Ruapehu and Tongariro stratovolcanoes: a review of current understanding

Leonard, Graham S.; Leonard, Graham; Christenson, Bruce; Conway, Chris E.; Cronin, Shane J.; Gamble, J. A.; Hurst, Arthur F.; Kennedy, Ben; Miller, Craig A.; Procter, Jonathan; Pure, Leo R.; Townsend, Dougal; White, James D. L.; Wilson, C. J. N.

doi:10.1080/00288306.2021.1909080

Cited by 26 publications

(11 citation statements)

References 186 publications

(296 reference statements)

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“…The shallow DBMS north of Lake Taupō is consistent with the thin crust and high productivity silicic magmatism in that region. Likewise the deeper DBMS south of Lake Taupō is consistent with thicker crust and a change in style to andesite driven volcanism (Leonard et al., 2021).…”

Section: Discussionmentioning

confidence: 70%

The Thermal Structure of Central Te Riu a Māui/Zealandia Continent as Determined From the Depth to Base of Magnetic Sources

Miller,

Kirkby,

Mortimer

et al. 2023

JGR Solid Earth

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To investigate the thermal structure of central Te Riu a Māui/Zealandia continent we estimate the depth to base of magnetic sources (DBMS), using an updated compilation of magnetic data. We calculate thousands of power spectral density estimates and solve an analytic solution for the fractal distribution of magnetization using a Bayesian method constrained by a sediment thickness model. Our DBMS results are broadly similar to a global model yet show complex relationships with independent models of crust and elastic thicknesses, and depth to base of seismicity (D90). Across central Zealandia, DBMS occurs above, coincident with, and below the Moho reflecting that factors additional to temperature influence DBMS. Away from subduction zones crustal thickness likely modulates DBMS while plate margins show varying influence dependent on margin characteristics. In the Taupō Volcanic Zone we interpret DBMS to reflect Curie point temperature at an average depth of 9–11 km. Error analysis shows that the choice of prior influences the posterior standard deviation and can result in counter intuitive error versus DBMS relationships. We use the DBMS as a basal temperature isotherm in heat flow models to compare with heat flow derived from borehole temperature measurements. Using the standard Curie point temperature of 580°C we find that DBMS derived heat flow models over estimate heat flow in areas underlain by plutonic rocks. We propose this reflects a higher titanomagnetite content in these rocks, although detailed studies of the magnetic mineralogy of Zealandia's plutonic rocks are required.

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Section: Discussionmentioning

confidence: 70%

The Thermal Structure of Central Te Riu a Māui/Zealandia Continent as Determined From the Depth to Base of Magnetic Sources

Miller,

Kirkby,

Mortimer

et al. 2023

JGR Solid Earth

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“…Ruapehu and Tongariro are active andesite-dacite volcanoes of the Taupō Volcanic Zone, New Zealand, with inception ages of ~230 a and ~350 ka, respectively (Leonard et al, 2021). The edifices are predominantly composed of andesitic lava flows and breccias, and display clear evidence of late Pleistocene lava-ice interaction and glacial erosion, although only small glaciers remain on Ruapehu's upper flanks today and none remain on Tongariro (Eaves and Brook, 2020).…”

Section: New Zealandmentioning

confidence: 99%

An assessment of potential causal links between deglaciation and eruption rates at arc volcanoes

Conway

Pure²,

Ishizuka

2023

Front. Earth Sci.

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One of the fundamental questions that underpins studies of the interactions between the cryosphere and volcanism is: do causal relationships exist between the ice volume on a volcano and its eruption rate? In particular, it is critical to determine whether the decompression of crustal magma systems via deglaciation has resulted in enhanced eruption rates along volcanic arcs in the middle to high latitudes. Evidence for such a feedback mechanism would indicate that ongoing glacier retreat could lead to future increases in eruptive activity. Archives of eruption frequency, size, and style, which can be used to test whether magma generation and eruption dynamics have been affected by local ice volume fluctuations, exist in the preserved eruptive products of Pleistocene-Holocene volcanoes. For this contribution, we have reviewed time-volume-composition trends for 33 volcanoes and volcanic groups in arc settings affected by glaciation, based on published radiometric ages and erupted volumes and/or compositions of edifice-forming products. Of the 33 volcanic systems examined that have geochronological and volumetric data of sufficient resolution to compare to climatic changes since ∼250 ka, increases in apparent eruption rates during post-glacial periods were identified for 4, with unclear trends identified for a further 12. Limitations in the geochronological and eruption volume datasets of the case studies make it difficult to test whether apparent eruption rates are correlated with ice coverage. Major caveats are: 1) the potential for biased preservation and exposure of eruptive materials within certain periods of a volcano’s lifespan; 2) the relative imprecision of geochronological constraints for volcanic products when compared with high-resolution climate proxy records; 3) the reliance on data only from immediately before and after the Last Glacial Termination (∼18 ka), which are rarely compared with trends throughout the Pleistocene to test the reproducibility of eruptive patterns; and 4) the lack of consideration that eruption rates and magma compositions may be influenced by mantle and crustal processes that operate independently of glacial advance/retreat. Addressing these limitations will lead to improvements in the fields of geochronology, paleoclimatology, and eruption forecasting, which could make valuable contributions to the endeavours of mitigating future climate change and volcanic hazards.

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“…Ruapehu has been active since the last 230 ka (Conway et al, 2016;Leonard et al, 2021) with 4 major cone building and collapse periods. These build and collapse cycles have resulted in a complex, compound edifice with concentrated areas of hydrothermal alteration reflecting past locations of central vent volcanism (Kereszturi et al, 2020;Miller et al, 2020;Kereszturi et al, 2021).…”

Section: Ruapehu Conceptual Modelmentioning

confidence: 99%

Automated Eruption Forecasting at Frequently Active Volcanoes Using Bayesian Networks Learned From Monitoring Data and Expert Elicitation: Application to Mt Ruapehu, Aotearoa, New Zealand

Christophersen

Behr²,

Miller³

2022

Front. Earth Sci.

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Volcano observatory best practice recommends using probabilistic methods to forecast eruptions to account for the complex natural processes leading up to an eruption and communicating the inherent uncertainties in appropriate ways. Bayesian networks (BNs) are an artificial intelligence technology to model complex systems with uncertainties. BNs consist of a graphical presentation of the system that is being modelled and robust statistics to describe the joint probability distribution of all variables. They have been applied successfully in many domains including risk assessment to support decision-making and modelling multiple data streams for eruption forecasting and volcanic hazard and risk assessment. However, they are not routinely or widely employed in volcano observatories yet. BNs provide a flexible framework to incorporate conceptual understanding of a volcano, learn from data when available and incorporate expert elicitation in the absence of data. Here we describe a method to build a BN model to support decision-making. The method is built on the process flow of risk management by the International Organization for Standardization. We have applied the method to develop a BN model to forecast the probability of eruption for Mt Ruapehu, Aotearoa New Zealand in collaboration with the New Zealand volcano monitoring group (VMG). Since 2014, the VMG has regularly estimated the probability of volcanic eruptions at Mt Ruapehu that impact beyond the crater rim. The BN model structure was built with expert elicitation based on the conceptual understanding of Mt Ruapehu and with a focus on making use of the long eruption catalogue and the long-term monitoring data. The model parameterisation was partly done by data learning, complemented by expert elicitation. The retrospective BN model forecasts agree well with the VMG elicitations. The BN model is now implemented as a software tool to automatically calculate daily forecast updates.

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Ruapehu and Tongariro stratovolcanoes: a review of current understanding

Cited by 26 publications

References 186 publications

The Thermal Structure of Central Te Riu a Māui/Zealandia Continent as Determined From the Depth to Base of Magnetic Sources

The Thermal Structure of Central Te Riu a Māui/Zealandia Continent as Determined From the Depth to Base of Magnetic Sources

An assessment of potential causal links between deglaciation and eruption rates at arc volcanoes

Automated Eruption Forecasting at Frequently Active Volcanoes Using Bayesian Networks Learned From Monitoring Data and Expert Elicitation: Application to Mt Ruapehu, Aotearoa, New Zealand

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