{"title":"An investigation of Juru River basin water quality using principal component analysis","authors":"B. Abdul-Karim, Shamshuritawati Sharif","doi":"10.1063/1.5121106","DOIUrl":null,"url":null,"abstract":"Water quality is a crucial requirement of human health, well-being and the environment. However, the rapid development of industrial and urbanisation around the area contribute to water pollution. In this paper, a principal component analysis are implemented to evaluate and interpret water quality dataset obtained from one of the polluted rivers in Malaysia which is the Juru River basin located in Pulau Pinang. Data is gathered bimonthly from 2008 to 2017 for 20 parameters used to evaluate the status of the water quality. As a conclusion, the most important parameter are salinity, conductivity, dissolved solids, calcium, zinc, pH, arsenic and ammonia nitrogen. This study presents the usefulness of principal component analysis in evaluating and interpreting water quality data for the purpose of monitoring water resource management.Water quality is a crucial requirement of human health, well-being and the environment. However, the rapid development of industrial and urbanisation around the area contribute to water pollution. In this paper, a principal component analysis are implemented to evaluate and interpret water quality dataset obtained from one of the polluted rivers in Malaysia which is the Juru River basin located in Pulau Pinang. Data is gathered bimonthly from 2008 to 2017 for 20 parameters used to evaluate the status of the water quality. As a conclusion, the most important parameter are salinity, conductivity, dissolved solids, calcium, zinc, pH, arsenic and ammonia nitrogen. This study presents the usefulness of principal component analysis in evaluating and interpreting water quality data for the purpose of monitoring water resource management.","PeriodicalId":325925,"journal":{"name":"THE 4TH INNOVATION AND ANALYTICS CONFERENCE & EXHIBITION (IACE 2019)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"THE 4TH INNOVATION AND ANALYTICS CONFERENCE & EXHIBITION (IACE 2019)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1063/1.5121106","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Water quality is a crucial requirement of human health, well-being and the environment. However, the rapid development of industrial and urbanisation around the area contribute to water pollution. In this paper, a principal component analysis are implemented to evaluate and interpret water quality dataset obtained from one of the polluted rivers in Malaysia which is the Juru River basin located in Pulau Pinang. Data is gathered bimonthly from 2008 to 2017 for 20 parameters used to evaluate the status of the water quality. As a conclusion, the most important parameter are salinity, conductivity, dissolved solids, calcium, zinc, pH, arsenic and ammonia nitrogen. This study presents the usefulness of principal component analysis in evaluating and interpreting water quality data for the purpose of monitoring water resource management.Water quality is a crucial requirement of human health, well-being and the environment. However, the rapid development of industrial and urbanisation around the area contribute to water pollution. In this paper, a principal component analysis are implemented to evaluate and interpret water quality dataset obtained from one of the polluted rivers in Malaysia which is the Juru River basin located in Pulau Pinang. Data is gathered bimonthly from 2008 to 2017 for 20 parameters used to evaluate the status of the water quality. As a conclusion, the most important parameter are salinity, conductivity, dissolved solids, calcium, zinc, pH, arsenic and ammonia nitrogen. This study presents the usefulness of principal component analysis in evaluating and interpreting water quality data for the purpose of monitoring water resource management.