Imaging and modeling crater floor subsidence at Nyiragongo Volcano, DRC
Abstract Localized crater deformation can shed insight into shallow magma processes and eruption hazards. To study localized crater deformation at Nyiragongo volcano (Democratic Republic of Congo), we processed Interferometric Synthetic Aperture Radar (InSAR) time series using RADARSAT-2 ultra-fine satellite data spanning 2012–2019. We observed persistent crater floor subsidence during August 2013-December 2015 and inverted the corresponding InSAR displacements to model candidate deformation sources with analytic solutions in a homogeneous elastic half-space. We identified a deflating source modeled as a sill at ~ 100 m depth beneath the crater surface, which we interpreted to be the cooling of magma accumulated in the crater. This observation was possible thanks to a quiescent period in 2013–2015 during which the lava lake did not overflow the bottom of the crater. Our study demonstrates the capabilities of imaging localized deformation patterns using high spatial resolution SAR data.
Authors
- Benoît Smets (ORCID: https://orcid.org/0000-0002-1044-8314)
- C. Wauthier (ORCID: https://orcid.org/0000-0002-3767-8080)
- Julien Barrière (ORCID: https://orcid.org/0000-0002-0948-2945)
- Sergey Samsonov
- Arthur Wan Ki Lo
- Nicolas d’Oreye
Institutions
- Natural Resources Canada (CA)
- Royal Museum for Central Africa (BE)
- Pennsylvania State University (US)
- Vrije Universiteit Brussel (BE)
- European Center for Geodynamics and Seismology (LU)
- Musée national d'histoire naturelle Luxembourg (LU)
Publication Details
- Journal
- Bulletin of Volcanology
- Published
- 2026-09-05
- DOI
- https://doi.org/10.1007/s00445-026-02041-0
- Primary Topic
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation
- University of Pennsylvania
- Pennsylvania State University
- Fonds National de la Recherche Luxembourg
- Belgian Federal Science Policy Office
- Institute for Computational and Data Sciences, Pennsylvania State University
- Canadian Space Agency