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Cyclical geothermal unrest as a precursor to Iceland’s 2021 Fagradalsfjall eruption

Nature Geoscience volume 15, pages 397–404 (2022)Cite this article

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Abstract

Understanding and constraining the source of geodetic deformation in volcanic areas is an important component of hazard assessment. Here, we analyse deformation and seismicity for one year before the March 2021 Fagradalsfjall eruption in Iceland. We generate a high-resolution catalogue of 39,500 earthquakes using optical cable recordings and develop a poroelastic model to describe three pre-eruptional uplift and subsidence cycles at the Svartsengi geothermal field, 8 km west of the eruption site. We find the observed deformation is best explained by cyclic intrusions into a permeable aquifer by a fluid injected at 4 km depth below the geothermal field, with a total volume of 0.11 ± 0.05 km3 and a density of 850 ± 350 kg m–3. We therefore suggest that ingression of magmatic CO2 can explain the geodetic, gravity and seismic data, although some contribution of magma cannot be excluded.

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Fig. 1: Overview of the tectonics and seismicity of the RP.
Fig. 2: Results from the poroelastic model.
Fig. 3: Sketch of fluid migration paths and aquifer location compared with observed seismicity and uplift.
Fig. 4: Comparison of observed M ≥ 1 seismicity with model predictions based on induced crustal stress changes related to the geodetically inverted source model.
Fig. 5: Cyclic fluid transport model.
Fig. 6: A conceptual model of the processes leading to the uplift, gravity changes, seismic unrest and volcanic eruption.

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Data availability

The basic data used in this paper consist of InSAR, seismic and gravity data. The InSAR data acquired by the Copernicus Sentinel-1A and 1B satellites are available at no cost from the European Space Agency’s Copernicus Open Access Hub (https://scihub.copernicus.eu/) and can be interferometrically processed using the freely available Sentinel-1 toolbox (https://step.esa.int/main/toolboxes/sentinel-1-toolbox/). The InSAR data generated from the Copernicus Sentinel-1A and 1B satellites and as published in the paper are available via Zenodo at https://doi.org/10.5281/zenodo.6344933. The earthquake catalogue based on waveform stacking from DAS and local seismic stations presented in this paper is available via Zenodo at https://doi.org/10.5281/zenodo.6337788. Seismic data from the permanent national seismic network in Iceland are available from the open database of the Iceland Met Office (https://skjalftalisa.vedur.is). For data from temporary stations from the Czech Academy of Sciences, Czech Republic, restrictions apply to the availability, which were used under licence for the current study and so are not publicly available. These data are, however, available from the corresponding author upon reasonable request and with permission of the Czech Academy of Sciences. The seismological data from temporary GFZ stations analysed during the current study are available in the GEOFON repository at https://geofon.gfz-potsdam.de/waveform/archive under code 9H and https://doi.org/10.14470/4U7575229166 (ref. 52; restricted until January 2026). Seismological waveform data from the glass-fibre cable monitoring in SW Reykjanes Peninsula are available from the GEOFON data centre, under network code 5 J. This dataset comprises a selection of waveforms recorded along an optical fibre of 21 km length. The subset consists of 40 channels at 100 Hz (spatially stacked 9×). The full dataset53 is available upon request from P.J. (pjousset@gfz-potsdam.de). Other seismic network data are available at https://doi.org/10.14470/0W7575244885. The preliminary seismic catalogue used in this study has been derived by combining horizontal strain DAS and local seismic stations in a migration-based detection and location approach using the open-source Lassie software (https://git.pyrocko.org/pyrocko/lassie/). The gravity data are available via Zenodo at https://doi.org/10.5281/zenodo.6344613. All other data generated or analysed during this study are included in the Article and the Supplementary Information or available from the corresponding author on reasonable request. All general requests regarding the paper, the geological interpretation, the conceptual model and the gravity data should be directed to Ó.G.F. Requests regarding other specific parts of the paper should be directed to other authors as follows: seismic data processing and interpretation: S.H. (hainzl@gfz-potsdam.de); poroelastic modelling: R.W. (wang@gfz-potsdam.de); InSAR data processing and modelling: T.R.W. (twalter@gfz-potsdam.de); cyclic fluid transport modelling: T.D. (dahm@gfz-potsdam.de). Source data are provided with this paper.

Code availability

The seismic recordings were processed with Pyrocko41. The software package Lassie (https://git.pyrocko.org/pyrocko/lassie.git) was used for detection and localization of earthquakes. Recorded DAS data were converted using iDAS Convert54 (https://doi.org/10.5880/GFZ.2.1.2021.005). The seismic software frameworks are publicly available at https://pyrocko.org. The seismic software code is open, and methods have been reviewed publicly.

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Acknowledgements

The authors are grateful to all those who assisted to generate this article, including H. Geirsson, University of Iceland, for providing the time series of a permanent GNSS station, allowing us to control InSAR data; I. Þór Magnússon for collecting and processing the gravity data; Þ. Þórðarson, University of Iceland, and A. Hobé, Uppsala University, for useful discussions; E. Bali and G. H. Guðfinnsson, University of Iceland, for valuable assistance with the geochemical calculations; Mila Telecommunication Company for access to the fibre-optic cable; Iceland Met Office for the access to the earthquake catalogue, seismic waveforms and GNSS stations; and C. Wollin, K. Erbas and T. Reinsch for DAS assistance. The fieldwork of GFZ was part of a HART rapid response activity funded by GFZ. DEM(s) were created from DigitalGlobe, Inc., imagery and funded under National Science Foundation awards 1043681, 1559691 and 1542736. The work of M.P.I. was supported by the DEEPEN project (BMWI 03EE4018).

Author information

Authors and Affiliations

  1. ÍSOR, Iceland GeoSurvey, Reykjavik, Iceland

    Ólafur G. Flóvenz, Gylfi Páll Hersir, Vincent Drouin, Egill Á. Gudnason, Kristján Ágústsson & Thorbjörg Ágústsdóttir

  2. Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany

    Rongjiang Wang, Torsten Dahm, Sebastian Hainzl, Magdalena Vassileva, Sebastian Heimann, Marius Paul Isken, Mahdi Motagh, Thomas R. Walter, Eleonora Rivalta, Philippe Jousset, Charlotte M. Krawczyk & Claus Milkereit

  3. Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan, China

    Rongjiang Wang

  4. Institute of Geosciences, University of Potsdam, Potsdam, Germany

    Torsten Dahm, Sebastian Heimann, Marius Paul Isken & Thomas R. Walter

  5. Institute of Photogrammetry and GeoInformation, Leibniz University Hannover, Hannover, Germany

    Magdalena Vassileva & Mahdi Motagh

  6. Icelandic Meteorological Office, Reykjavík, Iceland

    Vincent Drouin

  7. Institute of Geophysics, Czech Academy of Sciences, Prague, Czech Republic

    Josef Horálek

  8. Department of Physics and Astronomy, University of Bologna, Bologna, Italy

    Eleonora Rivalta

  9. Institute of Applied Geosciences, TU Berlin, Berlin, Germany

    Charlotte M. Krawczyk

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  1. Ólafur G. Flóvenz
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Contributions

Ó.G.F. contributed coordination, writing, analysis of gravity, seismic and geothermal data and modelling concepts. R.W. contributed numerical and theoretical modelling, development of porous media deformation approach and gravity modelling. G.P.H. contributed gravity measurements, data acquisition DAS and fieldwork management. T.D. contributed coordination, writing, modelling concepts and analytical model of cyclic channel flow. S. Hainzl contributed statistical analysis and modelling of seismicity. M.V. contributed analysis of InSAR data and Mogi model inversion. V.D. contributed analysis of InSAR data. S. Heimann contributed DAS processing, development of the Lassie stacking approach and automatic earthquake detection/location for the combined network. M.P.I. contributed DAS data conversion and processing, earthquake detection/location and code development. E.Á.G. contributed seismicity analysis, including focal mechanisms, data acquisition DAS and manual location of earthquakes from the enlarged network. K.Á. contributed seismicity analysis, seismic networks and field activity. T.Á. contributed seismicity analysis, including focal mechanisms. J.H. contributed data from Czech temporary network. M.M. contributed supervision and quality control InSAR analysis at GFZ. T.R.W. coordinated InSAR analysis and contributed to manuscript drafting and writing. E.R. contributed to manuscript review, internal review of channel flow and fluid transport models. P.J. contributed concept DAS measurements and coordinated DAS data acquisition and fieldwork in MAGIC at GFZ. C.M.K. contributed to support of MAGIC HART initiative at GFZ, coordination of DAS data processing and storage, and manuscript review. C.M. installed temporary seismic stations and contributed to fieldwork coordination, conversion of seismic data and coordination of analysis and writing team at GFZ.

Corresponding author

Correspondence to Ólafur G. Flóvenz.

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Nature Geoscience thanks Ben Kennedy, Steven Ingebritsen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Xujia Jiang and Rebecca Neely, in collaboration with the Nature Geoscience team.

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Extended data

Extended Data Fig. 1 Close up map of the Svartsengi high-temperature field.

The red lines denote postglacial eruption fissures. The yellow lines show the top of the resistive core at 0.5 and 1.0 km depth, respectively, according to TEM resistivity measurements55, defining the top of the geothermal reservoir. The blue line shows the location of the pro-posed inflated aquifer at 4 km depth inferred from the poroelastic model, while the centre of uplift is shown as a blue star and red circles with crosses are geothermal wellheads, of both production and re-injection wells. Note that the proposed aquifer is located below the geo-thermal field and follows its main direction.

Extended Data Fig. 2 Long-term (7-months) wrapped interferograms showing the extent of the inflated area.

Four fringes are visible in both ascending (left side) and descending (right side) geometries. One fringe corresponds to a line-of-sight (LOS) displacement of approximately 2.8 cm (C-band radar sensor) and therefore 4 fringes correspond to approximately 11 cm of LOS dis-placement.

Extended Data Fig. 3 Geodetic time series and derived displacements.

InSAR ascending (a) and descending (b) line-of-sight (LOS) time-series (points) compared to the LOS projected GNSS data (crosses); (c) vertical displacement obtained by 2D decomposition of the two LOS directions for the total maximum uplift registered on 17/07/2020: red and green lines show the linear interpolation of the single uplift and subsidence episodes, respectively; (d) ascending and descending LOS time-series over the area of the July 18th, 2020, earthquake (M4.1), showing that a new subsidence phase started after the earthquake.

Extended Data Fig. 4 Location of seismic instruments and gravity stations.

Gravity stations are marked with yellow circles (HS10 and 7058 were not measured in January 2020); triangles denote seismic stations of the different seismic networks; the yellow line is the track of the DAS cable. The uplift centres in Svartsengi and Krýsuvík are shown as blue stars. The red lines show eruption fissures from the last eruption episode that ended 1240AD, while the red star marks the 2021 eruption site at Fagradalsfjall. The dashed green line shows the NE-striking magmatic dyke intrusion, drawn according to InSAR analysis and seismicity. Continuous black lines show main roads, and topography is indicated as coloured background.

Extended Data Fig. 5 Free-air gravity and uplift prediction.

a-c) Observed free-air gravity changes during the time intervals between the four successive gravity surveys (diamonds) compared to model predictions (double blue curves, along major and minor axes of the elliptic uplift pattern). Note that a correction for the long-term trend is applied to the data. The trend is estimated to be location-dependent and proportional to the episodic uplift, with the maximum of -5.1 μGal/year. d) Temporal variation of the free-air gravity anomaly (diamonds) averaged from the campaign data of stations HS02 and HS05 in comparison of the model prediction (blue curve) for the uplift centre. The error bars are uniform and given by ±5.0 μGal. The red curve shows the theoretical central uplift.

Source data

Extended Data Fig. 6 New regional earthquake catalogue for the period February 1st to August 30th, 2020.

a) Earthquakes located using the combined network of permanent and temporary seismic stations (yellow triangles) and virtual stations along the DAS cable (yellow triangles in linear arrangement). For overview of earthquakes see a short video of the earthquake sequence. Earthquakes between 0–2 km, 2–4 km, 4–10 km and below 10 km depth are plotted as white, orange, red and blue open circles, respectively. The earthquake swarm events in November and December 2019 are indicated by green and gray-filled circles, respectively. Earthquakes between 20th-22nd January 2020 are plotted as blue-filled circles. The blue NE-SW line refers to the cross-sectional profile of Fig. 4, while the two blue crossing NW-SE lines refer to two cross-sections in b). The black contour lines indicate the shape of the uplift pattern measured in April 2020. The linear source model is indicted as a blue bar. b) Earthquakes within ± 1 km along the two crossing profiles were gridded and are plotted as event density (see Fig. 4 for the corresponding colour legend). The projected uplift profile is plotted above the cross-sections.

Extended Data Fig. 7 A schematic of the multi-layered poroelastic structure model used in this study.

The medium in each poroelastic layer is defined by five parameters: the shear rigidity (μ), the drained and undrained Poisson’s ratio (ν, νu), the Skempton coefficient (B) and the hydraulic diffusivity (D). Based on the assumption that seismic waves propagate under undrained conditions, the seismic reference model SIL45 is adopted to define the elastic parameters μ and νu and their layering in the present poroelastic structure. Outside the thin aquifer layer, which is inserted into the SIL structure at the depth of 4 km, all poroelastic layers have uniform values for parameters ν, B, and D.

Extended Data Fig. 8 Estimation of volume and density of the intruded fluid.

The blue curve shows the density variation given by 6.35·B [103 kg/m3], and the red curve shows the volume variation by 12.9/B [106 m3]. The product of the density and volume is constant and given by 82 Mt. The shadowed range covers 0.08 ≤ B ≤ 0.19 estimated in this study.

Extended Data Fig. 9 Average monthly vertical ground surface velocities at Krýsuvík between August 3rd and November 10th, 2020.

Velocities were estimated by decomposing the line-of-sight signal of the InSAR time-series analysis of Sentinel-1 images from ascending track T16 and descending track T155. Back-ground shows shaded topography and roads (black lines). The centre of uplift is shown by a black star. Similar uplift periods have been reported earlier in other the HT fields in Iceland56.

Supplementary information

Supplementary Information

Supplementary Figs. 1 and 2, Tables 1–4 and Sheets 1–3.

Supplementary Video 1

Video showing time and space evolution of the seismicity.

Source data

Source Data Fig. 2

Numerical data values as plotted on Fig. 2b–d.

Source Data Fig. 3

Numerical data values as plotted on Fig. 3.

Source Data Extended Data Fig. 5

Numerical data values as plotted on the figure.

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Flóvenz, Ó.G., Wang, R., Hersir, G.P. et al. Cyclical geothermal unrest as a precursor to Iceland’s 2021 Fagradalsfjall eruption. Nat. Geosci. 15, 397–404 (2022). https://doi.org/10.1038/s41561-022-00930-5

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