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Environmental vulnerability is an important tool to understand the natural and anthropogenic impacts associated with the susceptibility to environmental damage. This study aims to assess the environmental vulnerability of the Doce River basin in Brazil through Multicriteria Decision Analysis based on Geographic Information Systems (GIS-MCDA). Natural factors (slope, elevation, relief dissection, rainfall, pedology, and geology) and anthropogenic factors (distance from urban centers, roads, mining dams, and land use) were used to determine the environmental vulnerability index (EVI). The EVI was classified into five classes, identifying associated land uses. Vulnerability was verified in water resource management units (UGRHs) and municipalities using hot spot analysis. The study employed the water quality index (WQI) to assess the EVI and global sensitivity analysis (GSA) to evaluate the model input parameters that most influence the basin's environmental vulnerability. The results showed that the regions near the middle Doce River were considered environmentally more vulnerable, especially the UGRHs Guandu, Manhuaçu, and Caratinga; and 35.9% of the basin has high and very high vulnerabilities. Hot spot analysis identified regions with low EVI values (cold spot) in the north and northwest, while areas with high values (hot spot) were concentrated mainly in the middle Doce region. Water monitoring stations with the worst WQI values were found in the most environmentally vulnerable areas. The GSA determined that land use and slope were the primary factors influencing the model's response. The results of this study provide valuable information for supporting environmental planning in the Doce River basin., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Surface sediment concentration (SSC) is linked to several problems related to water quality and its monitoring is costly because of the required fieldwork and laboratory analyses. Thus, sediment measurements are often sporadic, punctual, and performed during a short period. Orbital remote sensing allows the monitoring of SSC along the river channel permitting continuous and spatial information. This work had two objectives: (1) to model the surface concentration of sediments in the main channel of the Doce river using data from Multispectral Instrument (MSI)/Sentinel 2 and Operational Land Imager (OLI)/Landsat 8 satellite sensors; and (2) to compare different linear modeling approaches to select the best variables for SSC monitoring. For comparison with actual field data, we used mean SSC measurements in 14 sediment gauge stations from 2013 to 2020. Reflectance data of the MSI/Sentinel 2 and OLI/Landsat 8 satellites bands and spectral indices related to the monitoring of water resources were used as explanatory variables. Simple and multiple linear regression models (SLR and MLR), least absolute shrinkage and selection operator (LASSO), and Elastic Net regression were used to predict the SSC. The near-infrared band images from both MSI/Sentinel 2 and OLI/Landsat 8 satellites showed a strong linear relationship with the SSC. Multiple linear regression, LASSO and Elastic Net regressions showed good performance for SSC prediction. Sediment flow maps show an SSC reduction in the Doce river channel in recent years, indicating that part of the material from the Fundão tailings dam rupture may have been transported through sediment resuspension and transport processes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

[This corrects the article DOI: 10.1371/journal.pone.0179414.].

Studies on the impacts of land-use and land-cover change on stream hydrochemistry in active deforestation zones of the Amazon agricultural frontier are limited and have often used low-temporal-resolution datasets. Moreover, these impacts are not concurrently assessed in well-established agricultural areas and new deforestations hotspots. We aimed to identify these impacts using an experimental setup to collect high-temporal-resolution hydrological and hydrochemical data in two pairs of low-order streams in catchments under contrasting land use and land cover (native vegetation vs. pasture) in the Amazon and Cerrado biomes. Our results indicate that the conversion of natural landscapes to pastures increases carbon and nutrient fluxes via streamflow in both biomes. These changes were the greatest in total inorganic carbon in the Amazon and in potassium in the Cerrado, representing a 5.0- and 5.5-fold increase in the fluxes of each biome, respectively. We found that stormflow, which is often neglected in studies on stream hydrochemistry in the tropics, plays a substantial role in the carbon and nutrient fluxes, especially in the Amazon biome, as its contributions to hydrochemical fluxes are mostly greater than the volumetric contribution to the total streamflow. These findings demonstrate that assessments of the impacts of deforestation in the Amazon and Cerrado biomes should also take into account rapid hydrological pathways; however, this can only be achieved through collection of high-temporal-resolution data., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Understanding the impacts of land-use change on landscape-hydrological dynamics is one of the main challenges in the Northern Brazilian Cerrado biome, where the Amazon agricultural frontier is located. Motivated by the gap in literature assessing these impacts, we characterized the soil hydro-physical properties and quantified surface water fluxes from catchments under contrasting land-use in this region. We used data from field measurements in two headwater micro-catchments with similar physical characteristics and different land use, i.e. cerrado sensu stricto vegetation and pasture for extensive cattle ranching. We determined hydraulic and physical properties of the soils, applied ground-based remote sensing techniques to estimate evapotranspiration, and monitored streamflow from October 2012 to September 2014. Our results show significant differences in soil hydro-physical properties between the catchments, with greater bulk density and smaller total porosity in the pasture catchment. We found that evapotranspiration is smaller in the pasture (639 ± 31% mm yr-1) than in the cerrado catchment (1,004 ± 24% mm yr-1), and that streamflow from the pasture catchment is greater with runoff coefficients of 0.40 for the pasture and 0.27 for the cerrado catchment. Overall, our results confirm that conversion of cerrado vegetation to pasture causes soil hydro-physical properties deterioration, reduction in evapotranspiration reduction, and increased streamflow.