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Estimating the Uncertainty of Contaminant Loads in Mined Watersheds

Pennsylvania Mine in the headwaters of Peru Creek, Colorado
Upper workings of the Pennsylvania Mine in the headwaters of Peru Creek, Colorado. Photograph by Robert L. Runkel, USGS.

USGS scientists have developed an improved approach for identifying the major sources of contaminants to streams in watersheds impacted by acid mine drainage. This new approach includes determining the uncertainty in estimated contaminant loads associated with

  1. natural variation in concentration of contaminants caused by daily cycles,
  2. variability in laboratory analyses of constituent and tracer concentrations, and
  3. variations introduced by field sampling. The uncertainty analysis is made possible by collection of replicate water-quality samples at key points along the impacted stream through a daily cycle.

This approach allows those tasked with cleaning up mining contamination to evaluate the implications of scientific uncertainty in decisionmaking.

Working in Peru Creek, Colorado, the scientists applied this replicate sampling approach to identify the major contaminant sources within the watershed. Peru Creek receives acidic, metal-rich drainage from the Pennsylvania Mine and other sources. Their analysis showed that under low-flow conditions, contaminant loading is dominated by drainage from the Pennsylvania Mine, with less loading coming from an adjacent wetland and a tributary to the creek. Given this assessment, remedial actions to decrease metal loading from the abandoned adit draining the Pennsylvania Mine are currently being considered by the State of Colorado and the U.S. Environmental Protection Agency.

Many watersheds in the western United States are adversely affected by past and present hardrock mining activities that release metals and acidity into the environment. This new approach will help water-resource managers, regulators, and cleanup professionals quantify and rank the various sources of contamination in a watershed within the context of variability and uncertainty caused by daily cycling, source variability, and sampling and analysis error—thereby enabling them to target remedial activities, with greater certainty, toward the most harmful sources.

The Toxic Substances Hydrology Program, the Colorado Department of Public Health and Environment, and the U.S. Environmental Protection Agency provided the funding for this study.


Runkel, R.L., Walton-Day, K., Kimball, B.A., Verplanck, P.L., and Nimick, D.A., 2013, Estimating instream constituent loads using replicate synoptic sampling, Peru Creek, Colorado: Journal of Hydrology, v. 489, p. 26-41, doi:10.1016/j.jhydrol.2013.02.031

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