What causes subsidence following the 2011 eruption at Nabro (Eritrea)?

Abstract

A major goal in volcanology is to be able to constrain the physical properties of a volcanic system using surface observations. The behaviour of a volcanic system following an eruption can provide powerful constraints on these properties and can provide valuable information for understanding future hazard. We use spatially and temporally dense observations of surface deformation following the 12 June 2011 eruption of Nabro (Eritrea) to place constraints on the mechanics of its subsurface volcanic system. Nabro was imaged 129 times by TerraSAR-X and COSMO-SkyMed satellites during a 15-month period following the eruption. We have produced a detailed time series of the line-of-sight (LOS) displacements at Nabro, finding that the volcano subsides during the entire observation period at a decaying rate. We found significant atmospheric artefacts remained in the data set after a standard spatio-temporal filter was applied. Applying an empirical correction using a linear phase-elevation relationship removed artefacts but also removed real topographically correlated deformation. Instead, we were able to correct each SAR acquisition using independent delay estimates derived from the ECMWF ERA-Interim (ERA-I) global atmospheric model. The corrected time series can be modelled with the deflation of a Mogi source at ∼ 6.4 ± 0.3 km depth. Modelling the time series using viscoelastic relaxation of a shell which surrounds a spherical magma chamber can explain the observed subsidence without a source of further volume loss if the magma is compressible. CO 2 outgassing is also a possible cause of continued subsidence. Contraction due to cooling and crystallisation, however, is probably minor. If any post-eruptive recharge of the magmatic system at Nabro is occurring, the rate of recharge must be slower than the post-eruptive relaxation processes. Combined with the lack of pre-eruptive inflation, we suggest that recharge of the magmatic system at Nabro either occurs at a rate that is slower than our detection limit, or it occurs episodically. This case study demonstrates the power of long, dense geodetic time series at volcanoes.

Goldilocks conditions required for earthquakes to trigger basaltic eruptions: Evidence from the 2015 Ambrym eruption

“…The observed post-intrusion subsidence may be related to continued drainage of magma into the dike or cooling and contraction of the residual material left in the sill after feeding the dike. Alternative mechanisms, such as viscoelastic relaxation or magma degassing, could also play a role (24). Regardless of the cause, the coincidence between the location of the inferred sill and base of the modeled dike supports the conclusion that the dike was fed from the same shallow reservoir.…”

Explosive Eruptions With Little Warning: Experimental Petrology and Volcano Monitoring Observations From the 2014 Eruption of Kelud, Indonesia

“…Indeed, some preeruptive periods show long‐term changes in deformation, but only a short run‐up of seismic activity (e.g., Okmok, Grimsvotn, and Wolf). Deformation can be caused by a range of volcanic processes including magma movement, degassing and phase changes, and hydrothermal processes (e.g., Biggs et al, ; Ebmeier et al, ; Hamlyn et al, ; Pinel et al, ). Even if deformation can be confidently attributed to magma movement, this is not necessarily a sign of imminent eruption, and more detections of deformation have been made during unrest than can be clearly linked to periods of eruption (e.g., Biggs et al, ; Ebmeier et al, ; Jay et al, ).…”

LiCSBAS: An Open-Source InSAR Time Series Analysis Package Integrated with the LiCSAR Automated Sentinel-1 InSAR Processor

“…This option is also available in LiCSBAS (Step 1-6 explained in Section 2.4.6), but the assumption that noise is uncorrelated in time is not always correct. If the tropospheric delay is correlated in time and/or the deformation is uncorrelated in time, the deformation time series may be poorly recovered [41][42][43]. Furthermore, temporal filtering does not improve the accuracy of the average velocities retrieved from the time series.…”