Most of the commonly used seismic discrimination approaches are designed for teleseismic and regional data. To monitor for the smallest events, some of these discriminants have been adapted for local distances (), with mixed level of success. We take advantage of the variety of seismic sources, including nontraditionally studied anthropogenic sources and the existence of a dense regional seismic network in the Utah region to evaluate amplitude ratio seismic discrimination at local distances. First, we explored phase‐amplitude Pg‐to‐Sg ratios for multiple frequency bands to classify events in a dataset that comprises populations of single‐shot surface explosions, shallow and deep ripple‐fired mining blasts, mining‐induced events (MIEs), and tectonic earthquakes. We achieved a success rate of about 59%–83%. Then, for the same dataset, we combined the Pg‐to‐Sg phase‐amplitude ratios with Sg‐to‐Rg spectral amplitude ratios in a multivariate quadratic discriminant function (QDF) approach. For two‐category pairwise classification, seven of ten population pairs show misclassification rates of about 20% or less, with five pairs showing rates of about 10% or less. The approach performs best for the pair involving the populations of single‐shot explosions and MIEs. By combining both Pg‐to‐Sg and Rg‐to‐Sg ratios in the multivariate QDFs, we are able to achieve an average improvement of about 4%–14% in misclassification rates compared with Pg‐to‐Sg ratios alone. When all five event populations are considered simultaneously, as expected, the potential for misclassification increases, and our QDF approach using both Pg‐to‐Sg and Rg‐to‐Sg ratios achieves an average success rate of about 74% compared with the rate of about 86% for two‐category pairwise classification.