Real time earthquake forecasting in Italy
Real time earthquake forecasting in Italy
复制标题
意大利实时地震预报
DOI：
10.1016/j.tecto.2008.09.010
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发表时间：
2009
期刊：
影响因子：
2.9
通讯作者：
G. Falcone
中科院分区：
文献类型：
--
作者：
M. Murru;R. Console;G. Falcone
我们已经应用了一个地震集群流行病模型的真实的时间数据在意大利地震数据中心经营的国家地球物理和火山学研究所（INGV）的短期预测中，大地震在意大利。在这种地震类型模型中，每一次地震都被认为是由先前的事件触发的，同时也是触发后续地震的。该模型仅使用地震数据，没有明确使用构造，地质或大地测量信息。预报结果显示为随时间变化的图，图中显示了M1 ≥4.0级地震的预期率密度和在最大预期率密度区周围100×100 km ~ 2范围内未来24 h内地面震动超过修正麦加利烈度VI（PGA≥0.01 g）的概率。为了检验的目的，还估算了在100×100 km ~ 2的同一地区发生M1 ≥4.5级地震的总概率。整个过程在INGV地震数据中心进行真实的测试，仅供内部使用。预测验证程序已在2006-2007年的INGV数据集上进行了前瞻性-回顾性的方式，利用统计工具，如相对运行特征（ROC）图。这些程序表明，聚类流行病模型的性能比一个简单的随机预测假设好几百倍。这样开发的地震危险性建模方法，经过一段时间的测试和完善，预计将提供一个有用的贡献，真实的时间地震危险性评估，甚至可能的实际应用决策和公共信息。
We have applied an earthquake clustering epidemic model to real time data at the Italian Earthquake Data Center operated by the Istituto Nazionale di Geofisica e Vulcanologia (INGV) for short-term forecasting of moderate and large earthquakes in Italy. In this epidemic-type model every earthquake is regarded, at the same time, as being triggered by previous events and triggering following earthquakes. The model uses earthquake data only, with no explicit use of tectonic, geologic, or geodetic information. The forecasts are displayed as time-dependent maps showing both the expected rate density of Ml≥4.0 earthquakes and the probability of ground shaking exceeding Modified Mercalli Intensity VI (PGA≥0.01 g) in an area of 100×100 km2around the zone of maximum expected rate density in the following 24 h. For testing purposes, the overall probability of occurrence of an Ml≥4.5 earthquake in the same area of 100×100 km2is also estimated. The whole procedure is tested in real time, for internal use only, at the INGV Earthquake Data Center. Forecast verification procedures have been carried out in forward-retrospective way on the 2006–2007 INGV data set, making use of statistical tools as the Relative Operating Characteristics (ROC) diagrams. These procedures show that the clustering epidemic model performs up to several hundred times better than a simple random forecasting hypothesis. The seismic hazard modeling approach so developed, after a suitable period of testing and refinement, is expected to provide a useful contribution to real time earthquake hazard assessment, even with a possible practical application for decision making and public information.