Abstract Our understanding of the dynamics of mountain belt growth is hampered by the lack of high-resolution kinematic observations spanning entire orogenic belts. This is particularly the case for the structurally complex and nascent Tian Shan plateau. Here we use 8 years of Sentinel-1 data across 2 million square kilometres of the Tian Shan to show that the mountain range is extending along its strike, predominantly by rotating along a northeast-trending distributed shear zone. This zone is conjugate to the range strike but aligned with fast axes of shear-wave splitting measurements and a band of strike-slip earthquakes. We interpret this broad zone of shear as resulting from the clockwise rotation of the indenting Tarim Basin, which drives the northeast-to-east motion of the part of the Tian Shan southeast of the cryptic shear zone. Conjugate strike-slip components on numerous basin-bounding faults within the Tian Shan likely facilitate this escape. The present-day vertical deformation of Tian Shan results from a mix of tectonic, climatic, and anthropogenic forcings, with uplift of the highest peak facilitated by thrust along a south-dipping Nalati fault that could be promoted by deglaciation.

Our ability to measure the deformation at the Earth's surface over a range of spatial and temporal scales is vital for understanding seismic hazard, detecting volcanic unrest and assessing the impacts of vertical land movements (VLM) on sea level rise. Here, we combine 9-years of Sentinel-1 InSAR observations and continuous GNSS timeseries to build a high-resolution (1-km) national timeseries and velocity field of New Zealand from 2017 to January 2026. Utilising the higher spatial and temporal observations provided by Sentinel-1, we provide an updated estimate of the coastal VLM following the Kaikōura earthquake at 50–100 m resolution including updated estimates of the uncertainty and temporal variability.

Satellite geodesy provides critical insights into tectonic deformation, fault activity, and seismic hazard. However, in regions of widespread continental deformation, observational coverage has until recently relied on sparse GNSS measurements, limiting the resolution of short-wavelength deformation features. By integrating InSAR we can greatly improve the resolution, and we have recently constructed a transnational velocity field for the entire Alpine-Himalayan Belt at 1 km spacing, from over 222,000 Sentinel-1 SAR images (2016–2024) and a new compilation of GNSS velocities [Elliott et al., in review]. This dataset spans more than 11,000 km from southwestern Europe to eastern China, covering over 20 million km², and is referenced consistently to the Eurasian frame.From these velocities, we derive horizontal strain rates, providing near-continuous deformation mapping across the planet’s largest actively deforming region. Results reveal a bimodal pattern of tectonic strain, which is concentrated along major faults in some regions but distributed across broader zones in others. Vertical motions, in contrast, exhibit shorter-wavelength signals dominated by non-tectonic processes, particularly groundwater depletion.Satellite geodesy also provides critical insights into volcanic deformation and hazard, and we have processed InSAR data for the ~1300 subaerial volcanoes most likely to erupt. Scale is less of an issue for volcanoes, with volcanic activity usually confined to within 40 km of each volcanic centre, but timeliness is important for hazard monitoring, and we process data in near-real time form a subset of volcanoes. For historical analyses we have integrated our InSAR results with local GNSS networks [Bedon et al, in prep], but it remains a challenge to incorporate GNSS from multiple disparate networks for ongoing monitoring on a global basis.The spatial resolution of InSAR measurements is better than GNSS by orders of magnitude, but inclusion of GNSS is key for two reasons: firstly, for tying InSAR to a global reference frame and secondly, to provide a third component of the velocity field, which allows the full 3-D field to be constrained. However, the combination leads to very different resolutions in the north-south direction, constrained predominantly by GNSS, and the east-west direction, where InSAR dominates. When estimating the strain rate this leads to non-localisation of strain for north-south trending strike-slip faults and east-west trending dip-slip faults but also leads to short wavelength shear strain (e.g., from near-surface creep) being wrongly attributed to dilatation on faults of any orientation [Fang et al., 2024].We are addressing this issue in two ways. Firstly, by inclusion of along-track velocity estimates from Sentinel-1 burst overlap regions [Nergizci et al., 2024] and secondly by the addition of InSAR velocity measurements from NISAR. The left-looking nature of NISAR acquisitions will provide two more independent velocity measurement vectors that will enable full 3-D estimation at high resolution. Whilst the accuracy in the north-south direction will be ~4 times worse than in the east-west direction, the improvement in resolution will be by orders of magnitude.ReferencesElliott et al. (in review). Preprint: doi:10.31223/X5GX6B.Fang et al (2024). doi:10.1029/2024GL111199.Nergizci et al. (2024). doi:10.1016/j.procs.2024.06.401.

Surface velocities and strain rates from satellite geodesy have become essential tools for understanding the dis tribution of tectonic deformation, faulting and seismic hazard. However, across large regions of distributed continental deformation, such as the Alpine-Himalayan Belt, data are only sparsely available. While previous studies have mainly used spatially sparse GNSS to measure deformation at such large scales, these approaches cannot characterize shorter wavelength features of deformation in many places. We use Sentinel-1 radar images acquired during 2016-2024 to provide trans-national average surface velocities and time series at 1 km spa tial resolution stretching a distance of over 11,000 km from south-western Europe to eastern China, covering an area more than 20 million square kilometres. We produce the velocity field by combining data from over 222,000 Sentinel-1 SAR images with a new belt-wide compilation of GNSS velocities, all combined in a consistent Eurasian reference frame. Horizontal strain rates are derived from gradients of the velocity field, yielding near-continuous spatial deformation information over the entirety of the largest deforming region on the planet. The horizontal velocities and strains are dominated by tectonic deformation, which has a bimodal behaviour-focused on major faults but distributed elsewhere. Shorter-wavelength vertical velocities are dominated by non-tectonic processes, in particular the widespread over-exploitation of groundwater. Our new velocity and strain rates are foundational data sets that reveal the details of how the continents deform for the first time at trans-continental scale.

Characterizing coastal multihazards in tectonically active regions requires consideration of the possible coseismic vertical deformation. Coseismic uplift or subsidence can cause near- instantaneous meter- scale relative sea- level changes that can exacerbate or reverse the effects of ongoing global sealevel rise. In this study, we developed a probabilistic model that forecasts coseismic vertical displacement over 100 years in the Wellington Region of Aotearoa New Zealand. This model builds upon fault source, earthquake rupture, and epistemic uncertainty data from the 2022 New Zealand National 2022) to quantify the amount, direction, and likelihood of vertical displacement from both crustal fault and subduction interface earthquakes. The results of the model show that both crustal fault and subduction sources pose significant (>0.2 m) vertical displacement hazard at most sites. In general, the subduction interface contributes more to subsidence hazard, while crustal faults contribute more to uplift hazard but also contribute to subsidence hazard at specific sites. We find that fault geometry and slip extent play a significant role in forecasted uplift and subsidence hazard. Future versions of both the NZ NSHM 2022 and our probabilistic model may benefit from refinements to fault geometry and simulated earthquake ruptures. The framework developed here can be used to harness regional- scale hazard models for coastal multihazard analysis, particularly in regions with many overlapping seismic sources.

Evaluating uncertainties and errors in interferometric synthetic aperture radar (InSAR)-derived displacements is challenging but important for any interpretation or analysis. InSAR observation error mainly arises from tropospheric delays, particularly tropospheric turbulence which is hard to quantify in a deterministic way (e.g., using global atmospheric models). Here we propose a new variance-covariance estimation (VCE) method to robustly model the stochastic properties of the uncorrected tropospheric turbulence in time-series of SAR images. Based on this, we further propose 1) an improved linear estimator to quantify interseismic deformation, and 2) a new minimum variance optimization (MVO) to monitor coseismic displacements of small to moderate earthquakes. Synthetic experiments show that compared with the previous VCE approach, the new VCE method is more than 50 % more accurate in deriving SAR variance components, and estimates of interseismic and coseismic displacements are 40 % and 55 % more accurate than those using conventional time-series analysis. Applying the VCE-based linear estimator to real Sentinel-1 time-series over the North Anatolian Fault, Turkey, interseismic displacements have uncertainties reduced by 28 %, 18 %, and 6 % compared to ordinary least-squares approach, for 2, 3 and 4 years of data, respectively. Applying the MVO approach to the 19 September 2023 Mw 5.6 Mount Harper (New Zealand) earthquake, coseismic displacements have uncertainties reduced by 23 % on average compared to the stacking approach. Our results highlight the importance of considering the spatiotemporal variance of InSAR measurements when mapping small tectonic displacements.

We use remote sensing observations to document surface deformation caused by the 2025 Mw7.7 Mandalay earthquake. This event is a unique case of an extremely long (~510 km) and sustained supershear rupture probably favored by the rather smooth and continuous geometry of this section of the structurally mature Sagaing Fault. The seismic rupture involved the locked portion of the fault over its entire depth extent (0 to 13 km) with a remarkably uniform slip distribution that averages 3.3 m, and an average stress drop of 4.7 MPa. No shallow-slip deficit is observed. The rupture extent challenges usual scaling laws relating earthquake magnitude, fault length, and slip. The fault ruptured along a known seismic gap that last ruptured in 1839 and tailed off into sections that ruptured during large earthquakes in 1930 and 1946. The amplitude and spatial distribution of fault slip in the 2025 event conform only approximatively to the slip-predictable model and the segmentation inferred from the fault geometry and past ruptures. Plausible sequences of earthquakes with variable magnitude, segmentation, and return periods, including events similar to the 2025 earthquake are produced in quasidynamic simulations using a simplified but nonplanar fault geometry. Based on this simulation, Mw>7.5 events return irregularly with an interevent time of ~141 y on average and a SD of ~40 y. The simulation is consistent with the historical seismicity and with the maximum magnitude ~Mw7.9 and return period (~250 y) derived from moment conservation. Data assimilation into such simulations could provide a way for time-dependent hazard assessment in the future.

The Tianshan is an intracontinental orogenic belt that has experienced over 100 Mw ≥ 6 earthquakes since 1700. However, strain rates and slip deficit rates on mapped faults in this region—key factors in assessing its seismic potential—remain underexplored. Using an updated interseismic Global Navigation Satellite System (GNSS) velocity field from 936 stations and four geodetic strain models, we compute surface horizontal strain rates and invert them to estimate slip deficit rates on 97 major mapped faults. We find that surface strain is primarily concentrated (∼70%) in the western half of the Tianshan, with ∼60% of the strain across the entire orogen accommodated by the mapped faults. Incorporating historical seismicity, we assess the seismic moment budget and identify 20 fault segments capable of generating future Mw ≥ 7.0 earthquakes.

We compile an integrated earthquake catalog for Aotearoa New Zealand (NZ) by overwriting event parameters in the national operational seismic catalog (the most complete record of NZ's seismicity) with refined estimates of event depths, focal mechanisms, locations, and magnitudes from other sources. This was required for several uses in the 2022 NZ National subduction-interface, and intraslab earthquakes to guide the statistics of separate components of the NZ NSHM 2022's Seismicity Rate Model. Starting from a branch of the operational catalog with standardized event magnitudes, we import revised parameters for 60% of the catalog (including 92% of all 2000-2020 events, 89% of 1951-2020 M >= 5.5 events and 84% of 1917-2020 M >= 6 events) from relocation studies, literature, the NZ Centroid Moment Tensor database and global catalogs. Next, we classify earthquakes as upper plate, subduction, or intraslab by comparing their depths, locations, and focal mechanisms to the Hikurangi-Kermadec and Puysegur subduction interface geometries and relative platemotion directions. We show that this event classification would be either highly error-prone or effectively blind in subduction regions if the catalog had not been revised beforehand. Finally, we estimate the depth distribution of upper-plate earthquakes in multiple regions for use in the NZ NSHM 2022 and explore some post-2022 developments of this approach.

The distribution of earthquakes in time and space is clustered and may exhibit a non-stationary behaviour. The impacts of non-stationarity are further amplified when the observation window is short compared to the timescales of the underlying tectonic process, such as in regions of low-seismicity. This can preclude a robust statistical analysis for PSHA models, which commonly assume stationary Poisson models. We investigate the performance of forecasts for PSHA, such as smoothed-seismicity models (SSM), with respect to the available training data. We design bootstrap experiments for multiple pairs of consecutive training/forecast windows of a catalogue to: (i) analyse the lowest available amount of training data for which SSM performs spatially better than the least-informative Uniform Rate Zone (URZ) model; (ii) characterise the temporal variability of rates in terms of their over-dispersion and non-stationarity. The results show rate variability up to 10 times higher than predicted by Poisson forecasts, and demonstrate the impact of non-stationarity when assuming a constant mean rate derived during a training period for forecasting purposes. Analytical distributions are used to describe rate variability, which are conditioned on the information available from a training period. Furthermore, we devise a data-driven method based on strain-rate maps to spatially delineate URZs, under the assumption that the strain-rates field is related to the time scales of earthquake occurrence and interaction. For each URZ, a rate temporal distribution is inferred from the training events within it. We provide forecasts for the update of the New Zealand Seismic Hazard Model that have increased rates by up to 10 times higher in extensive low-seismicity regions compared to optimised SSMs. The new forecasts are implemented as negative-binomial distributions in the hazard integral. For a 10% exceedance probability in 50 years, the use of URZ with rate variability descriptions increases the expected PGA by up to 0.16 g in low seismicity regions (e.g. Auckland, Dunedin) compared to SSM. Our results highlight the relevance, as well as the feasibility, of incorporating analytical formulations of seismicity that go beyond the inadequate stationary Poisson description of seismicity.

Probabilistic seismic hazard analysis requires a seismicity rate model, or in other words, a forecast of earthquake rates. In the New Zealand National Seismic Hazard Model 2022, the seismicity rate model is constructed through independent forecasts of earthquakes on mapped faults and earthquakes distributed over cells in a spatial grid. Here, we explore the seismicity rate model for upper plate (hypocenter >= 40 km) events, to investigate the shape of magnitude-frequency distributions (MFDs) considering events nucleating (or for which the hypocenters are located) within individual fault zone. We find that more than 80% of the fault zones have MFDs that are better described by a Gutenberg-Richter (GR) distribution, instead of a characteristic distribution (i.e., rates of larger magnitudes much higher than the GR trend). Furthermore, the MFD classifications are neither influenced by time -dependent (and time -independent) considerations nor directly affected by the size (or area) of the fault zones. Fault zones with faster slip rates ( > 20 mm/yr) exhibit characteristic MFDs, whereas those with slower slip rates may or may not. Although multifault ruptures are prevalent in the characteristic distributions, large maximum magnitude (M-w > 8.0) plays a pivotal role producing a characteristic MFD. On the other hand, physically unconnected multifault ruptures (i.e., involving rupture jumps >= 10 km) are mostly observed with GR distributions.

ABSTRACT As part of the 2022 revision of the Aotearoa New Zealand National Seismic Hazard Model (NZ NSHM 2022), deformation models were constructed for the upper plate faults and subduction interfaces that impact ground-shaking hazard in New Zealand. These models provide the locations, geometries, and slip rates of the earthquake-producing faults in the NZ NSHM 2022. For upper plate faults, two deformation models were developed: a geologic model derived directly from the fault geometries and geologic slip rates in the NZ Community Fault Model version 1.0 (NZ CFM v.1.0); and a geodetic model that uses the same faults and fault geometries and derives fault slip-deficit rates by inverting geodetic strain rates for back slip on those specified faults. The two upper plate deformation models have similar total moment rates, but the geodetic model has higher slip rates on low-slip-rate faults, and the geologic model has higher slip rates on higher-slip-rate faults. Two deformation models are developed for the Hikurangi–Kermadec subduction interface. The Hikurangi–Kermadec geometry is a linear blend of the previously published interface models. Slip-deficit rates on the Hikurangi portion of the deformation model are updated from the previously published block models, and two end member models are developed to represent the alternate hypotheses that the interface is either frictionally locked or creeping at the trench. The locking state in the Kermadec portion is less well constrained, and a single slip-deficit rate model is developed based on plate convergence rate and coupling considerations. This single Kermadec realization is blended with each of the two Hikurangi slip-deficit rate models to yield two overall Hikurangi–Kermadec deformation models. The Puysegur subduction interface deformation model is based on geometry taken directly from the NZ CFM v.1.0, and a slip-deficit rate derived from published geodetic plate convergence rate and interface coupling estimates.

Recurrence intervals of ground-surface rupturing earthquakes are one of numerous datasets used to constrain the rates of fault ruptures in the 2022 revision of the New Zealand National Seismic Hazard Model (NZ NSHM 2022). Paleoearthquake timing and single-event displacement (SED) data in the New Zealand Paleoseismic Site Database version 1.0 alongside geologic and geodetic slip rates from the New Zealand Community Fault Model version 1.0 and NZ NSHM 2022 Geodetic Deformation Model were used to estimate recurrence intervals on faults across New Zealand for inclusion in the NZ NSHM 2022. Past earthquake timings were fit with lognormal, exponential, and Brownian Passage Time recurrence models to derive probability density functions (PDFs) of mean recurrence interval (MRI) in a Bayesian framework. At some sites, SED and slip-rate (SR) data were used to estimate PDFs of MRI; and at sites where timings, slip rate, and displacement data are available, the timings-based and slip-based PDFs were combined to develop tighter constraints on MRI. Using these approaches, we produce a database of maximum-likelihood MRIs and their uncertainties for 80 sites across New Zealand. The resulting recurrence interval dataset is publicly available and is the largest such dataset in New Zealand to date. It provides a valuable resource for future seismic hazard modeling and highlights areas that would benefit from future study.

Intraslab seismicity within the Hikurangi and Puysegur subduction zones constitutes > 50% of recorded (Mw >= 4:0 events) earthquakes in Aotearoa New Zealand. Here, we develop a source model for intraslab seismicity using recently augmented datasets including models of subduction interface geometries, an earthquake catalog, and a regional moment tensor catalog. For the areal zones of uniform seismicity, we consider the whole of each slab, as well as demarcations between shallower (depth <= 40 km) and deeper regions. Thereafter, we evaluate the magnitude-frequency distributions in each zone. To compute smoothed seismicity distributions, we apply a novel quasi -3D approach that involve: 1)) delineation of midslab surfaces (defined by regions of maximum earthquake density), (2) orthogonal projections of hypocenters onto the midslab profiles, (3) uniform gridding of 0.1(degrees) down -dip on the midslab, and (4) application of smoothing kernel on the projected hypocenters. We also develop a model to characterize the focal mechanisms of the intraslab earthquakes using the regional moment tensor catalog. This model has median strike angles subparallel to subduction trenches and median dip angles >= 60(degrees) in both the subduction zones. The distribution of rake angles suggests that the Hikurangi slab has an extensional regime in the shallower parts but a compressional regime in the deeper parts, indicative of slab flexure. In contrast, the Puysegur slab predominantly exhibits a compressional regime.

ABSTRACT Using a new integrated earthquake catalog for Aotearoa New Zealand (described in a companion article), we estimate the magnitude–frequency distributions (MFDs) of earthquakes in the greater New Zealand region and along the Hikurangi–Kermadec and Puysegur subduction zones. These are key inputs into the seismicity rate model (SRM) component of the 2022 New Zealand National Seismic Hazard Model. The MFDs are parameterized by a b-value (describing the relative rates of small and large earthquakes) with its epistemic uncertainty expressed by three logic tree branches (low, central, and high), and by the annual rate of M ≥ 5 earthquakes, here called the N-value, which has a separate value conditioned on each b-value branch. The N-value has its own epistemic uncertainty besides the dependence on the b-value, and this is also estimated here and propagated through the SRM by scaling all event rates up and down by a “low” and a “high” scalar value on either side of 1.0, called “N scaling.” Adapting an approach used previously in California, we estimate these MFD parameters in the onshore and near-shore region incorporating data back to 1843, balanced with the better data in the more recent part of the instrumental catalog. We estimate the MFD parameters on the Hikurangi–Kermadec and Puysegur subduction zones using a slightly simplified version of this approach and more recent data. We then use a globally-based method to estimate the potential earthquake rate uncertainty on the Hikurangi–Kermadec subduction zone and an SRM-specific moment-rate-related argument to construct an appropriately wide rate uncertainty for the Puysegur subduction zone.

Tens of thousands of earthquakes are located by GeoNet across Aotearoa every year. However, spatial variability - both in station coverage and earthquake distributions - produce heterogeneity in earthquake location quality throughout the GeoNet catalogue. Here we consider simple, established criteria (including station azimuthal coverage, minimum station distance, phase arrival coverage and fixed location criteria) to score earthquakes on a network location Quality Score (QS) scale of QS0 (unconstrained) to QS6 (best constrained). Significant variation in QS exists nationwide; 48% and 20% of earthquakes score QS6 for the North and South Islands respectively. The Hawkes Bay region scores highest (68% QS6) closely followed by other Hikurangi regions. However, several regions score extremely poorly, with Fiordland, West Coast, Nelson, Otago-Southland and Auckland-Northland regions having <= 5% QS6 events and >75% of events scoring QS3 or lower. Low QS mostly arises from the failure of minimum distance criteria, whereby the closest station is too far from the earthquake to provide sufficient depth control. Our analysis quantitatively assesses the impact of network heterogeneity on GeoNet earthquake catalogue location quality to inform end users. This work also provides motivation for the expansion of the weak-motion network in critically under-instrumented regions, especially those with high seismic hazard.

Seismic and tsunami hazard modelling and preparedness are challenged by uncertainties in the earthquake source process. Important parameters such as the recurrence interval of earthquakes of a given magnitude at a particular location, the probability of multifault rupture, earthquake clustering, rupture directivity and slip distribution are often poorly constrained. Physics-based earthquake simulators, such as RSQSim, offer a means of probing uncertainties in these parameters by generating long-term catalogues of earthquake ruptures on a system of known faults. The fault initial stress state in these simulations is typically prescribed as a single uniform value, which can promote characteristic earthquake behaviours and reduce variability in modelled events. Here, we test the role of spatial heterogeneity in the distribution of the initial stresses and frictional properties on earthquake cycle simulations. We focus on the Hikurangi-Kermadec subduction zone, which may produce M-w > 9.0 earthquakes and likely poses a major hazard and risk to Aotearoa New Zealand. We explore RSQSim simulations of Hikurangi-Kermadec subduction earthquake cycles in which we vary the rate and state coefficients (a and b). The results are compared with the magnitude-frequency distribution (MFD) of the instrumental earthquake catalogue and with empirical slip scaling laws from global earthquakes. Our results suggest stress heterogeneity produces more realistic and less characteristic synthetic catalogues, making them particularly well suited for hazard and risk assessment. We further find that the initial stress effects are dominated by the initial effective normal stresses, since the normal stresses evolve more slowly than the shear stresses. A heterogeneous stress model with a constant pore-fluid pressure ratio and a constant state coefficient (b) of 0.003 produces the best fit to MFDs and empirical scaling laws, while the model with variable frictional properties produces the best fit to earthquake depth distribution and empirical scaling laws. This model is our preferred initial stress state and frictional property settings for earthquake modelling of the Hikurangi-Kermadec subduction interface. Introducing heterogeneity of other parameters within RSQSim (e.g. friction coefficient, reference slip rate, characteristic distance, initial state variable, etc.) could further improve the applicability of the synthetic earthquake catalogues to seismic hazard problems and form the focus of future research.

The 2022 revision of Aotearoa New Zealand National Seismic Hazard Model (NZ NSHM 2022) has involved significant revision of all datasets and model components. In this article, we present a subset of many results from the model as well as an overview of the governance, scientific, and review processes followed by the NZ NSHM team. The calculated hazard from the NZ NSHM 2022 has increased for most of New Zealand when compared with the previous models. The NZ NSHM 2022 models and results are available online.