Metals fate and transport modelling in streams and watersheds: state of the science and USEPA workshop review

Caruso, Brian S.; Cox, Trevor J.; Runkel, Robert L.; Velleux, Mark; Bencala, Kenneth E.; Nordstrom, D. Kirk; Juliën, Pierre Y.; Butler, Barbara A.; Alpers, Charles N.; Marion, Andrea; Smith, Kathleen S.

doi:10.1002/hyp.7114

Cited by 51 publications

(26 citation statements)

References 56 publications

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“…Extracting and processing of minerals from hard rock mines at an industrial scale can result in tremendous loading of trace elements into streams and rivers. Numerous studies have been conducted to characterize the geochemical speciation and reactive transport of trace element contaminants in mining-impacted streams (Cánovas et al 2012;Caruso et al 2008;Kimball and Runkel 2009). The spatial and temporal distribution of trace elements in surface water can be affected by various hydrological, geochemical, and microbiological processes.…”

Section: Introductionmentioning

confidence: 99%

Spatial Distribution of As, Cr, Pb, Cd, Cu, and Zn in the Water and Sediment of a River Impacted by Gold Mining

Zhang

Zhou

2013

Mine Water Environ

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Historical and active mining has adversely affected the geochemistry of the Jiehe River in the Jiaodong Peninsula, which has the largest gold ore reserves in China. Water and sediment samples were collected along the 37.8 km long river during the critical low flow season. Samples were analyzed for their geochemical properties, total concentrations of As, Cr, Pb, Cd, Cu, and Zn in the sediment, and dissolved/particulate concentrations of trace elements in filtered/unfiltered water samples. Our results demonstrate that substantial amount of these elements have been released into the Jiehe River during the processes of extracting, selecting, processing, and smelting at the many historical and active gold mining sites in the watershed. High concentrations of potentially toxic elements (1.9-1,004 lg L -1 As, 4.2-210 lg L -1 Cr, 7.9-9,529 lg L -1 Pb, 2.0-855 lg L -1 Cd, 47.4-8,494 lg L -1 Cu, and 105-11,336 lg L -1 Zn) have seriously affected water quality in the region. In addition, these contaminants have accumulated in the bed sediment (7.7-181 mg kg -1 As, 24.1-726 mg kg -1 Cr, 9.9-1,100 mg kg -1 Pb, 0.1-51.8 mg kg -1 Cd, 22.1-1,524 mg kg -1 Cu, and 53.5-5,484 mg kg -1 Zn). Spatial distribution of these contaminants in water and sediment is controlled by the discharge from point and non-point sources as well as the reactive transport processes. Spatial analysis conducted on the sediment and stream concentration of As, Pb, Cd, and Zn suggests that two mining-related sources, at 4.3 and 17.6 km downstream of the headwaters, contributed most of the As, Pb, Cd, and Zn load as particulates. In contrast, high levels of Cr and Cu in the sediment are not related to the current loading pattern and may be due to historical sources. As the first comprehensive study on the pollution caused by intensive gold mining in this area, this research has provided much needed information to establish effective management and remediation strategies.

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Section: Introductionmentioning

confidence: 99%

Spatial Distribution of As, Cr, Pb, Cd, Cu, and Zn in the Water and Sediment of a River Impacted by Gold Mining

Zhang

Zhou

2013

Mine Water Environ

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“…Although these models have been shown to provide excellent representation of metal speciation in laboratory environments (e.g. Almås et al 2007;Caruso et al 2008), the step from model applicability in small-scale controlled laboratory environments to real field conditions can be challenging. For instance, the equilibrium conditions that can be obtained in the laboratory and that are assumed by many speciation models may not exist in hydrological systems with flowing water.…”

Section: Materials Mobilization Via Bank and Bed Erosion Undermentioning

confidence: 99%

“…4a) than those in 2013, when DOC data are available. The absence of this parameter in most field sampling datasets (Caruso et al 2008) may greatly increase the prediction uncertainties associated with the transport and fate of metals. Several studies (Schelker et al 2012;Raymond and Saiers 2010) have shown that DOC concentrations can fluctuate up to several hundreds of per cent due to land use changes (e.g.…”

Section: Metals Governed By Equilibrium Processesmentioning

confidence: 99%

Speciation and hydrological transport of metals in non-acidic river systems of the Lake Baikal basin: Field data and model predictions

et al. 2016

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The speciation of metals in aqueous systems is central to understanding their mobility, bioavailability, toxicity and fate. Although several geochemical speciation models exist for metals, the equilibrium conditions assumed by many of them may not prevail in field-scale hydrological systems with flowing water. Furthermore, the dominant processes and/or process rates in non-acidic systems might differ from well-studied acidic systems. We here aim to increase knowledge on geochemical processes controlling speciation and transport of metals under nonacidic river conditions. Specifically, we evaluate the predictive capacity of a speciation model to novel measurements of multiple metals and their partitioning, under highpH conditions in mining zones within the Lake Baikal basin. The mining zones are potential hotspots for increasing metal loads to downstream river systems. Metals released from such upstream regions may be transported all the way to Lake Baikal, where increasing metal contamination of sediments and biota has been reported. Our results show clear agreement between speciation predictions and field measurements of Fe, V, Pb and Zn, suggesting that the partitioning of these metals mainly was governed by equilibrium geochemistry under the studied conditions. Systematic over-predictions of dissolved Cr, Cu and Mo by the model were observed, which might be corrected by improving the adsorption database for hydroxyapatite because that mineral likely controls the solubility of these metals. Additionally, metal complexation by dissolved organic matter is a key parameter that needs continued monitoring in the Lake Baikal basin because dependable predictions could not be made without considering its variability. Finally, our investigation indicates that further model development is needed for accurate As speciation predictions under non-acidic conditions, which is crucial for improved health risk assessments on this contaminant.

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“…These techniques range from relatively simple mass balance approaches (Foos, 1997;Yu, 1998) to detailed models of reactive transport Caruso et al, 2008). Included within this range is the synoptic mass balance approach of Kimball et al (2002Kimball et al ( , 2007, in which detailed spatial profiles of constituent load are developed.…”

Section: Introductionmentioning

confidence: 99%

A comparison of pre‐ and post‐remediation water quality, Mineral Creek, Colorado

Runkel

Bencala

Kimball

et al. 2009

Hydrological Processes

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Abstract:Pre-and post-remediation data sets are used herein to assess the effectiveness of remedial measures implemented in the headwaters of the Mineral Creek watershed, where contamination from hard rock mining has led to elevated metal concentrations and acidic pH. Collection of pre-and post-remediation data sets generally followed the synoptic mass balance approach, in which numerous stream and inflow locations are sampled for the constituents of interest and estimates of streamflow are determined by tracer dilution. The comparison of pre-and post-remediation data sets is confounded by hydrologic effects and the effects of temporal variation. Hydrologic effects arise due to the relatively wet conditions that preceded the collection of pre-remediation data, and the relatively dry conditions associated with the post-remediation data set. This difference leads to a dilution effect in the upper part of the study reach, where pre-remediation concentrations were diluted by rainfall, and a source area effect in the lower part of the study reach, where a smaller portion of the watershed may have been contributing constituent mass during the drier post-remediation period. A second confounding factor, temporal variability, violates the steady-state assumption that underlies the synoptic mass balance approach, leading to false identification of constituent sources and sinks. Despite these complications, remedial actions completed in the Mineral Creek headwaters appear to have led to improvements in stream water quality, as post-remediation profiles of instream load are consistently lower than the pre-remediation profiles over the entire study reach for six of the eight constituents considered (aluminium, arsenic, cadmium, copper, iron, and zinc). Concentrations of aluminium, cadmium, copper, lead, and zinc remain above chronic aquatic-life standards, however, and additional remedial actions may be needed. Future implementations of the synoptic mass balance approach should be preceded by an assessment of temporal variability, and modifications to the synoptic sampling protocol should be made if necessary. Published in

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Metals fate and transport modelling in streams and watersheds: state of the science and USEPA workshop review

Cited by 51 publications

References 56 publications

Spatial Distribution of As, Cr, Pb, Cd, Cu, and Zn in the Water and Sediment of a River Impacted by Gold Mining

Spatial Distribution of As, Cr, Pb, Cd, Cu, and Zn in the Water and Sediment of a River Impacted by Gold Mining

Speciation and hydrological transport of metals in non-acidic river systems of the Lake Baikal basin: Field data and model predictions

A comparison of pre‐ and post‐remediation water quality, Mineral Creek, Colorado

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