GNS Science

Hydrothermal alteration is known to enhance conduit sealing and modulate phreatic eruptions. However, the timescales of alteration are poorly understood and difficult to constrain. Here, we use new field- and laboratory-based observations and analyses of fresh and altered lavas from Tongariro, New Zealand, to reconstruct the timescales, fluid composition, and impacts of alteration at this volcano. We focus on Tongariro as it hosts a moderate-sized hydrothermal system across a distributed vent complex. Importantly, it is the site of recent phreatic eruptions in 2012. Fresh Tongariro lavas ( ∼ 500 years old) contain variable plagioclase and pyroxene phenocrysts in an aphanitic groundmass with trace titanomagnetite. Respective altered equivalents are characterized by secondary phyllosilicate minerals, including kaolin-group minerals, and other phases such as pyrite and alunite, reflecting (advanced) argillic alteration caused by acidic fluid flow and/or acidic steam percolation at shallow depths at ∼ 150-200 ° C. Notable, albeit rare, hydrothermal carbonates are present (e.g., dolomite). The rates of alteration of the primary lavas (e.g., using stratigraphy and/or radiometric dating) indicate that hydrothermal alteration can occur within years to thousands of years. Our detailed analysis of secondary mineral assemblages indicates complex and temporally evolving hydrothermal fluid chemistry (including pH) and temperature. The analyzed secondary minerals represent alteration processes associated with the 2012 eruptions, which may have involved deep magmatic fluid discharge followed by neutral meteoric water. Understanding these processes provides insights into hydrothermal fluid circulation, alteration history, and potential volcanic hazards including flank collapse and phreatic eruptions. • Approximate timescales of alteration at Te Maari, Tongariro. • Identified alteration style and conditions. • Mass balance calculations applied to hydrothermal alteration reactions.

Validation for computational modelling of volcanic ballistic projectiles (VBPs) has often been accomplished by replication of field-surveyed VBP distributions. However, a range of ejection parameters can result in the same impact location, with differing impact energies and therefore hazard implications. Ballistic hazard models must accurately represent the whole trajectory to better estimate ballistic energy and interpret eruption dynamics. We examine model performance by directly measuring Strombolian VBP ejection parameters and trajectories from high-speed video and comparing with modelled trajectories using the same parameters. We illustrate the effects of velocity and size on drag. We synthesize and investigate different methods by which the Reynolds number ( Re ) - drag coefficient (C D ) relationship is incorporated into models and how this affects modelling results. Our computational model allows for application of different existing Re -C D methods and direct comparison to tracked trajectories on the metrics of impact distance and peak height. Even with validated ejection parameters and appropriate Re -C D relationships, the model rarely accurately reproduces both height and distance within a 5% threshold. The most common scenario is model overestimation of both metrics. The gas jet is the largest factor contributing to this discrepancy. Significant slowing of VBPs in excess of gravity is observed while bombs are rising (and within the gas jet radius) but not while falling. Slowing in the gas jet is potentially caused by friction with ash and lapilli, surface temperature effects, or other fluid dynamics effects. • Drag affects small, fast volcanic bombs more. • Models often overestimate the height and impact distance of bomb paths. • The gas jet above the vent slows bombs down. • Slowdown might be due to friction with ash, denser gases, or the hot bomb surface.

Inorganic nanoparticles are widely used as sacrificial templates for the synthesis of porous carbons due to their good thermal stability, characteristic shapes, tunable sizes, compatibility with carbon precursors, and lower cost and toxicity than conventional silica-based templates. Their use not only ensures the development of hierarchical porosity but also the creation of short-range graphitic domains in the carbon matrix. These qualities make porous carbons suitable for different applications, including adsorption, separation, catalysis, and energy storage and conversion. Within the series of inorganic nanoparticle templates, metal oxides such as MgO, ZnO, Fe2O3, Fe3O4, and MnO2, and alkali metal salts such as NaCl and KCl stand tall as templates. They are thermally and structurally stable, do not react with the carbon precursor, and do not require high-cost, harsh removal methods such as HF washing. This review provides up-to-date discussions of metal oxides (MgO, ZnO, Fe2O3, Fe3O4, and MnO2) and metal salts (NaCl, KCl, and composite salts) to produce porous carbons and addresses other aspects of their structures. This is a focused review that critically analyzes the recently published literature and will serve as a guiding framework for the future design and development of porous carbons.

Abstract Many exceptionally Au-rich deposits are associated with subduction zones and Au-rich magmas. However, the origin of Au enrichment in arc magmas remains controversial. Here, we present a new high-precision geochemical dataset on 66 submarine glasses from the length of the oceanic Kermadec arc and Havre Trough back-arc system. The combined systematics of Au with other chalcophile elements (Ag, Cu, Se, Pt) shows that hydrous melting in the Kermadec subarc mantle occurs predominantely at relatively high temperatures above the sulfide liquidus and produces magmas with mantle-like Ag/Cu values. The highest Au (up to 6 ng/g) and Au/Cu (up to 0.06 × 10 -3 ) exceeds that in fertile mantle and primitive MORB by far, requiring remelting of previously depleted mantle. We demonstrate that high-degree multiple-stage melting of hydrous and oxidized subarc mantle are major drivers of Au enrichment of parental magmas in intra-oceanic island arcs, such as the Kermadec arc.

Seismic gaps are fault sections that have not hosted a large earthquake for a long time compared to neighbouring segments, making them likely sites for future large events. The 2025 Mw 7.7 Mandalay (Myanmar) earthquake, on the central section of the Sagaing Fault, ruptured through a known seismic gap and ~160 km beyond it, resulting in an exceptionally long rupture of ~460 km. Here we investigate the rupture process of this event and the factors that enabled it to breach the seismic gap by integrating satellite synthetic aperture radar observations, seismic waveform back-projection, Bayesian finite-fault inversion and dynamic rupture simulations. We identify a two-stage earthquake rupture comprising initial bilateral subshear propagation for ~20 s followed by unilateral supershear rupture for ~70 s. Simulation-based sensitivity tests suggest that the seismic gap boundary was not a strong mechanical barrier in terms of frictional strength, and that nucleation of the earthquake far from the gap boundary, rather than its supershear speed, allowed the rupture to outgrow the gap and propagate far beyond it. Hence, we conclude that the dimension of seismic gaps may not reflect the magnitude of future earthquakes. Instead, ruptures may cascade through multiple fault sections to generate larger and potentially more damaging events.

The 2016 Mw7.8 Kaikoura earthquake presents one of most challenging natural events to model dynamically, with up to 21 faults involved in the full rupture, according to geological measurements of surface rupture ( e.g. Litchfield et al. 2018). However, most studies using static displacement observations do not resolve individual fault activation and their temporal connectivity at some parts of the fault range (e.g. Hamling et al. 2017), as suggested by the near-source strong motion data (REF). A more recent complete aftershock catalog provides improved seismological constraints on the rupture kinematics, offering new insights into the fault geometry and faulting mechanisms (Chamberlain et al. 2021). These advances motivate a re‑examination of the mysterious multi-fault rupture with complete seismological observation and physics-based dynamic rupture modeling for to better understand the governing mechanisms of multi-fault ruptures.Compared to kinematic source inversions, dynamic modeling is a powerful numerical tool to compute realistic cases of earthquake occurrence due to complex ruptures. Yet, for earthquakes involving multiple interacting faults, even state-of-the-art dynamic models can lead to fundamentally different physical interpretations. On one hand, the corresponding dynamic modeling setup heavily depends on prior knowledge of the full system geometry, as well as on the stress-state and velocity model of the medium. On the other hand, due to the nonlinear nature of the problem, several models can produce similar results. Results show that for relatively simple ruptures, involving one or two fault planes, the solution is stable. However, when the rupture involves several faults, even minor changes to the dynamic setup result in instability and non-uniqueness of the solution.To gain insight into how such extreme fault complexity controls rupture evolution, we perform the dynamic modeling of the 2016 Mw7.8 Kaikoura earthquake using the open-access SeisSol package. We use the New Zealand 3D velocity model and compare two different geometries. The first geometry uses the NZ Community Fault Model, while the second is based on a previously published rupture model (Ando & Kaneko 2018). For the first geometry, we analyze whether the rupture actually used secondary faults to continue its path, or if subsequent rupture was triggered by the generated wavefield. For the second geometry, we investigate the impact of rupture bifurcation onto two faults and assess whether this process generates identifiable seismic phases in the wavefield.We analyze both dynamic scenarios using near-field and regional strong-motion records, which are expected to capture hidden features of the rupture. We further compare the simulated rupture evolution with previously published high-resolution earthquake catalogs to identify rupture patterns and evaluate potential changes in the stress field before and after the event. Our results highlight both the strengths and inherent ambiguities of dynamic rupture modeling for complex multi-fault earthquakes and provide new constraints on the physical processes governing the Kaikoura rupture.

Earthquake P-wave detection is the first and most critical step in Earthquake Early Warning (EEW), as detection speed determines how much time is available before strong shaking arrives, while detection accuracy governs the reliability of the warning. Conventional P-Wave detection methods such as Short-Term Average over Long-Term Average (STA/LTA) often struggle in complex noise environments and exhibit higher detection latency. Deep learning offers a more robust alternative by learning complex waveform characteristics directly from data, enabling faster and more reliable detections. However, the high computational cost of deep models limits their use on low-cost, resource-constrained edge devices in decentralized EEW networks. Here we present a lightweight Convolutional Neural Network optimized for real-time P- and S-wave detection on edge hardware using only two seconds of seismic input waveforms. Trained on approximately 89K waveform segments recorded by strong-motion sensors across New Zealand, the model achieves an overall accuracy of 97.12% and correctly identifies 98% of P-wave segments. With ~ 38K trainable parameters and sub-7-millisecond inference time on Raspberry Pi 5 hardware, the model demonstrates efficient operation under edge-computing constraints. Its ability to generalize to high-magnitude events highlights its strong potential for integration into distributed EEW systems.

Abstract The Alpine fault is a major transpressive plate boundary in southwestern New Zealand known on paleoseismological grounds to produce great (Mw∼8) earthquakes on <300 yr timescales. The fault is now late in its typical and well-determined interseismic period, having last ruptured in a great earthquake in 1717 C.E. Between October 2021 and November 2023, the Southern Alps Long Skinny Array (SALSA) consisting of 43 broadband and 4 short-period seismometers, was installed with ∼10 km interstation spacing along a 450 km stretch of the Alpine fault, between Maruia and Milford Sound/Piopiotahi. SALSA’s geometry was designed to enable the synthesis of virtual earthquakes representing slip at arbitrary points on the Alpine fault as part of research into the range of far-field ground motions that might result from geologically plausible rupture scenarios. Virtual earthquakes provide a means of evaluating ground motions from a much larger number of kinematic rupture scenarios than is computationally tractable using full-waveform simulations. In addition to providing closely spaced noise measurements, SALSA has yielded novel recordings of microseismicity and tremor along most of the onshore extent of the Alpine fault and will enable ongoing research into the present-day state of the fault and future rupture behavior. Here, we describe the rationale for deploying SALSA and present initial results and analysis that illustrate the dataset and indicate avenues for future research.

Empirical correlations between ground‐motion intensity measures (IMs) are essential for engineering applications, including conditional ground‐motion selection and vector‐valued probabilistic seismic hazard analysis (VPSHA). Although previous research has thoroughly investigated interperiod correlations of response spectral ordinates and relationships between nonspectral IMs and pseudo‐spectral acceleration (PSA), the connections between engineering IMs and Fourier spectral ordinates remain inadequately characterized from an engineering seismology standpoint. This investigation establishes comprehensive empirical correlations between PSAs, Arias intensity (AI), and cumulative absolute velocity (CAV) with Fourier spectral amplitudes utilizing the NGA‐West2 database. The linear correlations are presented using total residuals of the IMs with respect to established ground‐motion models from Abrahamson et al. (2014), Bora et al. (2019), Afshari and Stewart (2016), and Campbell and Bozorgnia (2019). A partial correlation methodology isolates frequency‐dependent relationships. The results confirm earlier observations by Bora et al. (2016) and identify specific frequency ranges controlling individual IMs. Peak ground acceleration (PGA) and peak ground velocity (PGV) are predominantly influenced by higher‐frequency content, with distinct frequency ranges characterizing each parameter. Conversely, AI and CAV exhibit sensitivity across a broader, overlapping frequency band (1–3 Hz). Scenario‐dependent analysis through magnitude binning reveals systematic correlation variations, which essentially explain the regional differences in IM‐Fourier amplitude relationships. These findings illuminate the physical foundation of engineering IMs and hold substantial implications for host‐to‐target adjustments of GMMs, next‐generation GMM development, physics‐based ground‐motion simulation, and understanding of IM correlations in existing literature. The work successfully connects seismological and engineering ground‐motion characterizations.

Understanding the key mechanisms that control the tectonic deformation of the continents remains a fundamental challenge in geodynamics. We present a high-resolution geodetic velocity field of the Tibetan Plateau, which shows that a few major strike-slip fault systems separate regions of more uniformly distributed deformation. We suggest that focused strain on major fault systems is enabled by relatively low-viscosity ductile shear zones extending through the lithosphere beneath the seismically active fault planes. Simple model calculations show that high slip rates on the Kunlun Fault enable east-west extension to be distributed broadly across the relatively weak southern and central Tibetan Plateau. Activation of the Kunlun fault in the Miocene at the same time as the onset of rifting in the north-south grabens suggests a causal relationship.