Deaggregation is one of the products of probabilistic seismic hazard analysis (PSHA) suitable for identifying the relative contributions of various magnitude-distance bins to a hazard or intensity measure (IM) level. In this paper, we elucidate some interesting features of deaggregations, such as: their monotonically decreasing nature with IM; their invariance to any minimum IM level; and the pertinence of their bins to a complementary cumulative distribution function (CCDF). We use these features of hazard deaggregation along with copula functions in a simplified method for computing vector deaggregation and vector hazard given the scalar counterparts. We validate our simplified procedure at a hypothetical site surrounded by multiple fault sources where seismic hazard is calculated using a logic tree. We also demonstrate the application of our approach to a real site in Los Angeles, CA. Finally, we explore whether the invariance property of deaggregations can be used to compute scalar hazard curves using new ground motion prediction models/IMs, and find that for low to moderate levels of IM, a reasonable approximation is obtained.

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