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Trend Analysis on Water Quality Index Using the Least Squares Regression Models

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dc.contributor.authorZawawi I.S.M.en_US
dc.contributor.authorHaniffah M.R.M.en_US
dc.contributor.authorAris H.en_US
dc.contributor.authorid55671668500en_US
dc.contributor.authorid57193212028en_US
dc.contributor.authorid13608397500en_US
dc.date.accessioned2023-05-29T09:36:24Z
dc.date.available2023-05-29T09:36:24Z
dc.date.issued2022
dc.description.abstractRiver water pollution requires continuous water quality monitoring that promotes the improvement of water resources. Therefore, the trend analysis on water quality data using mathematical model is an important task to determine whether the measured data increase or decrease during the time period. This paper is intended to highlight the applicability of the least squares regression models to fit the WQI data of the Skudai River, Tebrau River and Segget River located in Johor, Malaysia. As per the 12 years of trend analysis, the data of WQI are collected from the Environmental Quality Reports 2009-2020. The least squares method is utilized to estimate the unknown constants of the linear, quadratic, cubic, polynomial of degree four and degree five regression models. The advantage of using proposed models is that it can be implemented easily even on relatively low computational power systems. The results show that the higher degree polynomial model fits the data reasonably well, in which the polynomials of degree 4 and 5 have lowest average error. Assessment of actual and predictable values of WQI shows that the trends in WQI for all study areas are downward year after year. � 2022 by authors, all rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.13189/eer.2022.100504
dc.identifier.epage571
dc.identifier.issue5
dc.identifier.scopus2-s2.0-85139459535
dc.identifier.spage561
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85139459535&doi=10.13189%2feer.2022.100504&partnerID=40&md5=5c4c4d11400805a02f90bcabed8a48d3
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/26734
dc.identifier.volume10
dc.publisherHorizon Research Publishingen_US
dc.relation.ispartofAll Open Access, Gold
dc.sourceScopus
dc.sourcetitleEnvironment and Ecology Research
dc.titleTrend Analysis on Water Quality Index Using the Least Squares Regression Modelsen_US
dc.typeArticleen_US
dspace.entity.typePublication
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