Computation of vector hazard using salient features of seismic hazard deaggregation

Deaggregation is one of the products of probabilistic seismic hazard analysis (PSHA) suitable for identifying the relative contributions of various magnitudedistance 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.