Post-eruptive volcano inflation following major magma drainage: Interplay between models of viscoelastic response influence and models of magma inflow at Bárðarbunga caldera, Iceland, 2015-2018

&amp;lt;p&amp;gt;Unrest at B&amp;amp;#225;r&amp;amp;#240;arbunga after a caldera collapse in 2014-2015 includes elevated seismicity beginning about six months after the eruption ended, including nine Mw&amp;gt;4.5 earthquakes. The earthquakes occurred mostly on the northern and southern parts of a caldera ring fault. Global Navigation Satellite System (GNSS, in particular, Global Positioning System; GPS) and Interferometric Synthetic Aperture Radar (InSAR) geodesy are applied to evaluate the spatial and temporal pattern of ground deformation around B&amp;amp;#225;r&amp;amp;#240;arbunga caldera outside the icecap, in 2015-2018, when deformation rates were relatively steady. The aim is to study the role of viscoelastic relaxation following major magma drainage versus renewed magma inflow as an explanation for the ongoing unrest.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The largest horizontal velocity is measured at GPS station KISA (3 km from caldera rim), 141 mm/yr in direction N47&amp;lt;sup&amp;gt;o&amp;lt;/sup&amp;gt;E relative to the Eurasian plate in 2015-2018. GPS and InSAR observations show that the velocities decay rapidly outward from the caldera. We correct our observations for Glacial Isostatic Adjustment and plate spreading to extract the deformation related to volcanic activity. After this correction, some GPS sites show subsidence.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;We use a reference Earth model to initially evaluate the contribution of viscoelastic processes to the observed deformation field. We model the deformation within a half-space composed of a 7-km thick elastic layer on top of a viscoelastic layer with a viscosity of 5 x 10&amp;lt;sup&amp;gt;18&amp;lt;/sup&amp;gt; Pa s, considering two co-eruptive contributors to the viscoelastic relaxation: &amp;amp;#8220;non-piston&amp;amp;#8221; magma withdrawal at 10 km depth (modelled as pressure drop in a spherical source) and caldera collapse (modelled as surface unloading). The other model we test is the magma inflow in an elastic half-space. Both the viscoelastic relaxation and magma inflow create horizontal outward movements around the caldera, and uplift at the surface projection of the source center in 2015-2018. Viscoelastic response due to magma withdrawal results in subsidence in the area outside the icecap. Magma inflow creates rapid surface velocity decay as observed.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;We explore further two parameters in the viscoelastic reference model: the viscosity and the &amp;quot;non-piston&amp;quot; magma withdrawal volume. Our comparison between the corrected InSAR velocities and viscoelastic models suggests a viscosity of 2.6&amp;amp;#215;10&amp;lt;sup&amp;gt;18&amp;lt;/sup&amp;gt; Pa s and 0.36 km&amp;lt;sup&amp;gt;3&amp;lt;/sup&amp;gt; of &amp;amp;#8220;non-piston&amp;amp;#8221; magma withdrawal volume, given by the optimal reduced Chi-squared statistic. When the deformation is explained using only magma inflow into a single spherical source (and no viscoelastic response), the optimal model suggests an inflow rate at 1&amp;amp;#215;10&amp;lt;sup&amp;gt;7&amp;lt;/sup&amp;gt; m&amp;lt;sup&amp;gt;3&amp;lt;/sup&amp;gt;/yr at 700 m depth. A magma inflow model with more model parameters is also a possible explanation, including sill inflation at 10 km together with slip on caldera ring faults. Our reference Earth model and the two end-member models suggest that there is a trade-off between the viscoelastic relaxation and the magma inflow, since they produce similar deformation signals outside the icecap. However, to reproduce details of the observed deformation, both processes are required. A viscoelastic-only model cannot fully explain the fast velocity decay away from the caldera, whereas a magma inflow-only model cannot explain the subsidence observed at several locations.&amp;lt;/p&amp;gt; </jats:p

Global link between deformation and volcanic eruption quantified by satellite imagery

A key challenge for volcanological science and hazard management is that few of the world’s volcanoes are effectively monitored. Satellite imagery covers volcanoes globally throughout their eruptive cycles, independent of ground-based monitoring, providing a multidecadal archive suitable for probabilistic analysis linking deformation with eruption. Here we show that, of the 198 volcanoes systematically observed for the past 18 years, 54 deformed, of which 25 also erupted. For assessing eruption potential, this high proportion of deforming volcanoes that also erupted (46%), together with the proportion of non-deforming volcanoes that did not erupt (94%), jointly represent indicators with ‘strong’ evidential worth. Using a larger catalogue of 540 volcanoes observed for 3 years, we demonstrate how this eruption–deformation relationship is influenced by tectonic, petrological and volcanic factors. Satellite technology is rapidly evolving and routine monitoring of the deformation status of all volcanoes from space is anticipated, meaning probabilistic approaches will increasingly inform hazard decisions and strategic development

Unexpected large eruptions from buoyant magma bodies within viscoelastic crust

Large volume effusive eruptions with relatively minor observed precursory signals are at odds with widely used models to interpret volcano deformation. Here we propose a new modelling framework that resolves this discrepancy by accounting for magma buoyancy, viscoelastic crustal properties, and sustained magma channels. At low magma accumulation rates, the stability of deep magma bodies is governed by the magma-host rock density contrast and the magma body thickness. During eruptions, inelastic processes including magma mush erosion and thermal effects, can form a sustained channel that supports magma flow, driven by the pressure difference between the magma body and surface vents. At failure onset, it may be difficult to forecast the final eruption volume; pressure in a magma body may drop well below the lithostatic load, create under-pressure and initiate a caldera collapse, despite only modest precursors

Icelandic rhythmics : Annual modulation of land elevation and plate spreading by snow load - art. no. L24305

We find strong correlation between seasonal variation in CGPS time series and predicted response to annual snow load in Iceland. The load is modeled using Green's functions for an elastic halfspace and a simple sinusoidal load history on Iceland's four largest ice caps. We derive E = 40 +/- 15 GPa as a minimum value for the effective Young's modulus in Iceland, increasing with distance from the Eastern Volcanic Zone. We calculate the elastic response over all of Iceland to maximum snow load at the ice caps using E = 40 GPa. Predicted annual vertical displacements are largest under the Vatnajokull ice cap with a peak-to-peak seasonal displacement of similar to 37 mm. CGPS stations closest to the ice cap experience a peak-to-peak seasonal displacement of similar to 16 mm, consistent with our model. East and north of Vatnajokull we find the maximum of annual horizontal displacements of similar to 6 mm resulting in apparent modulation of plate spreading rates in this area

InSAR-observed surface deformation in New Mexico’s Permian Basin shows threats and opportunities presented by leaky injection wells

Abstract Knowledge of aquifer dynamics, including groundwater storage changes, is key to effective groundwater resource and reservoir management. Resolving and accurate modeling of these processes requires knowledge of subsurface poroelastic properties and lateral heterogeneity within units of interest. Computationally demanding methods for determining lateral heterogeneity in poroelastic properties exist but remain difficult to practically employ. The InSAR-based detection of uplift over a New Mexico well with a casing breach provides an opportunity to determine poroelastic properties using a tractable 2D analytical plane strain solution for surface uplift created by a pressurized reservoir with overburden. Using a Bayesian inversion framework, we calculate poroelastic properties under deep (depth of well-screen) and shallow (depth of well-breach) conditions. We find that shallow injection is necessary to produce the observed deformation. However, pressure-varying forward solutions for uplift are required to reproduce the temporal evolution of deformation. For this we use realistic shallow poroelastic properties and well dynamics, which reflect the evolving injection conditions at the well breach as the casing further erodes. Analysis of individual interferograms or InSAR time series may provide insights into shallow subsurface heterogeneity or anomalous injection conditions at operating wells more rapidly than scheduled field inspections

Quantifying Large-Scale Surface Change Using SAR Amplitude Images: Crater Morphology Changes During the 2019-2020 Shishaldin Volcano Eruption

Morphological processes often induce meter-scale elevation changes. When a volcano erupts, tracking such processes provides insights into the style and evolution of eruptive activity and related hazards. Compared to optical remote-sensing products, synthetic aperture radar (SAR) observes surface change during inclement weather and at night. Differential SAR interferometry estimates phase change between SAR acquisitions and is commonly applied to quantify deformation. However, large deformation or other coherence loss can limit its use. We develop a new approach applicable when repeated digital elevation models (DEMs) cannot be otherwise retrieved. Assuming an isotropic radar cross-section, we estimate meter-scale vertical morphological change directly from SAR amplitude images via an optimization method that utilizes a high-quality DEM. We verify our implementation through simulation of a collapse feature that we modulate onto topography. We simulate radar effects and recover the simulated collapse. To validate our method, we estimate elevation changes from TerraSAR-X stripmap images for the 2011-2012 eruption of Mount Cleveland. Our results reproduce those from two previous studies; one that used the same dataset, and another based on thermal satellite data. By applying this method to the 2019-2020 eruption of Shishaldin Volcano, Alaska, we generate elevation change time series from dozens of co-registered TerraSAR-X high-resolution spotlight images. Our results quantify previously unresolved cone growth in November 2019, collapses associated with explosions in December-January, and further changes in crater elevations into spring 2020. This method can be used to track meter-scale morphology changes for ongoing eruptions with low latency as SAR imagery becomes available

Quantifying crater morphology changes during the 2019-2020 Shishaldin Volcano eruption using SAR amplitude images

Compared to visual remote-sensing products, Synthetic Aperture Radar (SAR) data have the benefit of observing changes at volcanoes even during inclement weather conditions; InSAR utilizes the phase observations of the radar signal and is commonly applied to quantify volcano deformation and characterize eruptive activity. However, it is not always applicable if the deformation is large or if phase coherence is otherwise lost. Repeat amplitude images provide a way to observe change qualitatively but quantifying these morphological changes from a single look direction would increase our understanding of large-amplitude surface processes such as lava dome growth or collapses. We describe a new method to quantify morphological changes at volcanoes using the amplitude from SAR images with the assumption of an isotropic radar cross section. This method retrieves the gradient of elevation with respect to the radar range coordinates using a linear mapping function between amplitude values and gradient values from a digital elevation model. Integration of this gradient yields elevation values. We employ Bayesian inversions to determine the required integration constants and their confidence intervals required to compute the elevation uncertainties. We apply this method to dozens of coregistered TerraSAR-X spotlight images from both ascending and descending paths that observed the 2019-2020 eruption of Shishaldin Volcano, Unimak Island, Alaska. This eruption was characterized by months of summit scoria cone growth, lava effusion, and cone collapses, producing significant topographic change within the summit crater and ash fall on nearby communities. Our results suggest that the vertical elevation uncertainty of the method is on the order of several meters. Consequently, we were able to quantify cone growth in November 2019, collapses associated with explosions in December-January, and further changes in crater elevations into spring 2020. We conclude that this method detects and quantifies morphological changes on the order of tens of meters in a systematic way that might not be obvious during visual inspection of the imagery alone. The method can be automated to monitor morphological changes due to volcanic unrest in near-real-time as high-quality SAR images become available during an eruption