Physical and Statistical Behavior of Multifault Earthquakes: Darfield Earthquake Case Study, New Zealand

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 Mw 7.1 Darfield earthquake in New Zealand. 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. 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. 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. 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. 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 Mw (Mwmax = 7.1) than to remain confined to the hypocentral source fault (Mw = 6.3 to 6.8). 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. Other fault networks globally may exhibit similar physical and statistical behaviors. Key Points CSC and Mohr‐Coulomb fault slip tendency analyses are used to investigate multifault earthquakes The fault system responsible for the 2010 Mw7.1 Darfield earthquake is probabilistically favored to rupture in multifault earthquakes Fault network geometries and slip tendencies influence earthquake frequency‐magnitude distributions and maximum magnitude estimations