Sectorización de la calidad del agua del Arroyo del Azul, provincia de Buenos Aires, mediante la aplicación de técnicas estadísticas multivariadas

Английский. In the basin of the Azul Creek (centre of Buenos Aires Province) different uses are made (agricultural, recreational, the reception of urban effluents). Although there is a physicochemical characterization of its surface, it is necessary to do further studies in order to know the variables that determine the water quality of the resource to be managed more efficiently. This following aims at sectoring the basin according to its water quality and to identify significant parameters to describe the variations. Therefore, multivariate techniques were applied: Cluster (CA) and principal components (PCA) on standardized data. These techniques come from twelve seasonal campaigns where 27 variables were measured at 14 stations located in different sectors of the basin (n = 168). The results from CA show the formation of two groups: one consisting of samples of the upper and middle basin, and the other of some samples of the middle and lower basin. Due to the PCA, 3 factors were obtained that explain 53 % of the total variance, reducing the list of parameters to 13, weighing more than 0.70. To conclude, the results obtained by both techniques are consistent since areas with different water quality were identified and those affected by urban effluents were discriminated allowing the identification of parameters which explain this variability. The physicochemical sectoring of surface water which was obtained is not strictly coincident with that determined by the geomorphology and groundwater hydrochemistry.

Испанский язык; кастильский. In the basin of the Azul Creek (centre of Buenos Aires Province) different uses are made (agricultural, recreational, the reception of urban effluents). Although there is a physicochemical characterization of its surface, it is necessary to do further studies in order to know the variables that determine the water quality of the resource to be managed more efficiently. This following aims at sectoring the basin according to its water quality and to identify significant parameters to describe the variations. Therefore, multivariate techniques were applied: Cluster (CA) and principal components (PCA) on standardized data. These techniques come from twelve seasonal campaigns where 27 variables were measured at 14 stations located in different sectors of the basin (n = 168). The results from CA show the formation of two groups: one consisting of samples of the upper and middle basin, and the other of some samples of the middle and lower basin. Due to the PCA, 3 factors were obtained that explain 53 % of the total variance, reducing the list of parameters to 13, weighing more than 0.70. To conclude, the results obtained by both techniques are consistent since areas with different water quality were identified and those affected by urban effluents were discriminated allowing the identification of parameters which explain this variability. The physicochemical sectoring of surface water which was obtained is not strictly coincident with that determined by the geomorphology and groundwater hydrochemistry.