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North Fork Clear Creek (NFCC) in Colorado, an acid-mine drainage (AMD) impacted stream, was chosen to examine the distribution of dissolved and particulate Cu, Fe, Mn, and Zn in the water column, with respect to seasonal hydrologic controls. NFCC is a high-gradient stream with discharge directly related to snowmelt and strong seasonal storms. Additionally, conditions in the stream cause rapid precipitation of large amounts of hydrous iron oxides (HFO) that sequester metals. Because AMD-impacted systems are complex, geochemical modeling may assist with predictions and/or confirmations of processes occurring in these environments. This research used Visual-MINTEQ to determine if field data collected over a two and one-half year study would be well represented by modeling with a currently existing model, while limiting the number of processes modeled and without modifications to the existing model's parameters. Observed distributions between dissolved and particulate phases in the water column varied greatly among the metals, with average dissolved fractions being >90% for Mn, approximately 75% for Zn, approximately 30% for Cu, and <10% for Fe. A strong seasonal trend was observed for the metals predominantly in the dissolved phase (Mn and Zn), with increasing concentrations during base-flow conditions and decreasing concentrations during spring-runoff. This trend was less obvious for Cu and Fe. Within hydrologic seasons, storm events significantly influenced in-stream metals concentrations. The most simplified modeling, using solely sorption to HFO, gave predicted percentage particulate Cu results for most samples to within a factor of two of the measured values, but modeling data were biased toward over-prediction. About one-half of the percentage particulate Zn data comparisons fell within a factor of two, with the remaining data being under-predicted. Slightly more complex modeling, which included dissolved organic carbon (DOC) as a solution phase ligand, significantly reduced the positive bias between observed and predicted percentage particulate Cu, while inclusion of hydrous manganese oxide (HMO) yielded model results more representative of the observed percentage particulate Zn. These results indicate that there is validity in the use of an existing model, without alteration and with typically collected water chemistry data, to describe complex natural systems, but that processes considered optimal for one metal might not be applicable for all metals in a given water sample.

Three treatment cells were operated at a site near Durango, CO. One treatment cell operated for more than 3 years. The treatment cells were used for passive removal of contamination from groundwater at a uranium mill tailings repository site. Zero-valent iron [Fe(0)] that had been powdered, bound with aluminosilicate and molded into plates was used as a reactive material in one treatment cell. The others used granular Fe(0) and steel wool. The treatment cells significantly reduced concentrations of As, Mn, Mo, Se, U, V and Zn in groundwater that flowed through it. Zero-valent iron [Fe(0)], magnetite (Fe3O4), calcite (CaCO3), goethite (FeOOH) and mixtures of contaminant-bearing phases were identified in the solid fraction of one treatment cell. A reaction progress approach was used to model chemical evolution of water chemistry as it reacted with the Fe(0). Precipitation of calcite, ferrous hydroxide [Fe(OH)2] and ferrous sulfide (FeS) were used to simulate observed changes in major-ion aqueous chemistry. The amount of reaction progress differed for each treatment cell. Changes in contaminant concentrations were consistent with precipitation of reduced oxides (UO2, V2O3), sulfides (As2S3, ZnS), iron minerals (FeSe2, FeMoO4) and carbonate (MnCO3). Formation of a free gas phase and precipitation of minerals contributed to loss of hydraulic conductivity in one treatment cell.