Interferometric Synthetic Aperture Radar (InSAR) can be used to detect ground motion but also processed further to generate Digital Elevation Models (DEMS). Sentinel-1 images are acquired continuously, and data is made available free of access in near real time making it a valuable tool for Earth observation and volcanic hazard assessment. Mass flow simulations require up to date DEMs for the results to be integrated in volcanic hazard management and mitigation. This study investigates the applicability of InSAR generated terrains as information and data with respect to volcanic hazard analysis as well as the input data in simulating block-and-ash flows (BAFs) following the collapse of volcanic domes on Mount Taranaki, New Zealand, using the Titan2D simulation toolkit. Results show that the accuracy of Sentinel-1 InSAR generated DEMs are limited for volcanic hazard analysis in areas of dense vegetation and steep topography due to temporal decorrelation and geometrical distortions. Together, these conditions introduce major differences in inundation extent and thickness distribution of simulated flows yet can provide some indication of flow impact which may be of relevance for rapid decision making in response to rapidly changing volcanic landscapes.

Abstract Crystal size distribution (CSD) slopes are used to calculate magma residence times, based on the principle that the slope is inversely proportional to the product of crystal residence times and growth rate. Most CSD studies are based on two-dimensional (2D) data, relying on statistical calculations and stereological corrections of the analyzed data to estimate three-dimensional (3D) size distributions using specialized software. However, the effect of this estimation on the actual CSD distributions and their slopes remains unclear. To evaluate the effect of this CSD slope calculation/estimation on crystal residence times, we compare CSD slopes estimated from 2D and directly measured from 3D data. A 2D data set of pyroxene microlites from a glassy lava sample from Mount Ruapehu (New Zealand) was used to generate CSD (2D-CSD) applying three different aspect ratios. These aspect ratios were calculated using known databases (i.e., CSDSlice and ShapeCalc), and the average aspect ratios from a 3D dataset. The CSD slopes between 10 – 20 μm were extracted and compared to the slope obtained from a true CSD using synchrotron radiation X-ray computational tomography (3D-CSD). Our results show differences in the shape determination by the two databases compared to the average 3D aspect ratio, mainly impacting the intermediate/long axes ratio (I/L) showing a I/L ratio difference of 0.18 between both databases, that translate in slope differences of ±0.03 μm-1 compared to the 3D-CSD. The slopes were applied to the determination of crystal residence times using a known growth rate (i.e., 1.80 × 10−11 m/s), finding differences of approximately 31 h between those CSD determined with the databases, and nearly 17 h comparing the 2D-CSD to the 3D-CSD. Our results contribute to the discussion about which is the best shape estimate to use for 2D stereological conversions, highlighting the uncertainties derived from the statistical calculations of the aspect ratios, and the difficulties in replicating true 3D crystal distributions. We conclude that limitations can be circumvented by using 3D datasets.

Volcanic debris avalanches can transform into highly mobile debris flows, reaching long runout distances and posing significant hazards to downstream populations. This high mobility arises from complex, evolving rheological behavior driven by dynamic changes in pore pressure, internal resistance, and material properties during the flow. The 2012 Te Maari flank collapse at Tongariro, New Zealand, triggered a channelized debris avalanche that provides a valuable case study to explore these processes. Our modeling approach uses the depth-averaged, multiphase numerical model D-Claw, which captures the dynamic evolution of the material's apparent rheology. We examine the effect of key initial material properties (e.g., hydraulic permeability, compressibility and dilatancy) on the mechanical response of the avalanche at initiation and throughout its transformation into a debris flow. A linear regression analysis based on Te Maari simulations reveals that flow mobility is primarily controlled by hydraulic permeability and its interactions with compressibility and dilatancy, which together drive transitions in flow behavior. Notably, for the Te Maari case study, two contrasting sets of initial parameters (i.e., a low-permeability and high-permeability scenario) both accurately reproduce the observed flow runout. This suggests that different mechanical processes can compensate for one another to produce comparable mobility outcomes. These findings enhance our understanding of debris flow dynamics and point toward the need for future modeling approaches to incorporate the coupled, time-evolving nature of internal material properties.

Decoding magma evolution and transport mechanisms requires detailed examination of the groundmass glass and associated mineral phases in the eruptive products. These analyses can help determine crystal residence times and magma ascent rates prior to eruption. Magma storage and ascent rates are particularly relevant when assessing the controls on the type and style of eruptions from andesite volcanoes, which are capable of producing varied eruptive phases from highly explosive to dominantly effusive. Here, we focus on Mount Ruapehu, one of New Zealand's most active volcanoes and a significant portion of the Tongariro Volcanic Center, which has a rich geological history of eruptions spanning a broad range of eruptive phases from explosive to effusive. Previous analysis of crystal size distributions of microlites from Holocene tephra showed that magma ascent occurred over a relatively short period (i.e. similar to 2 days at <= 0.09 m/s) immediately prior to eruption. Here, we expand this approach to include analysis of massive lava flows emplaced from 50 to <10 ka (Mangawhero and Whakapapa formations) with similar andesitic composition and mineral assemblages dominated by plagioclase and two pyroxenes. We analyze the crystal size distributions of 17 lavas and conduct bulk rock analysis, groundmass laser ablation mass spectrometry analysis, and electron probe microanalysis on plagioclase and pyroxene phenocrysts and microlites. We use the chemical data to calculate the P-T-H2O conditions of crystallization. Then, we combine the derived crystal size distributions with thermobarometry and hygrometry results to determine the residence times and ascent rates of magmas that ultimately fed erupted lavas. Our data yields initial pressures up to 810 MPa, temperatures up to 1160 degrees C, and water contents up to similar to 2.7 wt % H2O, with average crystal residence times of similar to 3 days (maxima of 66 days considering growth rate uncertainty) and ascent rates up to similar to 0.08 m/s. The similar residence times and ascent rates from effusive and explosive eruptions suggest that similar crystallization paths and undercooling conditions take place irrespective of the eventual eruption style. We propose the eruption style may be modulated by the geometry of the conduit, as observed in other volcanic centers where conduit overpressure and gas accumulation trigger explosive eruptions.

Mass flow models are widely used for hazard assessment and risk mitigation, yet their predictive reliability is constrained by uncertainties in key input parameters. This study examines how incorporating failure characteristics influences runout predictions by coupling limit-equilibrium-derived source geometries with depth-averaged, two-phase D-Claw simulations. Thirty candidate source geometries were selected based on observations from the 2012 Te Maari debris avalanche (New Zealand). The coupled approach demonstrated a good ability to back-calculate complex, channelised mass flows, with the best-performing simulations achieving a critical success index (CSI) greater than 0·6, comparable to values reported in other studies. However, the ensemble of scenarios revealed substantial variability in runout extent and model performance, largely driven by differences in source geometry, volume and alignment. The potential of the method for predicting inundation extent in small-volume scenarios was evaluated using an exceedance probability map of flow depth. An unweighted version was compared with a factor of safety (FOS)-weighted version, in which the FOS served as a proxy for relative failure probability. The FOS-weighted map provided a closer match to the observed debris avalanche extent and demonstrated the potential of this approach to incorporate epistemic uncertainty, offering a more robust framework for probabilistic hazard assessment of future debris flows.

Detecting subsurface changes during volcanic unrest remains challenging when surface manifestations are weak or absent. Between March and July 2022, Ruapehu volcano (New Zealand) experienced heightened seismicity, volcanic tremor, and crater lake heating, yet no eruption occurred. To monitor temporal variations in the subsurface elastic properties during this unrest episode, we estimated relative velocity changes ( dv/v ) from the coda of the correlations using the Moving Window Cross-Spectral (MWCS) method. Our results show spatially heterogeneous changes: a distinct velocity drop occurred on the NE flank, while the NW flank showed no such pattern. The network mean velocity reached ∼ −0.26 ∼ 2–6 km. A 20-day temporal lag between the NE flank and summit signals suggests a lateral-to-vertical migration of magmatic fluids toward the vent. Following the unrest, dv/v recovered to background levels as the crater lake cooled. This may indicate a reversible restoration of the edifice’s elastic state and the cessation of volcanic forcing. Although environmental factors were considered, the magnitude and timing of the dv/v variations are more consistent with a primary volcanic driver. This is the first dv/v application at Ruapehu focusing on a non-eruptive unrest episode; it suggests that frequency-dependent depth constraints and spatial localization can effectively monitor magmatic processes in the absence of measurable geodetic deformation. As such, this approach may improve monitoring and risk assessments of volcanic hazards during similar episodes of unrest.

We outline a conceptual approach to forecast multihazard risk from a cascade of natural hazards events. Network models have been proposed for cascades of natural hazard events, for example storm, flooded river, breached stop banks, damaged infrastructure. These have generally not taken time into account, with the cascade of events effectively assumed to occur instantaneously. We extend the methodology to account for multiple temporal processes, often occurring on quite different time scales, and hence incoporating variable delays. Further, since state of the art physical models generally involve heavy computation, we advocate the use of computationally simple probability distributions to describe the dynamics and interaction of the hazard events in our proposed network model. All model components have estimable parameters, which permits application to specific situations. This enables a larger number of simulations of the model, ensuring greater accuracy of probabilistic model forecasts. The modelling approach takes into account the dynamic and evolving nature of the temporal processes. Thus, it may be possible to identify key elements of the system that are most vulnerable, develop strategies for mitigating risks, and examine restoration strategies.

Network models have been previously proposed for spatial cascades of natural hazard events. These have generally not taken time into account, with the cascade of events effectively assumed to occur instantaneously. This study introduces a dynamic, network-based stochastic model developed as a virtual testbed to simulate complex multihazard interactions between multiple temporal processes, often occurring on different time scales. Since state of the art physical models generally involve heavy computation, the use of computationally simple probability distributions to describe the dynamics and interaction of the hazard events enables a larger number of model simulations, promoting greater robustness of model forecasts. The network modelling approach aims to allow the identification of key elements of the system that are most vulnerable, develop risk mitigation strategies, and examine restoration plans. We exemplify our methodology by investigating impacts of volcanic ashfall on river flow dynamics in the Rangitaiki and Tarawera river systems in New Zealand, simulating hydrological processes over a 365-day period with a volcanic eruption. Our results demonstrate how testbeds can be use to explore “what-if” cascading impacts scenarios, by providing a flexible, computationally efficient framework, offering crucial support for Disaster Risk Management (DRM) in volcanic regions.

Depressurisation from edifice collapse events can impact the subvolcanic plumbing system as a propagation wave moves down through the system shifting the fragmentation zone. Understanding how this influences the eruptive behaviour at a volcano is important for understanding changes in hazards following a large edifice collapse event. Mt. Taranaki has experienced at least 16 collapse events within its > 200 kyr history. Two of the largest collapse events the 27.3 ka Ngaere and 24.8 ka Pungarehu debris avalanches occurred in close succession and were encompassed by the Poto and Paetahi tephra formations, made up of 28 subplinian eruptions over ~ 4,000 years. This eruptive period provides a unique opportunity to examine and understand the influence that edifice collapse events have on the subvolcanic plumbing system. Using 3D Micro-Computed Tomography at the Australian Synchrotron bubble textural analysis was undertaken to investigate the changes in pyroclastic textures from large explosive eruptions and how these change following an edifice collapse event. The high-resolution 3D scans indicate that the eruptive products from the Poto and Paetahi Formations are dominated by small bubbles (2.7 x 10-7 mm3) with high bubble number densities ranging from 2.56 x 1015 cm-3 to 1.74 x 1016 cm-3. Bubble size distributions for the Poto and Paetahi Formations indicate a range of bubble nucleation and growth processes occurring within the subvolcanic plumbing system below Mt. Taranaki initiating at different depths. Early onset of bubble nucleation and periods of magma stalling are indicated by the presence of large, coalesced bubbles within the eruptive products, while the dominance of smaller bubbles indicates a fast ascent of magma within the system with nucleation occurring higher up in the system. Changes are seen in the textural characteristics of pyroclasts produced following the 27.3 ka 5.85 km3 Ngaere collapse which depressurized the shallow magmatic system and shifted the fragmentation zone. Following the 24.8 ka 7.5 km3 Pungarehu collapse ~2,500 years later the same influence is not seen, due to the cone not having enough time to rebuild between edifice collapse events. The results from this study show that the depressurisation and subsequent propagation wave are dependent on the height above the plumbing system not just the mass removed and therefore two major collapses in close proximity do not show the same systematic impact on the fragmentation zone.

Volcanic ash is a widespread and destructive volcanic hazard. Timely and accurate forecasts for ash deposition and dispersal help mitigate the risks of volcanic hazards to society. Producing these forecasts requires numerous simulations with varying input parameters to encapsulate uncertainty and accurately capture the actual event to deliver a reliable forecast. However, exploring all possible combinations of input parameters is computationally infeasible in the lead up to an eruption. This research explores the input space of two volcanic ash transport and dispersion models, Tephra2, which is based on a simplified analytical solution, and Fall3D, which is a computational model based on more general assumptions, in the context of forecasting an unknown future eruption. We use the exemplar of Taranaki Mounga (Mount Taranaki), Aotearoa New Zealand, which has an estimated 30% to 50% chance of an explosive eruption in the next 50 years. We statistically determine how much each input parameter contributes to model output variance through a global sensitivity analysis via Sobol' indices and the extended Fourier Amplitude Sensitivity Test (eFAST). Our findings show that grain size distribution, diffusion, plume shape, and plume duration (Fall3D only) have a substantial first-order impact on model output variance. In contrast, mass, particle density, and plume height have minimal impact in the first-order but become influential when considering parameter-parameter inter-relationships (total-order). The results not only enhance our understanding of model sensitivities but also point to improved efficiency in forecasting efforts.

The sudden removal of large portions of a volcanic edifice through collapse can cause depressurisation in the subvolcanic magmatic system, influencing the nature of subsequent eruptions. At Mt. Taranaki, edifice failure has occurred frequently and at different timescales throughout the volcanic history, forming a broad pattern of cyclic collapse and regrowth. About 20-30,000 years ago, Mt. Taranaki experienced two such cycles in short succession, emplacing the 27.3 ka Ngaere and the 24.8 ka Pungarehu debris-avalanche deposits, which were preceded and followed by a sequence of twenty-eight closely spaced tephra deposits known as the Poto and Paetahi Formations. Here, we reconstruct the tephrastratigraphic framework of the Poto and Paetahi Formations, revealing a minimum total eruptive volume of 3 km3. While eruptions directly following edifice failure were larger compared to those prior to collapse, this 4,000-year long eruptive period was characterised by consistently large subplinian eruptions. In contrast, large explosive events within the Holocene sequence are less frequent, with more multi-phase periods of effusive and explosive activity recorded. Our new data highlights the need to include longer-term eruptive records in volcanic hazard modelling since the most recent volcanic history might not cover the full nature of volcanic processes occurring at long-lived stratovolcanoes.

Volcanic communities near long-lived stratovolcanoes are susceptible to the significant threat associated with edifice collapse events which produce volcanic debris avalanches. These events can have runout distances > 100 km and are the largest mass flows on Earth with volumes ranging from 0.1 to 100 km3 which have the potential to bury large sectors of the landscape posing a severe risk to people and infrastructure. However, the emplacement mechanisms of these large destructive phenomena are still poorly understood with the inability to accurately quantify the physical parameters such as frictional regimes, velocity, and temperature which contribute to the extreme runout. The internal structure and minerology of the avalanche deposits hold the key to understanding the transportation mechanisms. During transportation inter-particle collision and shearing occurs reducing grainsize and generating new minerals such as Pseudotachylytes, Frictionites and Silica polymorphs along shear zones between larger clasts and along the base of the flow. Twenty-five volcanic debris avalanches and rock avalanches of varying sizes were sampled from New Zealand and the USA to provide a representative variety of flow types to better understand transportation mechanisms. Using 3D Micro-Computed Tomography at the Australian Synchrotron the internal structure of the avalanche deposits were analysed to identify different minerals and structures present. Analysis of the microstructures of the samples show a variety of different fracture patterns that can be categorized based on the different source lithologies sampled as well as the different rheological emplacement conditions from the collapse and flow. Features seen at the micro-scale mimic larger centimeter to meter scale features traditionally observed in the flow. Investigating the formation of new minerals along collision and shear zones can provide insights on the physical constraints of the flow e.g., velocity and temperature. Data from this study will provide quantitative input parameters forming the foundation for developing a model for transportation and emplacement of long-runout volcanic debris avalanches. Data from these models can be used to assess the volcanic debris avalanche hazards from volcanoes globally, better informing risk assessments.

Accurate forecasts are needed to help mitigate the risks of volcanic hazards to society. Current approaches use probabilistic estimates based on sparse data, supplemented with expert judgment, to describe likely future eruption characteristics. These probabilistic eruption characteristics then inform input parameters required by hazard models. This process requires a lot of simulations with varying input parameters to constrain uncertainty around a future eruption’s hazard characteristics. It is also computationally intensive, and the outputs may quantify, but do not reduce eruption uncertainty. As hazard models become increasingly more complex, so do the number of input parameters that need to be estimated, thus increasing the number of sources of uncertainty. As input parameters used for volcanic hazard models are fundamentally uncertain before (and often also after) an eruption, how do they affect the accuracy and utility of forecasts made using these models? This research explores the input space of volcanic hazard models to understand the interactions between model complexity and robustness of hazard model forecasts. We use the exemplar of volcanic ash distribution models Tephra2 and Fall3D at Mt. Taranaki, Aotearoa-New Zealand (30-50% chance of eruption in the next 50 years). Sampling strategies for Tephra2 and Fall3D were developed to ensure that the input parameter space was fully covered and represent real-world values – both through independent and dependent sampling of parameters. For example, plume height is dependent on the amount of mass ejected during an eruption. A Global Sensitivity Analysis is presented here to investigate the input parameters that significantly influence model output variance. This exploration is conducted through the statistical assessment of Sobol’ indices and eFAST (extended Fourier Amplitude Sensitivity Tests) to discern the key parameters that contribute to variations in the model’s outputs. The results also shed light on which inputs are vital to robust short-term and real-time hazard forecasting, and ultimately require better understanding/quantification before an event.

Composite volcanoes consist of alternating layers with varying mechanical properties, which contribute to the instability of the flanks. This instability can lead to the onset of mass flows down volcanic slopes, posing significant risks to nearby populations and infrastructures. Tongariro, an active andesite volcano, experienced one of New Zealand's most recent debris avalanches at the Upper Te Maari crater on August 6, 2012. This debris avalanche, initiated simultaneously with a small-magnitude earthquake, released a volume of 7 x 105 m3 of material from the source, which by unloading the pressurised vapour-dominated hydrothermal system, led to a phreatic eruption. This paper aims to better constrain the preparatory and triggering factors, along with the failure mechanics, that led to the 2012 debris avalanche. To achieve this, we applied slope stability finite-element modelling to assess the volcanic slope's sensitivity to varying groundwater, seismic and mechanical conditions. Model results closely match the observed failure when considering the strength of hydrothermally altered rocks subjected to an increased pore pressure at shallow depth. We found that even a relatively minor rise in pore pressure, approximate to 250 kPa in the upper layers, could replicate the observed failure at Te Maari. Our simulations also reveal that this debris avalanche might be a multiple-stage failure involving the progressive sliding of two distinct blocks. These findings enhance our understanding of Tongariro's structure and improve hazard assessments for future potential collapses at Tongariro and other New Zealand volcanoes.

Ruapehu is an active andesitic composite volcano that erupted twice (in 2006 and 2007), following its major eruptive sequence in 1995–1996. Those eruptions were phreatic explosions that occurred with few no precursors. In March 2022, Ruapehu entered a period of significant volcanic unrest characterized by volcanic tremor, gas emissions, and heating of the crater lake. To monitor temporal variations in the elastic properties of Ruapehu volcano during this unrest episode, we applied the method ''Moving Window Cross-Spectral Analysis". This technique revealed a $\sim$0.5$\%$ decrease in relative seismic velocity at the beginning of 2022, coinciding with a small earthquake swarm. This correlation suggests that the process triggering the swarm may also be responsible for the observed velocity drop. A similar $\sim$0.5$\%$ relative seismic velocity reduction was observed during the volcanic unrest in the North-East sector of the volcanic edifice. This seismic velocity drop appears to be a reversible process, likely driven by magmatic or fluid movement. Possible causes include the opening of fractures within the magmatic reservoir, fluid fluxes (water, gas, or magma), magmatic anomalies (magma that does not reach the surface but intrudes into the subsurface), or environmental factors (e.g. rainfall or atmospheric pressure changes) that may contribute to the formation of low-velocity zones. By mid-May 2022, volcanic tremor and crater lake temperature began to decline, most likely due to a reduction in fluid circulation, through sealing processes. However, the reduction in seismic velocity persisted, indicating potential ongoing subsurface alteration. This study highlights the importance of using ambient noise monitoring to detect seismic velocity changes during volcanic unrest. By providing potential insights into subsurface processes, this method can complement current monitoring techniques and improve eruption forecasting and hazard assessment at Ruapehu.

Radar interferometry can be used to detect ground motion but also further processed to generate Digital Elevation Models (DEMS). Sentinel-1 images are acquired continuously, and data is made available free of access in near real time making it a valuable tool for Earth observation and hazard assessment. Interferometric radar requires strong coherence between pairs of images used to be able to generate accurate results. This study on Mount Taranaki, New Zealand shows that the accuracy of InSAR generated DEMs is of limited potential in areas of dense vegetation and steep topography due to temporal decorrelation and geometrical distortions.

The 1987 Edgecumbe earthquake caused vertical displacements of up to 1.3 m along the Rangitaiki River, New Zealand, creating a morphologic disturbance in the form of a knickpoint in the river. Subsequent river surveys identified migration of this knickpoint upstream and general degradation of the river bed. We attempt to simulate this change using a one-dimensional river morphological model. Bed changes in the model show a pattern of progressive profile-smoothing across the earthquake knickpoint, with degradation upstream and aggradation downstream. However, this did not correspond with the observed progressive river degradation both upstream and downstream of the knickpoint. Some of this discrepancy can be attributed to continued settlement post-earthquake, which will be investigated further.

Effective volcanic impact and risk assessment underpins effective volcanic disaster risk management. Yet contemporary volcanic risk assessments face a number of challenges, including delineating hazard and impact sequences, and identifying and quantifying systemic risks. A more holistic approach to impact assessment is required, which incorporates the complex, multi-hazard nature of volcanic eruptions and the dynamic nature of vulnerability before, during and after a volcanic event. Addressing this need requires a multidisciplinary, integrated approach, involving scientists and stakeholders to co-develop decision-support tools that are scientifically credible and operationally relevant to provide a foundation for robust, evidence-based risk reduction decisions. This study presents a dynamic, longitudinal impact assessment framework for multi-phase, multi-hazard volcanic events, and applies the framework to interdependent critical infrastructure networks in the Taranaki region of Aotearoa New Zealand, where Taranaki Mounga volcano has a high likelihood of producing a multi-phase explosive eruption within the next 50 years. In the framework, multi-phase scenarios temporally alternate multi-hazard footprints with risk reduction opportunities. Thus direct and cascading impacts, and any risk management actions, carry through to the next phase of activity. The framework forms a testbed for more targeted mitigation and response planning, and allows the investigation of optimal intervention timing for mitigation strategies during an evolving eruption. Using ‘risk management’ scenarios, we find the timing of mitigation intervention to be crucial in reducing disaster losses associated with volcanic activity. This is particularly apparent in indirect, systemic losses that cascade from direct damage to infrastructure assets. This novel, dynamic impact assessment approach addresses the increasing end-user need for impact-based decision-support tools that inform robust response and resilience planning.

Mitigating the impacts of agricultural nutrients (nitrogen and phosphorus) on water quality requires a clear understanding of their transport pathways and transformation processes from land to receiving waters. For nitrate, which is subject to subsurface denitrification, it is therefore important to assess the spatial variability and temporal stability of groundwater redox conditions, as nitrate reduction typically occurs in reducing conditions. This paper presents a robust assessment of a large groundwater quality data set collected across New Zealand landscapes, develops methods to impute missing groundwater redox-sensitive variables and characterises the spatial variability and temporal stability of groundwater redox conditions against relevant landscape hydrogeochemical characteristics. Random forest and extreme gradient boosting (XGBoost) outperformed linear regression in predicting missing Mn2+ values, achieving higher accuracy (R2 > 0.8) and lower error (RMSE < 0.2 mg/L). Analysis of groundwater redox conditions highlights considerable spatial variability, particularly influenced by subsurface geology (rock types) and soil characteristics such as soil carbon and drainage across various hydrogeological settings. Our findings also reveal a higher prevalence of oxidised redox status in shallower groundwater and greater temporal stability in oxidised conditions across New Zealand landscapes. These insights have significant implications for targeted management strategies to reduce nitrate losses from farming activities, particularly in oxidised, shallow groundwater across different hydrogeological land units.