Open AccessComparison of characteristic and Gutenberg–Richter models for time‐dependent M ≥ 7.9 earthquake probability in the Nankai‐Tokai subduction zone, Japan
Author(s) -
Parsons Tom,
Console Rodolfo,
Falcone Giuseppe,
Murru Maura,
Yamashina Ken’ichiro
Publication year - 2012
Publication title -
geophysical journal international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.302
H-Index - 168
eISSN - 1365-246X
pISSN - 0956-540X
DOI - 10.1111/j.1365-246x.2012.05595.x
Subject(s) - seismology , geology , subduction , seismic hazard , aftershock , earthquake simulation , remotely triggered earthquakes , foreshock , earthquake prediction , slip (aerodynamics) , seismic gap , earthquake swarm , fault (geology) , induced seismicity , tectonics , physics , thermodynamics
SUMMARY Earthquake forecasts are usually underinformed, and can be plagued by uncertainty in terms of the most appropriate model, and parameter values used in that model. In this paper, we explore the application of two different models to the same seismogenic area. The first is a renewal model based on the characteristic earthquake hypothesis that uses historical/palaeoseismic recurrence times, and fixed rupture geometries. The hazard rate is modified by the Coulomb static stress change caused by nearby earthquakes that occurred since the latest characteristic earthquake. The second model is a very simple earthquake simulator based on plate‐motion, or fault‐slip rates and adoption of a Gutenberg–Richter magnitude–frequency distribution. This information is commonly available even if historical and palaeoseismic recurrence data are lacking. The intention is to develop and assess a simulator that has a very limited parameter set that could be used to calculate earthquake rates in settings that are not as rich with observations of large‐earthquake recurrence behaviour as the Nankai trough. We find that the use of convergence rate as a primary constraint allows the simulator to replicate much of the spatial distribution of observed segmented rupture rates along the Nankai, Tonankai and Tokai subduction zones. Although we note rate differences between the two forecast methods in the Tokai zone, we also see enough similarities between simulations and observations to suggest that very simple earthquake rupture simulations based on empirical data and fundamental earthquake laws could be useful forecast tools in information‐poor settings.