Modeling Seismic Network Detection Thresholds using Production Picking Algorithms

The ability to estimate a network's detection threshold (the minimum magnitude earthquake that can be reliably detected) is a critical part of network design and can drive network maintenance efforts. A station's ability to detect an earthquake has typically been determined by modeling the predicted spectral amplitude for an earthquake (including computing attenuation for a range of epicentral distances) and comparing that amplitude to the average station background noise level. This approach has significant uncertainty because of unknown regional attenuation and complications in computing small event power spectra. We develop an approach to determine network detection thresholds using a multi-band picking algorithm that is currently in use at the USGS National Earthquake Information Center. Using these automatic picks, we use cataloged earthquakes to determine an empirical relationship of the observability of earthquakes as a function of magnitude and distance. Using this relationship, we produce maps of detection threshold as a function of station spacing, station spatial configuration, and station noise levels.