Hazard assessment at Mount Etna using a hybrid lava flow inundation model and satellite-based land classification

International audienceUsing a lava flow emplacement model and a satellite-based land cover classification, we produce a map to allow assessment of the type and quantity of natural, agricultural and urban land cover at risk from lava flow invasion. The first step is to produce lava effusion rate contours, i.e., lines linking distances down a volcano’s flank that a lava flow will likely extend if fed at a given effusion rate from a predetermined vent zone. This involves first identifying a vent mask and then running a downhill flow path model from the edge of every pixel around the vent mask perimeter to the edge of the DEM. To do this, we run a stochastic model whereby the flow path is projected 1,000 times from every pixel around the vent mask perimeter with random noise being added to the DEM with each run so that a slightly different flow path is generated with each run. The FLOWGO lava flow model is then run down each path, at a series of effusion rates, to determine likely run-out distance for channel-fed flow extending down each path. These results are used to plot effusion rate contours. Finally, effusion rate contours are projected onto a land classification map (produced from an ASTER image of Etna) to assess the type and amount of each land cover class falling within each contour. The resulting maps are designed to provide a quick look-up capability to assess the type of land at risk from lava extending from any location at a range of likely effusion rates. For our first (2,000 m) vent zone case used for Etna, we find a total of area of ~680 km2 is at risk from flows fed at 40 m3 s−1, of which ~6 km2 is urban, ~150 km2 is agriculture and ~270 km2 is grass/woodland. The model can also be run for specific cases, where we find that Etna’s 1669 vent location, if active today, would likely inundate almost 11 km2 of urban land, as well as 15.6 km2 of agricultural land, including 9.5 km2 of olive groves and 5.2 km2 of vineyards and fruit/nut orchards

Best‐fit results from application of a thermo‐rheological model for channelized lava flow to high spatial resolution morphological data

The FLOWGO thermo‐rheological model links heat loss, core cooling, crystallization, rheology and flow dynamics for lava flowing in a channel. We fit this model to laser altimeter (LIDAR) derived channel width data, as well as effusion rate and flow velocity measurements, to produce a best‐fit prediction of thermal and rheological conditions for lava flowing in a ∼1.6 km long channel active on Mt. Etna (Italy) on 16th September 2004. Using, as a starting condition for the model, the mean channel width over the first 100 m (6 m) and a depth of 1 m we obtain an initial velocity and instantaneous effusion rate of 0.3–0.6 m/s and ∼3 m3/s, respectively. This compares with field‐ and LIDAR‐derived values of 0.4 m/s and 1–4 m3/s. The best fit between model‐output and LIDAR‐measured channel widths comes from a hybrid run in which the proximal section of the channel is characterised by poorly insulated flow and the medial‐distal section by well‐insulated flow. This best‐fit model implies that flow conditions evolve down‐channel, where hot crusts on a free flowing channel maximise heat losses across the proximal section, whereas thick, stable, mature crusts of ′a′a clinker reduce heat losses across the medial‐distal section. This results in core cooling per unit distance that decreases from ∼0.02–0.015°C m−1 across the proximal section, to ∼0.005°C m−1 across the medial‐distal section. This produces an increase in core viscosity from ∼3800 Pa s at the vent to ∼8000 Pa s across the distal section

The DEM or Mt. Etna: geomorphological and structural implications

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TINITALY/01: a new Triangular Irregular Network of Italy

A new Digital Elevation Model (DEM) of the natural landforms of Italy is presented. A methodology is discussed to build a DEM over wide areas where elevation data from non-homogeneous (in density and accuracy) input sources are available. The input elevation data include contour lines and spot heights derived from the Italian Regional topographic maps, satellite-based global positioning system points, ground based and radar altimetry data. Owing to the great heterogeneity of the input data density, the DEM format that better preserves the original accuracy is a Triangular Irregular Network (TIN). A Delaunay-based TIN structure is improved by using the DEST algorithm that enhances input data by evaluating inferred break-lines. Accordingly to this approach, biased distributions in slopes and elevations are absent. To prevent discontinuities at the boundary between regions characterized by data with different resolution a cubic Hermite blending weight S-shaped function is adopted. The TIN of Italy consists of 1.39×109 triangles. The average triangle area ranges from 12 to about 13000 m2 accordingly to different morphologies and different sources. About 50% of the model has a local average triangle area <500 m2. The vertical accuracy of the obtained DEM is evaluated by more than 200000 sparse control points. The overall Root Mean Square Error (RMSE) is less than 3.5 m. The obtained national-scale DEM constitutes an useful support to carry out accurate geomorphological and geological investigations over large areas. The problem of choosing the best step size in deriving a grid from a TIN is then discussed and a method to quantify the loss of vertical information is presented as a function of the grid step. Some examples of DEM application are outlined. Under request, an high resolution stereo image database of the whole Italian territory (derived from the presented DEM) is available to browse via internet

The EARTHCRUISERS project (EARTH CRUst Imagery for investigating SEismicity, volcanism and marine natural Resources in the Sicilian offshore)

The EARTHCRUISERS project was developed for the MIUR’s call “Progetti Premiali 2015” by the “Istituto Nazionale di Oceanografia e di Geofisica Sperimentale” (Trieste, Italy) in collaboration with the “Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo” (Catania, Italy) and “Stazione Zoologica Anton Dohrn” (Naples, Italy). The main goals of the project are: (i) to identify and characterize the main crustal tectonic structures offshore Sicily and the Aeolian Islands, (ii) to better understand the geodynamic processes controlling seismicity and volcanism affecting this region, and (iii) to furnish a useful tool to estimate seismic, tsunamigenic and volcanic hazard in the highly populated coastal sectors. Furthermore, in order to contribute at the Blue Growth objectives, the project aims to analyze some relevant issues related to mineral prospecting offshore, such as the characterization of the hydrothermal systems in the Tyrrhenian Sea and the impact of the exploitation of oil and gas fields on the marine environment in the Sicily Channel. To achieve these objectives the acquisition of multibeam and sidescan sonar, multichannel seismic reflection, magnetic and gravimetric data is planned. Nearly 2500 km of multichannel seismic reflection lines will be acquired during the project in the Marsili Basin (Tyrrhenian Sea) and Mt. Etna offshore. This large amount of data will allow to: better understand the relationship between tectonics and evolution of volcanism; identify active faults and volcanic bodies; better constrain the seismostratigraphic and structural setting of the study areas, and investigate the eventual occurrence of unstable volcanic slopes which could lead to landslide and tsunami. Finally, the deployment offshore southeastern Sicily of a temporary Ocean Bottom Seismometer (OBS) network will carry out for monitoring the natural seismicity in the area of VEGA platform, the largest oil extraction site in Italian seas. Data collected will be used to study the eventual correlation between local seismicity and oil extractive activities.PublishedRome2T. Deformazione crostale attiv

Long-Term Outcome and Risk Stratification in Dilated Cardiolaminopathies

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Visualization and comparison of DEM-derived parameters. Application to volcanic areas

Digital Elevation Models (DEMs) are fruitfully used in volcanology as the topographic base for mapping and quantifying volcanic landforms. The increasing availability of free topographic data on the web, decreasing production costs for high-accuracy data and advances in computer technology, has triggered rapid growth of the number of DEM users in the volcanological community. DEMs are often visualized only as hill-shaded maps, and while this is among the major advantages in using them, the possibility of deriving a very large number of parameters froma single grid of elevation datamakes DEMs a powerful tool formorphometric analysis. However, many of these parameters have almost the sameinformative content, and before starting to elaborate topographic data it is recommended to knowa-prioriwhat parameters best visualize the investigated landform, and therefore what is necessary and what is redundant. In thiswork,we reviewa number of analytical procedures used to parameterize and represent DEMs. A LIDAR-derived DEM matrix acquired over the Valle del Bove valley, on Mt. Etna, is used as test-case elevation data for deriving the parameters.Wefirst reviewwell known parameters such as hill-shading, slope and aspect, curvature, and roughness, before extending the review to some less common parameters such as Sky View Factor (SVF), openness, and Red Relief Image Maps (RRIM). For each parameter a description is given emphasizing how it can be used for identifying and delimiting specific volcanic elements. The analyzed surface parameters are then cross-compared in order to infer which of them is most uncorrelated, and the results are represented in the formof a correlation matrix. Finally, the reviewed DEM-derived parameters and the correlationmatrix are used for analyzing the volcanic landforms of two case studies:Michoacán-Guanajuato volcanic field and a phonolitic lava flow at the Island of Tenerife.Published69-845V. Dinamica dei processi eruttivi e post-eruttiviJCR Journa

Numerical simulation of the tsunamis generated by the Sciara del Fuoco landslides (Stromboli Island, Italy)

Stromboli volcano (Aeolian Arc, Italy) experiences many mass failures along the Sciara del Fuoco (SdF) scar, which frequently trigger tsunamis of various sizes. In this work, we simulate tsunami waves generated by landslides occurring in the SdF through numerical simulations carried out in two steps: (i) the tsunami triggering, wave propagation and the effects on Stromboli are simulated using the 3D non-hydrostatic model NHWAVE; (ii) generated train waves are then input into the 2D Boussinesq model FUNWAVE-TVD to simulate wave propagation in the Southern Tyrrhenian Sea (STS). We simulated the following scenarios: (i) the tsunami runup, inland inundation and wave propagation at Stromboli triggered by submarine landslides with volumes of 6, 10, 15 and 20 × 106 m3 and subaerial landslides with volumes of 4, 6, 10 and 30 × 106 m3; (ii) tsunami propagation in the STS triggered by submarine landslides with volumes of 10 and 15 × 106 m3 and by subaerial landslides with volumes of 6 and 30 × 106 m3. We estimate that the damages of the last relevant tsunami at Stromboli, which occurred in 2002, could have been generated either by a subaqueous failure of about 15-20 × 106 m3 along the SdF or/and a subaerial failure of about 4-6 × 106 m3. The coasts most affected by this phenomenon are not necessarily located near the failure, because the bathymetry and topography can dramatically increase the waves heights locally. Tsunami waves are able to reach the first Stromboli populated beaches in just over 1 minute and the harbour in less than 7 minutes. After about 30 minutes the whole Aeolian Arc would be impacted by maximum tsunami waves. After 1 hour and 20 minutes, waves would encompass the whole STS arriving at Capri.Publishedid 185425V. Processi eruttivi e post-eruttivi6V. Pericolosità vulcanica e contributi alla stima del rischioJCR Journa

DOWNFLOW code and LIDAR technology for lava flow analysis and hazard assessment at Mount Etna

The use of a lava-flow simulation (DOWNFLOW) probabilistic code and airborne light detection and ranging (LIDAR) technology are combined to analyze the emplacement of compound lava flow fields at Mount Etna (Sicily, Italy). The goal was to assess the hazard posed by lava flows. The LIDAR-derived time series acquired during the 2006 Mount Etna eruption records the changing topography of an active lava-flow field. These short-time-interval, high-resolution topographic surveys provide a detailed quantitative picture of the topographic changes. The results highlight how the flow field evolves as a number of narrow (5-15 m wide) disjointed flow units that are fed simultaneously by uneven lava pulses that advance within formed channels. These flow units have widely ranging advance velocities (3-90 m/h). Overflows, bifurcations and braiding are also clearly displayed. In such a complex scenario, the suitability of deterministic codes for lava-flow simulation can be hampered by the fundamental difficulty of measuring the flow parameters (e.g. the lava discharge rate, or the lava viscosity of a single flow unit). However, the DOWNFLOW probabilistic code approaches this point statistically and needs no direct knowledge of flow parameters. DOWNFLOW intrinsically accounts for complexities and perturbations of lava flows by randomly varying the pre-eruption topography. This DOWNFLOW code is systematically applied here over Mount Etna, to derive a lava-flow hazard map based on: (i) the topography of the volcano; (ii) the probability density function for vent opening; and (iii) a law for the expected lava-flow length for all of the computational vents considered. Changes in the hazard due to the recent morphological evolution of Mount Etna have also been addressed

Crystal size distributions of plagioclase in lavas from the July–August 2001 Mount Etna eruption

During the 2001 eruption of Mount Etna, two independent vent systems simultaneously erupted two different lavas. The Upper Vents system (UV), opened between 3100 and 2650 m a.s.l., emitted products that are markedly porphyritic and rich in plagioclase, while the Lower Vents system (LV), opened at 2100 and 2550 m a.s.l., emitted products that are sparsely porphyritic with scarce plagioclase. In this study, the crystal size distributions (CSDs) of plagioclase were measured for a series of 14 samples collected from all the main flows of the 2001 eruption. The coefficient of R2 determination was used to evaluate the goodness of fit of linear models to the CSDs, and the results are represented as a grid of R2 values by using a numerical code developed ad hoc. R2 diagrams suggest that the 2001 products can be separated into two main groups with slightly different characteristics: plagioclase CSDs from the UVs can be modeled by three straight lines with different slopes while the plagioclase CSDs from the LVs are largely concave.We have interpreted the CSDs of the UVs as representing three different populations of plagioclases: (i) the large phenocrysts (type I), which started to crystallize at lower cooling rate in a deep reservoir from 13 to 8 months before eruption onset; (ii) the phenocrysts (type II), which crystallized largely during continuous degassing in a shallow reservoir; and (iii) the microlites, which crystallized during magma ascent immediately prior to the eruption. The plagioclase CSD curves for the LVs lava are interpreted to reflect strong and rapid changes in undercooling induced by strong and sudden degassing