Yulia Starodubtseva

Russian Academy of Sciences

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Alexander Korotkii

N.N. Krasovskii Institute of Mathematics and Mechanics of the Ural Branch of the Russian Academy of Sciences

Oleg Melnik

Lomonosov Moscow State University

Igor Tsepelev

N.N. Krasovskii Institute of Mathematics and Mechanics of the Ural Branch of the Russian Academy of Sciences

Alik Ismail‐Zadeh

Karlsruhe Institute of Technology

Illya Starodubtsev

N.N. Krasovskii Institute of Mathematics and Mechanics of the Ural Branch of the Russian Academy of Sciences

Natalya Zeinalova

Karlsruhe Institute of Technology

A. Ismail-Zadeh

Azerbaijan National Academy of Sciences

Cooperative Institutions

Institute of Earthquake Prediction Theory and Mathematical Geophysics

Russian Academy of Sciences

N.N. Krasovskii Institute of Mathematics and Mechanics of the Ural Branch of the Russian Academy of Sciences

Ural Federal University

Ural Branch of the Russian Academy of Sciences

Karlsruhe Institute of Technology

Czech Academy of Sciences, Institute of Mathematics

International Science Council

International Union of Geodesy and Geophysics

Institut de physique du globe de Paris

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Predicting Lava Dome Viscosity by Analyzing its Observed Morphology

AGU Fall Meeting Abstracts (2020)

A. Ismail-Zadeh Yulia Starodubtseva Illya Starodubtsev Igor Tsepelev Alexander Korotkii

Lava dome

Dome (geology)

Morphology

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Inverse Problems in Lava Dynamics

Cambridge University Press eBooks (2023)

Alik Ismail‐Zadeh Alexander Korotkii Oleg Melnik Illya Starodubtsev Yulia Starodubtseva

: Lava flow and lava dome growth are two main manifestations of effusive volcanic eruptions. Less-viscous lava tends to flow long distances depending on slope topography, heat exchange with the surroundings, eruption rate, and the erupted magma rheology. When magma is highly viscous, its eruption on the surface results in a lava dome formation, and an occasional collapse of the dome may lead to a pyroclastic flow. In this chapter, we consider two models of lava dynamics: a lava flow model to determine the internal thermal state of the flow from its surface thermal observations, and a lava dome growth model to determine magma viscosity from the observed lava dome morphological shape. Both models belong to a set of inverse problems. In the first model, the lava thermal conditions at the surface (at the interface between lava and the air) are known from observations, but its internal thermal state is unknown. A variational (adjoint) assimilation method is used to propagate the temperature and heat flow inferred from surface measurements into the interior of the lava flow. In the second model, the lava dome viscosity is estimated based on a comparison between the observed and simulated morphological shapes of lava dome shapes using computer vision techniques.

Lava dome

Effusive eruption

Dome (geology)

10.1017/9781009180412.013

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CRUST DEVELOPMENT INFERRED FROM NUMERICAL MODELS OF LA V A FLOW AND ITS SURFACE THERMAL MEASUREMENTS

Annals of Geophysics (2019)

Igor Tsepelev Alik Ismail‐Zadeh Yulia Starodubtseva Alexander Korotkii Oleg Melnik

Propagation of a lava flow is governed by slope topography, magma rheology, heat exchange with the atmosphere and the underlying terrain, and the rate of the eruption. Highly viscous crust is formed due to cooling and solidification of the uppermost layer of the flow. We consider here two numerical model problems for lava flows, both based on the fundamental physics of a hot fluid flow: a model problem, where thermal conditions (e.g. temperature and heat flow) at the lava surface are unknown a priori (a direct model problem), and a model problem, where the lava surface conditions are known and determined from observations(an inverse model problem). In both models, the lava viscosity depends on temperature and the volume fraction of crystals. By way of solving the direct model problem, we perform a parametric study of steady state lava flows to investigate the influence of the heat flux, viscosity, and effusion rate on the lava crust development. Numerical experiments show that a lava crust becomes thicker in the case of the nonlinear heat transfer compared to the case of a linear heat flow at the interface of lava with the atmosphere. Also, the crust thickens at lower lava effusion rates, while higher rates result in a rapid lava advection, slower cooling, and development of a thinner crust. Moreover, a lava crust becomes thicker with a higher coefficient of conductive heat transfer, or a higher lava viscosity, or the growth of effective emissivity of the lava surface. By way of solving the inverse model problem, we use an assimilation technique (that is, a method for an optimal combination of a numerical model of lava flows with observations) to propagate the temperature and heat flow, inferred from measurements at the interface between lava and the atmosphere, into the lava flow interior and to analyse the evolving lava crust. Results of thermal data assimilation illustrate that the physical parameters of lava flows, including the thickness of it crust, can be recovered from measured surface thermal data well enough at least for slow effusion rates.

Lava dome

Effusive eruption

10.4401/ag-7745

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Assimilation of thermal observations into numerical models of lava flow

EGUGA (2017)

Yulia Starodubtseva Alik Ismail‐Zadeh Igor Tsepelev Alexander Korotkii Oleg Melnik

Heat flow

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