Understanding the drivers of volcano deformation through geodetic model verification and validation

Crozier, Josh; Karlstrom, Leif; Montgomery-Brown, Emily; Angarita, Mario; Cayol, Valérie; Bato, Mary Grace; Wang, Taiyi A.; Grapenthin, Ronni; Shreve, Tara; Anderson, Kyle; Astort, Ana; Bodart, Olivier; Cannavò, Flavio; Currenti, Gilda; Dabaghi, Farshid; Erickson, Brittany A.; Garg, Deepak; Head, Matthew; Iozzia, Adriana; Kim, Young Cheol; Le Mével, Hélène; Novoa Lizama, Camila; Rucker, Cody; Silverii, Francesca; Trasatti, Elisa; Zhan, Yan

doi:10.1007/s00445-023-01687-4

Cited by 5 publications

(7 citation statements)

References 80 publications

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“…The framework also allows inversion using multiple data types at the same time with multiple inversion algorithms. Crozier et al (2023) showed a surprising dependency of model results on the chosen inversion methodology, which makes straightforward change or addition of inversion strategies an important feature of frameworks like VSM (Trasatti, 2022) and VMOD.…”

Section: Discussionmentioning

confidence: 99%

“…For instance, include implementations for ring fault models and regularized sills/faults composed of smaller rectangular dislocation models. We benchmarked our forward and inverse modeling framework by replicating published results and as a part of a community volcano deformation model verification exercise (Battaglia et al, 2013a;Crozier et al, 2023;Segall, 2010). We use the framework to simultaneously characterize two deformation sources at Unimak Island for Westdahl volcano and Fisher Caldera using InSAR data, and continuous and campaign GNSS data, including observations from a new campaign at Fisher Caldera.…”

Section: Discussionmentioning

confidence: 99%

“…However, this has been only validated for vertical displacements using the Mogi (1958) and McTigue (1987) models. This is also not advisable for near field solutions (Crozier et al, 2023).…”

Section: Source Modelsmentioning

confidence: 99%

“…To validate our implementations of the analytical models we test them against well-proven published implementations and reproduce characteristic figures from the literature (Figures S4 and S5 in Supporting Information S1). We also participated in the Drivers of Volcano Deformation (DVD) community exercise (Crozier et al, 2023), the purpose of which was to verify and validate geodetic model implementations (Figure S6 in Supporting Information S1).…”

Section: Source Modelsmentioning

confidence: 99%

“…The drawbacks of simplified models are well known (e.g., Masterlark, 2003Masterlark, , 2007. For instance, the analytical models do not account for heterogeneity in the crust (Albright & Gregg, 2020;Heap et al, 2020) or topography (Crozier et al, 2023). However, the continued use of these models, especially in monitoring settings, is driven by the scarcity of (time-varying) observations, poor a-priori information on the host rock properties, model uniqueness issues, and the increased computational resources required by more complex models.…”

Section: Introductionmentioning

confidence: 99%

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Versatile Modeling Of Deformation (VMOD) Inversion Framework: Application to 20 Years of Observations at Westdahl Volcano and Fisher Caldera, Alaska, US

Angarita,

Grapenthin,

Henderson

et al. 2024

Geochem Geophys Geosyst

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We developed an open source, extensible Python‐based framework, that we call the Versatile Modeling Of Deformation (VMOD), for forward and inverse modeling of crustal deformation sources. VMOD abstracts from specific source model implementations, data types and inversion methods. We implement the most common geodetic source models which can be combined to model and analyze multi‐source deformation. VMOD supports Global Navigation Satellite System (GNSS), InSAR, electronic distance measurement, Leveling and tilt data. To infer source characteristics from observations, VMOD implements non‐linear least squares and Markov Chain Monte‐Carlo Bayesian inversions, including joint inversions using different sources of data. VMOD's structure allows for easy integration of new geodetic models, data types, and inversion strategies. We benchmark the forward models against other published results and the inversion approaches against other implementations. We apply VMOD to analyze deformation at Unimak Island, Alaska, observed with continuous and campaign GNSS, and ascending and descending InSAR time series generated from Sentinel‐1 satellite radar acquisitions. These data show an inflation pattern at Westdahl volcano and subsidence at Fisher Caldera. We use VMOD to test a range of source models by jointly inverting the GNSS and InSAR data sets. Our final model simultaneously constrains the parameters of two sources. Our results reveal a depressurizing spheroid under Fisher Caldera ∼4–6 km deep, contracting at a rate of ∼2–3 Mm3/yr, and a pressurizing spherical source underneath Westdahl volcano ∼6–8 km deep, inflating at ∼5 Mm3/yr. This and past applications of VMOD to volcanic unrest benefit from an extensible framework which supports jointly inversions of data sets for parameters of easily composable multi‐source models.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Source Modelsmentioning

confidence: 99%

Section: Source Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Versatile Modeling Of Deformation (VMOD) Inversion Framework: Application to 20 Years of Observations at Westdahl Volcano and Fisher Caldera, Alaska, US

Angarita,

Grapenthin,

Henderson

et al. 2024

Geochem Geophys Geosyst

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4D imaging of the volcano feeding system beneath the urban area of the Campi Flegrei caldera

Tizzani,

Fernández,

Vitale

et al. 2024

Remote Sensing of Environment

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Inversions of Surface Displacements in Scaled Experiments of Analog Magma Intrusion

Poppe,

Wauthier,

Fontijn

2024

Geophysical Research Letters

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Standard geodetic models simplify magma sheet injection to the opening of geometrically simple dislocations in a linearly elastic, homogeneous medium. Intrusion geometries are often complex, however, and non‐elastic deformation mechanisms can dominate the response of heterogeneous rocks to magma‐induced stresses. We used three‐dimensional near‐surface displacements of a scaled laboratory experiment in which a steeply inclined analog magma sheet was injected into granular material. We ran forward models and inverted for eight parameters of an “Okada‐type” tensile rectangular dislocation in a homogeneous, isotropic, and linearly elastic half‐space. Displacements generated by a forward model largely mismatch the experimental displacements, but full or restricted non‐linear inversions of geometrical parameters reduce the residual displacements. The intrusion opening, dip, depth, and to a lesser degree length and width mismatch the most between the experiment and inversion results, whereas location and strike mismatch the least. Our results challenge assumptions made by many analytical and geodetic models.

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Understanding the drivers of volcano deformation through geodetic model verification and validation

Cited by 5 publications

References 80 publications

Versatile Modeling Of Deformation (VMOD) Inversion Framework: Application to 20 Years of Observations at Westdahl Volcano and Fisher Caldera, Alaska, US

Versatile Modeling Of Deformation (VMOD) Inversion Framework: Application to 20 Years of Observations at Westdahl Volcano and Fisher Caldera, Alaska, US

4D imaging of the volcano feeding system beneath the urban area of the Campi Flegrei caldera

Inversions of Surface Displacements in Scaled Experiments of Analog Magma Intrusion

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