Rupture Passing Probabilities at Fault Bends and Steps, with Application to Rupture Length Probabilities for Earthquake Early Warning (original) (raw)
Related papers
Geophysical Journal International, 2010
Earthquake Early Warning (EEW) predicts future ground shaking based on presently available data. Long ruptures present the best opportunities for EEW since many heavily shaken areas are distant from the earthquake epicentre and may receive long warning times. Predicting the shaking from large earthquakes, however, requires some estimate of the likelihood of the future evolution of an ongoing rupture. An EEW system that anticipates future rupture using the present magnitude (or rupture length) together with the Gutenberg-Richter frequencysize statistics will likely never predict a large earthquake, because of the rare occurrence of 'extreme events'. However, it seems reasonable to assume that large slip amplitudes increase the probability for evolving into a large earthquake. To investigate the relationship between the slip and the eventual size of an ongoing rupture, we simulate suites of 1-D rupture series from stochastic models of spatially heterogeneous slip. We find that while large slip amplitudes increase the probability for the continuation of a rupture and the possible evolution into a 'Big One', the recognition that rupture is occurring on a spatially smooth fault has an even stronger effect. We conclude that an EEW system for large earthquakes needs some mechanism for the rapid recognition of the causative fault (e.g., from real-time GPS measurements) and consideration of its 'smoothness'. An EEW system for large earthquakes on smooth faults, such as the San Andreas Fault, could be implemented in two ways: the system could issue a warning, whenever slip on the fault exceeds a few metres, because the probability for a large earthquake is high and strong shaking is expected to occur in large areas around the fault. A more sophisticated EEW system could use the present slip on the fault to estimate the future slip evolution and final rupture dimensions, and (using this information) could provide probabilistic predictions of seismic ground motions along the evolving rupture. The decision on whether an EEW system should be realized in the first or in the second way (or in a combination of both) is user-specific.
Predicting rupture arrests, rupture jumps and cascading earthquakes
The devastation inflicted by recent earthquakes demonstrates the danger of under-predicting the size of earthquakes. Unfortunately, earthquakes may rupture fault-sections larger than previously observed, making it essential to develop predictive rupture models. We present numerical models based on earthquake physics and fault zone data, that determine whether a rupture on a segmented fault could cascade and grow into a devastating, multisegment earthquake. We demonstrate that weakened (damaged) fault zones and bi-material interfaces promote rupture propagation and greatly increase the risk of cascading ruptures and triggered seismicity. This result provides a feasible explanation for the outstanding observation of a very large (10 km) rupture jump documented in the MW7.8 2001 Kunlun, China earthquake. However, enhanced inter-seismic deformation and energy dissipation at fault tips suppress rupture propagation and may turn even small discontinuities into effective earthquake barriers. By assessing fault stability, identifying rupture barriers and foreseeing multisegment earthquakes, we provide a tool to improve earthquake prediction and hazard analysis.
Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3)--The Time-Independent Model
Bulletin of the Seismological Society of America, 2014
The 2014 Working Group on California Earthquake Probabilities (WGCEP14) present the time-independent component of the Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3), which provides authoritative estimates of the magnitude, location, and time-averaged frequency of potentially damaging earthquakes in California. The primary achievements have been to relax fault segmentation and include multifault ruptures, both limitations of UCERF2. The rates of all earthquakes are solved for simultaneously and from a broader range of data, using a system-level inversion that is both conceptually simple and extensible. The inverse problem is large and underdetermined, so a range of models is sampled using an efficient simulated annealing algorithm. The approach is more derivative than prescriptive (e.g., magnitude-frequency distributions are no longer assumed), so new analysis tools were developed for exploring solutions. Epistemic uncertainties were also accounted for using 1440 alternative logic-tree branches, necessitating access to supercomputers. The most influential uncertainties include alternative deformation models (fault slip rates), a new smoothed seismicity algorithm, alternative values for the total rate of M w ≥ 5 events, and different scaling relationships, virtually all of which are new. As a notable first, three deformation models are based on kinematically consistent inversions of geodetic and geologic data, also providing slip-rate constraints on faults previously excluded due to lack of geologic data. The grand inversion constitutes a system-level framework for testing hypotheses and balancing the influence of different experts. For example, we demonstrate serious challenges with the Gutenberg-Richter hypothesis for individual faults. UCERF3 is still an approximation of the system, however, and the range of models is limited (e.g., constrained to stay close to UCERF2). Nevertheless, UCERF3 removes the apparent UCERF2 overprediction of M 6.5-7 earthquake rates and also includes types of multifault ruptures seen in nature. Although UCERF3 fits the data better than UCERF2 overall, there may be areas that warrant further site-specific investigation. Supporting products may be of general interest, and we list key assumptions and avenues for future model improvements. Manuscript Organization Because of manuscript length and model complexity, we begin with an outline of this report to help readers navigate the various sections: • Future Improvements 7. Conclusions and Recommendations 8. Data and Resources 9. Acknowledgments 10. References Except where noted, all magnitudes (M) referenced here represent moment magnitude. Spatial distribution of off-fault gridded seismicity set by choosing one of the spatial probability density maps SRP Scientific Review Panel
Dynamics of the Markov Time Scale of Seismic Activity May Provide a Short-Term Alert for Earthquakes
2005
We propose a novel method for analyzing precursory seismic data before an earthquake that treats them as a Markov process and distinguishes the background noise from real fluctuations due to an earthquake. A short time (on the order of several hours) before an earthquake the Markov time scale tM increases sharply, hence providing an alarm for an impending earthquake. To distinguish a false alarm from a reliable one, we compute a second quantity, T1, based on the concept of extended self-similarity of the data. T1 also changes strongly before an earthquake occurs. An alarm is accepted if both tM and T1 indicate it simultaneously. Calibrating the method with the data for one region provides a tool for predicting an impending earthquake within that region. Our analysis of the data for a large number of earthquakes indicate an essentially zero rate of failure for the method.
Uniform California Earthquake Rupture Forecast, Version 2 (UCERF 2
Bulletin of The Seismological Society of America, 2009
The 2007 Working Group on California Earthquake Probabilities (WGCEP, 2007) presents the Uniform California Earthquake Rupture Forecast, Version 2 (UCERF 2). This model comprises a time-independent (Poisson-process) earthquake rate model, developed jointly with the National Seismic Hazard Mapping Program and a time-dependent earthquake-probability model, based on recent earthquake rates and stress-renewal statistics conditioned on the date of last event. The models were developed from updated statewide earthquake catalogs and fault deformation databases using a uniform methodology across all regions and implemented in the modular, extensible Open Seismic Hazard Analysis framework. The rate model satisfies integrating measures of deformation across the plate-boundary zone and is consistent with historical seismicity data. An overprediction of earthquake rates found at intermediate magnitudes (6:5 ≤ M ≤ 7:0) in previous models has been reduced to within the 95% confidence bounds of the historical earthquake catalog. A logic tree with 480 branches represents the epistemic uncertainties of the full time-dependent model. The mean UCERF 2 time-dependent probability of one or more M ≥ 6:7 earthquakes in the California region during the next 30 yr is 99.7%; this probability decreases to 46% for M ≥ 7:5 and to 4.5% for M ≥ 8:0. These probabilities do not include the Cascadia subduction zone, largely north of California, for which the estimated 30 yr, M ≥ 8:0 time-dependent probability is 10%. The M ≥ 6:7 probabilities on major strike-slip faults are consistent with the WGCEP (2003) study in the San Francisco Bay Area and the WGCEP (1995) study in southern California, except for significantly lower estimates along the San Jacinto and Elsinore faults, owing to provisions for larger multisegment ruptures. Important model limitations are discussed.
Reports on Progress in Physics
Charles Richter's observation that 'only fools and charlatans predict earthquakes,' reflects the fact that despite more than 100 years of effort, seismologists remain unable to do so with reliable and accurate results. Meaningful prediction involves specifying the location, time, and size of an earthquake before it occurs to greater precision than expected purely by chance from the known statistics of earthquakes in an area. In this context, 'forecasting' implies a prediction with a specification of a probability of the time, location, and magnitude. Two general approaches have been used. In one, the rate of motion accumulating across faults and the amount of slip in past earthquakes is used to infer where and when future earthquakes will occur and the shaking that would be expected. Because the intervals between earthquakes are highly variable, these long-term forecasts are accurate to no better than a hundred years. They are thus valuable for earthquake hazard mitigation, given the long lives of structures, but have clear limitations. The second approach is to identify potentially observable changes in the Earth that precede earthquakes. Various precursors have been suggested, and may have been real in certain cases, but none have yet proved to be a general feature preceding all earthquakes or to stand out convincingly from the normal variability of the Earth's behavior. However, new types of data, models, and computational power may provide avenues for progress using machine learning that were not previously available. At present, it is unclear whether deterministic earthquake prediction is possible. The frustrations of this search have led to the observation that (echoing Yogi Berra) 'it is difficult to predict earthquakes, especially before
A Synoptic View of the Third Uniform California Earthquake Rupture Forecast (UCERF3)
Seismological Research Letters
Probabilistic forecasting of earthquake-producing fault ruptures informs all major decisions aimed at reducing seismic risk and improving earthquake resilience. Earthquake forecasting models rely on two scales of hazard evolution: long-term (decades to centuries) probabilities of fault rupture, constrained by stress renewal statistics, and short-term (hours to years) probabilities of distributed seismicity, constrained by earthquake-clustering statistics. Comprehensive datasets on both hazard scales have been integrated into the Uniform California Earthquake Rupture Forecast, Version 3 (UCERF3). UCERF3 is the first model to provide self-consistent rupture probabilities over forecasting intervals from less than an hour to more than a century, and it is the first capable of evaluating the short-term hazards that result from multievent sequences of complex faulting. This article gives an overview of UCERF3, illustrates the short-term probabilities with aftershock scenarios, and draws some valuable scientific conclusions from the modeling results. In particular, seismic, geologic, and geodetic data, when combined in the UCERF3 framework, reject two types of fault-based models: long-term forecasts constrained to have local Gutenberg-Richter scaling, and short-term forecasts that lack stress relaxation by elastic rebound.