1,721,026 research outputs found
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
Full text linkThe 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
Runout modelling of gravity-induced pyroclastic density currents at Stromboli volcano (Italy)
No full textGravity-induced pyroclastic density currents (PDCs) at Stromboli volcano were investigated by means numerical and empirical modelling. With the aim of testing the suitability of landslide numerical model DAN- 3D and empirical models are used related to gravity-induced PDCs, in particular this work presents the results of the back analysis of three events occurred on 1906, 1930 and 1944 at Stromboli volcano. These two methods were able to reproduce the extension and the order of magnitude of the thickness of the PDCs reported in the literature. The best results of DAN-3D models were obtained using a Voellmy model with frictional coefficient of f = 0.19 and a turbulence parameter ξ = 1000 m/s. The mobility terms, find with the numerical model, are compared with empirical data of literature of the similar events
Probabilistic evaluation of the physical impact of future tephra fallout events for the Island of Vulcano, Italy
Full text linkA first probabilistic scenario-based hazard assessment for tephra fallout is presented for La Fossa volcano (Vulcano Island, Italy) and subsequently used to assess the impact on the built environment. Eruption scenarios are based upon the stratigraphy produced by the last 1000 years of activity at Vulcano and include long–lasting Vulcanian and sub-Plinian eruptions. A new method is proposed to quantify the evolution through time of the hazard associated with pulsatory Vulcanian eruptions lasting from weeks to years, and the increase in hazard related to typical rainfall events around Sicily is also accounted for. The impact assessment on the roofs is performed by combining a field characterization of the buildings with the composite European vulnerability curves for typical roofing stocks. Results show that a sub-Plinian eruption of VEI 2 is not likely to affect buildings, whereas a sub-Plinian eruption of VEI 3 results in 90 % of the building stock having a ≥12 % probability of collapse. The hazard related to long-lasting Vulcanian eruptions evolves through time, and our analysis shows that the town of Il Piano, located downwind of the preferential wind patterns, is likely to reach critical tephra accumulations for roof collapse 5–9 months after the onset of the eruption. If no cleaning measures are taken, half of the building stock has a probability >20 % of suffering roof collapse
Guidelines on the use of inverse velocity method as a tool for setting alarm thresholds and forecasting landslides and structure collapses
Full text linkPredicting 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
Multi-Temporal Evaluation of Landslide Movements and Impacts on Buildings in San Fratello (Italy) By Means of C-Band and X-Band PSI Data
Full text linkThis work provides a multi-temporal and spatial investigation of landslide effects in the San Fratello area (Messina province within the Sicily region, Italy), by means of C-band and X-band Persistent Scatterer Interferometry (PSI) data, integrated with in situ field checks and a crack pattern survey. The Sicily region is extensively affected by hydrogeological hazards since several landslides regularly involved local areas across time. In particular, intense and catastrophic landslide phenomena have recently occurred in the San Fratello area; the last event took place in February 2010, causing large economic damage. Thus, the need for an accurate ground motions and impacts mapping and monitoring turns out to be significantly effective, in order to better identify active unstable areas and to help proper risk-mitigation measures planning. The combined use of historical and recent C-band satellites and current X-band Synthetic Aperture Radar sensors of a new generation permits spatially and temporally detection of landslide-induced motions on a local scale and to properly provide a complete multi-temporal evaluation of their effects on the area of interest. PSI ground motion rates are cross-compared with local failures and damage of involved buildings, recently recognized by in situ observations. As a result, the analysis of landslide-induced movements over almost 20Â years and the validation of radar data with manufactured crack patterns, permits one to finally achieve a complete and reliable assessment in the San Fratello test site
Shifts in the eruptive styles at Stromboli in 2010-2014 revealed by ground-based InSAR data
Full text linkGround-Based Interferometric Synthetic Aperture Radar (GBInSAR) is an efficient technique for capturing short, subtle episodes of conduit pressurization in open vent volcanoes like Stromboli (Italy), because it can detect very shallow magma storage, which is difficult to identify using other methods. This technique allows the user to choose the optimal radar location for measuring the most significant deformation signal, provides an exceptional geometrical resolution, and allows for continuous monitoring of the deformation. Here, we present and model ground displacements collected at Stromboli by GBInSAR from January 2010 to August 2014. During this period, the volcano experienced several episodes of intense volcanic activity, culminated in the effusive flank eruption of August 2014. Modelling of the deformation allowed us to estimate a source depth of 482 ± 46 m a.s.l. The cumulative volume change was 4.7 ± 2.6 × 10(5) m(3). The strain energy of the source was evaluated 3-5 times higher than the surface energy needed to open the 6-7 August eruptive fissure. The analysis proposed here can help forecast shifts in the eruptive style and especially the onset of flank eruptions at Stromboli and at similar volcanic systems (e.g. Etna, Piton de La Fournaise, Kilauea)
Semi-automatic delimitation of volcanic edifice boundaries: Validation and application to the cinder cones of the Tancitaro–Nueva Italia region (Michoacán–Guanajuato Volcanic Field, Mexico)
Full text linkThe shape and size of monogenetic volcanoes are the result of complex evolutions involving the interaction of eruptive activity, structural setting and degradational processes. Morphological studies of cinder cones aim to evaluate volcanic hazard on the Earth and to decipher the origins of various structures on extraterrestrial planets. Efforts have been dedicated so far to the characterization of the cinder cone morphology in a systematic and comparable manner. However, manual delimitation is time-consuming and influenced by the user subjectivity but, on the other hand, automatic boundary delimitation of volcanic terrains can be affected by irregular topography.
In this work, the semi-automatic delimitation of volcanic edifice boundaries proposed by Grosse et al. (2009) for stratovolcanoes was tested for the first time over monogenetic cinder cones. The method, based on the integration of the DEM-derived slope and curvature maps, is applied here to the Tancitaro–Nueva Italia region of the Michoacán–Guanajuato Volcanic Field (Mexico), where 309 Plio-Quaternary cinder cones are located. The semiautomatic extraction allowed identification of 137 of the 309 cinder cones of the Tancitaro–Nueva Italia region, recognized by means of the manual extraction. This value corresponds to the 44.3% of the total number of cinder cones. Analysis on vent alignments allowed us to identify NE–SW vent alignments and cone elongations, consistent with a NE–SW σmax and a NW–SE σmin. Constructing a vent intensity map, based on computing the number of vents within a radius r centred on each vent of the data set and choosing r = 5 km, four vent intensity maxima were derived: one is positioned in the NW with respect to the Volcano Tancitaro, one in the NE, one to the S and another vent cluster located at the SE boundary of the studied area. The spacing of centroid of each cluster (24 km) can be related to the thickness of the crust (9–10 km) overlying the magma reservoir
Editorial: Flank dynamics, sector collapses, lahars, and rockfalls: analysis, monitoring, and modelling of small to large scale volcanic slope instability
No full textSlope dynamics in volcanic environments comprise a wide spectrum of phenomena, from large lateral collapse to shallow debris remobilization, which may represent a major threat for human communities and infrastructures. Many volcanos built up from the ocean floor and large portions of the volcano edifice are submerged. In these settings, only the edifice's summit can be investigated by terrestrial remote sensing and in-situ approaches. Growth and destruction, including tectonics and gravitational phenomena, affect entire volcano flanks and are not limited to the physical boundary of the sea level but could comprise their subaqueous part
Monitoring high geomorphologic dynamics and slope instability at Stromboli volcano
Full text linkSlope failures of volcanic edifices produce a wide spectrum of instability phenomena, from small rock-falls to
large-scale slope deformation, eventually evolving in rock-slides or debris avalanches With the aim of under-
standing the relationship between geomorphologic evolution and slope instability at Stromboli volcano (Italy),
displacement data from X-band, space-borne, COSMO-SkyMed satellites (CSK-SAR) and a permanent-sited,
Ground Based Interferometric Synthetic Aperture Radar (GBInSAR) device were analysed. To track lithological
and geomorphological changes in space and time, the evolution of reflectivity (amplitude) of CSK-SAR were also
examined.
This study is focussed on Stromboli (Italy) volcano, optimal environmental setting and case history of volcano
slope instability phenomena, since: i) it experienced moderate to major instability events, ii) its slopes are prone to
mass-wasting phenomena, iii) it is affected by persistent volcanic activity that can significantly affect the stability
of slopes, iv) landslides from its flanks could generate tsunamis that could affect areas inhabited, and iv) it is
one of the best studied and, among all, monitored volcanoes on Earth, providing exceptional validation data and
ground-truth constrains.
GBInSAR data were collected every 11 minutes in the period 1 January 2010 – 18 December 2014, whereas the
CSK-SAR images were collected between 22 February 2010 and 18 December 2014. Multi-Temporal InSAR
(MT-InSAR) algorithms were used for both CSK-SAR and GBInSAR datasets.
Backscattered intensity of each CSK-SAR image was transformed in amplitude image and then decibel scaled.
In order to detect and interpret changes in land-cover in correspondence of the SdF slope, two steps were applied
in the employed procedure: i) RGB colour composites, and rationing, ii) texture analysis, using the GLCM (Grey
Level Co-occurrence Matrix) method.
The analysis of the entire dataset cover a period characterized by “normal” Strombolian activity, punctuated by
episodes of “high-intensity activity”, with the occurrence of overflows from the crater terrace toward the Sciara
del Fuoco (SdF), and the 2014 flank eruption. This study highlights that during periods characterized by "normal"
Strombolian activity, the production of materials ejected from the crater terrace to the SdF is generally low, and
erosion is the prevailing process, mainly affecting the central portion of the SdF. GBInSAR apparatus allows for
the identification of very low displacement rates (0.01–0.001 mm/h) related to the creep of the northern sector
of the SdF. After the emplacement of the 2014 lava field, high displacements in the area located between the
central and the northern portions of the SdF were recorded. The lava accumulation on the SdF slope, especially
between its northern and central portions, has favoured the detection of slope instability due to the difference in
the involved material (lava flows and breccia layers vs volcaniclastic loose deposits) below the newly emplaced
lava
Factors Contributing to Volcano Lateral Collapse
No full textMany factors can lead to volcano lateral collapse, which can produce devastating debris avalanches that travel up to several tens to over 100 km and cover hundreds to more than a thousand km2 with debris. Volcanic lateral collapses are severe hazards because of their destructive power and size, and sudden onset. Although their frequency of occurrence is not as high as those of smaller volcanic mass movements, such as rock falls and lahars, globally large collapses ≥0.1 km3 have occurred at least five times per century over the last 500 years. A large variety of destabilizing factors such as over-steepened slopes, magma intrusions, hydrothermal activity, climate fluctuations, deformation of the basement, and faulting can create the conditions for volcano collapse. Once a volcano reaches its critical point, a mechanism is necessary to trigger the failure event. We present the state-of-the-art of the knowledge acquired in the last few decades concerning the causes of large-scale volcanic failures to better understand the triggers, preparatory factors, and timing of volcano lateral collapse.</p
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