Fully probabilistic seismic risk assessment considering local site effects for the portfolio of buildings in Medellín,Colombia

A fully probabilistic seismic risk analysis using a comprehensive approach is conducted for Medellin, the second largest city of Colombia, using a building by building database constructed and complemented from aerial images, considering characteristics such as building use categories, socio-economic levels and replacement values. The seismic hazard used for the analysis corresponds to the most updated study available in the country with the same model that was included in the national building code maps definition. Spectral transfer functions are determined for each of the seismic microzonation zones in order to take into account the dynamic soil response and amplification effects in the risk analysis. Several building types are defined for the city and individual vulnerability functions are assigned to each of them. Risk results are presented in the state of the art metrics such as the loss exceedance curve, probable maximum losses for different return periods, average annual losses and risk maps. The obtained results can be classified by use and socio-economic sectors as well as by structural systems that may help the stakeholders to identify where the risk concentrates.     

Discriminating the long distance dispersal of fine ash from sustained columns or near ground ash clouds: The example of the Pomici di Avellino eruption (Somma-Vesuvius,Italy)

Ash samples from tephra layers correlated with the Pomici di Avellino (Avellino Pumice) eruption of Somma-Vesuvius were collected in distal archives and their composition and particle morphology investigated in order to infer their behaviour of transportation and deposition. Differences in composition and particle morphologies were recognised for ash particles belonging to the magmatic Plinian and final phreatomagmatic phases of the eruption. The ash particles were dispersed in opposite directions during the two different phases of the eruption, and these directions are also different from that of coarse-grained fallout deposits. In particular, ash generated during magmatic phase and injected in the atmosphere to form a sustained column shows a prevailing SE dispersion, while ash particles generated during the final phreatomagmatic phase and carried by pyroclastic density currents show a general NW dispersion. These opposite dispersions indicate an ash dispersal influenced by both high and low atmosphere dynamics. In particular, the magmatic ash dispersal was first driven by stratospheric wind towards NE and then the falling particles encountered a variable wind field during their settling, which produced the observed preferential SE dispersal. The wind field encountered by the rising ash clouds that accompanied the pyroclastic density currents of the final phreatomagmatic phase was different with respect to that encountered by the magmatic ash, and produced a NW dispersal. These data demonstrate how ash transportation and deposition are greatly influenced by both high and low atmosphere dynamics. In particular, fine-grained particles transported in ash clouds of small-scale pyroclastic density currents may be dispersed over distances and cover areas comparable with those injected into the stratosphere by Plinian, sustained columns. This is a point not completely addressed by present day mitigation plans in case of renewal of activity at Somma-Vesuvius, and can yield important information also for other volcanoes potentially characterised by explosive activity.     

Multiplatform observation of the surface circulation in the Gulf of Naples (Southern Tyrrhenian Sea)

The Gulf of Naples (Southern Tyrrhenian Sea) is a highly urbanised area, where human activities and natural factors (e.g. river runoff, exchanges with adjacent basins) can strongly affect the water quality. In this work we show how surface transport can influence the distribution of passively drifting surface matter, and more in general if and how the circulation in the basin can promote the renovation of the surface layer. To this aim, we carried out a multiplatform analysis by putting together HF radar current fields, satellite images and modelling tools. Surface current fields and satellite images of turbidity patterns were used to initialise and run model simulations of particle transport and diffusion. Model results were then examined in relation to the corresponding satellite distributions. This integrated approach permits to investigate the concurrent effects of surface dynamics and wind forcing in determining the distribution of passive tracers over the basin of interest, identifying key mechanisms supporting or preventing the renewal of surface waters as well as possible areas of aggregation and retention.     

Compositional Bayesian indicator estimation

Indicator kriging is widely used for mapping spatial binary variables and for estimating the global and local spatial distributions of variables in geosciences. For continuous random variables, indicator kriging gives an estimate of the cumulative distribution function, for a given threshold, which is then the estimate of a probability. Like any other kriging procedure, indicator kriging provides an estimation variance that, although not often used in applications, should be taken into account as it assesses the uncertainty of the estimate. An alternative approach to indicator estimation is proposed in this paper. In this alternative approach the complete probability density function of the indicator estimate is evaluated. The procedure is described in a Bayesian framework, using a multivariate Gaussian likelihood and an a priori distribution which are both combined according to Bayes theorem in order to obtain a posterior distribution for the indicator estimate. From this posterior distribution, point estimates, interval estimates and uncertainty measures can be obtained. Among the point estimates, the median of the posterior distribution is the maximum entropy estimate because there is a fifty-fifty chance of the unknown value of the estimate being larger or smaller than the median; that is, there is maximum uncertainty in the choice between two alternatives. Thus in some sense, the latter is an indicator estimator, alternative to the kriging estimator, that includes its own uncertainty. On the other hand, the mode of the posterior distribution estimator, assuming a uniform prior, is coincidental with the simple kriging estimator. Additionally, because the indicator estimate can be considered as a two-part composition which domain of definition is the simplex, the method is extended to compositional Bayesian indicator estimation. Bayesian indicator estimation and compositional Bayesian indicator estimation are illustrated with an environmental case study in which the probability of the content of a geochemical element in soil being over a particular threshold is of interest. The computer codes and its user guides are public domain and freely available.     

Adapting a texture synthesis algorithm for conditional multiple point geostatistical simulation

Computer vision provides several tools for analyzing and simulating textures. The principles of these techniques are similar to those in multiple-point geostatistics, namely, the reproduction of patterns and consistency in the results from a perceptual point of view, thus, ensuring the reproduction of long range connectivity. The only difference between these techniques and geostatistical simulation accounting for multiple-point statistics is that conditioning is not an issue in computer vision. We present a solution to the problem of conditioning simulated fields while simultaneously honoring multiple-point (pattern) statistics. The proposal is based on a texture synthesis algorithm where a fixed search (causal) pattern is used. Conditioning is achieved by adding a non-causal search neighborhood that modifies the conditional distribution from which the simulated category is drawn, depending on the conditioning information. Results show an excellent reproduction of the features from the training image, while respecting the conditioning information. Some issues related to the data structure and to the computer efficiency are discussed.     

Magnetic field transforms with low sensitivity to the direction of source magnetization and high centricity

Magnetic data interpretation faces difficulties due to the various shapes of magnetic anomalies and the positions of their extrema with respect to the causative bodies for different directions of the source magnetization. The well‐known transforms — reduction to the pole, pseudogravity field, and analytic signal (total gradient) — help in reducing the problem. Another way to achieve the required effect is the transformation of magnetic data, ΔT or Z, into values of the anomalous magnetic intensity T. In this respect, we have found some transforms based on differential operators such as the gradient of T and its modulus R = |?T|, the Laplacian L = ?²T, the product T ?²T and its square root Q, and the Laplacian ?²(T²) and its square root E, to be useful. They are slightly sensitive to the magnetization orientation and their extrema occur above the sources. For a 2D anomaly of a homogeneous causative body, the proposed transforms do not depend on the inclination of magnetization. In the 3D case, such independence does not exist even for the elementary field of a point dipole. The influence of the magnetization direction is estimated by an integral coefficient of sensitivity. This coefficient takes values of up to 2.0 for ΔT or Z anomalies, while their transforms T, R, E, Q and L have values of less than 0.28, 0.29, 0.24, 0.16 and 0.07, respectively, i.e. on average, 10 times less. The estimation of the centricity is carried out using the relative deviation of the principal extremum of the anomaly or its transforms from the epicentre of the model body at a depth equal to 100 units. For a ΔT anomaly this deviation is up to 67%; for the L transform it is less than 8%; for Q, E, R and T it is less than 10%, 15%, 20% and 25%, respectively. The proposed transforms take only non‐negative values. With respect to their shape, the peripheral magnetic extrema are removed, the anomalous configuration is simplified and the resolution of complicated interference patterns is improved. Their calculation does not require additional data for the direction of magnetization, which is an essential advantage over the reduction‐to‐the‐pole and pseudogravity‐field transforms. A joint analysis of the measured field and its transforms T, E and L offers possibilities for more confident separation of the anomalous effects and direct correlation to their sources. The model tests performed and the 3D field applications to real magnetic data confirm the useful properties of the transforms suggested here.     

Magnetic data analysis at low latitudes using magnitude transforms

Magnitude transforms include magnitude magnetic anomalies (MMA), their gradients and Laplacians. They can be calculated from the total magnetic anomalies or other component anomalies. Magnitude magnetic anomalies have a space distribution different from that of the component anomalies. Their values are non‐negative and their respective patterns are similar to the positive gravity anomalies. Magnitude transforms are an effective tool for magnetic data analysis due to their simplified pattern and direct correlation with the space location of the source. They have advantages over the traditionally used reduction‐to‐the‐pole (RTP) transform, especially at low magnetic latitudes. The calculation of magnitudes of the anomalous field requires the total field data to be transformed into the component anomalies, while the reduction‐to‐the‐pole transform also includes a rotation of the magnetization vector, the orientation of which is usually assumed. For equal latitudes, the transfer functions of component‐component transforms in the frequency domain show better stability than the component‐component‐rotation transfer function. This is illustrated by a comparison of analytical expressions, and synthetic models of magnetic fields. The Dixon seamount case shows the possibilities for an improved data analysis and more confident source recognition at low latitudes using magnetic transforms.     

Spectral density regression for bivariate extremes

We introduce a density regression model for the spectral density of a bivariate extreme value distribution, that allows us to assess how extremal dependence can change over a covariate. Inference is performed through a double kernel estimator, which can be seen as an extension of the Nadaraya–Watson estimator where the usual scalar responses are replaced by mean constrained densities on the unit interval. Numerical experiments with the methods illustrate their resilience in a variety of contexts of practical interest. An extreme temperature dataset is used to illustrate our methods.     

A study of the geophysical response of distributed fibre optic acoustic sensors through laboratory‐scale experiments

In the past few years, distributed acoustic sensing has gained great interest in geophysics. This acquisition technology offers immense improvement in terms of efficiency when compared with current geophysical acquisition methods. However, the fundamentals of the measurement are still not fully understood because direct comparisons of fibre data with conventional geophysical sensors are difficult during field tests. We present downscaled laboratory experiments that enabled us to characterise the relationship between the signals recorded by conventional seismic point receivers and by distributed fibre optic sensors. Interrogation of the distributed optical fibre sensor was performed with a Michelson interferometer because this system is suited to compact test configurations, and it requires only a very simple data processing workflow for extracting the signal outputs. We show acoustic data that were recorded simultaneously by both the fibre optical interferometer and conventional three‐component accelerometers, thus enabling the comparison of sensor performance. We present results focused on the directionality of fibre measurements, on the amplitude variation with angle of incidence, and on the transfer function that allows accelerometer signals to be transformed into optical fibre signals. We conclude that the optical fibre response matches with the array of the displacement differences of the inline accelerometers deployed along the fibre length. Moreover, we also analysed the influence of various types of coupling and fibre cable coating on the signal responses, emphasising the importance of these parameters for field seismic acquisitions when using the distributed fibre optic technology.     

A new method for the determination of the specific kinetic energy (SKE) released to pyroclastic particles at magmatic fragmentation: theory and first experimental results

Brittle magmatic fragmentation plays a crucial role in explosive eruptions. It represents the starting point of hazardous explosive events that can affect large areas surrounding erupting volcanoes. Knowing the initial energy released during this fragmentation process is fundamental for the understanding of the subsequent dynamics of the eruptive gas-particle mixture and consequently for the forecasting of the erupting column’s behavior. The specific kinetic energy (SKE) of the particles quantifies the initial velocity shortly after the fragmentation and is therefore a necessary variable to model the gas-particle conduit flow and eruptive column regime. In this paper, we present a new method for its determination based on fragmentation experiments and identification of the timings of energy release. The results obtained on compositions representative for basaltic and phonolitic melts show a direct dependence on magma material properties: poorly vesiculated basaltic melts from Stromboli show the highest SKE values ranging from 7.3 to 11.8 kJ/kg, while experiments with highly vesiculated samples from Stromboli and Vesuvius result in lower SKE values (3.1 to 3.8 kJ/kg). The described methodology presents a useful tool for quantitative estimation of the kinetic energy release of magmatic fragmentation processes, which can contribute to the improvement of hazard assessment.