STATISTICAL SHORT-TERM EARTHQUAKE PREDICTION
STATISTICAL SHORT-TERM EARTHQUAKE PREDICTION
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DOI：
10.1126/science.236.4808.1563
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发表时间：
1987-06-19
期刊：
影响因子：
56.9
通讯作者：
KNOPOFF, L
中科院分区：
文献类型：
--
作者：
KAGAN, YY;KNOPOFF, L
一个统计过程，来自裂缝生长的理论模型，是用来识别前震序列，而它是在进行中。作为一个预测，该程序减少了平均不确定性的发生率为未来的强震的因素超过1000时，发生的泊松比。在加州中部，大约三分之一的当地震级大于或等于4.0的主震可以用这种方法预测，从一个7年的数据库开始，该数据库的震级下限为1.5。对于2.0 ~ 5.0级的前震，这种预测的时间尺度是几小时到几天。
A statistical procedure, derived from a theoretical model of fracture growth, is used to identify a foreshock sequence while it is in progress. As a predictor, the procedure reduces the average uncertainty in the rate of occurrence for a future strong earthquake by a factor of more than 1000 when compared with the Poisson rate of occurrence. About one-third of all main shocks with local magnitude greater than or equal to 4.0 in central California can be predicted in this way, starting from a 7-year database that has a lower magnitude cutoff of 1.5. The time scale of such predictions is of the order of a few hours to a few days for foreshocks in the magnitude range from 2.0 to 5.0.