PREDICTING RISKS TO AQUATIC LIFE BASED on LITHOLOGIC SPECIFIC GEOCHEMICAL BASELINES

Regional hydrothermal alteration and mineralization in mining districts can make it difficult to select appropriate restoration endpoints. We developed lithology based geochemical baselines for Colorado using stream water and sediment chemistry data from unmined mineralized catchments as analogs for pre-mining baselines in comparison to catchments which were mined. Mineral deposit, alteration, and geologic maps, and mining databases were used to classify catchment lithology. Of the eight classes of mineral deposits observed, we focused on polymetallic veins (PMV) and porphyry-Cu and Cu-Mo deposits. Unmined and unmineralized sites were used for lithologic reference (n = 62). Unmined PMV (n = 25) and porphyry deposits (n = 15) comprised background values. Mined PMV deposits were classified based on style of mineralization, propylitic-altererd PMV (n = 27) and quartz-sericite-pyrite (QSP)-altered PMV (n = 14). A mined porphyry class was not developed. Regression on Ordered Statistics was used to estimate baselines because of the database size and frequency of non-detections of trace elements. Baselines were used to calculate the probability that each lithology exceeded aquatic life standards (Cd, Cu, Zn, Pb, Ni) in water (US EPA Criterion Continuous Concentration) and sediment (Consensus-Based Sediment Quality Guidelines, Macdonald et al. 2000) and crustal abundance averages for sediment (Clark Index-I). There was a > 50% probability that Pb and Zn exceeded average crustal abundance in all classes including background and reference. The probability of exceeding aquatic life standards for Cd, Cu, Zn, Pb, and Ni in surface water was near 0 in reference and PMV background catchments and > 50% likelihood of exceeding in porphyry and both mined classes. Porphyry background and mined catchments were observed to have >50% likelihood of exceeding sediment quality guidelines for Cd, Cu, Pb, and Zn, while Ni only exceeded this threshold in mined lithologies. The style of mineralization and type of deposit significantly affect the likelihood that streams exceeded aquatic life standards. However, locally set baselines appear more protective of aquatic ecosystems as compared to aquatic life standards. These data could be used to predict effects to aquatic ecosystems in regions with similar geologic characteristics.