SEISMIC SOURCE SCALING AND DISCRIMINATION IN DIVERSE TECTONIC ENVIRONMENTS

The objectives of this study are to improve low-magnitude regional seismic discrimination by performing a thorough investigation of earthquake source scaling using diverse, high-quality datasets from varied tectonic regions. Local-to-regional high-frequency discrimination requires an estimate of how earthquakes scale with size. Walter and Taylor (2002) developed the MDAC (Magnitude and Distance Amplitude Corrections) method to empirically account for these effects through regional calibration. The accuracy of these corrections has a direct impact on our ability to identify clandestine explosions in the broad regional areas characterized by low seismicity. Unfortunately our knowledge of source scaling at small magnitudes (i.e., m{sub b} < {approx}4.0) is poorly resolved. It is not clear whether different studies obtain contradictory results because they analyze different earthquakes, or because they use different methods. Even in regions that are well studied, such as test sites or areas of high seismicity, we still rely on empirical scaling relations derived from studies taken from half-way around the world at inter-plate regions. We investigate earthquake sources and scaling from different tectonic settings, comparing direct and coda wave analysis methods. We begin by developing and improving the two different methods, and then in future years we will apply them both to each more » set of earthquakes. Analysis of locally recorded, direct waves from events is intuitively the simplest way of obtaining accurate source parameters, as these waves have been least affected by travel through the earth. But there are only a limited number of earthquakes that are recorded locally, by sufficient stations to give good azimuthal coverage, and have very closely located smaller earthquakes that can be used as an empirical Green's function (EGF) to remove path effects. In contrast, coda waves average radiation from all directions so single-station records should be adequate, and previous work suggests that the requirements for the EGF event are much less stringent. We can study more earthquakes using the coda-wave methods, while using direct wave methods for the best recorded subset of events so as to investigate any differences between the results of the two approaches. Finding 'perfect' EGF events for direct wave analysis is difficult, as is ascertaining the quality of a particular EGF event. We develop a multi-taper method to obtain time-domain source-time-functions by frequency division. If an earthquake and EGF event pair are able to produce a clear, time-domain source pulse then we accept the EGF event. We then model the spectral (amplitude) ratio to determine source parameters from both direct P and S waves. We use the well-recorded sequence of aftershocks of the M5 Au Sable Forks, NY, earthquake to test the method and also to obtain some of the first accurate source parameters for small earthquakes in eastern North America. We find that the stress drops are high, confirming previous work suggesting that intraplate continental earthquakes have higher stress drops than events at plate boundaries. We simplify and improve the coda wave analysis method by calculating spectral ratios between different sized earthquakes. We first compare spectral ratio performance between local and near-regional S and coda waves in the San Francisco Bay region for moderate-sized events. The average spectral ratio standard deviations using coda are {approx}0.05 to 0.12, roughly a factor of 3 smaller than direct S-waves for 0.2 < f < 15.0 Hz. Also, direct wave analysis requires collocated pairs of earthquakes whereas the event-pairs (Green's function and target events) can be separated by {approx}25 km for coda amplitudes without any appreciable degradation. We then apply coda spectral ratio method to the 1999 Hector Mine mainshock (M{sub w} 7.0, Mojave Desert) and its larger aftershocks. We observe a clear departure from self-similarity, consistent with previous studies using similar regional datasets. « less