Abstract
Early predictive modeling of seepage water quality from mine rock stockpiles is critical for effective
operational materials management, water management, and closure planning. Sulfide oxidation and metal
leaching rates from laboratory-scale kinetic tests are often used to estimate long-term seepage water
quality from mine rock stockpiles under field conditions. However, the use of laboratory-scale kinetic test
data typically requires application of scaling factors to account for potential important differences between
laboratory and field conditions, such as temperature, precipitation, grain size, etc. Previous studies have
demonstrated that scaling factors can vary by several orders of magnitude, depending on site conditions
and material characteristics—leading to large uncertainties in water quality predictions. The goal of this
study was to generate a dataset of empirically derived scaling factors that can be used to improve the early
prediction of seepage water quality from stockpiles. In this study, scaling factors were calculated for 21
stockpiles at 15 mine sites using sulfate release rates from laboratory kinetic tests and full-scale rock piles
or large-scale field test piles. Ratios of lab-to-field release rates ranged from 1.9 to 176, with higher
factors at cold and/or dry sites. Despite the inherent variability of the sites evaluated, scaling factors could
be reasonably well predicted using the Arrhenius equation, with improved predictions when using in situ
pile temperatures rather than ambient air temperatures. The dataset developed in this study may also
provide insight into analog sites to bound model predictions for mine sites with comparable climatic and
hydrogeochemical conditions.