Journal ArticleDOI
Assessment of surface water quality using multivariate statistical techniques: A case study of the Fuji river basin, Japan
Sangam Shrestha,Futaba Kazama +1 more
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This study illustrates the usefulness of multivariate statistical techniques for analysis and interpretation of complex data sets, and in water quality assessment, identification of pollution sources/factors and understanding temporal/spatial variations in waterquality for effective river water quality management.Abstract:
Multivariate statistical techniques, such as cluster analysis (CA), principal component analysis (PCA), factor analysis (FA) and discriminant analysis (DA), were applied for the evaluation of temporal/spatial variations and the interpretation of a large complex water quality data set of the Fuji river basin, generated during 8 years (1995–2002) monitoring of 12 parameters at 13 different sites (14 976 observations). Hierarchical cluster analysis grouped 13 sampling sites into three clusters, i.e., relatively less polluted (LP), medium polluted (MP) and highly polluted (HP) sites, based on the similarity of water quality characteristics. Factor analysis/principal component analysis, applied to the data sets of the three different groups obtained from cluster analysis, resulted in five, five and three latent factors explaining 73.18, 77.61 and 65.39% of the total variance in water quality data sets of LP, MP and HP areas, respectively. The varifactors obtained from factor analysis indicate that the parameters responsible for water quality variations are mainly related to discharge and temperature (natural), organic pollution (point source: domestic wastewater) in relatively less polluted areas; organic pollution (point source: domestic wastewater) and nutrients (non-point sources: agriculture and orchard plantations) in medium polluted areas; and organic pollution and nutrients (point sources: domestic wastewater, wastewater treatment plants and industries) in highly polluted areas in the basin. Discriminant analysis gave the best results for both spatial and temporal analysis. It provided an important data reduction as it uses only six parameters (discharge, temperature, dissolved oxygen, biochemical oxygen demand, electrical conductivity and nitrate nitrogen), affording more than 85% correct assignations in temporal analysis, and seven parameters (discharge, temperature, biochemical oxygen demand, pH, electrical conductivity, nitrate nitrogen and ammonical nitrogen), affording more than 81% correct assignations in spatial analysis, of three different sampling sites of the basin. Therefore, DA allowed a reduction in the dimensionality of the large data set, delineating a few indicator parameters responsible for large variations in water quality. Thus, this study illustrates the usefulness of multivariate statistical techniques for analysis and interpretation of complex data sets, and in water quality assessment, identification of pollution sources/factors and understanding temporal/spatial variations in water quality for effective river water quality management.read more
Citations
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Pesticide occurrence and water quality assessment from an agriculturally influenced Latin-American tropical region
Didier Ramírez-Morales,Marta Pérez-Villanueva,Juan Salvador Chin-Pampillo,Paula Aguilar-Mora,Víctor Arias-Mora,Mario Masís-Mora +5 more
TL;DR: The results suggest that the water quality in the microcatchments seems to be affected by the nearby agricultural and urban activities in the region.
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Regional Non point Source Organic Pollution Modeling and Critical Area Identification for Watershed Best Environmental Management
TL;DR: In this article, a geographic information system based Soil and Water Assessment Tool was applied in Bahe River watershed, a part of the Yangtze River basin, for a 10-year period (1996-2005).
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A fishy odor episode in a north China reservoir: Occurrence, origin, and possible odor causing compounds
TL;DR: It is demonstrated that the fishy odor episode in this reservoir might be caused by the abnormal growth of chrysophytes and diatoms under the ice-cover.
Journal ArticleDOI
Water quality assessment using NSFWQI, OIP and multivariate techniques of Ganga River system, Uttarakhand, India
TL;DR: In this article, the surface water quality of the River Ganga in India, using NSFWQI, OIP and multivariate techniques was assessed using water quality indices (WQIs) to classify the overall impact of different variables of water.
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Spatio-temporal variability and pollution sources identification of the surface sediments of Shatt Al-Arab River, Southern Iraq.
Hadi Allafta,Christian Opp +1 more
TL;DR: This study addresses several of the major limitations of the current knowledge on this river’s pollution sources and analysis, such as the limited number of analyzed pollutants and restricted samplings in the current literature.
References
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Applied Multivariate Statistical Analysis
R. A. Johnson,Dean W. Wichern +1 more
TL;DR: In this article, the authors present an overview of the basic concepts of multivariate analysis, including matrix algebra and random vectors, as well as a strategy for analyzing multivariate models.
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TL;DR: In this article, the authors present an overview of the basic concepts of multivariate analysis, including matrix algebra and random vectors, as well as a strategy for analyzing multivariate models.
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Jae-on Kim,Charles W. Mueller +1 more
TL;DR: Describes the mathematical and logical foundations at a level which does not presume advanced mathematical or statistical skills, illustrating how to do factor analysis with several of the more popular packaged computer programmes.
Journal ArticleDOI
Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India)—a case study
TL;DR: This study presents necessity and usefulness of multivariate statistical techniques for evaluation and interpretation of large complex data sets with a view to get better information about the water quality and design of monitoring network for effective management of water resources.
Journal ArticleDOI
Application of factor analysis in the assessment of groundwater quality in a blackfoot disease area in Taiwan
TL;DR: The over-extraction of groundwater is the major cause of groundwater salinization and arsenic pollution in the coastal area of Yun-Lin, Taiwan and this model explains over 77.8% of the total groundwater quality variation.