HR: 13:55h
AN: S13E-02    [Abstracts]
TI: The Influence of Declustering on Seismicity Rate Change Estimations
AU: * van Stiphout, T
EM: vanstiphout@sed.ethz.ch
AF: ETH Zurich, Schafmattstrasse 30, Zurich, ZH 8093, Switzerland
AU: Schorlemmer, D
EM: danijel@usc.edu
AF: University of Southern California Department of Earth Sciences, 3651 Trousdale Parkway, MC-0740, Los Angeles, CA 90089-0740, United States
AU: Wiemer, S
EM: wiemer@sed.ethz.ch
AF: ETH Zurich, Schafmattstrasse 30, Zurich, ZH 8093, Switzerland
AB: Analyzing seismicity rate changes (SRC) is widely used in statistical seismology because transients in activity can be related to changes in physical properties in the Earth's crust (e.g., changes in static/dynamic stress, fluid migration, precursory signal). However, how to best estimate the significance of SRC in the presence of earthquake clustering remains a challenge. Declustering is commonly applied to separate dependent events (fore- and aftershocks, swarms) from independent events (background) that may contain imprints of changes in physical processes. Because declustering is a non-unique process, it potentially has a large impact on the estimated SRC and, consequently, the interpretation of an observed transient. We present a new approach for estimating the significance of SRC based on extensive Monte Carlo simulations over the entire parameter space of common declustering algorithms. We also include uncertainties of the hypocenter parameters, variations in sampling volumes, duration of rate changes, and bin sizes. To be able to compare the significance of the SRC values across different parameter spaces and different SRC estimators (e.g., z- and β-values) , we translate the values of different estimators into parameter-independent probabilities. We have performed a sensitivity analysis to quantify the impact of declustering algorithms and parameters settings on seismicity analysis. As an example application, we investigate the influence on estimating the significance of precursory seismic quiescence (PSQ). The PSQ hypothesis states that some main shocks are preceded by a significant decrease in the seismicity rate of micro-earthquakes, in the years to months prior, and including parts or all of the subsequent ruptured volume. Detecting PSQ requires careful measurements of background SRC. For the sensitivity analysis, we use a variety of data sets. Preliminary results on simple stochastic simulated catalogs indicate that declustering may have a significant influence on SRC. We will present results using successively increased complexity in the simulated catalogs by combining Poissonian background activity with a PSQ, and/or by including Epidemic Type Aftershock Sequences. Finally, we investigate these effects on real catalog data, using the ANSS catalog for southern California.
DE: 7200 SEISMOLOGY
DE: 7223 Earthquake interaction, forecasting, and prediction (1217, 1242)
DE: 7290 Computational seismology
SC: Seismology [S]
MN: 2007 Fall Meeting