Abstract
To better characterize seismic hazard, particularly, for induced seismicity, there is an increasing interest in methods to estimate moment magnitude (Mw) for small earthquakes. Mw is generally preferred over other magnitude types, but, it is difficult to estimate Mw for earthquakes with local magnitude (ML) <3–3.5, using conventional moment tensor (MT) inversion. The 2020 Mww 5.7 Magna, Utah, seismic sequence provides an opportunity to illustrate and evaluate the value of spectral methods for this purpose. Starting with a high-quality seismic catalog of 2103 earthquakes (ML<5.6), we estimate Mw using two independent spectral methods—one based on direct waves, yielding Mw,direct, and the other based on coda waves, yielding Mw,coda. For the direct-wave method, we present a non-parametric (NP) inversion scheme that solves for apparent geometrical spreading, G(R), and site effects (S), similar to other NP procedures that have been used to calibrate regional ML scales. The NP inversion is constrained using Mws derived from MTs for nine events in the Magna sequence. We recover statistically robust and physically reasonable G(R) and S and compute Mw,direct for 635 Magna earthquakes down to ML 0.7. For the coda-wave method, we consider two separate calibration schemes involving previous MT solutions and compute Mw,coda for 311 earthquakes down to ML 1.0. For 280 of the events that were processed with both methods—Mw,direct and Mw,coda—are strongly correlated (r = 0.98), with a mean difference of only 0.05. We compare Mw,direct and Mw,coda with ML and find reasonably good agreement for ML<3.6 with the theoretically predicted relationship of Mw=(2/3)ML+C, in which C is a regional constant. Our results imply that seismic network operators can use spectral-based Mw estimates to replace ML estimates for events with ML≥1.0, and possibly smaller. The main requirement is the existence of a small number of MT solutions for calibration purposes.
Determination of mass transfer rates and deposition levels of polycyclic aromatic hydrocarbons (PAHs) using a modified water surface sampler
