Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kannel, Prakash Raj | - |
dc.contributor.author | Lee, Seockheon | - |
dc.contributor.author | Kanel, Sushil Raj | - |
dc.contributor.author | Khan, Siddhi Pratap | - |
dc.date.accessioned | 2024-01-21T01:34:25Z | - |
dc.date.available | 2024-01-21T01:34:25Z | - |
dc.date.created | 2021-09-05 | - |
dc.date.issued | 2007-01-23 | - |
dc.identifier.issn | 0003-2670 | - |
dc.identifier.uri | https://pubs.kist.re.kr/handle/201004/134725 | - |
dc.description.abstract | The study presents the application of selected chemometric techniques: cluster analysis, principal component analysis, factor analysis and discriminant analysis, to classify a river water quality and evaluation of the pollution data. Seventeen stations, monitored for 16 physical and chemical parameters in 4 seasons during the period 1999-2003, located at the Bagmati river basin in Kathmandu Valley, Nepal were selected for the purpose of this study. The results allowed, determining natural clusters of monitoring stations with similar pollution characteristics and identifying main discriminant variables that are important for regional water quality variation and possible pollution sources affecting the river water quality. The analysis enabled to group 17 monitoring sites into 3 regions with 5 major discriminating variables: EC, DO, CL, NO2N and BOD. Results revealed that some locations were under the high influence of municipal contamination and some others under the influence of minerals. This study demonstrated that chemometric method is effective for river water classification, and for rapid assessment of water qualities, using the representative sites; it could serve to optimize cost and time without losing any significance of the outcome. (c) 2006 Elsevier B.V All rights reserved. | - |
dc.language | English | - |
dc.publisher | ELSEVIER SCIENCE BV | - |
dc.subject | MULTIVARIATE STATISTICAL TECHNIQUES | - |
dc.subject | PRINCIPAL COMPONENT ANALYSIS | - |
dc.subject | WATER-QUALITY | - |
dc.subject | CLUSTER-ANALYSIS | - |
dc.subject | INDIA | - |
dc.subject | RECOGNITION | - |
dc.subject | PROGRAM | - |
dc.title | Chemometric application in classification and assessment of monitoring locations of an urban river system | - |
dc.type | Article | - |
dc.identifier.doi | 10.1016/j.aca.2006.09.006 | - |
dc.description.journalClass | 1 | - |
dc.identifier.bibliographicCitation | ANALYTICA CHIMICA ACTA, v.582, no.2, pp.390 - 399 | - |
dc.citation.title | ANALYTICA CHIMICA ACTA | - |
dc.citation.volume | 582 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 390 | - |
dc.citation.endPage | 399 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.identifier.wosid | 000243665400027 | - |
dc.identifier.scopusid | 2-s2.0-33845618121 | - |
dc.relation.journalWebOfScienceCategory | Chemistry, Analytical | - |
dc.relation.journalResearchArea | Chemistry | - |
dc.type.docType | Article | - |
dc.subject.keywordPlus | MULTIVARIATE STATISTICAL TECHNIQUES | - |
dc.subject.keywordPlus | PRINCIPAL COMPONENT ANALYSIS | - |
dc.subject.keywordPlus | WATER-QUALITY | - |
dc.subject.keywordPlus | CLUSTER-ANALYSIS | - |
dc.subject.keywordPlus | INDIA | - |
dc.subject.keywordPlus | RECOGNITION | - |
dc.subject.keywordPlus | PROGRAM | - |
dc.subject.keywordAuthor | quality | - |
dc.subject.keywordAuthor | classification | - |
dc.subject.keywordAuthor | Bagmati river | - |
dc.subject.keywordAuthor | chemometrics | - |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.