A model of characteristic earthquakes and its implications for regional seismicity
ABSTRACT Regional seismicity (i.e. that averaged over large enough areas over long enough periods of time) has a size–frequency relationship, the Gutenberg–Richter law, which differs from that found for some seismic faults, the Characteristic Earthquake relationship. But all seismicity comes in the end from active faults, so the question arises of how one seismicity pattern could emerge from the other. The recently introduced Minimalist Model of Vázquez-Prada et al. of characteristic earthquakes provides a simple representation of the seismicity originating from a single fault. Here, we show that a Characteristic Earthquake relationship together with a fractal distribution of fault lengths can accurately describe the total seismicity produced in a region. The resulting earthquake catalogue accounts for the addition of both all the characteristic and all the non-characteristic events triggered in the faults. The global accumulated size–frequency relationship strongly depends on the fault length fractal exponent and, for fractal exponents close to 2, correctly describes a Gutenberg–Richter distribution with a b exponent compatible with real seismicity.
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ABSTRACT: Numerical models are starting to be used for determining the future behaviour of seismic faults and fault networks. Their final goal would be to forecast future large earthquakes. In order to use them for this task, it is necessary to synchronize each model with the current status of the actual fault or fault network it simulates (just as, for example, meteorologists synchronize their models with the atmosphere by incorporating current atmospheric data in them). However, lithospheric dynamics is largely unobservable: important parameters cannot (or can rarely) be measured in Nature. Earthquakes, though, provide indirect but measurable clues of the stress and strain status in the lithosphere, which should be helpful for the synchronization of the models. The rupture area is one of the measurable parameters of earthquakes. Here we explore how it can be used to at least synchronize fault models between themselves and forecast synthetic earthquakes. Our purpose here is to forecast synthetic earthquakes in a simple but stochastic (random) fault model. By imposing the rupture area of the synthetic earthquakes of this model on other models, the latter become partially synchronized with the first one. We use these partially synchronized models to successfully forecast most of the largest earthquakes generated by the first model. This forecasting strategy outperforms others that only take into account the earthquake series. Our results suggest that probably a good way to synchronize more detailed models with real faults is to force them to reproduce the sequence of previous earthquake ruptures on the faults. This hypothesis could be tested in the future with more detailed models and actual seismic data. Comment: Revised version. Recommended for publication in TectonophysicsTectonophysics 10/2006; 424(3-4):319-334. · 2.68 Impact Factor
Dataset: 013 Synchronization of EQ models
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ABSTRACT: A cellular automata model for the interaction between seismic faults in an extended region is presented. Faults are represented by boxes formed by a different number of sites and located in the nodes of a fractal tree. Both the distribution of box sizes and the interaction between them is assumed to be hierarchical. Load particles are randomly added to the system, simulating the action of external tectonic forces. These particles fill the sites of the boxes progressively. When a box is full it topples, some of the particles are redistributed to other boxes and some of them are lost. A box relaxation simulates the occurrence of an earthquake in the region. The particle redistributions mostly occur upwards (to larger faults) and downwards (to smaller faults) in the hierarchy producing new relaxations. A simple and efficient bookkeeping of the information allows the running of systems with more than fifty million faults. This model is consistent with the definition of magnitude, i.e., earthquakes of magnitude m take place in boxes with a number of sites ten times bigger than those boxes responsible for earthquakes with a magnitude m-1 which are placed in the immediate lower level of the hierarchy. The three parameters of the model have a geometrical nature: the height or number of levels of the fractal tree, the coordination of the tree and the ratio of areas between boxes in two consecutive levels. Besides reproducing several seismicity properties and regularities, this model is used to test the performance of some precursory patterns.Physical Review E 07/2010; 82(1 Pt 2):016118. · 2.31 Impact Factor