Abstract:
In the numerical simulation of strong ground motion of future destructive earthquakes, the accuracy of source parameters selection has a great impact on the results of ground motion prediction. There are many uncertain factors in determining source parameters, including both random and cognitive uncertainties. Based on a large number of seismic events and literature researches, this paper focuses on statistical analysis of source parameters with random uncertainty characteristics by using statistical methods. Through regression analysis, a mathematical model is established to explain the randomness and uncertainty of source parameters in the form of empirical formula. In order to study the scaling relation characteristics of source parameters in local regions, we get more empirical relations which are more suitable for local seismic densely regions, especially those of the local regions including the Chinese mainland. This paper more than 1 700 seismic events with
MW≥5.5 are selected from the global CMT catalogue. The empirical relationship of source parameters in earthquake intensive areas is studied by using statistical methods, including focal depth, magnitude, seismic moment, rupture area, etc. The number of seismic samples of asperity in a relatively large local range is increased, so as to obtain more suitable experience for local areas to calculate source parameters from the perspective of statistics relationship. The statistical results show that there are differences between the empirical relationship of source parameters obtained from local earthquake cases and those obtained from unlimited regional cases, especially when it comes to fault rupture area and asperity related parameters. The empirical relationship of source parameters obtained from local earthquake cases is more representative. When using the empirical formula obtained in this paper to calculate the focal parameters required for the strong ground motion of future destructive earthquakes, the ground motion prediction results will better reflect the real ground motion characteristics of the target area. It could improve the reliability of the ground motion prediction results.