The stress shadow problem in physics-based aftershock forecasting: Does incorporation of secondary stress changes help? (original) (raw)
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We calculate stress changes resulting from the M = 6.0 West Napa earthquake on north San Francisco Bay area faults. The earthquake ruptured within a series of long faults that pose significant hazard to the Bay area, and we are thus concerned with potential increases in the probability of a large earthquake through stress transfer. We conduct this exercise as a prospective test because the skill of stress-based aftershock forecasting methodology is inconclusive. We apply three methods: (1) generalized mapping of regional Coulomb stress change, (2) stress changes resolved on Uniform California Earthquake Rupture Forecast faults, and (3) a mapped rate/state aftershock forecast. All calculations were completed within 24 h after the main shock and were made without benefit of known aftershocks, which will be used to evaluative the prospective forecast. All methods suggest that we should expect heightened seismicity on parts of the southern Rodgers Creek, northern Hayward, and Green Valley faults.
Evaluation of static stress change forecasting with prospective and blind tests
Geophysical Journal International, 2012
Controversy and uncertainty about the physics of earthquake triggering mean that stress interactions are rarely incorporated into formal probabilistic forecasts. Statistical methods capture and predict complex features in short-term aftershock forecasts, but we ultimately want to understand the physics behind earthquake triggering. In this paper, we show two fully prospective static stress forecasts that have failed to reproduce spatial patterns of microseismicity. We demonstrate that these failures are not the result of complex main shock ruptures, but are instead caused in part by secondary triggering as deduced from an epidemic type aftershock sequence (ETAS) based stochastic declustering calculation. Prospective testing highlights difficulties in validating physics-based forecasts using microseismicity that can evolve rapidly in time and space. We therefore turn to a global catalogue of larger potentially triggered earthquakes. Prior study with this database found that M ≥ 5 earthquakes after main shocks had a ratio of stress-increased to total number of events of 61 per cent, a barely significant result relative to the null value of 50 ± 4.6 per cent. The initial study included every catalogue event; our conclusions from the prospective tests cause us to revisit this choice and to conduct a systematic study of test-event selection. Free parameters include main shock and aftershock magnitude thresholds, as well as calculated probability that aftershocks are background events. We find a mean ratio of stress-increased to total number of events of ∼70 per cent across the test parameter range, with high values greater than 80 per cent. The most important parameter is triggered-event magnitude. We therefore conclude that the static stress change hypothesis is significantly more consistent with observation of large earthquake clustering than random chance.
Testing the stress shadow hypothesis
Journal of Geophysical Research, 2005
1] A fundamental question in earthquake physics is whether aftershocks are predominantly triggered by static stress changes (permanent stress changes associated with fault displacement) or dynamic stresses (temporary stress changes associated with earthquake shaking). Both classes of models provide plausible explanations for earthquake triggering of aftershocks, but only the static stress model predicts stress shadows, or regions in which activity is decreased by a nearby earthquake. To test for whether a main shock has produced a stress shadow, we calculate time ratios, defined as the ratio of the time between the main shock and the first earthquake to follow it and the time between the last earthquake to precede the main shock and the first earthquake to follow it. A single value of the time ratio is calculated for each 10 Â 10 km bin within 1.5 fault lengths of the main shock epicenter. Large values of the time ratio indicate a long wait for the first earthquake to follow the main shock and thus a potential stress shadow, whereas small values indicate the presence of aftershocks. Simulations indicate that the time ratio test should have sufficient sensitivity to detect stress shadows if they are produced in accordance with the rate and state friction model. We evaluate the 1989 M W 7.0 Loma Prieta, 1992 M W 7.3 Landers, 1994 M W 6.7 Northridge, and 1999 M W 7.1 Hector Mine main shocks. For each main shock, there is a pronounced concentration of small time ratios, indicating the presence of aftershocks, but the number of large time ratios is less than at other times in the catalog. This suggests that stress shadows are not present. By comparing our results to simulations we estimate that we can be at least 98% confident that the Loma Prieta and Landers main shocks did not produce stress shadows and 91% and 84% confident that stress shadows were not generated by the Hector Mine and Northridge main shocks, respectively. We also investigate the long hypothesized existence of a stress shadow following the 1906 San Francisco Bay area earthquake. We find that while Bay Area catalog seismicity rates are lower in the first half of the twentieth century than in the last half of the nineteenth, this seismicity contrast is also true outside of the Bay Area, in regions not expected to contain a stress shadow. This suggests that the rate change is due to a more system wide effect, such as errors in the historical catalog or the decay of aftershocks of the larger 1857 Fort Tejon earthquake.
An improved version of the Load/Unload Response Ratio method for forecasting strong aftershocks
Tectonophysics, 2011
a b s t r a c t Epidemic-type aftershock sequence (ETAS) model Aftershock forecast Wenchuan earthquake Temporal clustering and spatial concentration of aftershock sequences can be observed after the occurrence of most major earthquakes. Earthquake clustering effects, such as the rapid decay of aftershocks and secondstage aftershocks, cause large fluctuations in the Load/Unload Response Ratio (LURR). In order to eliminate the influence of such clustering, we introduce a new formula for calculating the LURR, taking the epidemictype aftershock sequence (ETAS) model as the baseline seismicity model. We have applied the new formula retrospectively to the Wenchuan earthquake sequence in 2008 in China. The results show that the LURR increases slowly to a peak and then decreases sharply before strong aftershocks and that the new LURR performs better than the original LURR.