[1] Campi Flegrei is an active, resurgent caldera that is located a few kilometres west of the city of Naples, a densely populated urban settlement in southern Italy. Identifying, locating at depth and better defining the geometry of the magma feeding system of the caldera is highly relevant for assessing and monitoring its volcanic hazard. Based on a high resolution seismic reflection data set, we investigated the deep structure of the volcano. Here we show that seismic wave amplitude variations with distance from the radiating source provide clear evidence for large amplitude seismic reflections from the top of an extended supercritical fluid-bearing rock formation at about 3,000 m and of an about 7,500 m deep, 1,000 m thick, low velocity layer, which is associated with a mid-crust, partial melting zone beneath the caldera. The modeling of magma properties based on measured seismic velocities indicates a relatively high melt percentage (in the range 80-90%). These new data suggest that a large magmatic sill is present well within the basement formations, which is possibly linked to the surface through a system of deep fractures bordering the caldera. The lateral extension and similar depth of the melt zone observed beneath the nearby Mt.Vesuvius support the hypothesis of a single continuous magma reservoir feeding both of these volcanoes.

S U M M A R YBARENTS50, a new 3-D geophysical model of the crust in the Barents Sea Region has been developed by the University of Oslo, NORSAR and the U.S. Geological Survey. The target region comprises northern Norway and Finland, parts of the Kola Peninsula and the East European lowlands. Novaya Zemlya, the Kara Sea and Franz-Josef Land terminate the region to the east, while the Norwegian-Greenland Sea marks the western boundary. In total, 680 1-D seismic velocity profiles were compiled, mostly by sampling 2-D seismic velocity transects, from seismic refraction profiles. Seismic reflection data in the western Barents Sea were further used for density modelling and subsequent density-to-velocity conversion. Velocities from these profiles were binned into two sedimentary and three crystalline crustal layers. The first step of the compilation comprised the layer-wise interpolation of the velocities and thicknesses. Within the different geological provinces of the study region, linear relationships between the thickness of the sedimentary rocks and the thickness of the remaining crystalline crust are observed. We therefore, used the separately compiled (area-wide) sediment thickness data to adjust the total crystalline crustal thickness according to the total sedimentary thickness where no constraints from 1-D velocity profiles existed. The BARENTS50 model is based on an equidistant hexagonal grid with a node spacing of 50 km. The P-wave velocity model was used for gravity modelling to obtain 3-D density structure. A better fit to the observed gravity was achieved using a grid search algorithm which focussed on the density contrast of the sediment-basement interface. An improvement compared to older geophysical models is the high resolution of 50 km. Velocity transects through the 3-D model illustrate geological features of the European Arctic. The possible petrology of the crystalline basement in western and eastern Barents Sea is discussed on the basis of the observed seismic velocity structure. The BARENTS50 model is available at http://www.norsar.no/seismology/barents3d/.

Induced seismicity from anthropogenic sources can be a significant nuisance to a local population and in extreme cases lead to damage to vulnerable structures. One type of induced seismicity of particular recent concern, which, in some cases, can limit development of a potentially important clean energy source, is that associated with geothermal power production. A key requirement for the accurate assessment of seismic hazard (and risk) is a ground-motion prediction equation (GMPE) that predicts the level of earthquake shaking (in terms of, for example, peak ground acceleration) of an earthquake of a certain magnitude at a particular distance. Few such models currently exist in regard to geothermal-related seismicity, and consequently the evaluation of seismic hazard in the vicinity of geothermal power plants is associated with high uncertainty.Various ground-motion datasets of induced and natural seismicity (from Basel, Geysers, Hengill, Roswinkel, Soultz, and Voerendaal) were compiled and processed, and moment magnitudes for all events were recomputed homogeneously. These data are used to show that ground motions from induced and natural earthquakes cannot be statistically distinguished. Empirical GMPEs are derived from these data; and, although they have similar characteristics to recent GMPEs for natural and miningrelated seismicity, the standard deviations are higher. To account for epistemic uncertainties, stochastic models subsequently are developed based on a single corner frequency and with parameters constrained by the available data. Predicted ground motions from these models are fitted with functional forms to obtain easy-to-use GMPEs. These are associated with standard deviations derived from the empirical data to characterize aleatory variability. As an example, we demonstrate the potential use of these models using data from Campi Flegrei.Online Material: Sets of coefficients and standard deviations for various groundmotion models.

S U M M A R YMagnetotelluric and seismic methods provide complementary information about the resistivity and velocity structure of the subsurface on similar scales and resolutions. No global relation, however, exists between these parameters, and correlations are often valid for only a limited target area. Independently derived inverse models from these methods can be combined using a classification approach to map geologic structure. The method employed is based solely on the statistical correlation of physical properties in a joint parameter space and is independent of theoretical or empirical relations linking electrical and seismic parameters. Regions of high correlation (classes) between resistivity and velocity can in turn be mapped back and reexamined in depth section. The spatial distribution of these classes, and the boundaries between them, provide structural information not evident in the individual models. This method is applied to a 10 km long profile crossing the Dead Sea Transform in Jordan. Several prominent classes are identified with specific lithologies in accordance with local geology. An abrupt change in lithology across the fault, together with vertical uplift of the basement suggest the fault is sub-vertical within the upper crust.The interpretation of geophysical models derived by inversion is a highly subjective part of any geologic study. Our incomplete knowledge of the subsurface, the spatially-varying resolution of the models, and the non-uniqueness of the geophysical inverse problem make it difficult to objectively interpret physical property models in terms of geologic structure. The problem is exacerbated by the many-tomany, or at best, many-to-one, relationship between geologic units and their physical properties. It is thus commonplace to use multiple methods to determine multiple physical properties over an area of interest in order to discriminate between the range of possible geologic/lithologic structures. The analysis of such complementary data, however, is rarely taken beyond a qualitative comparison. Attempts at a quantitative comparison are, for the most part, centered upon constitutive or empirical relations between physical properties, which tend to be limited in scale and applicability.Seismic and magnetotelluric (MT) methods are often favored for crustal studies as they provide images of acoustic velocity (V p , V s ) and electrical resistivity (ρ), respectively, on similar scales and with comparable spatial resolution (Jones 1987). By looking in tandem at velocity and resistivity we retain the strengths of each method, while lessening the susceptibility of our interpretation to their individual weaknesses. Seismic refraction, for example, has difficulty imaging vertical velocity contrasts. Along a similar vein, MT has difficulty resolving structure beneath strong conductors due to the large amount of energy dissipated within them. A properly formulated joint interpretation must take these variations in resolution into account, but unfortunately there exists no fundame...

[1] On several recordings of linear seismometer arrays crossing the Arava Fault (AF) in the Middle East, we see prominent wave trains emerging from in-fault explosions which we interpret as waves being guided by a fault zone related low-velocity layer. The AF is located in the Arava Valley and is considered the principal active fault of the mainly N-S striking Dead Sea Transform System in this section. Observations of these wave trains are confined to certain segments of the receiver lines and occur only for particular shot locations. They exhibit large amplitudes and are almost monochromatic. We model them by a two-dimensional (2-D) analytical solution for the scalar wave field in models with a vertical waveguide embedded in two quarter spaces. A hybrid search scheme combining genetic algorithm and a local random search is employed to explore the multimodal parameter space. Resolution is investigated by synthetic tests. The observations are adequately fit by models with a narrow, only 3-12 m wide waveguide with S wave velocity reduced by 10-60% of the surrounding rock. We relate this vertical low-velocity layer with the damage zone of the AF since the location of receivers observing and of shots generating the guided waves, respectively, match with the surface trace of the fault. The thickness of the damage zone of the AF, at least at shallow depths, seems to be much smaller than in other major fault zones. This could be due to less total slip on this fault.