Optical Spectral Tools for Diagnosing Water Media Quality: A Case Study on the Angara/Yenisey River System in the Siberian Region

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.

A combined GIS-MCDA approach to prioritize stream water quality interventions, based on the contamination risk and intervention complexity

Water management decisions are complex ever since they are dependent on adopted politics, social objectives, environmental impacts, and economic determinants. To adequately address hydric resources issues, it is crucial to rely on scientific data and models guiding decision-makers. The present study brings a new methodology, consisting of a combined GIS-MCDA, to prioritize catchments that require environmental interventions to improve surface water quality. A Portuguese catchment, Ave River Basin, was selected to test this methodology due to the low water quality. First, it was calculated the contamination risk of each catchment, based on a GIS-MCDA using point source pressures, landscape metrics, and diffuse emissions as criteria. This analysis was compared to local data of ecological and chemical status through ANOVA and the Tukey test. The results showed the efficiency of the method since the contamination risk was lower for catchments under a good status and higher in catchments with a lower classification. In a second task, it was calculated the intervention complexity using a different GIS-MCDA. For this approach, it was chosen five criteria that condition environmental interventions, population density, slope, percentage of burned areas, Strahler order, and the number of effluent discharge sites. Both multicriteria methods were combined in a graphical analysis to rank the catchments intervention priority, subdividing the prioritization into four categories from 1st to 4th^, giving a higher preference for catchments with high contamination risk and low intervention complexity. As a result, catchments with a good status were dominantly placed under low intervention priority, and catchments with a lower ecological status were classified as a high priority, 1st and 2nd. In total, 248 catchments were spatially ranked, which is an essential finding for decision-makers, that are willing to safeguard the catchment water quality.

Environmental Monitoring of the Littoral Zone of Lake Baikal Using a Network of Automatic Hydro-Meteorological Stations: Development and Trial Run

An automatic hydro-meteorological station (AHMS) was designed to monitor the littoral zone of Lake Baikal in areas with high anthropogenic pressure. The developed AHMS was installed near the Bolshiye Koty settlement (southern basin). This AHMS is the first experience focused on obtaining the necessary competencies for the development of a monitoring network of the Baikal natural territory. To increase the flexibility of adjustment and repeatability, we developed AHMS as a low-cost modular system. AHMS is equipped with a weather station and sensors measuring water temperature, pH, dissolved oxygen, redox potential, conductivity, chlorophyll-a, and turbidity. This article describes the main AHMS functions (hardware and software) and measures taken to ensure data quality control. We present the results of the first two periods of its operation. The data acquired during this periods have demonstrated that, to obtain accurate measurements and to detect and correct errors that were mainly due to biofouling of the sensors and calibration bias, a correlation between AHMS and laboratory studies is necessary for parameters such as pH and chlorophyll-a. The gained experience should become the basis for the further development of the monitoring network of the Baikal natural territory.