Relationship between land use and water quality in a watershed impacted by iron ore tailings and domestic sewage

• Published in: Revista ambiente & água Vol. 14; no. 5; pp. 1 - 11
• Main Authors: Nascimento, Laura Pereira do, Reis, Deyse Almeida, Roeser, Hubert Mathias Peter, Santiago, Aníbal Da Fonseca
• Format: Journal Article
• Language: English
• Published: Taubaté Instituto de Pesquisas Ambientais em Bacias Hidrográficas 2019; Instituto de Pesquisas Ambientais em Bacias Hidrográficas (IPABHi)
• Subjects: Components; Deforestation; E coli; ENGINEERING, ENVIRONMENTAL; Environmental impact; Erosion; Heavy metals; Household wastes; Iron; iron mining; Iron ores; Land cover; Land use; Lithology; Metal concentrations; Metalloids; Metals; Mine tailings; Multivariate analysis; multivariate statistics; Phosphorus; Principal components analysis; rio doce; River basins; Rivers; Sewage; Stations; Statistical analysis; Statistical methods; Surface water; Turbidity; Urbanization; Water analysis; Water quality; Water sampling; Watersheds; Brazil; mineração de ferro; iron mining; Rio Doce; estatística multivariada; multivariate statistics
• ISSN: 1980-993X; 1980-993X
• DOI: 10.4136/ambi-agua.2383

Changes in land use and land cover in watersheds, together with population increases and urbanization of these areas, have caused negative impacts on surface water quality. Based on land-use types, we conducted a comprehensive water quality study of the Rio do Peixe watershed, a tributary of the Rio Doce River, located in the Iron Quadrangle, with different land uses/land covers. For this study, the relationship between water quality variables and land use types were examined according to the water quality index and principal components analysis. The water samples were collected from twelve stations located along the basin in two different seasons. The results of metals/semimetals concentrations reflected regional lithology, and in the case of iron, it was anthropic activities. Also, the computed water quality index values were between 26.8 and 74.9. The water quality was poor in four stations of the river basin in both seasons. Furthermore, the variables that influence water quality the most were E. coli, DBO, turbidity, nitrate, and total phosphorus. The multivariate statistics gave five principal components that together accounted for 58.3%, whereas analysis of score plots identified the formation of two groups with more perceptible anthropic influence. Finally, environmental impacts of the river basin, such as deforestation, erosion, domestic sewage, and iron ore tailings, were the main factors that interfered with water quality.