Journal Articles
Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915
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Item Global sensitivity analysis of models for volcanic ash forecasting(Elsevier B V, 2025-10-01) Scott E; Whitehead M; Mead S; Bebbington M; Procter JVolcanic 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.Item Understanding the evolution of scoria cone morphology using multivariate models(Springer Nature Limited, 2025-06-06) Kereszturi G; Grosse P; Whitehead M; Guilbaud M-N; Downs DT; Noguchi R; Kervyn MScoria cones are the most abundant type of volcano in the Solar System. They occur in every tectonic setting and often overlap with human populations, yet our ability to provide complete geochronology within volcanic fields remains limited. Appropriate geochronology underpins the reconstruction of size-frequency distribution and is a key input for robust volcanic hazard assessment. Morphometric data have long been used to estimate relative ages of scoria cones; however, they have only shown promise at single volcanic fields and simple cones with homogenous pyroclastics. Here, we present a new global inventory of dated scoria cones (n = 572) from 71 volcanic fields formed under diverse magmatic, tectonic and climatic regimes, and build data-driven age models for dating scoria cones using easily accessible morphometric, reflectance and climatic variables. Our models suggest chemical composition of ascending magma may influence the initial scoria cone morphology which is then gradually modified by erosion over time. (Figure presented.)Item The complexities of assessing volcanic hazards along the Cameroon Volcanic Line using spatial distribution of monogenetic volcanoes(Elsevier B V, Amsterdam, 2022-07) Schmidt C; Laag C; Whitehead M; Profe J; Tongwa Aka F; Hasegawa T; Kereszturi GVolcanic eruptions represent hazards for local communities and infrastructure. Monogenetic volcanoes (usually) erupt only once, and then volcanic activity moves to another location, making quantitative assessment of eruptive hazards challenging. Spatio-temporal patterns in the occurrence of these eruptions may provide valuable information on locations more likely to host future eruptions within monogenetic volcanic fields. While the eruption histories of many stratovolcanoes along the Cameroon Volcanic Line (CVL) are relatively well studied, only fragmentary data exist on the distribution and timing of this region's extensive monogenetic volcanism (scoria cones, tuff rings, maars). Here, we present for the first time a catalog of monogenetic vents on the CVL. These were identified by their characteristic morphologies using field knowledge, the global SRTM Digital Elevation Model (30 m resolution), and satellite imagery. More than ~1100 scoria cones and 50 maars/tuff rings were identified and divided into eight monogenetic volcanic fields based on the visual assessment of clustering and geological information. Spatial analyses show a large range of areal densities between the volcanic fields from >0.2 km−2 to 0.02 km−2 from the southwest towards the northeast. This finding is in general agreement with previous observations, indicating closely spaced and smaller edifices typical of fissure-fed eruptions on the flanks of Bioko and Mt. Cameroon in the southwest, and a more focused plumbing system resulting in larger edifices of lower spatial density towards the northeast. Spatial patterns were smoothed via kernel density estimates (KDE) using the Summed Asymptotic Mean Squared Error (SAMSE) bandwidth estimator, the results of which may provide an uncertainty range for a first-order hazard assessment of vent opening probability along the CVL. Due to the scarce chronological data and the complex structural controls across the region, it was not possible to estimate the number of vents formed during the same eruptive events. Similarly, the percentage of hidden (buried, eroded) vents could not be assessed with any acceptable statistical certainty. Furthermore, the impact of different approaches (convex hull, minimum area rectangle and ellipse, KDE isopaches) to define volcanic field boundaries on the spatial distribution of vents was tested. While the KDE boundary definition appears to reflect the structure of a monogenetic volcanic field better than other approaches, no ideal boundary definition was found. Finally, the dimension of scoria cones (approximated by their basal diameters) across the CVL was contrasted to the specific geodynamic setting. This region presents a complex problem for volcanic hazard analysis that cannot be solved through basic statistical methods and, thus, provides a potential testbed for novel, multi-disciplinary approaches.
