Review of ten years of volcano deformations recorded by the ground-based InSAR monitoring system at Stromboli volcano: a tool to mitigate volcano flank dynamics and intense volcanic activity

Traglia, Federico Di; Nolesini, Teresa; Intrieri, Emanuele; Mugnai, Francesco; Leva, D.; Rosi, Mauro; Casagli, Nicola

doi:10.1016/j.earscirev.2014.09.011

Cited by 63 publications

(48 citation statements)

References 115 publications

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“…Toc (Vajont), Voight (1988) found that rates can be suitably (Fig. 10a) are obtained by Bstacking^the interferograms phase using 8-h averaged SAR images, with a measurement accuracy of ±0.5 mm (Antonello et al 2004;Intrieri et al 2013;Di Traglia et al 2014;Di Traglia et al 2015). Interferometric phase can be corrupted by noise (decorrelation), caused by the contribution of scatterers summing up differently among SAR acquisitions and estimated by a calculation of the Bcoherence^between two images (values in the range 0-1).…”

Section: Effect Of Noise On the Reliability Of T F Predictionsmentioning

confidence: 99%

“…Growth stages of this debris talus at Stromboli are a common phenomenon related to the explosive activity, which produces accumulation of volcaniclastic debris around the active craters (Calvari et al 2014). Contrariwise, the roto-translational slides occurred at the onset of the [2002][2003]2007 and 2014 flank eruptions, characterized by magma propagation from the central conduit towards the NEC (Di Traglia et al 2014Traglia et al , 2015. The debris talus is composed by loose volcaniclastic material, prevalently breccias alternating with tuff, lapillistones and thin (<2-3 m) lava flows (Apuani et al 2005).…”

Section: Stromboli Debris Talus Roto-translational Slidementioning

confidence: 99%

“…The debris talus is composed by loose volcaniclastic material, prevalently breccias alternating with tuff, lapillistones and thin (<2-3 m) lava flows (Apuani et al 2005). The NEC area has been continuously monitored by a Ground-Based Interferometric Synthetic Aperture Radar (GBInSAR) system (Di Traglia et al 2014, Fig. 9).…”

Section: Stromboli Debris Talus Roto-translational Slidementioning

confidence: 99%

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Guidelines on the use of inverse velocity method as a tool for setting alarm thresholds and forecasting landslides and structure collapses

et al. 2016

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Predicting the time of failure is a topic of major concern in the field of geological risk management. Several approaches, based on the analysis of displacement monitoring data, have been proposed in recent years to deal with the issue. Among these, the inverse velocity method surely demonstrated its effectiveness in anticipating the time of collapse of rock slopes displaying accelerating trends of deformation rate. However, inferring suitable linear trend lines and deducing reliable failure predictions from inverse velocity plots are processes that may be hampered by the noise present in the measurements; data smoothing is therefore a very important phase of inverse velocity analyses. In this study, different filters are tested on velocity time series from four case studies of geomechanical failure in order to improve, in retrospect, the reliability of failure predictions: Specifically, three major landslides and the collapse of an historical city wall in Italy have been examined. The effects of noise on the interpretation of inverse velocity graphs are also assessed. General guidelines to conveniently perform data smoothing, in relation to the specific characteristics of the acceleration phase, are deduced. Finally, with the aim of improving the practical use of the method and supporting the definition of emergency response plans, some standard procedures to automatically setup failure alarm levels are proposed. The thresholds which separate the alarm levels would be established without needing a long period of neither reference historical data nor calibration on past failure events.

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Section: Effect Of Noise On the Reliability Of T F Predictionsmentioning

confidence: 99%

Section: Stromboli Debris Talus Roto-translational Slidementioning

confidence: 99%

Section: Stromboli Debris Talus Roto-translational Slidementioning

confidence: 99%

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Guidelines on the use of inverse velocity method as a tool for setting alarm thresholds and forecasting landslides and structure collapses

et al. 2016

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“…On average, during the background activity, the explosions occur at a rate of \10 events/hour, shifting to a rate of [14 events/hour during unrests (measured by thermal cameras, Calvari et al 2014). This shift is commonly associated with changes in the features of the erupted products Houghton 2005, 2007;D'Oriano et al 2011) and in the parameters monitored by the geophysical (Casagli et al 2007;Ripepe et al 2009;Calvari et al 2014;Coppola et al 2012;Di Traglia et al 2014b) and geochemical monitoring network (Aiuppa et al 2009(Aiuppa et al , 2011Inguaggiato et al 2011). Modeling ground displacements collected at Stromboli by the GBInSAR from January 2010 to August 2014 revealed a deformation source at 482 ± 46 m a.s.l.…”

Section: Geological and Volcanological Backgroundmentioning

confidence: 99%

“…The data were acquired using the Leica ADS80 sensor, whose instrumental vertical and horizontal accuracy is ±10/20 and ±25 cm, respectively. Map was generated using ESRI platform Nat Hazards (2016) 84:669-683 671 Planar deep creep occurs in fact on long slopes when the strata dip parallel to the slope (Intrieri et al 2013a;Di Traglia et al 2014b). Unrests at Stromboli are characterized by changes in the background activity of the volcano in terms of frequency and intensity of the Strombolian explosions.…”

Section: Geological and Volcanological Backgroundmentioning

confidence: 99%

A statistical-based approach for determining the intensity of unrest phases at Stromboli volcano (Southern Italy) using one-step-ahead forecasts of displacement time series

2016

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The evaluation of the intensity of unrest phases at active volcanoes is a crucial topic in volcano hazard studies. This is particularly troublesome in the case of persistently active volcanoes like Stromboli (Southern Italy), where intense eruptive summit activity (overflows, strong spattering, powerful explosions) has in some cases anticipated a flank eruption. In this context, a new approach for the analysis of displacement data is introduced. Daily displacements of the Stromboli crater terrace measured between January 1, 2010, and August 7, 2014, by a ground-based interferometric synthetic aperture radar system were compared, in retrospect, to displacement predictions provided by an autoregressive integrated moving average-based model. The methodology consisted in assessing when the actual displacements exceeded a fixed probability threshold for the forecasts (*95 %). Two sets of data were consequently produced: (1) series of residuals between actual displacements and model threshold (''anomalies'') and (2) series of normalized residuals between actual displacements and model threshold (''normalized anomalies''). This permitted to statistically identify and quantify the anomalous deformation at the crater terrace over the reference time interval of the analysis. Anomalies started to occur before each period of intense volcanic activity, highlighting the possibility to discern between background activity and unrest. Moreover, results indicated that the inflation of the crater terrace during the preparatory phase of the 2014 flank eruption was characterized by the greatest amount of anomalous deformation.

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Inversion of coeval shear and normal stress of Piton de la Fournaise flank displacement

et al. 2016

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The April 2007 eruption of Piton de la Fournaise was the biggest volcano eruptive crisis of the 20th and 21st centuries. Interferometric synthetic aperture radar (InSAR) captured a large coeruptive seaward displacement on the volcano's eastern flank, which continued for more than a year at a decreasing rate. Coeruptive uplift and posteruptive subsidence were also observed. While it is generally agreed that flank displacement is induced by fault slip, we suggest that this flank displacement might have been induced by a sheared sill, based on observations of sheared sills at Piton des Neiges. To test this hypothesis, we develop a new method to invert a quadrangular curved source submitted to simultaneous pressure and shear stress changes. This method, based on boundary elements, is applied to data acquired along six Envisat orbits covering a 14 month period subsequent to the April 2007 eruption. Posteruptive displacement is well explained by closure and slip of a large (5 km by 8 km) and shallow (500 m) trapezoidal fracture parallel to the flank and probably coincident with a lithological discontinuity. We investigate whether thermal contraction or degassing of a coeruptive sill can explain the displacement. Such a sill would have to be 10 times thicker than inferred from the coeruptive uplift and solidification time 10 times shorter (~20 days) than the duration of the posteruptive subsidence (24 to 33 months). Instead, we propose that the posteruptive eastern flank displacement is due to the compaction and ongoing slow slip on a shallow detachment fault.

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Review of ten years of volcano deformations recorded by the ground-based InSAR monitoring system at Stromboli volcano: a tool to mitigate volcano flank dynamics and intense volcanic activity

Cited by 63 publications

References 115 publications

Guidelines on the use of inverse velocity method as a tool for setting alarm thresholds and forecasting landslides and structure collapses

Guidelines on the use of inverse velocity method as a tool for setting alarm thresholds and forecasting landslides and structure collapses

A statistical-based approach for determining the intensity of unrest phases at Stromboli volcano (Southern Italy) using one-step-ahead forecasts of displacement time series

Inversion of coeval shear and normal stress of Piton de la Fournaise flank displacement

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