ABSTRACT
Following the B1 dam collapse at Córrego do Feijão Mine, actions were taken to address environmental damage and enhance the quality of water in the Paraopeba River. Natural processes in the river involve gradual reduction of contamination through dispersion and downstream transportation of tailings-a slow, nature-driven process. Dredging, a human intervention, aimed to expedite recovery. Hence, this study aimed to explore dredging's role in reducing contamination in the impacted Paraopeba River zone. Analysis revealed a direct link between dredging and post-collapse turbidity, though recent trends suggest a lessening impact on pre-collapse conditions. Distinct seasonal variations were observed in iron and manganese concentrations, peaking during wet seasons and displaying notable upstream-downstream disparities. An analysis of ratios (downstream/upstream) was conducted to understand and even predict the return to pre-collapse conditions. Wet season averages for iron and manganese decreased by around 90 % over time, with standard deviations reducing by about 48 % and 58 %, respectively. In the dry season, the averages decreased by over 100 %, indicating water quality improvements surpassing pre-collapse levels. Standard deviations also decreased significantly, by approximately 67 % and 79 %, respectively. Employing an exponential decay model revealed that the contribution of dredging in the dry period is negligible, but in the wet period the contribution can be estimated at 28.6 % in the case of iron and 25 % in the case of manganese. While the models performed well based on extensive data, some limitations occur in estimating dredging contribution rates. The model's sensitivity might overlook influential factors, underscoring the importance of considering sediment nature and dredged area extent in understanding water quality dynamics. Despite these potential limitations, this investigation provides crucial insights into the intricate relationship between dredging and water quality in the Paraopeba River. These findings pave the way for future studies aimed at deeper exploration and more accurate assessments of this association.
ABSTRACT
Water management is a crucial tool for addressing the increasing uncertainties caused by climate change, biodiversity loss and the conditions of socioeconomic limits. The multiple factors affecting water resources need to be successfully managed to achieve optimal governance and thus move towards water security. This study seeks to obtain a holistic vision of the various threats that affect the ecological integrity of the basins that form the hydrological district of Galicia-Costa, through the method of partial least squares path modelling (PLS-PM). The data is analysed overall for the hydrological years from 2009 to 2015. The independent latent variables are "Anthropogenic" (comprising the percentage of water bodies with edges alongside artificial surfaces, the percentage connected to artificial land use patches, the edge density of artificial surfaces and population density) and "Nature" (edge density of forestry land uses, edge length of land water bodies alongside forested areas and the percentage of land occupied by the largest patch of forest). The dependent latent variables are "SWP", which represents surface water parameters (biological oxygen demand, chlorides, conductivity and dissolved iron) and "Ecological Integrity" (METI Bioindicator). The connections between latent variables are uantified through path coefficients (ß). From an overall perspective, the PLS-PM results reveal that 69.0% of "SWP" is predicted by the independent variables (R2 = 0.690), "Anthropogenic" contributes by increasing SWP (ß = 0.471), while "Nature" decreases the concentration of SWP (ß = -0.523), which indicates the polluting parameters in the water. The variables "Anthropogenic" (ß = -0.351) and "SWP" (ß = -0.265) lower the quality of "Ecological Integrity". This variable must be managed through soil conservation measures for the benefit of water security. This study has been able to identify and quantify the variables that increase contaminant concentration and decrease ecological integrity, providing a promising methodology that facilitates protection and correction measures to guarantee water safety.
