Water quality assessment of the Cassaffousth Reservoir using multivariate statistical techniques

LEDESMA, MICAELA; BONANSEA, MATIAS; LEDESMA, CLAUDIA; RODRIGUEZ, CLAUDIA; PINOTTI, LUCIO

Revista Científica FAV-UNRC Ab Intus

Facultad de Agronomia y Veterinaria, UNRC

Lugar: Río Cuarto; Año: 2018 vol. 2 p. 27 - 34

2618-2734

Lakes, rivers and reservoirs are the main water resources for multiple purposes, so it is important to have reliable information on the state and quality of the resource through the implementation of a monitoring plan. Due to spatial and temporal variations in water quality, these programs must include a large numberof physicochemical and biological parameters taken at different sampling sites,which implies large financial inputs, generating a complex data matrix that is difficult to interpret. Thus, it is necessary to optimize these monitoring, without losing useful information through the application of different multivariate statistical techniques, which allow a better interpretation and understanding of extensive and complex databases. The objective of this work was to analyze the water quality variability of the Cassaffousth reservoir (Córdoba, Argentina), detecting the main sources of contamination. On a data matrix obtained during a monitoring program carried out in 2016, several statistical techniques were applied, finding differences and similarities between sampling sites and measured variables. By means of cluster analysis (CA), sites with similar characteristics were grouped. A principal component analysis (PCA) was performed to detect similarities between the measured variables. It was also observed that the greatest variation in water quality was explained by soluble salts, while the rest of the variation was related to nutrients, organic pollutants and physical parameters. Based on the results, it was possible to optimize the sampling strategy, reducing the number of sampling sites and measured variables, which would lead to a reduction of economic costs.