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TheNew Zealand National Seismic Hazard Model (NSHM) was recently overhauled and revised in a three-year international effort. Of the many inputs into the NSHM, three of the most important ones are the total magnitude-frequency distribution (MFD) of earthquakes in the near-shore upper-plate region (e.g. the 2010-16 Canterbury and 2016 Kaikoura sequences), the MFD on the Hikurangi-Kermadec subduction zone, and the MFD on the Puysegur subduction zone (e.g. the 2009 Dusky Sound earthquake). To constrain these MFDs, we need good earthquake magnitudes, good event depths, and focal mechanisms (the latter two in order to distinguish whether earthquakes in the subduction regions are upper-plate, interface or intraslab). Recent work (Christophersen et al., 2022) has greatly improved the earthquake magnitudes in the New Zealand catalogue. Starting from their catalogue, we import higher-quality event depths, focal mechanisms, and locations and magnitudes from several relocated and global catalogues. Next, we use event depths, focal mechanisms, 3D models of the Hikurangi and Puysegur subduction interfaces, and relative plate motion directions to classify earthquakes as upper-plate, interface or intraslab. Then using this integrated catalogue, we estimate the MFD of earthquakes in the upper-plate region incorporating data back to 1843, balanced with the better data in the more recent catalogue. We estimate the MFDs on the Hikurangi–Kermadec and Puysegur subduction zones using a simplified approach with more recent data. Here, we will describe ongoing work in this area, including incorporating new earthquake data and describing earthquake clustering and rate uncertainty in less model-driven ways., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

The “Every Earthquake a Precursor According to Scale” (EEPAS) model provides the medium-term component of public earthquake forecasts in New Zealand (NZ). EEPAS employs the “precursory scale increase” (Ψ-) phenomenon to forecast future earthquake occurrence rates with time-horizons up to a few decades. Ψ is the rate and magnitude increase of minor earthquakes preceding major earthquakes. Three associated predictive-scaling relations link mainshock magnitude , precursor time and precursory area .Studies of Ψ in synthetic catalogues showed that the expected is inversely proportional to an overall reduction of fault slip rates. The slip-strain rate connection therefore motivates us to enhance EEPAS forecasts by incorporating strain-rate. We allow the time distribution in EEPAS to depend on the strain-rate and introduce an additional parameter to quantify this dependence. Optimising the new parameter for the New Zealand catalogue confirms an inverse proportionality between the local strain-rate and the local precursor time. The information gain over the original EEPAS model is small because few target earthquakes occur where the strain-rate is low. The forecast should be compensated for incompleteness of precursory earthquake contributions due to the limited lead-time from the start of the catalogue to the occurrence of target earthquakes. The incompleteness is especially severe for low strain-rate areas where is longer. Further incompleteness can result from the precursory area for some target earthquakes extending outside the region covered by the catalogue. Such considerations should improve forecasting for low strain-rate areas., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

This is an electronic supplement toA time-dependent seismic hazard model following the Kaikōura M7.8 earthquake. It was writtenby the same authors and published in the New Zealand Journal of Geology and Geophysics

The 2019 Ridgecrest sequence provides the first opportunity to evaluate Uniform California Earthquake Rupture Forecast v.3 with epidemic-type aftershock sequences (UCERF3-ETAS) in a pseudoprospective sense. For comparison, we include a version of the model without explicit faults more closely mimicking traditional ETAS models (UCERF3-NoFaults). We evaluate the forecasts with new metrics developed within the Collaboratory for the Study of Earthquake Predictability (CSEP). The metrics consider synthetic catalogs simulated by the models rather than synoptic probability maps, thereby relaxing the Poisson assumption of previous CSEP tests. Our approach compares statistics from the synthetic catalogs directly against observations, providing a flexible approach that can account for dependencies and uncertainties encoded in the models. We find that, to the first order, both UCERF3-ETAS and UCERF3-NoFaults approximately capture the spatiotemporal evolution of the Ridgecrest sequence, adding to the growing body of evidence that ETAS models can be informative forecasting tools. However, we also find that both models mildly overpredict the seismicity rate, on average, aggregated over the evaluation period. More severe testing indicates the overpredictions occur too often for observations to be statistically indistinguishable from the model. Magnitude tests indicate that the models do not include enough variability in forecasted magnitude-number distributions to match the data. Spatial tests highlight discrepancies between the forecasts and observations, but the greatest differences between the two models appear when aftershocks occur on modeled UCERF3-ETAS faults. Therefore, any predictability associated with embedding earthquake triggering on the (modeled) fault network may only crystalize during the presumably rare sequences with aftershocks on these faults. Accounting for uncertainty in the model parameters could improve test results during future experiments.

The static coulomb stress hypothesis is a widely known physical mechanism for earthquake triggering and thus a prime candidate for physics-based operational earthquake forecasting (OEF). However, the forecast skill of coulomb-based seismicity models remains controversial, especially compared with empirical statistical models. A previous evaluation by the Collaboratory for the Study of Earthquake Predictability (CSEP) concluded that a suite of coulomb-based seismicity models were less informative than empirical models during the aftershock sequence of the 1992 Mw 7.3 Landers, California, earthquake. Recently, a new generation of coulomb-based and coulomb/statistical hybrid models were developed that account better for uncertainties and secondary stress sources. Here, we report on the performance of this new suite of models compared with empirical epidemic-type aftershock sequence (ETAS) models during the 2010-2012 Canterbury, New Zealand, earthquake sequence. Comprising the 2010 M 7.1 Darfield earthquake and three subsequent M = 5:9 shocks (including the February 2011 Christchurch earthquake), this sequence provides a wealth of data (394 M = 3:95 shocks). We assessed models over multiple forecast horizons (1 day, 1 month, and 1 yr, updated after M = 5:9 shocks). The results demonstrate substantial improvements in the coulomb-based models. Purely physics-based models have a performance comparable to the ETAS model, and the two coulomb/statistical hybrids perform better or similar to the corresponding statistical model. On the other hand, an ETAS model with anisotropic (fault-based) aftershock zones is just as informative. These results provide encouraging evidence for the predictive power of coulomb-based models. To assist with model development, we identify discrepancies between forecasts and observations. © 2018 Seismological Society of America. All rights reserved.