This report summarises the Seismicity Rate Model (SRM) of the 2022 New Zealand National Seismic Hazard Model revision. The SRM is comprised of multiple component models that fall into one of two classes: (1) inversion fault model (IFM) or (2) distributed seismicity model (DSM). The full details of each component model are further detailed in reports specific to each component. The IFM uses an inversion-based method to model occurrence rates for hundreds of thousands of...

This document provides a high-level summary of the ground-motion characterisation model component of the 2022 New Zealand National Seismic Hazard Model. This includes: development of a New-Zealand-specific ground-motion database; consideration of alternative empirical ground-motion models based on global datasets; two new New-Zealand-specific models that were developed as part of the project; comparisons of the alternative models against observational data; and considered modifications of the ‘base’ models to account for near-fault directivity, back-arc attenuation for subduction...

Directivity of ground motion in the near-field region of large earthquakes is a well-observed phenomenon whose impacts can be particularly detrimental to structures that sit close to an earthquake rupture. Predictive models of this phenomenon and its amplifying effect on ground motion have been available for more than 20 years, with recent projects such as the Next Generation Attenuation West 2 (NGA-West2) yielding several advanced models for application in probabilistic seismic hazard analysis (PSHA). Despite...

The distribution of earthquakes in time and space is seldom stationary. In low-seismicity regions, non-stationarity and data scarcity may preclude a significant statistical analysis. We investigate the performance of traditional stationary Poisson forecasts (such as smoothed-seismicity models [SSM]), with applications in Probabilistic Seismic Hazard Assessment, in terms of the available training data. We design bootstrap experiments that use multiple pairs of consecutive training-forecast windows of a catalogue to: (i) analyse the lowest available training data...