Open AccessAssessing temporal and spatial patterns of surface-water quality with a multivariate approach: a case study in Uruguay
Author(s) -
Angela Gorgoglione,
Julia R. Alonso,
Christian Chreties,
Mónica Fossati
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/612/1/012002
Subject(s) - watershed , environmental science , water quality , multivariate statistics , principal component analysis , turbidity , eutrophication , pollution , hydrology (agriculture) , cluster (spacecraft) , geography , ecology , statistics , nutrient , mathematics , geotechnical engineering , machine learning , computer science , engineering , biology , programming language
The ecological state of inland waters of the Santa Lucía watershed, the primary drinking water source of Uruguay, has raised interest since it presents the seasonal phenomenon of eutrophication. For this reason, an in-depth understanding of the behaviour in time and space of the water-quality variables that characterize this stream is essential. Therefore, this study aims to evaluate the occurrence of spatial and temporal patterns of water-quality variables (Q, turbidity, T, TN, NO 3 - , NO 2 - , NH 4 + , TP, DO, BOD 5 ) in the Santa Lucía Chico watershed with the aid of multivariate statistical tools. The principal component analysis, coupled with k-means cluster analysis, helped to identify a seasonal variation (fall-winter and spring-summer). The hierarchical cluster analysis allowed us to classify the water-quality monitoring stations in three groups in the fall-winter season. The loadings values of the cluster analysis highlighted the most significant pollutants at each monitoring station. The outcomes of this work are expected to contribute valuable knowledge for determining effective management strategies to reduce stream pollution and protect the aquatic ecosystem health of the study area.