4.7 Article

Systematic survey of high-resolution b value imaging along Californian faults: Inference on asperities

Journal

JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH
Volume 119, Issue 3, Pages 2029-2054

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1002/2013JB010867

Keywords

-

Funding

  1. SNF [PMPDP2 134174]

Ask authors/readers for more resources

Understanding and forecasting earthquake occurrences is presumably linked to understanding the stress distribution in the Earth's crust. This cannot be measured instrumentally with useful coverage. However, the size distribution of earthquakes, quantified by the Gutenberg-Richter b value, is possibly a proxy to differential stress conditions and could therewith act as a crude stress-meter wherever seismicity is observed. In this study, we improve the methodology of b value imaging for application to a high-resolution 3-D analysis of a complex fault network. In particular, we develop a distance-dependent sampling algorithm and introduce a linearity measure to restrict our output to those regions where the magnitude distribution strictly follows a power law. We assess the catalog completeness along the fault traces using the Bayesian Magnitude of Completeness method and systematically image b values for 243 major fault segments in California. We identify and report b value structures, revisiting previously published features, e. g., the Parkfield asperity, and documenting additional anomalies, e. g., along the San Andreas and Northridge faults. Combining local b values with local earthquake productivity rates, we derive probability maps for the annual potential of one or more M6 events as indicated by the microseismicity of the last three decades. We present a physical concept of how different stressing conditions along a fault surface may lead to b value variation and explain nonlinear frequency-magnitude distributions. Detailed spatial b value information and its physical interpretation can advance our understanding of earthquake occurrence and ideally lead to improved forecasting ability.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available