Evaluation and monitoring of the water quality of an Argentinian urban river applying multivariate statistics

In this work, we present the water quality assessment of an urban river, the San Luis River, located in San Luis Province, Argentina. The San Luis River flows through two developing cities; hence, urban anthropic activities affect its water quality. The river was sampled spatially and temporally, ev...

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Bibliographic Details
Published in:Environmental science and pollution research international 2024-04, Vol.31 (20), p.30009-30025
Main Authors: Tello, Jesica Alejandra, Leporati, Jorge Leandro, Colombetti, Patricia Laura, Ortiz, Cynthia Gabriela, Jofré, Mariana Beatriz, Ferrari, Gabriela Verónica, González, Patricia
Format: Article
Language:English
Subjects:
Anthropogenic factors
Aquatic Pollution
Argentina
Atmospheric Protection/Air Quality Control/Air Pollution
Cities
Cluster analysis
Contamination
Continuity (mathematics)
Correlation analysis
Earth and Environmental Science
Ecotoxicology
Environment
Environmental Chemistry
Environmental Health
Environmental management
Environmental monitoring
Environmental Monitoring - methods
Monitoring
Multivariate Analysis
Multivariate statistical analysis
Organic matter
Principal Component Analysis
Principal components analysis
Quality assessment
Quality control
Regression models
Research Article
River flow
River water
Rivers
Rivers - chemistry
Statistical analysis
Statistical methods
Variance analysis
Waste Water Technology
Water analysis
Water Management
Water Pollutants, Chemical - analysis
Water Pollution Control
Water Quality
Water quality assessments
Water sampling
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Summary:In this work, we present the water quality assessment of an urban river, the San Luis River, located in San Luis Province, Argentina. The San Luis River flows through two developing cities; hence, urban anthropic activities affect its water quality. The river was sampled spatially and temporally, evaluating ten physicochemical variables on each water sample. These data were used to calculate a Simplified Index of Water Quality in order to estimate river water quality and infer possible contamination sources. Data were statistically analyzed with the opensource software R, 4.1.0 version. Principal component analysis, cluster analysis, correlation matrices, and heatmap analysis were performed. Results indicated that water quality decreases in areas where anthropogenic activities take place. Robust inferential statistical analysis was performed, employing an alternative of multivariate analysis of variance (MANOVA), MANOVA.wide function. The most statistically relevant physicochemical variables associated with water quality decrease were used to develop a multiple linear regression model to estimate organic matter, reducing the variables necessary for continuous monitoring of the river and, hence, reducing costs. Given the limited information available in the region about the characteristics and recovery of this specific river category, the model developed is of vital importance since it can quickly detect anthropic alterations and contribute to the environmental management of the rivers. This model was also used to estimate organic matter at sites located in other similar rivers, obtaining satisfactory results.
ISSN:1614-7499
0944-1344
1614-7499
DOI:10.1007/s11356-024-33205-0