This has implications for estimating regional seismic hazard parameters such as the maximum moment magnitude ( M w max Kijko, 2004) and for characterizing earthquake frequency-magnitude distributions (Parsons et al., 2012). Understanding how fault networks rupture is important because the coseismic amalgamation of multifault ruptures increases the M o of the earthquake relative to the M o sourced from individual fault or fault segment ruptures (Elliott et al., 2012 Fletcher et al., 2016a, 2016b). Many continental earthquakes result from the rupture of multiple faults with different geometries, rupture kinematics, and seismic moments ( M o Beavan et al., 2012 Eberhart-Phillips et al., 2003 Fletcher et al., 2016a, 2016b Hamling et al., 2017). Other fault networks globally may exhibit similar physical and statistical behaviors. Our favored hypothesis is that system rupture behavior is regulated by misoriented faults that occupy critical geometric positions within the network, as previously proposed for the 2010 El Mayor-Cucapah earthquake in Baja California. However, characteristic behavior is more favored probabilistically because ruptures initiating on individual source faults in the system are statistically more likely to cascade into multifault ruptures with larger amalgamated M w ( M w max = 7.1) than to remain confined to the hypocentral source fault ( M w = 6.3 to 6.8). Analysis of earthquake frequency-magnitude distributions indicates that a Gutenberg-Richter frequency-magnitude distribution for the near-source region cannot be rejected in favor of a characteristic earthquake distribution. CSC modeling using the same criteria but initiating the earthquake on other faults in the network results in a multifault rupture cascade for five of seven scenarios. The observed rupture sequence is most successfully modeled if maximum CSC imposed by rupture of the hypocentral fault on to receiver faults exceeds theoretical threshold values of 1 to 5 MPa that are assigned based on fault slip tendency and stress drop analyses.
Geodetic and seismologic data indicate this earthquake initiated on a severely misoriented reverse fault and propagated across a structurally complex fault network including optimally oriented faults. We use Coulomb stress change (CSC) analyses and seismicity data to model the physical and statistical behavior of the multifault source of the 4 September 2010 M w 7.1 Darfield earthquake in New Zealand.
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