Influence of Land Use/Land Cover on Surface-Water Quality of Santa Lucía River, Uruguay

Angela Gorgoglione, Javier Gregorio, Agustín Ríos, Jimena Alonso, Christian Chreties and Mónica Fossati
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Angela Gorgoglione: Department of Fluid Mechanics and Environmental Engineering (IMFIA), School of Engineering (FIng), Universidad de la República (UdelaR), Julio Herrera y Reissig 565, Montevideo 11300, Uruguay
Javier Gregorio: Department of Fluid Mechanics and Environmental Engineering (IMFIA), School of Engineering (FIng), Universidad de la República (UdelaR), Julio Herrera y Reissig 565, Montevideo 11300, Uruguay
Agustín Ríos: Department of Fluid Mechanics and Environmental Engineering (IMFIA), School of Engineering (FIng), Universidad de la República (UdelaR), Julio Herrera y Reissig 565, Montevideo 11300, Uruguay
Jimena Alonso: Department of Fluid Mechanics and Environmental Engineering (IMFIA), School of Engineering (FIng), Universidad de la República (UdelaR), Julio Herrera y Reissig 565, Montevideo 11300, Uruguay
Christian Chreties: Department of Fluid Mechanics and Environmental Engineering (IMFIA), School of Engineering (FIng), Universidad de la República (UdelaR), Julio Herrera y Reissig 565, Montevideo 11300, Uruguay
Mónica Fossati: Department of Fluid Mechanics and Environmental Engineering (IMFIA), School of Engineering (FIng), Universidad de la República (UdelaR), Julio Herrera y Reissig 565, Montevideo 11300, Uruguay

Sustainability, 2020, vol. 12, issue 11, 1-19

Abstract: Land use/land cover is one of the critical factors that affects surface-water quality at catchment scale. Effective mitigation strategies require an in-depth understanding of the leading causes of water pollution to improve community well-being and ecosystem health. The main aim of this study is to assess the relationship between land use/land cover and biophysical and chemical water-quality parameters in the Santa Lucía catchment (Uruguay, South America). The Santa Lucía river is the primary potable source of the country and, in the last few years, has had eutrophication issues. Several multivariate statistical analyses were adopted to accomplish the specific objectives of this study. The principal component analysis (PCA), coupled with k-means cluster analysis (CA), helped to identify a seasonal variation (fall/winter and spring/summer) of the water quality. The hierarchical cluster analysis (HCA) allowed one to classify the water-quality monitoring stations in three groups in the fall/winter season. The factor analysis (FA) with a rotation of the axis (varimax) was adopted to identify the most significant water-quality variables of the system (turbidity and flow). Finally, another PCA was run to link water-quality variables to the dominant land uses of the watershed. Strong correlations between TP and agriculture-land use, TP and livestock farming, NT and urban areas arose. It was found that these multivariate exploratory tools can provide a proper overview of the water-quality behavior in space and time and the correlations between water-quality variables and land use.

Keywords: land use/land cover; water quality; nutrients; multicriteria statistical analysis; Santa Lucía watershed (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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