Screening Techniques for Legacy Mine Land (LML) Sites Using Data Mining and Site-specific Studies in the Western U.S.
The main goal of this project is to provide a science-based approach for screening legacy mine land (LML) sites for remediation and identifying watersheds where relatively low-cost restoration efforts may yield substantial improvements to stream water quality. We are combing analysis of multiple existing regional data coverages with focused field studies to develop a protocol that land managers can use to screen LML sites at multiple scales and efficiently evaluate the potential value of performing limited site remediation.
Science Issue and Relevance
There are tens of thousands of abandoned mines and prospects in the western U.S., many of which have continuing harmful effects on the environment. Currently, prioritization of these LML sites for receiving the limited funds available for remediation is often driven by geopolitical factors, with little or no systematic evaluation of the scientific factors dictating the probability of meeting desired clean-up goals.
Applying an integrated science-based approach in decision-making process about where and how to remediate mine sites may increase chances for remediation success, and help avoid investments in watersheds where such efforts are unlikely to succeed due to high natural background or other factors. The USGS has under-utilized datasets that could be valuable for evaluating LML sites and prioritizing sites for future modest restoration efforts.
Methods to Address Issue
This project includes two tasks representing a two-stage approach for screening LML sites for remediation at different scales.
Task 1: GIS-based screening techniques. The objective of this task is to assemble and interpret databases relevant to past mining and current environmental conditions in a GIS model covering central Colorado. Key databases include: (a) the new USGS USMIN database to identify all mine-related features; (b) USGS NWIS database, USEPA Storet database, and USGS Central Colorado Assessment Project database for stream water chemistry; (c) USGS hydrothermal alteration mapping from hyperspectral ASTER satellite data for the abundance of exposed sulfide minerals. The GIS model will be analyzed to identify "yellow-light" sites where stream metal concentrations only moderately exceed regulatory levels and apparent mining-related sources are few and well defined.
Task 2: Field characterization of candidate sites. The objective of this task is to develop straightforward sampling regimes for application at candidate "yellow-light" sites identified through Task 1 to provide more specific information on stream water chemical conditions and potential metal sources. A reconnaissance level sampling program will be initially applied at a set of candidate sites, followed by a more comprehensive sampling program performed at 1-2 priority sites selected based on the reconnaissance data. Field characterization methods will include stream tracer dilution studies, stream habitat quality evaluation, solids sampling for chemistry, and surface water and groundwater sample for chemistry, multiple isotopic tracers, and age.
Below are other science projects we collaborate with.
USMIN Mineral Deposit Database
Processes Controlling Fate and Transport of Metals Associated with Legacy Mining
Below are data releases associated with this project.
Strontium isotopic data from the Mount Emmons-Redwell area, Crested Butte, Colorado
Whole rock major, minor, and trace element geochemistry of the upper part of the Mount Emmons-Redwell porphyry molybdenum (Climax-type) deposit, Redwell Basin, Crested Butte, Colorado
Stream discharge, sodium, bromide, and specific conductance data for stream and hyporheic zone samples affected by injection of sodium bromide tracer, Leavenworth Creek, Clear Creek County, Colorado, August 2012
Water quality and discharge data from draining mine tunnels near Silverton, Colorado 1993-2015
Digital map of iron sulfate minerals, other mineral groups, and vegetation of the western United States derived from automated analysis of Landsat 8 satellite data
Digital map of iron sulfate minerals, other mineral groups, and vegetation of the San Juan Mountains, Colorado, and Four Corners Region derived from automated analysis of Landsat 8 satellite data
Trace metals in water and biota in and near headwater streams in the Colorado Mineral Belt
Geochemistry and Environmental Tracer Data for Groundwater, Stream Water, and Ferricrete Samples from Handcart Gulch, Colorado
Improved Automated Identification and Mapping of Iron Sulfate Minerals, Other Mineral Groups, and Vegetation using Landsat 8 Operational Land Imager Data, San Juan Mountains, Colorado, and Four Corners Region
Below are publications associated with this project.
Incorporating streambank wells in stream mass loading studies to more effectively identify sources of solutes in stream water
Quantification of metal loading using tracer dilution and instantaneous synoptic sampling and importance of diel cycling in Leavenworth Creek, Clear Creek County, Colorado, 2012
Regional occurrence of aqueous tungsten and relations with antimony, arsenic and molybdenum concentrations (Sardinia, Italy)
Variation in metal concentrations across a large contamination gradient is reflected in stream but not linked riparian food webs
Water-quality change following remediation using structural bulkheads in abandoned draining mines, upper Arkansas River and upper Animas River, Colorado USA
Using stream-side groundwater discharge for geochemical exploration in mountainous terrain
The main goal of this project is to provide a science-based approach for screening legacy mine land (LML) sites for remediation and identifying watersheds where relatively low-cost restoration efforts may yield substantial improvements to stream water quality. We are combing analysis of multiple existing regional data coverages with focused field studies to develop a protocol that land managers can use to screen LML sites at multiple scales and efficiently evaluate the potential value of performing limited site remediation.
Science Issue and Relevance
There are tens of thousands of abandoned mines and prospects in the western U.S., many of which have continuing harmful effects on the environment. Currently, prioritization of these LML sites for receiving the limited funds available for remediation is often driven by geopolitical factors, with little or no systematic evaluation of the scientific factors dictating the probability of meeting desired clean-up goals.
Applying an integrated science-based approach in decision-making process about where and how to remediate mine sites may increase chances for remediation success, and help avoid investments in watersheds where such efforts are unlikely to succeed due to high natural background or other factors. The USGS has under-utilized datasets that could be valuable for evaluating LML sites and prioritizing sites for future modest restoration efforts.
Methods to Address Issue
This project includes two tasks representing a two-stage approach for screening LML sites for remediation at different scales.
Task 1: GIS-based screening techniques. The objective of this task is to assemble and interpret databases relevant to past mining and current environmental conditions in a GIS model covering central Colorado. Key databases include: (a) the new USGS USMIN database to identify all mine-related features; (b) USGS NWIS database, USEPA Storet database, and USGS Central Colorado Assessment Project database for stream water chemistry; (c) USGS hydrothermal alteration mapping from hyperspectral ASTER satellite data for the abundance of exposed sulfide minerals. The GIS model will be analyzed to identify "yellow-light" sites where stream metal concentrations only moderately exceed regulatory levels and apparent mining-related sources are few and well defined.
Task 2: Field characterization of candidate sites. The objective of this task is to develop straightforward sampling regimes for application at candidate "yellow-light" sites identified through Task 1 to provide more specific information on stream water chemical conditions and potential metal sources. A reconnaissance level sampling program will be initially applied at a set of candidate sites, followed by a more comprehensive sampling program performed at 1-2 priority sites selected based on the reconnaissance data. Field characterization methods will include stream tracer dilution studies, stream habitat quality evaluation, solids sampling for chemistry, and surface water and groundwater sample for chemistry, multiple isotopic tracers, and age.
Below are other science projects we collaborate with.
USMIN Mineral Deposit Database
Processes Controlling Fate and Transport of Metals Associated with Legacy Mining
Below are data releases associated with this project.
Strontium isotopic data from the Mount Emmons-Redwell area, Crested Butte, Colorado
Whole rock major, minor, and trace element geochemistry of the upper part of the Mount Emmons-Redwell porphyry molybdenum (Climax-type) deposit, Redwell Basin, Crested Butte, Colorado
Stream discharge, sodium, bromide, and specific conductance data for stream and hyporheic zone samples affected by injection of sodium bromide tracer, Leavenworth Creek, Clear Creek County, Colorado, August 2012
Water quality and discharge data from draining mine tunnels near Silverton, Colorado 1993-2015
Digital map of iron sulfate minerals, other mineral groups, and vegetation of the western United States derived from automated analysis of Landsat 8 satellite data
Digital map of iron sulfate minerals, other mineral groups, and vegetation of the San Juan Mountains, Colorado, and Four Corners Region derived from automated analysis of Landsat 8 satellite data
Trace metals in water and biota in and near headwater streams in the Colorado Mineral Belt
Geochemistry and Environmental Tracer Data for Groundwater, Stream Water, and Ferricrete Samples from Handcart Gulch, Colorado
Improved Automated Identification and Mapping of Iron Sulfate Minerals, Other Mineral Groups, and Vegetation using Landsat 8 Operational Land Imager Data, San Juan Mountains, Colorado, and Four Corners Region
Below are publications associated with this project.