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Understanding the origins of sediment transport in river systems is crucial for effective watershed management, especially after catastrophic events. This information is essential for the development of integrated strategies that guarantee water security in river basins. The present study aimed to investigate the rupture of the B1 tailings dam of the Córrego do Feijão mine, which drastically affected the Brumadinho region (Minas Gerais, Brazil). To address this issue, a confluence-based sediment fingerprinting approach was developed through the SedSAT model. Uncertainty was assessed through Monte Carlo simulations and Mean Absolute Error (MAE). Estimates of the overall average contributions of each tributary were quantified for each station and annually during the period 2019-2021. It was observed that the sampling point PT-09, closest to the dam breach, contributed to almost 80% of the Paraopeba River in 2019. Despite the dredging efforts, this percentage increased to 90% in 2020 due to the need to restore the highly degraded area. Additionally, the main tributaries contributing to sediment increase in the river are Manso River "TT-03" (almost 36%), associated with an area with a high percentage of urban land use, and Cedro stream "TT-07" (almost 71%), whose geology promotes erosion, leading to higher sediment concentration. Uncertainties arise from the limited number of available tracers, variations caused by dredging activities, and reduced data in 2020 due to the pandemic. Parameters such as land use, riparian vegetation degradation, downstream basin geology, and increased precipitation are key factors for successfully assessing tributary contributions to the Paraopeba River. The obtained results are promising for a preliminary analysis, allowing the quantification of key areas due to higher erosion and studying how this disaster affected the watershed. This information is crucial for improving decision-making, environmental governance, and the development of mitigating measures to ensure water security. This study is pioneering in evaluating this methodology in watersheds affected by environmental disasters, where restoration efforts are ongoing.

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This study investigated the collapse of B1 mine-tailings dam that occurred in 25 January 2019 and severely affected the Brumadinho region (Minas Gerais state, Brazil) socially, economically and environmentally. As regards water resources, the event impacted the Paraopeba River in the first 155.3 km counted from the dam site, meaning nearly half the main water course downstream of B1. In the impacted sector, high concentrations of tailings-related Al, Fe, Mn, P in river sediment-tailings mixtures and water were detected, as well as changes to the reflectance of riparian forests. In the river water, the metal concentrations raised significantly above safe levels. For caution, the water management authorities declared immediate suspension of Paraopeba River as drinking water source to the Metropolitan Region of Belo Horizonte (6 million people), irrespective of representing nearly 30% of all supply. In this study, the main purpose was to assess potential links between tailings distribution, river water composition and reflectance of forest vegetation, which worked out as latent variables in regression models. The latent variables were represented by numerous physical and chemical parameters, measured 4 times in 22 sites during the dry period of 2019. The modeling results suggested the release of aluminum and phosphorus from sand fractions in the mine tailings as major cause of water contamination. The NDVI changes were interpreted as environmental deterioration. Changes in redox potential may have raised manganese concentrations in surface water further affecting the forest NDVI. Distance from the B1 dam and dissolved calcium appear to attenuate deterioration. Overall, the regressions allowed robust prognoses of environmental deterioration in the Paraopeba River under low flow conditions. More importantly, they can be transposed to similar dam ruptures helping environmental authorities to decide upon measures that can bring the affected rivers to pre-rupture conditions.

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In January 25, 2019, the B1 dam of Córrego do Feijão mine located in Brumadinho municipality (Minas Gerais, Brazil) collapsed and injected nearly 2.8 Mm3 of iron (Fe)- and manganese (Mn)-rich tailings in the Paraopeba River. This study assessed the contribution of tailings to the contamination of sediments and water by those metals. The dataset was built through daily to weekly samplings executed in the two years following the event, at 27 sites located along the Paraopeba plus 9 sites located at the confluence of main tributaries. The results evidenced a distinct contribution in the sectors "Anomalous" (8.6-63.3 km downstream from the dam) and "Natural" (115.8-341.6 km). The "Anomalous" sector presented large Fe/Al (12.2 ± 6.4) and Mn/Al (0.33 ± 0.19) ratios in sediments, thus being rich in tailings, while the "Natural" sector presented small ratios (2.4 ± 1.0; 0.06 ± 0.03) comparable to the natural sediments. A 500-700 m3/s stream flow discharge in the Paraopeba caused pronounced drops to the Fe/Al and Mn/Al ratios in the "Anomalous" sector, attributed to the mixture of contaminated sediments from the main water course with uncontaminated sediments injected by the tributaries during the event. Non-linear regressions showed Fe/Al and Mn/Al declines in the "Anomalous" sector, related with tailings mobilization downstream. The concentrations of Fe and Al in the sediments correlated positively with the corresponding concentrations in the Paraopeba water, conditioned by raising discharge rates and variations in the water pH. The contribution of tailings to the Fe correlation was demonstrated. No direct relation was established between the Mn concentrations in water and stream discharge, because manganese is associated with fine particles in the tailings that are mobilized to the water column even under low flows. The preliminary results of Seasonal Autoregressive Integrated Moving Average models predicted the return of Paraopeba to a pre-collapse condition in 7-11 years.

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Cattle grazing is a major source of income across the globe, and therefore conservation of pastures is vital to society. Pasture conservation requires the full understanding of factors contributing to their degradation, which is facilitated through panoramic analyses capable to handle all factors and capture their relationships at once. In this study, Partial Least Squares - Path Modeling (PLS-PM) was used to accomplish that task. The study area was the Environmental Protection Area of Uberaba River Basin (525 km2), located in the state of Minas Gerais, Brazil, and extensively used for livestock pasturing (51%). The selected (15) contributing factors comprised soil characteristics (e.g., organic matter, phosphorus content), runoff indicators (e.g., percentage of sand and clay in the soil), environmental land use conflicts (deviations of actual from natural uses), stream water quality parameters (e.g., oxidation-reduction potential-ORP, turbidity), and pasture conservation indicators (extent of degraded pasture within a pre-defined buffer). These measured variables were assembled into 5 conceptual (latent) variables to form the PLS-PM model, namely Groundcover, Pasture Conservation, Surface Runoff, Environmental Land Use Conflicts and Water Quality. The results elected Groundcover as prominent contributor to Pasture Conservation, because of its largest regression (path) coefficient (ß = 0.984). The most influent measured variable was organic matter. Surface Runoff (ß = -0.108) and Environmental Land Use Conflicts (ß = -0.135) contribute to pasture degradation. The role of conflicts is, however, limited to predefined areas where the deviations of actual from natural uses are more expressive. Pasture Conservation contributes unequivocally to improved Water Quality (ß = 0.800), expressed as high ORP. The PLS-PM model was free from multi-collinearity problems and model fits (R2) were high. This gives us confidence to implement conservation measures and improved management techniques based on the PLS-PM results, and to transpose the model to other areas requiring pasture quality improvements.

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Water erosion has historically been assessed by various methods, with the purpose to help reducing this phenomenon. However, application of models capable to handle complex relationships between large numbers of variables is still relatively scarce. The method of Partial Least Squares-Path Modeling (PLS-PM), used in this study, was able to expose complex causal paths between soil erosion and potentially related factors, namely "Surface Runoff", "Environmental Land Use Conflicts", "Soil Fertility" and "Relief Factors", within the Environmental Protection Area of Uberaba River Basin (EPA) located in Minas Gerais state, Brazil. In the context of PLS-PM, soil erosion (dependent) and the related factors (independent) are called latent variables and described by measured or estimated parameters. For example, the "Relief Factors" were described by measured drainage density and topographic slope. These were linked to the corresponding latent variables through weights and the later joined to each other through paths. During the PLS-PM runs, weights and paths were quantified and latent variables interpreted in regard to their importance for soil erosion and spatial incidence. The spatial incidence was used to prioritize areas for soil conservation. To test the model, data were obtained from soil samples (texture and fertility parameters) or digitally extracted from cartographic products (e.g., maps of soil loss, land use, brightness index, topographic slope, drainage density), at 37 sites within the EPA. The PLS-PM results revealed that 70.2% of soil erosion is predicted by the independent variables (R2 = 0.702), and that "Soil Fertility" and "Environmental Land Use Conflicts" were the most influencing ones (ß = -0.758 and ß = 0.346, respectively). These variables can be managed by man, through implementation of effective soil conservation measures and respect for suitable land use. It is therefore urgent to act in these regard, considering the socioeconomic and environmental importance of the EPA.

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The potential of karst aquifers as a drinking water resource is substantial because of their large storage capacity gained in the course of carbonate dissolution. Carbonate dissolution and consequent development of preferential paths are also the reasons for the complex behavior of these aquifers as regards surface and underground flow. Hydrological modeling is therefore of paramount importance for an adequate assessment of flow components in catchments shaped on karsts. The cross tabulation of such components with geology, soils, and land use data in Geographic Information Systems helps decision makers to set up sustainable groundwater abstractions and allocate areas for storage of quality surface water, in the context of conjunctive water resources management. In the present study, a hydrologic modeling using the JAMS J2000 software was conducted in a karst area of Jequitiba River basin located near the Sete Lagoas town in the state of Minas Gerais, Brazil. The results revealed a very high surface water component explained by urbanization of Sete Lagoas, which hampers the recharge of 7.9 hm3 yr-1 of storm water. They also exposed a very large negative difference (-8.3 hm3 yr-1) between groundwater availability (6.3 hm3 yr-1) and current groundwater abstraction from the karst aquifer (14.6 hm3 yr-1), which is in keeping with previously reported water table declines around drilled wells that can reach 48 m in old wells used for public water supply. Artificial recharge of excess surface flow is not recommended within the urban areas, given the high risk of groundwater contamination with metals and hydrocarbons potentially transported in storm water, as well as development of suffosional sinkholes as a consequence of concentrated storm flow. The surface component could however be stored in small dams in forested areas from the catchment headwaters and diverted to the urban area to complement the drinking water supply. The percolation in soil was estimated to be high in areas used for agriculture and pastures. The implementation of correct fertilizing, management, and irrigation practices are considered crucial to attenuate potential contamination of groundwater and suffosional sinkhole development in these areas.

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Roads play an important role in the economic development of cities and regions, but the transport of cargo along highways may represent a serious environmental problem because a large portion of transported goods is composed of dangerous products. In this context, the development and validation of risk management tools becomes extremely important to support the decision-making of people and agencies responsible for the management of road enterprises. In the present study, a method for determination of environmental vulnerability to road spills of hazardous substances is coupled with accident occurrence data in a highway, with the purpose to achieve a diagnosis on soil and water contamination risk and propose prevention measures and emergency alerts. The data on accident occurrences involving hazardous and potentially harmful products refer to the highway BR 050, namely the segment between the Brazilian municipalities of Uberaba and Uberlândia. The results show that many accidents occurred where vulnerability is high, especially in the southern sector of the segment, justifying the implementation of prevention and alert systems. The coupling of vulnerability and road accident data in a geographic information system proved efficient in the preparation of quick risk management maps, which are essential for alert systems and immediate environmental protection. Overall, the present study contributes with an example on how the management of risk can be conducted in practice when the transport of dangerous substances along roads is the focus problem.

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