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Volcano Deformation and Eruption Forecasting using Data Assimilation: Is it Feasible? Mary Grace Bato *1 , Virginie Pinel 1 , Yajing Yan 2 1 ISTerre, Chamb´ ery, Universit´ e Savoie Mont Blanc, France 2 LISTIC, Annecy-Chamb´ ery, Universit´ e Savoie Mont Blanc, France * [email protected] The recent advances in Interferometric Synthetic Aperture Radar (InSAR) imaging and the increas- ing number of continuous Global Positioning System (GPS) networks recorded on volcanoes provide continuous and spatially extensive evolution of surface displacements during inter-eruptive periods. For basaltic volcanoes, these measurements combined with simple dynamical models (Lenglin` e et al. 2008 [2], Pinel et al, 2011 [3], Reverso et al, 2014 [1]) can be exploited to characterise and constrain parameters of one or several magmatic reservoirs using inversion methods. On the other hand, data assimilation–a time-stepping process that best combines models, real observations, a priori information and error statistics to predict the state of a system–has gained popularity in various fields of geoscience (e.g. ocean-weather forecasting, geomagnetism and natural resources exploration). In this work, we aim to first test the applicability and benefit of data assimilation, in particular the Kalman Filter, in the field of volcanology. We predict the temporal behaviors of the overpressures and deformations by applying the two-magma chamber model of Reverso et. al., 2014 [1] and by using synthetic deformation data in order to first establish our forecasting strategy. GPS time-series data of the recent eruptions at Grimsv¨otn volcano will be used if possible, as preliminary test data for the real case applicability of the method. Grimsv¨ otn volcano is the most active subglacial basaltic volcano in Iceland sitting on top of the Vatnaj¨okull ice cap. Its last eruptions were in 1998, 2004 and 2011. The availability of continuous GPS data at Grimv¨otn makes it a good test site in order to analyse both its long term and short term behaviors. Furthermore, the two reservoir model of Reverso et. al., 2014 [1] had previously shown consistency with the deformations measured by GPS during its last three successive eruptive cycles. References [1] T. Reverso, J. Vandemeulebrouck, F. Jouanne, V. Pinel, T. Villemin, E. Sturkell, A two-magma chamber as a source of deformation at Grimsv¨ otn volcano, Iceland, en ligne JGR, 2014 [2] Lenglin` e, O., D Marsan, J Got, V. Pinel, V. Ferrazzini, P. Obuko, Seismicity and deformation induced by magma accumulation at three basaltic volcanoes, J. Geophys. Res., 113, B12305, 2008. [3] V. Pinel, C. Jaupart and F. Albino, On the relationship between cycles of eruptive activity and volcanic edifice growth, J. Volc. Geotherm. Res, 194, 150-164, 2010

Volcano Deformation and Eruption Forecasting using Data Assimilation: Is it Feasible?

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Page 1: Volcano Deformation and Eruption Forecasting using Data Assimilation: Is it Feasible?

Volcano Deformation and Eruption Forecasting

using Data Assimilation: Is it Feasible?

Mary Grace Bato∗1, Virginie Pinel1, Yajing Yan2

1ISTerre, Chambery, Universite Savoie Mont Blanc, France2LISTIC, Annecy-Chambery, Universite Savoie Mont Blanc, France

[email protected]

The recent advances in Interferometric Synthetic Aperture Radar (InSAR) imaging and the increas-ing number of continuous Global Positioning System (GPS) networks recorded on volcanoes providecontinuous and spatially extensive evolution of surface displacements during inter-eruptive periods.For basaltic volcanoes, these measurements combined with simple dynamical models (Lengline et al.2008 [2], Pinel et al, 2011 [3], Reverso et al, 2014 [1]) can be exploited to characterise and constrainparameters of one or several magmatic reservoirs using inversion methods.

On the other hand, data assimilation–a time-stepping process that best combines models, realobservations, a priori information and error statistics to predict the state of a system–has gainedpopularity in various fields of geoscience (e.g. ocean-weather forecasting, geomagnetism and naturalresources exploration). In this work, we aim to first test the applicability and benefit of data assimilation,in particular the Kalman Filter, in the field of volcanology. We predict the temporal behaviors of theoverpressures and deformations by applying the two-magma chamber model of Reverso et. al., 2014[1] and by using synthetic deformation data in order to first establish our forecasting strategy. GPStime-series data of the recent eruptions at Grimsvotn volcano will be used if possible, as preliminarytest data for the real case applicability of the method. Grimsvotn volcano is the most active subglacialbasaltic volcano in Iceland sitting on top of the Vatnajokull ice cap. Its last eruptions were in 1998,2004 and 2011. The availability of continuous GPS data at Grimvotn makes it a good test site inorder to analyse both its long term and short term behaviors. Furthermore, the two reservoir model ofReverso et. al., 2014 [1] had previously shown consistency with the deformations measured by GPSduring its last three successive eruptive cycles.

References[1] T. Reverso, J. Vandemeulebrouck, F. Jouanne, V. Pinel, T. Villemin, E. Sturkell, A two-magma

chamber as a source of deformation at Grimsvotn volcano, Iceland, en ligne JGR, 2014

[2] Lengline, O., D Marsan, J Got, V. Pinel, V. Ferrazzini, P. Obuko, Seismicity and deformationinduced by magma accumulation at three basaltic volcanoes, J. Geophys. Res., 113, B12305, 2008.

[3] V. Pinel, C. Jaupart and F. Albino, On the relationship between cycles of eruptive activity andvolcanic edifice growth, J. Volc. Geotherm. Res, 194, 150-164, 2010