Skip to content

Uncertainty analysis of a model of wind-blown volcanic plumes

Research output: Contribution to journalArticle

Original languageEnglish
Article number83
Number of pages28
JournalBulletin of Volcanology
Issue number10
Early online date8 Sep 2015
DateAccepted/In press - 23 Jul 2015
DateE-pub ahead of print - 8 Sep 2015
DatePublished (current) - 1 Oct 2015


Mathematical models of natural processes can be used as inversion tools to predict unobserved properties from measured quantities. Uncertainty in observations and model formulation impact on the efficacy of inverse modelling. We present a general methodology, history matching, that can be used to investigate the effect of observational and model uncertainty on inverse modelling studies. We demonstrate history matching on an integral model of volcanic plumes that is used to estimate source conditions from observations of the rise height of plumes during the eruptions of Eyjafjallajökull, Iceland, in 2010 and Grímsvötn, Iceland, in 2011. Sources of uncertainty are identified and quantified, and propagated through the integral plume model. A preliminary sensitivity analysis is performed to identify the uncertain model parameters that strongly influence model predictions. Model predictions are assessed against observations through an implausibility measure that rules out model inputs that are considered implausible given the quantified uncertainty. We demonstrate that the source mass flux at the volcano can be estimated from plume height observations, but the magmatic temperature, exit velocity and exsolved gas mass fraction cannot be accurately determined. Uncertainty in plume height observations and entrainment coefficients results in a large range of plausible values of the source mass flux. Our analysis shows that better constraints on entrainment coefficients for volcanic plumes and more precise observations of plume height are required to obtain tightly constrained estimates of the source mass flux.

Additional information

Date of Acceptance: 22/07/2015

    Research areas

  • Uncertainty analysis, History matching, Plume model, Sensitivity analysis, Turbulent entrainment

Download statistics

No data available



  • Full-text PDF (final published version)

    Rights statement: Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

    Final published version, 7 MB, PDF document

    Licence: CC BY


View research connections

Related faculties, schools or groups