Sediment source fingerprints of natural processes and anthropogenic pressures: A contribution to manage the Paraopeba River basin impacted by the B1 tailings dam collapse.

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.

Geomorphologic risk zoning to anticipate tailings dams' hazards: A study in the Brumadinho's mining area, Minas Gerais, Brazil.

The use of tailings dams in the mining industry is recurrent and a matter of concern given the risk of collapse. The planning of tailings dam's emplacement usually attends construction design criteria and site geotechnical properties, but often neglects the risk of installing the depositional facilities in potentially unstable landscapes, namely those characterized by steep slopes and(or) high drainage densities. In order to help bridging this gap, the present study developed a framework model whereby geomorphologic vulnerability is assessed by a set of morphometric parameters (e.g., drainage density; relief ratio; roughness coefficient). Using the Ribeirão Ferro-Carvão micro-basin (3265.16 ha) as test site, where six dams currently receive tailings from the mining of iron-ore deposits in the Brumadinho region (Minas Gerais, Brazil) and one has collapsed in 25 January 2019 (the B1 dam of Córrego do Feijão mine of Vale, S.A.), the risk of dam instability derived from geomorphologic vulnerability was assessed and alternative suitable locations were highlighted when applicable. The results made evident the location of five dams (including the collapsed B1) in high-risk regions and two in low-risk regions, which is preoccupying. The alternative locations represent 58 % of Ribeirão Ferro-Carvão micro-basin, which is a reasonable and workable share. Overall, the study exposed the fragility related with tailings dams' geography, which is not restricted to the studied micro-basin, because dozens of active tailings dams exist in the parent basin (the Paraopeba River basin) that can also be vulnerable to geomorphologically-dependent hydrologic hazards such as intensive erosion, valley incision or flash floods. Attention to this issue is therefore urgent to prevent future tragedies related with tailings dams' breaks, in the Paraopeba River basin or elsewhere, using the proposed framework model as guide.

Scenarios of environmental deterioration in the Paraopeba River, in the three years after the breach of B1 tailings dam in Brumadinho (Minas Gerais, Brazil).

The collapse of B1 dam at the Córrego do Feijão mine of Vale, S.A., located in the Ferro-Carvão stream watershed (Brazil), released 11.7 Mm3 of tailings rich in iron and manganese, and 2.8 Mm3 entered the Paraopeba River 10 km downstream. Seeking to predict the evolution of environmental deterioration in the river since the dam break on January 25, 2019, the present study generated exploratory and normative scenarios based on predictive statistical models, and proposed mitigating measures and subsides to ongoing monitoring plans. The scenarios segmented the Paraopeba into three sectors: "anomalous" for distances ≤63.3 km from the B1 dam site, "transition" (63.3-155.3 km), and "natural" (meaning unimpacted by the mine tailings in 2019; >155.3 km). The exploratory scenarios predicted a spread of the tailings until reaching the "natural" sector in the rainy season of 2021, and their containment behind the weir of Igarapé thermoelectric plant located in the "anomalous" sector, in the dry season. Besides, they predicted the deterioration of water quality and changes to the vigor of riparian forests (NDVI index) along the Paraopeba River, in the rainy season, and a restriction of these impacts to the "anomalous" sector in the dry season. The normative scenarios indicated exceedances of chlorophyll-a in the period January 2019-January 2022, but not exclusively caused by the rupture of B1 dam as they also occurred in areas not affected by the accident. Conversely, the manganese exceedances clearly flagged the dam failure, and persist. The most effective mitigating measure is likely the dredging of the tailings in the "anomalous" sector, but currently it represents solely 4.6 % of what has entered the river. Monitoring is paramount to update the scenarios until the system enters a route towards rewilding, and must include water and sediments, the vigor of riparian vegetation, and the dredging.

A framework model to determine groundwater contamination risk based on a L-Matrix of aquifer vulnerability and hazardous activity indices.

The method presented in this study assesses groundwater contamination risk using a L-Matrix system approach. The L-Matrix in this case is a cartesian diagram where the XX-axis represents aquifer vulnerability (0≤V≤1) determined by the well-known DRASTIC model, and the YY-axis represents the potential hazardousness (0≤H≤1) of an activity (infrastructural development, industrial activities, livestock and agriculture) measured by a European Commission approach. The diagram is divided into four regions, the boundaries of which are set to V = 0.5 and H = 0.5. Watersheds are represented in this diagram considering their V and H indices, and assigned a potential contamination risk if groundwater sites located within their limits show contaminant concentrations above legal limits for a given use. Depending on the region the watershed falls in the L-Matrix diagram, different management or contamination prevention actions are highlighted: activity development, activity monitoring, activity planning or activity inspecting. Watersheds located in the inspecting region and simultaneously evidencing contamination risk require immediate action, namely conditioning or even suspension of use. The method is tested in the Paraopeba River basin (Minas Gerais, Brazil), a densely industrialized basin that was recently affected by an iron-ore mine tailings dam break.•The L-Matrix diagram highlights different groundwater susceptibility realities experienced by watersheds with different combinations of aquifer vulnerability and activity hazardousness, namely possibility for potential expansion of new hazardous activities but also the necessity to periodically inspect and eventually condition or suspend others.•The L-Matrix diagram is likely a better approach to implement contamination prevention measures in watersheds, than the integrated contamination risk index used by most methods.

A partial least squares-path model of environmental degradation in the Paraopeba River, for rainy seasons after the rupture of B1 tailings dam, Brumadinho, Brazil.

The present study aimed to investigate the rupture of B1 tailings dam of Córrego do Feijão mine, which drastically affected the region of Brumadinho (Minas Gerais, Brazil). The contamination of water resources reached 155.3 km from the dam site. In the river channel, high concentrations of Mn, Al, As and Fe were detected and correlated to the spillage of the tailings in the river. The presence of the tailings also affected the chlorophyll-a content in the water, as well as the reflectance of riparian forests. With the increase of metal(oid) concentrations above permitted levels, water management authorities suspended the use of Paraopeba River as resource in the impacted areas, namely the drinking water supply to the Metropolitan region of Belo Horizonte. This study aimed to evaluate possible links between tailings distribution, river water quality, and environmental degradation, which worked as latent variables in partial least squares regression models. The latent variables were represented by numerous physical and chemical parameters of water and sediment, measured four times in 22 locations during the rainy season of 2019, in addition to stream flow and to NDVI evaluated in satellite images processed daily. The modeling results suggested a relationship between river flow turbulence and increased arsenic release from sand fractions, as well as desorption of Mn from metal oxides, both representing causes of water quality reduction. They also revealed increasing iron concentrations affecting the forest NDVI (greening), which was interpreted as environmental degradation. The increase of chlorophyll-a concentrations (related with turbidity decreases), as well as the increase of river flows (responsible for dilution effects), seemed to work out as attenuators of degradation. Although applied to a specific site, our modeling approach can be transposed to equivalent dam failures and climate contexts, helping water resource management authorities to decide upon appropriate recovery solutions.

Water security threats and challenges following the rupture of large tailings dams.

The rupture of mine-tailings dams can severely contaminate rivers, because released tailings can interact with water for years keeping contaminant concentrations high. The general purpose of this study was to examine the rupture of B1 tailings dam in Ferro-Carvão stream (municipality of Brumadinho, state of Minas Gerais, Brazil), which occurred in 25 January 2019 and contaminated the main water course (Paraopeba River) with 2.8 Mm3 of metal-rich tailings. The specific purpose was to assess the percentage of non-conforming concentrations following the event, considering the Normative Deliberation COPAM/CERH-MG no. 1. The results showed non-conforming aluminum, iron, manganese, lead, phosphorus and turbidity concentrations, clearly above pre-rupture averages, especially in the rainy period. The catastrophe triggered the suspension of Paraopeba River as drinking water source to the Metropolitan Region of Belo Horizonte (BHMR; 6 million people). Since then, the supply to the BHMR became an everyday challenge to water management authorities, because the Paraopeba source represented a 30% share. Mitigation measures are therefore urgently needed. As complementary objective to this study, we aimed to verify the possibility to restore drinking water supply through conventional treatment. The treatability of Paraopeba River water was assessed by the Raw Water Quality Index considering the rainy and dry periods in separate. The results suggested the possibility to lift up the suspension in the dry period, improving the regional water security. Considering the huge dataset on which this study is standing, our results are generalizable to similar events with sparser information.

A partial least squares-path model of causality among environmental deterioration indicators in the dry period of Paraopeba River after the rupture of B1 tailings dam in Brumadinho (Minas Gerais, Brazil).

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.

Prognosis of metal concentrations in sediments and water of Paraopeba River following the collapse of B1 tailings dam in Brumadinho (Minas Gerais, Brazil).

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.

Estimating water erosion from the brightness index of orbital images: A framework for the prognosis of degraded pastures.

The inadequate management of soils and the absence of conservation practices favor the degradation of pastures and can trigger adverse environmental alterations and damage under the terms of Brazilian Federal Law no. 6.938/1981. Based on this premise, this study aimed to estimate soil losses caused by water erosion in pasture areas using the brightness index (BI) from the annual series of Landsat 8 images in different geological formations. A specifically prepared Google Earth Engine (GEE) script automatically extracted the BI from the images. The study occurred in the Environmental Protection Area (EPA) of Uberaba River basin (Minas Gerais, Brazil). To accomplish the goal, 180 digital 500-wide random buffers were selected from 3 geologic types (60 points per type), and then analyzed for zonal statistics of USLE (Universal Soil Loss Equation) soil loss and BI in a Geographic Information System. The regression models BI versus USLE soil loss allowed estimating BI soil losses over the pastures of EPA. The model fittings were remarkable. The validation of soil loss maps in the EPA occurred in pasture phytophysiognomies through the probing of penetration resistance in 37 randomly selected locations. The results were satisfactory, mostly those based on the BI. The BI losses increased for greater resistances. Amplified losses also occurred in regions exposed to environmental land use conflicts (actual uses that deviate from land capability or natural use). Overall, the BI approach proved efficient to accurately track soil losses and pasture degradation over large areas, with the advantage of standing on a single parameter easily accessed through remote sensed data. From an environmental standpoint, this is an important result, because the accurate diagnosis and prognosis of degraded pastures is paramount to implement mitigation measures following the "polluter pays principle", even more in Brazil where the areas occupied by degraded pastures are enormous.

A case study of factors controlling water quality in two warm monomictic tropical reservoirs located in contrasting agricultural watersheds.

The integration of internal (e.g., stratification) and external (e.g., pollution) factors on a comprehensive assessment of reservoir water quality determines the success of ecosystem restoration initiatives and aids watershed management. However, integrated analyses are scarcer than studies addressing factors separately. Integration is likely more efficient in studies of small well-characterized (experimental) reservoir watersheds, because the isolation of factor contributions is presumably clearer. But those studies are uncommon. This work describes the water quality of two small 5.5 m-deep reservoirs (MD-Main and VD-Voçoroca dams) located in Pindorama Experimental Center, state of São Paulo, Brazil, considering the interplay between reservoir dimension, seasonal thermal stratification, chemical gradients, erosive rainfall events, presence of natural biofilters, and land uses and landscape patterns around the reservoirs and within the contributing watersheds. The monitoring of agricultural activities and water quality parameters occurred in October 2018-July 2019. A 4 °C thermal stratification occurred in October (difference between surface and bottom water temperature), which decreased until disappearance in January (VD) or April (MD). The longer stratification period of MD was justified by its larger area relative to VD (≈10×). Thermal stratification triggered hypoxia at the bottom of both reservoirs (DO ≈ 1 mg/L), more prolonged and severe in MD. Hypoxia activated Ec and TDS peaks in January likely explained by bottom-sediment nutrient releases, presumably phosphorus. The Ec peak reached 560 µS/cm in MD and 290 µS/cm in VD. The smaller VD peak was probably explained by the action of macrophytes. In March, a 240 NTU turbidity peak occurred in MD, caused by precedent erosive rainfall and the lack of vegetation protection alongside the south border. As expected, the study accomplished clear isolation of factor contributions, verified by Factor and Cluster analyses. Our results can subsidize studies on larger reservoir watersheds requiring restoration, where the isolation of factors is more challenging.

The modeling of pasture conservation and of its impact on stream water quality using Partial Least Squares-Path Modeling.

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.

The assessment of water erosion using Partial Least Squares-Path Modeling: A study in a legally protected area with environmental land use conflicts.

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.