EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Numerical modelling of unrest signals at Mt. Ruapehu (New Zealand)

Fee Arens1, Joachim Gottsmann1, Armando Coco2, James Hickey3, and Geoff Kilgour4
Fee Arens et al.
  • 1School of Earth Sciences, University of Bristol, Bristol, UK
  • 2Department of Mathematics and Computer Science, University of Catania, Italy
  • 3Camborne School of Mines, University of Exeter, Cornwall, UK
  • 4GNS Science, Wairakei Research Center, Taupo, New Zealand

The absence of precursory signals of recent eruptions at Mt. Ruapehu poses a problem for hazard assessment and risk mitigation at the popular Tongariro National Park. Ruapehu hosts an active hydrothermal system with volcanic unrest being driven by either migration of magma, hydrothermal fluids, or a combination of both. In our study, we develop a suite of 2D axisymmetric numerical models to study the detectability limit of precursory subsurface processes at Ruapehu to inform recommendations for monitoring protocols. In our models magmatic unrest (MU) results from pressurisation of a transcrustal elliptical mush zone due to the intrusion of juvenile magma which triggers a poroelastic response in the hydrothermal system. Hydrothermal unrest (HTU) is simulated by the injection of hot multicomponent and multiphase fluids (H2O and CO2) into Ruapehu’s hydrothermal system (HTS), where thermo-poroelastic responses are triggered. We simultaneously solve for ground displacement, self-potential (SP) anomalies and residual gravity changes resulting from the subsurface perturbations, with model parameterization adapted to Ruapehu. All models account for topography and subsurface mechanical and hydro-electric heterogeneities.

For a plausible reference parameter set, we find that geophysical observables are markedly distinct in their magnitude and wavelength in both magmatic and hydrothermal unrest scenarios. Most geophysical anomalies show their largest magnitudes directly above the hydrothermal system, with signals falling off rapidly with distance. At Ruapehu’s summit plateau (500 m from the HTS) vertical displacement amplitudes for MU simulations are 1.5 times smaller than maximum magnitudes of 1.2 cm for HTU simulations, with the latter being above conventical detection limits (1 cm in the vertical). Maximum residual gravity changes on the plateau are -4 μGal for HTU simulations and hence below detection levels of standard field observations, while for MU simulations with a source density change of 10 kg/m3 resulting signal magnitude is twice as high. Modelled SP anomalies are predicted to exceed conventional detection levels of 0.1 mV with typical SP signals for HTU simulations attaining maximal amplitudes of 1.3 mV, which are ~3 times larger than those resulting from MU simulations.

Parameter exploration shows that residual gravity changes for MU simulations are predominantly controlled by reservoir density changes, while SP polarity and magnitude strongly depends on the hydro-electric coupling coefficient for both unrest scenarios. Moreover, we find that the Biot-Willis coefficient (degree of poroelastic response) has the greatest influence on displacement amplitudes for HTU simulations, with negligible effect on displacement, SP and gravity changes resulting from MU simulations. Although gravity changes and displacements for reservoir strengths (volume/overpressure) > 7 km3/MPa are greater as for reference simulations, vertical displacement remains below detection levels. Magnitudes of all signals from HTU simulations correlate with fluid fluxes. Our interpretation of the findings is that magmatic unrest at Ruapehu should be identifiable by joint residual gravity and SP time series, whereas ground displacements >1 cm in the vertical and SP anomalies should be indicative of hydrothermal unrest.

How to cite: Arens, F., Gottsmann, J., Coco, A., Hickey, J., and Kilgour, G.: Numerical modelling of unrest signals at Mt. Ruapehu (New Zealand), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5637,, 2022.