Modeling lava flow propagation over a flat landscape by using MrLavaLoba: the case of the 2014–2015 eruption at Holuhraun, Iceland

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Simone Tarquini
http://orcid.org/0000-0002-8064-621X
Mattia de' Michieli Vitturi
https://orcid.org/0000-0002-1626-0822
Esther Jensen
Gro Pedersen
Sara Barsotti
Diego Coppola
Melissa Anne Pfeffer

Abstract

During the emplacement of the 2014-2015 lava flow in Holuhraun (Iceland) a new

code for the simulation of lava flows (MrLavaLoba) was developed and tested. MrLavaLoba is a probabilistic code which derives the area likely to be inundated and the thickness of the final lava deposit. The flow field in Holuhraun progressed through a fairly flat floodplain, and the initial limited availability of topographic data was challenging, forcing us to develop specific modeling strategies. The development of the code, as well as simulation tests, continued after the end of the eruption, and latest results largely benefitted from the availability of improved topographic data. MrLavaLoba simulations of the Holuhraun scenario are compared with detailed observational analyses derived from the literature. The obtained results highlight that small-scale morphological features in the pre-emplacement topography can strongly influence the propagation of the flow. The distribution of the volume settling throughout the extension of the flow field turned out to be very important, and strongly affects the fit between the simulated and the real extent of the flow field. The performed analysis suggests that an improvement in the code should allow adaptable calibration during the course of the eruption in order to mimic different emplacement styles in different phases.

 

Article Details

How to Cite
Tarquini, S., de’ Michieli Vitturi, M., Jensen, E., Pedersen, G., Barsotti, S., Coppola, D. and Pfeffer, M. A. (2019) “Modeling lava flow propagation over a flat landscape by using MrLavaLoba: the case of the 2014–2015 eruption at Holuhraun, Iceland”, Annals of Geophysics, 62(2), p. VO228. doi: 10.4401/ag-7812.
Section
Special Issue: MeMoVolc

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