Causality among landscape characteristics, seasonality and stream water quality in the Paraopeba river basin

Anthropogenic pressures on the environment are increasingly evident, characterized by uncontrolled changes in land use that adversely affect water quality. This study aims to assess how land use and land cover contribute to water quality and to evaluate the influence of spatial landscape metrics on...

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Main Authors: Fernando Arão Bila Júnior, Fernando António Leal Pacheco, Renato Farias do Valle Junior, Maytê Maria Abreu Pires de Melo Silva, Teresa Cristina Tarlé Pissarra, Marília Carvalho de Melo, Carlos Alberto Valera, Luís Filipe Sanches Fernandes, João Paulo Moura
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Case Studies in Chemical and Environmental Engineering
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Online Access:http://www.sciencedirect.com/science/article/pii/S2666016424002500
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author Fernando Arão Bila Júnior
Fernando António Leal Pacheco
Renato Farias do Valle Junior
Maytê Maria Abreu Pires de Melo Silva
Teresa Cristina Tarlé Pissarra
Marília Carvalho de Melo
Carlos Alberto Valera
Luís Filipe Sanches Fernandes
João Paulo Moura
author_facet Fernando Arão Bila Júnior
Fernando António Leal Pacheco
Renato Farias do Valle Junior
Maytê Maria Abreu Pires de Melo Silva
Teresa Cristina Tarlé Pissarra
Marília Carvalho de Melo
Carlos Alberto Valera
Luís Filipe Sanches Fernandes
João Paulo Moura
author_sort Fernando Arão Bila Júnior
collection DOAJ
description Anthropogenic pressures on the environment are increasingly evident, characterized by uncontrolled changes in land use that adversely affect water quality. This study aims to assess how land use and land cover contribute to water quality and to evaluate the influence of spatial landscape metrics on water quality variability in eight tributary sub-basins of the Paraopeba River. The analysis considers two seasonal periods reflective of the region's tropical climate. The dataset includes spatial data on land use and land cover, digital elevation models, soil types, geology, geomorphology, spatial-temporal data, and landscape fragmentation metrics. First, spatial differences in water quality data collected at each sampling site were tested, and the significance of seasonal variations was assessed. Correlation analyses were then conducted to determine the relationships between landscape metrics and water quality parameters across the eight sub-basins, considering both seasonal periods. Key findings include the identification of mixed pollution sources, such as pasture, urban areas, and mining, which significantly affect water quality, particularly during the rainy period. Conversely, forest plantations were found to be the land use category that most positively contributed to the preservation of water quality. The relationships between landscape patterns and water quality, analyzed using redundancy analysis, revealed that the influence of landscape metrics on the variation of water quality parameters was significantly more pronounced during the dry period, explaining 75 % of the variation, compared to 49 % during the rainy period.
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spelling doaj-art-4fc19d9a91e9477c99d00905ed5633752024-12-02T05:05:50ZengElsevierCase Studies in Chemical and Environmental Engineering2666-01642024-12-0110100856Causality among landscape characteristics, seasonality and stream water quality in the Paraopeba river basinFernando Arão Bila Júnior0Fernando António Leal Pacheco1Renato Farias do Valle Junior2Maytê Maria Abreu Pires de Melo Silva3Teresa Cristina Tarlé Pissarra4Marília Carvalho de Melo5Carlos Alberto Valera6Luís Filipe Sanches Fernandes7João Paulo Moura8CITAB - Centro de Investigação e Tecnologias Agroambientais e Biológicas, Universidade de Trás-os-Montes e Alto Douro, Ap. 1013, 5001-801, Vila Real, PortugalCQVR - Chemistry Center of Vila Real, University of Trás-os-Montes and Alto Douro, Ap. 1013, 5001-801, Vila Real, Portugal; Corresponding author.Federal Institute of the Triângulo Mineiro, Campus Uberaba, Geoprocessing Laboratory, Uberaba, MG, 38064-790, BrazilFederal Institute of the Triângulo Mineiro, Campus Uberaba, Geoprocessing Laboratory, Uberaba, MG, 38064-790, BrazilSchool of Agricultural and Veterinary Sciences, Universidade Estadual Paulista (UNESP), Via de Acesso Prof. Paulo Donato Castellane, s/n, Jaboticabal, SP, 14884-900, BrazilState Secretariat for the Environment and Sustainable Development, Administrative City of the State of Minas Gerais, Rodovia João Paulo II, 4143, Bairro Serra Verde, Belo Horizonte, Minas Gerais, BrazilRegional Coordination of Environmental Justice Promoters of the Paranaíba and Baixo Rio Grande River Basins, Rua Coronel Antônio Rios, 951, Uberaba, MG, 38061-150, BrazilCITAB - Centro de Investigação e Tecnologias Agroambientais e Biológicas, Universidade de Trás-os-Montes e Alto Douro, Ap. 1013, 5001-801, Vila Real, PortugalCITAB - Centro de Investigação e Tecnologias Agroambientais e Biológicas, Universidade de Trás-os-Montes e Alto Douro, Ap. 1013, 5001-801, Vila Real, PortugalAnthropogenic pressures on the environment are increasingly evident, characterized by uncontrolled changes in land use that adversely affect water quality. This study aims to assess how land use and land cover contribute to water quality and to evaluate the influence of spatial landscape metrics on water quality variability in eight tributary sub-basins of the Paraopeba River. The analysis considers two seasonal periods reflective of the region's tropical climate. The dataset includes spatial data on land use and land cover, digital elevation models, soil types, geology, geomorphology, spatial-temporal data, and landscape fragmentation metrics. First, spatial differences in water quality data collected at each sampling site were tested, and the significance of seasonal variations was assessed. Correlation analyses were then conducted to determine the relationships between landscape metrics and water quality parameters across the eight sub-basins, considering both seasonal periods. Key findings include the identification of mixed pollution sources, such as pasture, urban areas, and mining, which significantly affect water quality, particularly during the rainy period. Conversely, forest plantations were found to be the land use category that most positively contributed to the preservation of water quality. The relationships between landscape patterns and water quality, analyzed using redundancy analysis, revealed that the influence of landscape metrics on the variation of water quality parameters was significantly more pronounced during the dry period, explaining 75 % of the variation, compared to 49 % during the rainy period.http://www.sciencedirect.com/science/article/pii/S2666016424002500Landscape patternLandscape compositionRiver water contaminationMultiple-use watershedMultivariate statistics
spellingShingle Fernando Arão Bila Júnior
Fernando António Leal Pacheco
Renato Farias do Valle Junior
Maytê Maria Abreu Pires de Melo Silva
Teresa Cristina Tarlé Pissarra
Marília Carvalho de Melo
Carlos Alberto Valera
Luís Filipe Sanches Fernandes
João Paulo Moura
Causality among landscape characteristics, seasonality and stream water quality in the Paraopeba river basin
Case Studies in Chemical and Environmental Engineering
Landscape pattern
Landscape composition
River water contamination
Multiple-use watershed
Multivariate statistics
title Causality among landscape characteristics, seasonality and stream water quality in the Paraopeba river basin
title_full Causality among landscape characteristics, seasonality and stream water quality in the Paraopeba river basin
title_fullStr Causality among landscape characteristics, seasonality and stream water quality in the Paraopeba river basin
title_full_unstemmed Causality among landscape characteristics, seasonality and stream water quality in the Paraopeba river basin
title_short Causality among landscape characteristics, seasonality and stream water quality in the Paraopeba river basin
title_sort causality among landscape characteristics seasonality and stream water quality in the paraopeba river basin
topic Landscape pattern
Landscape composition
River water contamination
Multiple-use watershed
Multivariate statistics
url http://www.sciencedirect.com/science/article/pii/S2666016424002500
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