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首页> 外文会议>International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering >Towards a bayesian seismotectonic zoning for usein Probabilistic Seismic Hazard Assessment(PSHA)
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Towards a bayesian seismotectonic zoning for usein Probabilistic Seismic Hazard Assessment(PSHA)

机译：朝着普通概率地震危害评估（PSHA）的贝叶斯地震局部分区

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The mathematical representation of seismic sources is an important part of probabilistic seismic hazard assessment. It reflects the association of the seismicity with the tectonically-active geological structures evidenced by seismotectonic studies. Given that most active faults are not characterized well enough, seismic sources are generally defined as areal zones, delimited with finite boundary polygons, within which the geological features of active tectonics and the seismicity are deemed homogeneous (e.g., focal depth, seismicity rate, and maximum magnitude). Besides the lack of data (e.g., narrow range of recorded magnitudes), the application of this representation generates different problems: 1) a large sensitivity of resulting hazard maps on the location of zone boundaries, while these boundaries are set by expert decision; 2) the zoning can not represent any variation in faulting mechanism; 3) the seismicity rates are distributed throughout the zones and we lose the location of the determinant information used for their calculation. We propose an exploratory study for an alternative procedure in area source modeling. First, different data (e.g., geomorphology, geology, fault orientations) will be combined by using automated spatial partitioning (investigation of both supervised and unsupervised methods) in order to obtain several information classes, which may be defined as areal source zones. Then, a given hypocenter belonging to a given "zone", from now on called seismicity model, will be expressed by a probability computed from the 2D (spatial) probability density function (pdf) for the active tectonic model used as an a priori and updated with specific data from seismicity catalogs (e.g., focal mechanism) or other new data sources (e.g., geomorphology, subsurface exploration). This hypocenter will thus be allowed to contribute to several models, with weights given by the value of the pdf for each model. The annual rate of occurrence, for a given model, will be calculated by the weighted average of the different hypocenter contributions contained in this model. Future applications will couple the seismicity models to Ground Motion Prediction Equations. In consequence, the results will provide the full spectrum of variability in the hazard and will highlight zones badly constrained and deserving to be more studied.
机译：地震来源的数学表示是概率地震危害评估的重要组成部分。它反映了地震性与地震调节研究证明的根本活跃的地质结构的关联。鉴于大多数有源故障的表征得足够好，地震源通常被定义为面积区域，与有限的边界多边形界定，在那中，活性构造和地震性的地质特征被认为是均匀的（例如，焦点深度，地震率，和最大幅度）。除了缺乏数据（例如，狭窄的录制量大量）之外，该表示的应用产生了不同的问题：1）在区域边界的位置上产生的危险映射的较大敏感性，而这些边界由专家决策设定; 2）分区不能代表故障机制的任何变化; 3）地震率分布在整个区域内，并且我们失去了用于计算的决定因素信息的位置。我们提出了一个在区域源建模中的替代程序的探索性研究。首先，通过使用自动空间分区（调查监督和无监督的方法）来组合不同数据（例如，地貌，地质，故障方向），以便获得多个信息类，这可以定义为区域源区。然后，从现在在称为地震性模型上，属于给定的“区域”的给定的低缩小者将通过从2D（空间）概率密度函数（PDF）计算的概率来表示，用于主动构造模型作为先验和使用来自地震性目录（例如，焦点机制）或其他新数据源（例如，地貌，地下探索）的特定数据更新。因此，将允许该低置换器贡献到几个模型，其具有由每个模型的PDF的值给出的权重。对于给定模型的年度发生率将通过该模型中包含的不同次级贡献的加权平均值来计算。未来的应用程序将对地震模型耦合到地面运动预测方程。结果，结果将在危险中提供全面的变异性，并将突出严重限制的区域，并且值得更加研究。

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