Assessment of the water self-purification capacity on a river affected by organic pollution: application of chemometrics in spatial and temporal variations

Abstract

Water pollution caused by organic matter is a major global problem which requires continuous evaluation. Multivariate statistical analysis was applied to assess spatial and temporal changes caused by natural and anthropogenic phenomena along Potrero de los Funes River. Cluster analysis (CA), principal component analysis (PCA) and analysis of variance (ANOVA) were applied to a data set collected throughout a period of 3 years (2010-2012), which monitored 22 physical, chemical and biological parameters. Content of dissolved oxygen in water and biochemical oxygen demand in a watercourse are indicators of pollution caused by organic matter. For this reason, the Streeter-Phelps model was used to evaluate the water self-purification capacity. Hierarchical cluster analysis grouped the sampling sites based on the similarity of water quality characteristics. PCA resulted in two latent factors explaining 75.2 and 17.6 % of the total variance in water quality data sets. Multidimensional ANOVA suggested that organic pollution is mainly due to domestic wastewater run-offs and anthropogenic influence as a consequence of increasing urbanization and tourist influx over the last years. Besides, Streeter-Phelps parameters showed a low reaeration capacity before dam with low concentration of dissolved oxygen. Furthermore, self-purification capacity loss was correlated with the decrease of the Benthic Index. This measurement suggested that biological samplings complement the physical-chemical analysis of water quality.