High-resolution image of Calaveras Fault seismicity

By measuring relative earthquake arrival times using waveform cross correlation and locating earthquakes using the double difference technique, we are able to reduce hypocentral errors by 1 to 2 orders of magnitude over routine locations for nearly 8000 events along a 35-km section of the Calaveras Fault. This represents ∼92% of all seismicity since 1984 and includes the rupture zone of the M 6.2 1984 Morgan Hill, California, earthquake. The relocated seismicity forms highly organized structures that were previously obscured by location errors. There are abundant repeating earthquake sequences as well as linear clusters of earthquakes. Large voids in seismicity appear with dimensions of kilometers that have been aseismic over the 30-year time interval, suggesting that these portions of the fault are either locked or creeping. The area of greatest slip in the Morgan Hill main shock coincides with the most prominent of these voids, suggesting that this part of the fault may be locked between large earthquakes. We find that the Calaveras Fault at depth is extremely thin, with an average upper bound on fault zone width of 75 m. Given the location error, however, this width is not resolvably different from zero. The relocations reveal active secondary faults, which we use to solve for the stress field in the immediate vicinity of the Calaveras Fault. We find that the maximum compressive stress is at a high angle, only 13° from the fault normal, supporting previous interpretations that this fault is weak

Seismically induced landslide hazard and exposure modelling in Southern California based on the 1994 Northridge, California earthquake event

Quantitative modelling of landslide hazard, as opposed to landslide susceptibility, as a function of the earthquake trigger is vital in understanding and assessing future potential exposure to landsliding. Logistic regression analysis is a method commonly used to assess susceptibility to landsliding; however, estimating probability of landslide hazard as a result of an earthquake trigger is rarely undertaken. This paper utilises a very detailed landslide inventory map and a comprehensive dataset on peak ground acceleration for the 1994 Mw6.7 Northridge earthquake event to fit a landslide hazard logistic regression model. The model demonstrates a high success rate for estimating probability of landslides as a result of earthquake shaking. Seven earthquake magnitude scenarios were simulated using the Open Source Seismic Hazard Analysis (OpenSHA) application to simulate peak ground acceleration, a covariate of landsliding, for each event. The exposure of assets such as population, housing and roads to high levels of shaking and high probabilities of landsliding was estimated for each scenario. There has been urban development in the Northridge region since 1994, leading to an increase in prospective exposure of assets to the earthquake and landslide hazards in the event of a potential future earthquake. As the earthquake scenario magnitude increases, the impact from earthquake shaking initially increases then quickly levels out, but potential losses from landslides increase at a rapid rate. The modelling approach, as well as the specific model, developed in this paper can be used to estimate landslide probabilities as a result of an earthquake event for any scenario where the peak ground acceleration variable is available