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Multivariate statistical analysis to support the minimum streamflow regionalization REA
Elesbon,Abrahão A. A.; Silva,Demetrius D. da; Sediyama,Gilberto C.; Guedes,Hugo A. S; Ribeiro,Carlos A. A. S.; Ribeiro,Celso B. de M..
ABSTRACT This study aimed to develop a methodology based on multivariate statistical analysis of principal components and cluster analysis, in order to identify the most representative variables in studies of minimum streamflow regionalization, and to optimize the identification of the hydrologically homogeneous regions for the Doce river basin. Ten variables were used, referring to the river basin climatic and morphometric characteristics. These variables were individualized for each of the 61 gauging stations. Three dependent variables that are indicative of minimum streamflow (Q7,10, Q90 and Q95). And seven independent variables that concern to climatic and morphometric characteristics of the basin (total annual rainfall – Pa; total semiannual rainfall...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Principal component analysis; Cluster analysis; Homogeneous regions.
Ano: 2015 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162015000500838
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Warning system based on theoretical-experimental study of dispersion of soluble pollutants in rivers REA
Ribeiro,Celso B. de M.; Silva,Demétrius D. da; Soares,José H. P.; Guedes,Hugo A. S..
Information about capacity of transport and dispersion of soluble pollutants in natural streams are important in the management of water resources, especially in planning preventive measures to minimize the problems caused by accidental or intentional waste, in public health and economic activities that depend on the use of water. Considering this importance, this study aimed to develop a warning system for rivers, based on experimental techniques using tracers and analytical equations of one-dimensional transport of soluble pollutants conservative, to subsidizing the decision-making in the management of water resources. The system was development in JAVA programming language and MySQL database can predict the travel time of pollutants clouds from a point...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Longitudinal dispersion; Water pollution; Computational modeling.
Ano: 2011 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162011000500016
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