Toward Physics-Based Nonergodic PSHA: A Prototype Fully Deterministic Seismic Hazard Model for Southern California

Abstract

ABSTRACT We present a nonergodic framework for probabilistic seismic-hazard analysis (PSHA) that is constructed entirely of deterministic, physical models. The use of deterministic ground-motion simulations in PSHA calculations is not new (e.g., CyberShake), but prior studies relied on kinematic rupture generators to extend empirical earthquake rupture forecasts. Fully dynamic models, which simulate rupture nucleation and propagation of static and dynamic stresses, are still computationally intractable for the large simulation domains and many seismic cycles required to perform PSHA. Instead, we employ the Rate-State earthquake simulator (RSQSim) to efficiently simulate hundreds of thousands of years of M≥6.5 earthquake sequences on the California fault system. RSQSim produces full slip-time histories for each rupture, which, unlike kinematic models, emerge from frictional properties, fault geometry, and stress transfer; all intrinsic variability is deterministic. We use these slip-time histories directly as input to a 3D wave-propagation code within the CyberShake platform to obtain simulated Fmax=0.5 Hz ground motions. The resulting 3 s spectral acceleration ground motions closely match empirical ground-motion model (GMM) estimates of median and variability of shaking. When computed over a range of sources and sites, the variability is similar to that of ergodic GMMs. Variability is reduced for individual pairs of sources and sites that repeatedly sample a single path, which is expected for a nonergodic model. This results in increased exceedance probabilities for certain characteristic ground motions for a source–site pair, while decreasing probabilities at the extreme tails of the ergodic GMM predictions. We present these comparisons and preliminary fully deterministic physics-based RSQSim–CyberShake hazard curves, as well as a new technique for estimating within- and between-event variability through simulation.