Spatial probability distribution of future volcanic eruptions at El Hierro Island (Canary Islands, Spain)

Becerril, Laura; Cappello, Annalisa; Galindo, Inés; Neri, Marco; Negro, Ciro Del

doi:10.1016/j.jvolgeores.2013.03.005

Cited by 68 publications

(71 citation statements)

References 33 publications

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“…This is an essential concept when dealing with volcano monitoring and eruption forecasting. Most volcanic models or methods that have been developed (Connor, 1990;Connor et al, 1992Ho, 1992Ho, , 1995Martin et al, 1994;Ho and Smith, 1998;Alberico et al, 2002;Martí and Felpeto, 2010;Cappello et al, 2012;Selva et al, 2012;Bartolini et al, 2013;Becerril et al, 2013a;Bevilacqua et al, 2015) consider the observable tectonic structures (eruptive fissures, joints, faults, dykes, sills, lineations, vent location) as indicators of paleostresses, so when they are combined with the age at which they formed we can obtain a picture of the stress evolution with time at surface. In this sense, the youngest structures will indicate the most recent stress configuration, and will define the areas with higher probabilities of hosting new vents.…”

Section: Discussionmentioning

confidence: 99%

“…While in central volcanoes it is generally assumed that future eruptions will occur through the same vents that have been active in the past, in monogenetic systems forecasting the position of new vents is much more challenging due to this lack of a permanent shallow stress configuration. Spatial analysis addressed to infer the location of future vents (volcanic susceptibility, see Martí and Felpeto, 2010) in monogenetic volcanism generally assumes that the next eruption will occur close to the location of the previous ones (Connor, 1990;Connor et al, 1992Ho, 1992Ho, , 1995Martin et al, 1994;Ho and Smith, 1998;Alberico et al, 2002;Martí and Felpeto, 2010;Bebbington and Cronin, 2011;Cappello et al, 2012;Selva et al, 2012;Bartolini et al, 2013;Becerril et al, 2013a;Le Corvec et al, 2013a;Bevilacqua et al, 2015). The reason to make this assumption is based on the fact that in last eruptive episodes volcanoes had formed near previous ones (forming a cluster), so we assume that this behavior will continue.…”

Section: Introductionmentioning

confidence: 99%

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Stress Controls of Monogenetic Volcanism: A Review

et al. 2016

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The factors controlling the preparation of volcanic eruptions in monogenetic fields are still poorly understood. The fact that in monogenetic volcanism each eruption has a different vent suggests that volcanic susceptibility has a high degree of randomness, so that accurate forecasting is subjected to a very high uncertainty. Recent studies on monogenetic volcanism reveal how sensitive magma migration is to the existence of changes in the stress field caused by regional and/or local tectonics or rheological contrasts (stratigraphic discontinuities). These stress variations may induce changes in the pattern of further movements of magma, thus conditioning the location of future eruptions. This implies that a precise knowledge of the stress configuration and distribution of rheological and structural discontinuities at crustal level of such volcanic systems would aid in forecasting monogenetic volcanism. This contribution reviews several basic concepts relative to the stress controls of magma transport into the brittle lithosphere, and uses this information to explain how magma migrates inside monogenetic volcanic systems and how it prepares to trigger a new eruption.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Stress Controls of Monogenetic Volcanism: A Review

et al. 2016

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“…The PDFs were obtained for each type of structural data with the method of the least square cross validation method (LSCV; Bartolini et al 2013;Becerril et al 2013) to obtain the bandwidth parameter, as it was the best method to represent the distribution of analysed data, and Fig. 3 a Workflow adopted in this study.…”

Section: Volcanic Susceptibilitymentioning

confidence: 99%

Susceptibility of intrusion-related landslides at volcanic islands: the Stromboli case study

et al. 2017

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Susceptibility of intrusion-related landslides in an active volcano was evaluated coupling the landslide susceptibility estimation by random forest (RF), and the probabilistic volcanic vent opening distribution, as proxy for magma injection, using the QVAST tool. In order to develop and test the method proposed here, the RF/QVAST approach was adopted for Stromboli volcano (Southern Italy) since it experienced moderate to huge instability events, it is geomorphologically prone to instability events, and it is affected by active intense volcanic activity that can produce slope instability. The main destabilizing factors of the volcanic flanks are the slope, the aspect, the terrain roughness, the land cover and the litho-technical features of the outcropping rocks. Estimation of volcanic susceptibility shows that the areas with high probability of new vent opening are located in the north-western unstable volcano flank (Sciara del Fuoco), in the volcano summit and the north-eastern volcano flank coherent with the possible reactivation of the eruptive fissures related to the regional tectonic setting. The areas with higher probability of intrusion-related landslides are located in the upper part of the Sciara del Fuoco, while the rest of the island show moderate to low probability of intrusion-related landslide occurrence.

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“…Lutz and Gutmann (1995) discounted any distal vents deemed to be located at the edges of the Pinacate volcanic field when performing lineament analysis using a circular region. For island-based distributed volcanism (Jeju, Brenna et al 2012; Ambae Island, Vanuatu, Németh and Cronin 2009), offshore eruptions are often discounted when forming a volcanic field boundary for spatial intensity estimation (Tenerife, Martí et al 2009;El Hierro, Canaries, Melían et al 2014), although they were included in work by Becerril et al (2013). This may considerably underestimate the hazard, especially where magma-water interaction may cause the most explosive eruptions from such fields (Németh and Cronin 2009).…”

Section: Anomalous Ventsmentioning

confidence: 99%

Sensitivity to volcanic field boundary

et al. 2015

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Volcanic hazard analyses are desirable where there is potential for future volcanic activity to affect a proximal population. This is frequently the case for volcanic fields (regions of distributed volcanism) where low eruption rates, fertile soil, and attractive landscapes draw populations to live close by. Forecasting future activity in volcanic fields almost invariably uses spatial or spatio-temporal point processes with model selection and development based on exploratory analyses of previous eruption data. For identifiability reasons, spatio-temporal processes, and practically also spatial processes, the definition of a spatial region is required to which volcanism is confined. However, due to the complex and predominantly unknown sub-surface processes driving volcanic eruptions, definition of a region based solely on geological information is currently impossible. Thus, the current approach is to fit a shape to the known previous eruption sites. The class of boundary shape is an unavoidable subjective decision taken by the forecaster that is often overlooked during subsequent analysis of results. This study shows the substantial effect that this choice may have on even the simplest exploratory methods for hazard forecasting, illustrated using four commonly used exploratory statistical methods and two very different regions: the Auckland Volcanic Field, New Zealand, and Harrat Rahat, Kingdom of Saudi Arabia. For Harrat Rahat, sensitivity of results to boundary definition is substantial. For the Auckland Volcanic Field, the range of options resulted in similar shapes, nevertheless, some of the statistical tests still showed substantial variation in results. This work highlights the fact that when carrying out any hazard analysis on volcanic fields, it is vital to specify how the volcanic field boundary has been defined, assess the sensitivity of boundary choice, and to carry these assumptions and related uncertainties through to estimates of future activity and hazard analyses.

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Spatial probability distribution of future volcanic eruptions at El Hierro Island (Canary Islands, Spain)

Cited by 68 publications

References 33 publications

Stress Controls of Monogenetic Volcanism: A Review

Stress Controls of Monogenetic Volcanism: A Review

Susceptibility of intrusion-related landslides at volcanic islands: the Stromboli case study

Sensitivity to volcanic field boundary

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