS-WQI is flexible and is thoroughly more sensitive compared to the other two (2) existing methods.

Item Type: Thesis (Masters)
Additional Information: Thesis (M.Sc.) -- Universiti Malaysia Sarawak, 2015
Uncontrolled Keywords: water quality, water quality index, partial least squares regression, Sejingkat River,Water quality,unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, Postgraduate, research, Universiti Malaysia Sarawak
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
Q Science > Q Science (General)
Divisions: Academic Faculties, Institutes and Centres > Faculty of Resource Science and Technology
Depositing User: Karen Kornalius
Date Deposited: 05 Nov 2015 02:39
Last Modified: 05 Nov 2015 02:39
URI: http://ir.unimas.my/id/eprint/9416

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