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Please use this identifier to cite or link to this item: http://scholars.ntou.edu.tw/handle/123456789/20859
DC FieldValueLanguage
dc.contributor.authorEdward Ming-Yang Wuen_US
dc.contributor.authorChia Cheng Tsaien_US
dc.contributor.authorJuey Fu Chengen_US
dc.contributor.authorShu Lung Kuoen_US
dc.contributor.authorWei Ting Luen_US
dc.date.accessioned2022-03-02T02:51:12Z-
dc.date.available2022-03-02T02:51:12Z-
dc.date.issued2014-03-
dc.identifier.urihttp://scholars.ntou.edu.tw/handle/123456789/20859-
dc.description.abstractThis study investigates six water quality monitoring stations in the watershed of the Feitsui Reservoir. It uses nine parameters of water quality collected in an interval of two and half years for factor analyses, which was first conducted to determine four types of factors, respectively, those for organic pollution, eutrophication, seasonal influence, and sediment pollution. The analysis results effectively help to determine water quality in the watershed of the reservoir. The authors reutilize analysis of moment structures (AMOS) to acquire further results in order to confirm the goodness of fit of the previous factor analysis model. During the confirmation, we examine the hypothesized orthogonal results as well as utilize oblique rotation to explore the goodness of fit of the reflective indicators of the orthogonal rotation. As shown in the algorithm results, as long as the covariance curve is included in the four factors, no related issues are detected in the goodness of fit of reflective indicators and interior and external quality is reported with excellence. The orthogonal model, thus, stands. Additionally, when the analysis of structural equation modeling (SEM) is conducted, sample data mismatches the hypotheses of multivariate normality. Therefore, this study adopts the generalized least square (GLS) for an algorithm. Research results of this study have been submitted to the reservoir management authorities in Taiwan for the improvement of statistical application and strategic evaluation of water quality monitoring data in order to strengthen the managerial effectiveness of water quality in watersheds.en_US
dc.language.isoen_USen_US
dc.publisherSpringer Natureen_US
dc.relation.ispartofEnvironmental Modeling & Assessmenten_US
dc.titleThe application of water quality monitoring data in a reservoir watershed using AMOS confirmatory factor analysesen_US
dc.typejournal issueen_US
dc.identifier.doi10.1007/s10666-014-9407-5-
dc.relation.journalvolume19en_US
dc.relation.journalissue4en_US
dc.relation.pages325-333en_US
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.languageiso639-1en_US-
item.fulltextno fulltext-
item.grantfulltextnone-
item.openairetypejournal issue-
crisitem.author.deptCollege of Engineering-
crisitem.author.deptBachelor Degree Program in Ocean Engineering and Technology-
crisitem.author.deptNational Taiwan Ocean University,NTOU-
crisitem.author.deptCenter of Excellence for Ocean Engineering-
crisitem.author.deptBasic Research-
crisitem.author.orcidhttp://orcid.org/0000-0002-4464-5623-
crisitem.author.parentorgNational Taiwan Ocean University,NTOU-
crisitem.author.parentorgCollege of Engineering-
crisitem.author.parentorgNational Taiwan Ocean University,NTOU-
crisitem.author.parentorgCenter of Excellence for Ocean Engineering-
Appears in Collections:海洋工程科技學士學位學程(系)
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