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<p>Surface water quality in the Quadrilátero Ferrífero, a mining province in southeastern Brazil, was evaluated by combining water quality indices (WQI), land use and land cover (LULC), and population data to identify spatial and seasonal influences on river chemistry. We analyzed 835 (rainy) and 845 (dry) samples and calculated WQI scores using established methods from the literature. The methods for calculating the WQI detected broad signals of eutrophication and those related to sanitation but were less sensitive to inorganic and potentially toxic elements (PTE), whereas CCME, especially when including PTE variables, offered a more rigorous and adaptable assessment for mining-influenced areas. Microcatchments were classified into LULC groups based on the proportional dominance and co-occurrence of classes. Across methods and seasons, WQI values showed a clear degradation gradient aligned with increasing human activity. Catchments dominated by natural cover and low-intensity uses consistently exhibited the highest WQI values; notably, mining-influenced classes with substantial natural vegetation often clustered towards this higher-quality end. In contrast, catchments shaped by human occupation in urban and rural settings showed the lowest WQI scores and were statistically distinct from the low-intensity group in most pairwise comparisons, although overlaps occurred among the anthropogenic classes depending on method and season. Total population per micro-catchment was inversely related to WQI results by IGAM method in both seasons, highlighting the impact of urban expansion and infrastructure pressures on water-quality decline. Overall, the LULC-based microcatchment classification was crucial for understanding how dominant land use patterns influence water quality and for guiding targeted watershed management in mining regions.</p>

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Land use controls the spatiotemporal patterns of surface water quality of the Quadrilátero Ferrífero mineral province, Brazil

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月20日

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  • Gabriel Soares de Almeida,
  • Rafael Tarantino Amarante,
  • Normara Yane Mar da Costa Andrade,
  • Roberto Dall’Agnol,
  • Prafulla Kumar Sahoo,
  • Paulo Rógenes Monteiro Pontes,
  • Emmanoel Vieira Silva-Filho,
  • Eduardo Duarte Marques,
  • Raquel Fernandes Mendonça,
  • Abraão Gomes Soares Junior,
  • Gabriel Negreiros Salomão

摘要

Surface water quality in the Quadrilátero Ferrífero, a mining province in southeastern Brazil, was evaluated by combining water quality indices (WQI), land use and land cover (LULC), and population data to identify spatial and seasonal influences on river chemistry. We analyzed 835 (rainy) and 845 (dry) samples and calculated WQI scores using established methods from the literature. The methods for calculating the WQI detected broad signals of eutrophication and those related to sanitation but were less sensitive to inorganic and potentially toxic elements (PTE), whereas CCME, especially when including PTE variables, offered a more rigorous and adaptable assessment for mining-influenced areas. Microcatchments were classified into LULC groups based on the proportional dominance and co-occurrence of classes. Across methods and seasons, WQI values showed a clear degradation gradient aligned with increasing human activity. Catchments dominated by natural cover and low-intensity uses consistently exhibited the highest WQI values; notably, mining-influenced classes with substantial natural vegetation often clustered towards this higher-quality end. In contrast, catchments shaped by human occupation in urban and rural settings showed the lowest WQI scores and were statistically distinct from the low-intensity group in most pairwise comparisons, although overlaps occurred among the anthropogenic classes depending on method and season. Total population per micro-catchment was inversely related to WQI results by IGAM method in both seasons, highlighting the impact of urban expansion and infrastructure pressures on water-quality decline. Overall, the LULC-based microcatchment classification was crucial for understanding how dominant land use patterns influence water quality and for guiding targeted watershed management in mining regions.