No abstract

[1] We explore the hypothesis that the relative size distribution of earthquakes, or b-value, systematically depends on the style-of-faulting of seismotectonic zones. Because the b-value has been shown to be inversely proportional to stress, we expect to find b(thrust) < b (strike-slip) < b(normal). We test this expectation for the case of Italy. We first of all build a seismotectonic zonation model, consisting of 10 distinct tectonic zones. The faulting style of each zone is then characterized by the summed moment tensor of first-motion and full-waveform based focal mechanism. We calculate the b-value for each zone: the lowest values are obtained for reverse zones (0.75-0.81), highest for the normal (1.09), followed by the strikeslips (0.9-0.92). Our results suggest that b-values, which are a critical parameter in all seismic hazard assessments, should be set according to the local faulting regimes. In addition, seismotectonic zonation models should take b-value variations as one input. Citation: Gulia, L., and S. Weimer (2010), The influence of tectonic regimes on the earthquake size distribution: A case study for Italy, Geophys. Res. Lett.,

A systematic decay of the aftershock rate over time is one of the most fundamental empirical laws in Earth science. However, the equally fundamental effect of a mainshock on the size distribution of subsequent earthquakes has still not been quantified today and is therefore not used in earthquake hazard assessment. We apply a stacking approach to well‐recorded earthquake sequences to extract this effect. Immediately after a mainshock, the mean size distribution of events, or b value, increases by 20–30%, considerably decreasing the chance of subsequent larger events. This increase is strongest in the immediate vicinity of the mainshock, decreasing rapidly with distance but only gradually over time. We present a model that explains these observations as a consequence of the stress changes in the surrounding area caused by the mainshocks slip. Our results have substantial implications for how seismic risk during earthquake sequences is assessed.

Laboratory experiments highlight a systematic b value decrease during the stress increase period before failure, and some large natural events are known to show a precursory decrease in the b value. However, short‐term forecast models currently consider only the generic probability that an event can trigger subsequent seismicity in the near field. While the probability increase over a stationary Poissonian background is substantial, selected case studies have shown through cost‐benefit analysis that the absolute main shock probability remains too low to warrant significant mitigation actions. We analyze the probabilities considering both changes in the seismicity rates and temporal changes in the b value. The precursory b value decrease in the 2009 L'Aquila case results in an additional fiftyfold probability increase for a M6.3 event. Translated into time‐varying hazard and risk, these changes surpass the cost‐benefit threshold for short‐term evacuation.

&lt;p&gt;Immediately after a large earthquake, the main question asked by the public and decision-makers is whether it was the mainshock or a foreshock to an even stronger event yet to come. So far, scientists can only offer empirical evidence from statistical compilations of past sequences, arguing that normally the aftershock sequence will decay gradually whereas the occurrence of a forthcoming larger event has a probability of a few per cent.&lt;/p&gt;&lt;p&gt;We analyse the average size distribution of aftershocks of the 2016 Amatrice&amp;#8211;Norcia (Italy) and Kumamoto (Japan) earthquake sequences and we suggest that in many cases it may be possible to discriminate whether an ongoing sequence represents a decaying aftershock sequence or foreshocks to an upcoming large event.&lt;/p&gt;&lt;p&gt;We propose a simple traffic light classification (FTLS, Foreshock Traffic Light System) to assess in real time the level of concern about a subsequent larger event and test it against 58 sequences, achieving a classification accuracy of 95 per cent.&lt;/p&gt;&lt;p&gt;We finally test, in near-real-time, the performance of the FTLS to the 2019 Ridgecrest sequence, California: a Mw6.4 followed, about 2 days later, by a Mw7.1. We find that in the hours after the first Ridgecrest event (Mw 6.4, the b-value drops by 23% on average, when compared to the background value, resulting in a &amp;#8216;red&amp;#8217; foreshock traffic light.&lt;/p&gt;&lt;p&gt;Mapping in space the changes in b, we identify an area to the north of the rupture plane as the most likely location of a subsequent event. The second mainshock of magnitude 7.1 then indeed occurred in this location and after this event, the b-value increased by 26 percent over the background value, resulting in a green traffic light state.&lt;/p&gt;

Abstract The Mw 7.1 Ridgecrest earthquake sequence in California in July 2019 offered an opportunity to evaluate in near-real time the temporal and spatial variations in the average earthquake size distribution (the b-value) and the performance of the newly introduced foreshock traffic-light system. In normally decaying aftershock sequences, in the past studies, the b-value of the aftershocks was found, on average, to be 10%–30% higher than the background b-value. A drop of 10% or more in “aftershock” b-values was postulated to indicate that the region is still highly stressed and that a subsequent larger event is likely. In this Ridgecrest case study, after analyzing the magnitude of completeness of the sequences, we find that the quality of the monitoring network is excellent, which allows us to determine reliable b-values over a large range of magnitudes within hours of the two mainshocks. We then find that in the hours after the first Mw 6.4 Ridgecrest event, the b-value drops by 23% on average, compared to the background value, triggering a red foreshock traffic light. Spatially mapping the changes in b values, we identify an area to the north of the rupture plane as the most likely location of a subsequent event. After the second, magnitude 7.1 mainshock, which did occur in that location as anticipated, the b-value increased by 26% over the background value, triggering a green traffic light. Finally, comparing the 2019 sequence with the Mw 5.8 sequence in 1995, in which no mainshock followed, we find a b-value increase of 29% after the mainshock. Our results suggest that the real-time monitoring of b-values is feasible in California and may add important information for aftershock hazard assessment.

The presence of quarry and mine blasts in seismic catalogues is detected using the Wiemer and Baer (Bull Seism Soc Am 90 (2): [525][526][527][528][529][530] 2000) algorithm. The procedure is based on the observation that quarry blasts generally take place during daytime hours: the areas with a high ratio of daytime and night-time events are likely to be regions with quarry activity. In the first part of this work we have tested the method, using both a synthetic and a regional catalogue; in the second part the procedure has been applied to some of the European regional catalogues available on line. The comparison between the results obtained and the location of known quarries and mines for the analysed catalogues confirms the reliability of the methodology in identifying mining areas.

Artifacts often affect seismic catalogs. Among them, the presence of man-made contaminations such as quarry blasts and explosions is a well-known problem. Using a contaminated dataset reduces the statistical significance of results and can lead to erroneous conclusions, thus the removal of such nonnatural events should be the first step for a data analyst. Blasts misclassified as natural earthquakes, indeed, may artificially alter the seismicity rates and then the b-value of the Gutenberg and Richter relationship, an essential ingredient of several forecasting models. At present, datasets collect useful information beyond the parameters to locate the earthquakes in space and time, allowing the users to discriminate between natural and nonnatural events. However, selecting them from webservices queries is neither easy nor clear, and part of such supplementary but fundamental information can be lost during downloading. As a consequence, most of statistical seismologists ignore the presence in seismic catalog of explosions and quarry blasts and assume that they were not located by seismic networks or in case they were eliminated. We here show the example of the Italian Seismological Instrumental and Parametric Database. What happens when artificial seismicity is mixed with natural one?