Two synoptic sampling campaigns were conducted to quantify metal loading to Illinois Gulch, a
small stream affected by historical mining activities. The first campaign was designed to
determine the degree to which Illinois Gulch loses water to the underlying mine workings, and to
determine the effect of these losses on observed metal loads. The second campaign was designed to evaluate metal loading within Iron Springs, a subwatershed that was responsible for the majority of the metal loading observed during the first campaign. A continuous, constant-rate
injection of a conservative tracer was initiated prior to both sampling campaigns and maintained
throughout the duration of each study. Tracer concentrations were subsequently used to determine streamflow in gaining stream reaches using the tracer-dilution method, and as an indicator of hydrologic connections between Illinois Gulch and subsurface mine workings. Streamflow losses to the mine workings were quantified during the first campaign using a series of slug additions in which specific conductivity readings were used as a surrogate for tracer concentration. Data from the continuous injections and slug additions were combined to develop spatial streamflow profiles along each study reach. Streamflow estimates were multiplied by observed metal concentrations to yield spatial profiles of metal load that were in turn used to quantify and rank metal sources. Study results indicate that Illinois Gulch loses water to subsurface mine workings and suggest that remedial measures that reduce flow loss (e.g. channel lining) could lessen metal loading from the Iron Springs area. The primary sources of metals to Illinois Gulch include diffuse springs and groundwater, and a draining mine adit. Diffuse sources were determined to have a much larger effect on water quality than other sources that had been the subject of previous investigations due to their visual appearance, supporting the idea that “the truth is in the stream”. The overall approach of combining spatially intensive sampling with a rigorous hydrological characterization is applicable to non-mining constituents such as nutrients and pesticides.