Separating Magmatic and Hydrothermal Deformation Using InSAR Timeseries: Independent Component Analysis at Corbetti Caldera, Ethiopia

Abstract The cause of unrest at large quaternary silicic calderas, specifically whether the source is magmatic or hydrothermal, has critical implications for the potential eruptive hazard and is debated, even at well‐studied systems. Recent advances in Interferometric Synthetic Aperture Radar (InSAR), driven by the Sentinel‐1 mission, allow us to examine the spatial and temporal patterns of deformation in unprecedented detail. Here, we apply spatial Independent Component Analysis (sICA) to separate the contribution of magmatic and hydrothermal processes to deformation based on their distinct spatial and temporal characteristics. We use Corbetti Caldera, Ethiopia as an example. The hydrothermal system here is known to be laterally bound by a major rift‐perpendicular structure, which means deformation associated with the hydrothermal system has a distinctly different spatial pattern to that of the underlying magmatic source. The sICA is able to separate two spatially distinct deformation signals associated with (a) the shallow magmatic system with constant uplift at a rate of 5.1 cm/yr in the satellite line‐of‐sight and (b) a laterally bound hydrothermal system that includes a strong seasonal signal with a magnitude of 0.65 cm. Although a magmatic source modeled using a Mogi point source fits the original data well, a two‐source inversion improves the model quality. As debates regarding the source of unrest at silicic systems continue, we demonstrated the potential of new data sets and machine learning techniques to isolate contributions of magmatic and non‐magmatic processed to surface deformation when they have distinct spatial and temporal patterns, which can have important implications for interpretation and consequently hazard forecasts.

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Publication Details

Journal
Journal of Geophysical Research Solid Earth
Published
2025-03-28
DOI
https://doi.org/10.1029/2024jb030974
Citations
5
Primary Topic
Earthquake Detection and Analysis
Type
article
Field-Weighted Citation Impact
9.33

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article

Separating Magmatic and Hydrothermal Deformation Using InSAR Timeseries: Independent Component Analysis at Corbetti Caldera, Ethiopia

Edna W. Dualeh, Juliet Biggs
5 citations
Journal of Geophysical Research Solid Earth
Earthquake Detection and Analysis
9.33
article

Separating Magmatic and Hydrothermal Deformation Using InSAR Timeseries: Independent Component Analysis at Corbetti Caldera, Ethiopia

Edna W. Dualeh, Juliet Biggs
article en
5 citations

Abstract

Abstract The cause of unrest at large quaternary silicic calderas, specifically whether the source is magmatic or hydrothermal, has critical implications for the potential eruptive hazard and is debated, even at well‐studied systems. Recent advances in Interferometric Synthetic Aperture Radar (InSAR), driven by the Sentinel‐1 mission, allow us to examine the spatial and temporal patterns of deformation in unprecedented detail. Here, we apply spatial Independent Component Analysis (sICA) to separate the contribution of magmatic and hydrothermal processes to deformation based on their distinct spatial and temporal characteristics. We use Corbetti Caldera, Ethiopia as an example. The hydrothermal system here is known to be laterally bound by a major rift‐perpendicular structure, which means deformation associated with the hydrothermal system has a distinctly different spatial pattern to that of the underlying magmatic source. The sICA is able to separate two spatially distinct deformation signals associated with (a) the shallow magmatic system with constant uplift at a rate of 5.1 cm/yr in the satellite line‐of‐sight and (b) a laterally bound hydrothermal system that includes a strong seasonal signal with a magnitude of 0.65 cm. Although a magmatic source modeled using a Mogi point source fits the original data well, a two‐source inversion improves the model quality. As debates regarding the source of unrest at silicic systems continue, we demonstrated the potential of new data sets and machine learning techniques to isolate contributions of magmatic and non‐magmatic processed to surface deformation when they have distinct spatial and temporal patterns, which can have important implications for interpretation and consequently hazard forecasts.

Journal of Geophysical Research Solid EarthVol. 130(4)
University of Bristol (GB), Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics (GB)
Natural Environment Research Council, European Research Council
Openalex Percentile: Top 2%
Earthquake Detection and Analysis
9.33
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