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Geyer A.,University of Bristol | Marti J.,CSIC - Institute of Earth Sciences Jaume Almera
Tectonophysics | Year: 2010

One of the most characteristic features of volcanic islands is the existence of rift zones defined commonly as orientated eruptive fissures or parallel rows of elongate cinder cones and dyke swarms. Occasionally, these rifts can appear at the birth of the volcanic island and persist until the last episodes of its constructions, controlling the form and structure of the island (e.g. Azores Islands). In the case of Tenerife (Canary Islands), it is possible to observe two rift zones (Santiago del Teide and Dorsal rifts) running NW-SE and ENE-WSW, marked by parallel rows of aligned cones and eruptive fissures. Additionally, at the southern part of the island (Southern Volcanic Zone) basaltic volcanism is characterized by scattered vents and apparently non-coherently orientated eruptive fissures. Some authors relate the existence of the latter volcanism to a N-S running rift zone that defines the third branch of a three-armed rift system in the island. In the present paper, we first investigate the tectonic controls on the distribution of basaltic volcanism at the Southern Volcanic Zone, and their relation with the NW-SE and ENE-WSW rifts. The numerical results obtained suggest that basaltic volcanism of the southern part of Tenerife can be easily explained as the result of a extensional stress field derived from the combined effects of the NW-SE and ENE-WSW rifts. As a second objective, we have also investigated the origin of the Santiago del Teide and Dorsal rift zones and their role on the formation of the original shield volcano and the subsequent evolution of the whole island. Our numerical results contrast with previously published explanations on the origin of the Tenerife rifts that included fracturing due to volcano spreading or to deformation of the volcano due to magma intrusion. We consider that volcanic activity in Tenerife began throughout fissural volcanism along these structures that were already present in the oceanic basement, progressively accumulating the basaltic series that gave rise to the construction of the composite shield volcano. © 2009 Elsevier B.V. All rights reserved. Source


Marti J.,CSIC - Institute of Earth Sciences Jaume Almera | Felpeto A.,Instituto Geografico Nacional
Journal of Volcanology and Geothermal Research | Year: 2010

A new method to calculate volcanic susceptibility, i.e. the spatial probability of vent opening, is presented. Determination of volcanic susceptibility should constitute the first step in the elaboration of volcanic hazard maps of active volcanic fields. Our method considers different criteria as possible indicators for the location of future vents, based on the assumption that these locations should correspond to the surface expressions of the most likely pathways for magma ascent. Thus, two groups of criteria have been considered depending on the time scale (short or long term) of our approach. The first one accounts for long-term hazard assessment and corresponds to structural criteria that provide direct information on the internal structure of the volcanic field, including its past and present stress field, location of structural lineations (fractures and dikes), and location of past eruptions. The second group of criteria concerns to the computation of susceptibility for short term analyses (from days to a few months) during unrest episodes, and includes those structural and dynamical aspects that can be inferred from volcano monitoring. Thus, a specific layer of information is obtained for each of the criteria used. The specific weight of each criterion on the overall analysis depends on its relative significance to indicate pathways for magma ascent, on the quality of data and on their degree of confidence. The combination of the different data layers allows to create a map of the spatial probability of future eruptions based on objective criteria, thus constituting the first step to obtain the corresponding volcanic hazards map. The method has been used to calculate long-term volcanic susceptibility on Tenerife (Canary Islands), and the results obtained are also presented. © 2010 Elsevier B.V. Source


Mouthereau F.,CNRS Institute of Earth Sciences | Lacombe O.,CNRS Institute of Earth Sciences | Verges J.,CSIC - Institute of Earth Sciences Jaume Almera
Tectonophysics | Year: 2012

The Zagros Mountains are the result of the Arabia/Eurasia collision initiated at ~. 35. Ma as the rifted Arabian lithosphere was underthrusted beneath the Iranian plate due to its negative buoyancy. The onset of crustal thickening started at ~. 25. Ma, as recorded by the hinterland exhumation and foreland clastic deposition. Deformation throughout the Arabia/Eurasia collision zone and the uplift of the Iranian plateau occurred after 15-12. Ma, as a result of shortening/thickening of the thin Iranian crust. We emphasize that only 42% of the post-35. Ma convergence is partitioned by shortening within central Iran. Tomographic constraints show ongoing slab steepening or breakoff in the NW Zagros, whereas underthrusting of the Arabian plate is observed beneath central Zagros. The current subduction dynamics can be explained by the original lateral difference in the buoyancy of the distal margin that promoted slab sinking in NW Zagros and underthrusting in central Zagros. Critical wedge approach applied to the Zagros favors the hypothesis of strong brittle crust detached above a viscous lower crust. In contrast, the weak sedimentary cover deforms by buckling of a thick multilayered cover. Thrust faulting associated with folding occurs in the competent layers and is responsible for most of the earthquakes. There is evidence that the role of the slab pull force in driving the Arabian plate motion was reduced after ~. 12. Ma. Large-scale mantle flow induced by mantle upwelling at the Afar plume appears to be the main driver of the Arabia plate motion. We stress that the main kinematic change in the Zagros region occurred at 15-12. Ma as the Zagros uplifted, before the Arabian slab detached. The Zagros appears key to investigate coupling between continental rheology, plate driving forces and mountain building, in which the role of rift inheritance appears to be central. © 2012 Elsevier B.V. Source


Mancilla F.L.,University of Granada | Diaz J.,CSIC - Institute of Earth Sciences Jaume Almera
Tectonophysics | Year: 2015

Crustal thickness maps at regional scales are typically compiled using estimations inferred from different geophysical datasets providing a variable coverage of the investigated area. Consequently, spurious effects related to changes in data resolution or artifacts in grid interpolation may affect significant zones of those maps. The TopoIberia-IberArray broad-band seismic network, covering the Iberian Peninsula and Northern Morocco with stations distributed on a regular 60 × 60 km grid provides a unique opportunity to avoid such technical problems and to obtain a crustal thickness map derived from a same method sampling evenly all the region. Data from more than 340 stations has been gathered and analyzed using the P-to-S conversion phases at the Moho discontinuity (receiver functions). The crustal thickness has been inferred applying the classical H-κ stacking technique, though in regions of complex crustal structure, we have preferred to estimate the thickness directly from the arrival time of the converted phase at some sites.The topography of the Moho discontinuity is strongly correlated with tectonic processes. The investigated area, extending from the Sahara platform to the Bay of Biscay, has a great geodynamic diversity, including, North to South, crustal imbrication in the Pyrenean and Cantabrian range, a large and relatively undisturbed Variscan Massif in the center of Iberia and areas of complex and still not completely understood geodynamics in the Alboran crust domain and the Atlas range. The crustal thickness map reflects this diversity, showing variations reaching 30. km between the thickest and thinnest zones of continental crust. The final map has an overall similarity with previous estimations of the crustal thickness using independent data, as those coming from more sparse deep seismic sounding profiles, but provides further constraints at regional scale. © 2015 Elsevier B.V. Source


Ardhuin F.,French Research Institute for Exploitation of the Sea | Stutzmann E.,CNRS Paris Institute of Global Physics | Schimmel M.,CSIC - Institute of Earth Sciences Jaume Almera | Mangeney A.,CNRS Paris Institute of Global Physics
Journal of Geophysical Research: Oceans | Year: 2011

Noise with periods 3 to 10 s, ubiquitous in seismic records, is expected to be mostly generated by pairs of ocean wave trains of opposing propagation directions with half the seismic frequency. Here we present the first comprehensive numerical model of microseismic generation by random ocean waves, including ocean wave reflections. Synthetic and observed seismic spectra are well correlated (r > 0.85). On the basis of the model results, noise generation events can be clustered in three broad classes: wind waves with a broad directional spectrum (class I), sea states with a significant contribution of coastal reflections (class II), and the interaction of two independent wave systems (class III). At seismic stations close to western coasts, noise generated by class II sources generally dominates, but it is intermittently outshined by the intense class III sources, limiting the reliability of seismic data as a proxy for storm climates. The modeled seismic noise critically depends on the damping of seismic waves. At some mid-ocean island stations, low seismic damping is necessary to reproduce the observed high level and smoothness of noise time series that result from a spatial integration of sources over thousands of kilometers. In contrast, some coastal stations are only sensitive to noise within a few hundreds of kilometers. This revelation of noise source patterns worldwide provides a wealth of information for seismic studies, wave climate applications, and new constraints on the possible directional distribution of wave energy. Copyright 2011 by the American Geophysical Union. Source

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