The PEER NGA-Sub ground-motion intensity measure database is used to develop new conditional ground-motion models (CGMMs), a set of scenario-based models, and non-conditional models to estimate the cumulative absolute velocity (CAV) of ground motions from subduction zone earthquakes. In the CGMMs, the median estimate of CAV is conditioned on the estimated peak ground acceleration (PGA), the time-averaged shear-wave velocity in the top 30 m of the soil (VS30), the earthquake magnitude (Mw), and the spectral acceleration at the period of 1 s (PSA(1.0s)). Multiple scenario-based CAV models are developed by combining the CGMMs with pseudo-spectral acceleration (PSA) ground-motion models (GMMs) for PGA and PSA(1.0s) to directly estimate CAV given an earthquake scenario and site conditions. Scenario-based CAV models are capable of capturing the complex ground-motion effects (e.g. soil non-linearity and regionalization effects) included in their underlying PGA/PSA GMMs. This approach also ensures the consistency of the CAV estimates with a PSA design spectrum. In addition, two non-conditional CAV GMMs are developed using Bayesian hierarchical regressions. Finally, we present comparisons between the developed models. The comparisons show that if non-conditional GMMs are properly constrained, they are consistent with scenario-based GMMs. The CAV GMMs developed in this study advance the performance-based earthquake engineering practice in areas affected by subduction zone earthquakes.

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