Characterizing and Locating Very Weak (−2.2 ≥ M L ≥ −3.4) Induced Seismicity in Unstable Sandstone Cliffs by Nanoseismic Monitoring

Unloaded natural rock masses are known to generate seismic signals (Green et al., 2006; Hainzl et al., 2006; Husen et al., 2007; Kraft et al., 2006). Following a 1,000 m³ mass failure into the Mediterranean Sea, centimeter-wide tensile cracks were observed to have developed on top of an unstable segment of the coastal cliff. Nanoseismic monitoring techniques (Wust-Bloch and Joswig, 2006; Joswig, 2008), which function as a seismic microscope for extremely weak seismic events, were applied to verify whether brittle failure is still generated within this unconsolidated sandstone mass and to determine whether it can be detected. Sixteen days after the initial mass failure, three small-aperture sparse arrays (Seismic Navigation Systems-SNS) were deployed on top of this 40-m high shoreline cliff. This paper analyzes dozens of spiky nanoseismic (?2.2 ≥ M _L ≥ ?3.4) signals recorded over one night in continuous mode (at 200 Hz) at very short slant distances (3–67 m). Waveform characterization by sonogram analysis (Joswig, 2008) shows that these spiky signals are all short in duration (>0.5 s). Most of their signal energy is concentrated in the 10–75 Hz frequency range and the waveforms display high signal similarity. The detection threshold of the data set reaches M _L ?3.4 at 15 m and M _L ?2.7 at 67 m. The spatial distribution of source signals shows 3-D clustering within 10 m from the cliff edge. The time distribution of M _L magnitude does not display any decay pattern of M _L over time. This corroborates an unusual event decay over time (modified Omori’s law), whereby an initial quiet period is followed by regained activity, which then fades again. The polarization of maximal waveform amplitude was used to estimate spatial stress distribution. The orientation of ellipses displaying maximal signal energy is consistent with that of tensile cracks observed in the field and agrees with rock mechanics predictions. The M _L– surface rupture length relationship displayed by our data fits a constant-slope extrapolation of empirical data collected by Wells and Coppersmith (1994) for normal fault features at much larger scale. Signal characterization and location as well as the absence of direct anthropogenic noise sources near the monitoring site, all indicate that these nanoseismic signals are generated by brittle failure within the top section of the cliff. The atypical event decay over time that was observed suggests that the cliff material is undergoing post-collapse bulk strain accommodation. This feasibility study demonstrates the potential of nanoseismic monitoring in rapidly detecting, locating and analyzing brittle failure generated within unconsolidated material before total collapse occurs.     

Semiparametric regression models for spatial prediction and uncertainty quantification of soil attributes

In many studies, the distribution of soil attributes depends on both spatial location and environmental factors, and prediction and process identification are performed using existing methods such as kriging. However, it is often too restrictive to model soil attributes as dependent on a known, parametric function of environmental factors, which kriging typically assumes. This paper investigates a semiparametric approach for identifying and modeling the nonlinear relationships of spatially dependent soil constituent levels with environmental variables and obtaining point and interval predictions over a spatial region. Frequentist and Bayesian versions of the proposed method are applied to measured soil nitrogen levels throughout Florida, USA and are compared to competing models, including frequentist and Bayesian kriging, based an array of point and interval measures of out-of-sample forecast quality. The semiparametric models outperformed competing models in all cases. Bayesian semiparametric models yielded the best predictive results and provided empirical coverage probability nearly equal to nominal.     

Slope instabilities triggered by the 11th May 2011 Lorca earthquake (Murcia,Spain): comparison to previous hazard assessments and proposition of a new hazard map and probability of failure equation

The Lorca Basin has been the object of recent research aimed at studying the phenomena of earthquake-induced landslides and its assessment in the frame of different seismic scenarios. However, it has not been until the 11th May 2011 Lorca earthquakes when it has been possible to conduct a systematic approach to the problem. In this paper we present an inventory of slope instabilities triggered by the Lorca earthquakes which comprises more than 100 cases, mainly rock and soil falls of small size (1–100  \(\hbox {m}^{3}\) ). The distribution of these instabilities is here compared to two different earthquake-triggered landslide hazard maps: one considering the occurrence of the most probable earthquake for a 475-years return period in the Lorca Basin \((\hbox {M}_{\mathrm{w}}=5.0)\) based on both low- and high-resolution digital elevation model (DEM); and a second one matching the occurrence of the \(\hbox {M}_{\mathrm{w}}=5.2\) 2011 Lorca earthquake, which was performed using the higher resolution DEM. The most frequent Newmark displacements related to the slope failures triggered by the 2011 Lorca earthquakes are lower than 2 cm in both the hazard scenarios considered. Additionally, the predicted Newmark displacements were correlated to the inventory of slope instabilities to develop a probability of failure equation. The fit seems to be very good since most of the mapped slope failures are located on the higher probability areas. The probability of slope failure in the Lorca Basin for a seismic event similar to the \(\hbox {M}_{\mathrm{w}}\) 5.2 2011 Lorca earthquake can be considered as very low (0–4 %).     

Towards fully data driven ground-motion prediction models for Europe

We have used the Artificial Neural Network method (ANN) for the derivation of physically sound, easy-to-handle, predictive ground-motion models from a subset of the Reference database for Seismic ground-motion prediction in Europe (RESORCE). Only shallow earthquakes (depth smaller than 25 km) and recordings corresponding to stations with measured $V_{s30}$ properties have been selected. Five input parameters were selected: the moment magnitude $M_{W}$ , the Joyner–Boore distance $R_{JB}$ , the focal mechanism, the hypocentral depth, and the site proxy $V_{S30}$ . A feed-forward ANN type is used, with one 5-neuron hidden layer, and an output layer grouping all the considered ground motion parameters, i.e., peak ground acceleration (PGA), peak ground velocity (PGV) and 5 %-damped pseudo-spectral acceleration (PSA) at 62 periods from 0.01 to 4 s. A procedure similar to the random-effects approach was developed to provide between and within event standard deviations. The total standard deviation ( $\sigma $ ) varies between 0.298 and 0.378 (log $_{10}$ unit) depending on the period, with between-event and within-event variabilities in the range 0.149–0.190 and 0.258–0.327, respectively. Those values prove comparable to those of conventional GMPEs. Despite the absence of any a priori assumption on the functional dependence, our results exhibit a number of physically sound features: magnitude scaling of the distance dependency, near-fault saturation distance increasing with magnitude, amplification on soft soils and even indications for nonlinear effects in softer soils.     

Why do we need and how should we implement Bayesian kriging methods

The spatial prediction methodology that has become known under the heading of kriging is largely based on the assumptions that the underlying random field is Gaussian and the covariance function is exactly known. In practical applications, however, these assumptions will not hold. Beyond Gaussianity of the random field, lognormal kriging, disjunctive kriging, (generalized linear) model-based kriging and trans-Gaussian kriging have been proposed in the literature. The latter approach makes use of the Box–Cox-transform of the data. Still, all the alternatives mentioned do not take into account the uncertainty with respect to the distribution (or transformation) and the estimated covariance function of the data. The Bayesian trans-Gaussian kriging methodology proposed in the present paper is in the spirit of the “Bayesian bootstrap” idea advocated by Rubin (Ann Stat 9:130–134, 1981) and avoids the unusual specification of noninformative priors often made in the literature and is entirely based on the sample distribution of the estimators of the covariance function and of the Box–Cox parameter. After some notes on Bayesian spatial prediction, noninformative priors and developing our new methodology finally we will present an example illustrating our pragmatic approach to Bayesian prediction by means of a simulated data set.     

The role of site effects in the comparison between code provisions and the near field strong motion of the Emilia 2012 earthquakes

A damaging seismic sequence hit a wide area mainly located in the Emilia-Romagna region (Northern Italy) during 2012 with several events of local magnitude \(\hbox {M}_\mathrm{l} \ge 5\) , among which the \(\hbox {M}_\mathrm{l}\) 5.9 May 20 and the \(\hbox {M}_\mathrm{l}\) 5.8 May 29 were the main events. Thanks to the presence of a permanent accelerometric station very close to the epicentre and to the temporary installations performed in the aftermath of the first shock, a large number of strong motion recordings are available, on the basis of which, we compared the recorded signals with the values provided by the current Italian seismic regulations, and we observed several differences with respect to horizontal components when the simplified approach for site conditions (based on Vs30 classes) is used. On the contrary, when using the more accurate approach based on the local seismic response, we generally obtain a much better agreement, at least in the frequency range corresponding to a quarter wavelength comparable with the depth of the available subsoil data. Some unresolved questions still remain, such as the low frequency behaviour ( \(<\) 1 Hz) that could be due either to complex propagation at depth larger than the one presently investigated or to near source effects, and the behaviour of vertical spectra whose recorded/code difference is too large to be explained with the information currently available.     

New Seismic Noise Models Obtained Using Very Broadband Stations

It has been two decades since the last comprehensive standard model of ambient earth noise was published Peterson (Observations and modelling of seismic background noise, US Geological Survey, open-file report 93–322, 1993). The PETERSON model was updated by analyzing the absolute quietest conditions for stations within the GSN (Berger et al. in J Geophys Res 109, 2005; Mcnamara and Buland in Bull Seism Soc Am 94:1517–1527, 2004; Ringler et al. in Seismol Res Lett 81(4) doi:10.1785/gssrl.81.4.605, 2010). Unfortunately, both the original model and the updated models did not include any deployed station in North Africa and Middle East, which reflects the noise levels within the desert environment of those regions. In this study, a survey was conducted to create a new seismic noise model from very broadband stations which recently deployed in North Africa. For this purpose, 1 year of continuous recording of seismic noise data of the Egyptian National Seismic Network (ENSN) was analyzed in order to create a new noise model. Seasonal and diurnal variations in noise spectra were recorded at each station. Moreover, we constructed a new noise model for each individual station. Finally, we obtained a new cumulative noise model for all the stations. We compared the new high-noise model (EHNM) and new low-noise model (ELNM) with both the high-noise model (NHNM) and low-noise model (NLNM) of Peterson (Observations and modelling of seismic background noise, US Geological Survey, open-file report 93–322, 1993). The obtained noise levels are considerably lower than low-noise model of Peterson (Observations and modelling of seismic background noise, US Geological Survey, open-file report 93–322, 1993) at ultra long period band (ULP band), but they are still below the high-noise model of Peterson (Observations and modelling of seismic background noise, US Geological Survey, open-file report 93–322, 1993). The results of this study could be considered as a first step to create permanent seismic noise models for North Africa and Middle East regions.     

Interannual variability of the air–sea CO2 flux in the north Indian Ocean

A simple biogeochemical model coupled to an offline ocean tracer transport model driven by reanalysis ocean data is used to simulate the seasonal and interannual CO $_2$ flux variability in the northern Indian Ocean. The maximum of seasonal and interannual CO $_2$ emission variances in the northern Indian Ocean are located in the coastal Arabian Sea (AS) and Southern Peninsular India (SP) with a basin-wide seasonal amplitude and standard deviation of 0.044 $\pm $ 0.04 Pg C year $^{-1}$ . The area integrated CO $_2$ emissions from these two regions in the model are significantly correlated (above a 95 % level) with the observations of Takahashi et al. (Deep-Sea Res-II, 56:554–577, 2009). The interannual anomalies of CO $_2$ emission from the AS and SP are found as 40 and 30 % of their respective seasonal amplitudes. Both the Arabian Sea (AS) and Southern Peninsular India (SP) interannual CO $_2$ emission anomalies show a 3–4-year variability. The correlations of AS and SP CO $_2$ emission anomalies with the Indian Ocean Dipole/Zonal Mode (IODZM) and Southern Oscillation (SO) indices from 1980 to 1999 are 0.35, 0.21 and 0.32, 0.01 respectively. A 5-year window moving correlation analysis shows that the relationship of AS and SP CO $_2$ emission to the SO and IODZM are complementary to each other. During the years when the correlation of air–sea CO $_2$ emission with the IODZM is stronger, the corresponding correlation with the SO is weaker or opposite. The total change in pCO $_2$ is broken down into changes induced by the individual components such as dissolved inorganic carbon (DIC), sea surface temperature (SST), alkalinity, and salinity and found that (1) the effect of SST in the AS CO $_2$ emission increases (decreases) when the correlation of CO $_2$ emission with the IODZM is positive (negative), and (2) the SP CO $_2$ emission is strongly controlled by the circulation-driven DIC changes; however, this relation is found to be weaker when the SO correlates negatively with the SP CO $_2$ emission.     

Recent evolution and challenges in the Seismic Hazard Analysis of the Po Plain region, Northern Italy

SH evaluation in Po Plain region is revisited with a view to: ( $a)$ updating available seismic source and ground motion attenuation models with recent data and testing the sensitivity of the results, ( $b)$ exploiting available non-stationary models to check their predictive performance at particular sites and, ( $c)$ handling the ground motion hazard generated by composite fault systems. Update of area source models and GMPEs does not strongly affect SH evaluated at representative sites, while usefulness of predictions derived from non-stationary models needs to be assessed on a site-by-site basis. A hybrid (deterministic-probabilistic) approach seems to be a promising tool for assessing site-specific hazard contributed by composite sources.     

Calibration/Data Assimilation Approach for Integrating GRACE Data into the WaterGAP Global Hydrology Model (WGHM) Using an Ensemble Kalman Filter: First Results

We introduce a new ensemble-based Kalman filter approach to assimilate GRACE satellite gravity data into the WaterGAP Global Hydrology Model. The approach (1) enables the use of the spatial resolution provided by GRACE by including the satellite observations as a gridded data product, (2) accounts for the complex spatial GRACE error correlation pattern by rigorous error propagation from the monthly GRACE solutions, and (3) allows us to integrate model parameter calibration and data assimilation within a unified framework. We investigate the formal contribution of GRACE observations to the Kalman filter update by analysis of the Kalman gain matrix. We then present first model runs, calibrated via data assimilation, for two different experiments: the first one assimilates GRACE basin averages of total water storage and the second one introduces gridded GRACE data at \(5^\circ\) resolution into the assimilation. We finally validate the assimilated model by running it in free mode (i.e., without adding any further GRACE information) for a period of 3 years following the assimilation phase and comparing the results to the GRACE observations available for this period.     

Gradual Fault Weakening with Seismic Slip: Inferences from the Seismic Sequences of L’Aquila, 2009, and Northridge, 1994

We estimate seismological fracture energies from two subsets of events selected from the seismic sequences of L’Aquila (2009), and Northridge (1994): 57 and 16 selected events, respectively, including the main shocks. Following Abercrombie and Rice (Geophys J Int 162: 406–424, 2005), we postulate that fracture energy (G) represents the post-failure integral of the dynamic weakening curve, which is described by the evolution of shear traction as a function of slip. Following a direct-wave approach, we compute mainshock-/aftershock-source spectral ratios, and analyze them using the approach proposed by Malagnini et al. (Pure Appl. Geophys., this issue, 2014) to infer corner frequencies and seismic moment. Our estimates of source parameters (including fracture energies) are based on best-fit grid-searches performed over empirical source spectral ratios. We quantify the source scaling of spectra from small and large earthquakes by using the MDAC formulation of Walter and Taylor (A revised Magnitude and Distance Amplitude Correction (MDAC2) procedure for regional seismic discriminants, 2001). The source parameters presented in this paper must be considered as point-source estimates representing averages calculated over specific ruptured portions of the fault area. In order to constrain the scaling of fracture energy with coseismic slip, we investigate two different slip-weakening functions to model the shear traction as a function of slip: (i) a power law, as suggested by Abercrombie and Rice (Geophys J Int 162: 406–424, 2005), and (ii) an exponential decay. Our results show that the exponential decay of stress on the fault allows a good fit between measured and predicted fracture energies, both for the main events and for their aftershocks, regardless of the significant differences in the energy budgets between the large (main) and small earthquakes (aftershocks). Using the power-law slip-weakening function would lead us to a very different situation: in our two investigated sequences, if the aftershock scaling is extrapolated to events with large slips, a power law (a la Abercrombie and Rice) would predict unrealistically large stress drops for large, main earthquakes. We conclude that the exponential stress evolution law has the advantage of avoiding unrealistic stress drops and unbounded fracture energies at large slip values, while still describing the abrupt shear-stress degradation observed in high-velocity laboratory experiments (e.g., Di Toro et al., Fault lubrication during earthquakes, Nature 2011).     

Sub-Gaussian model of processes with heavy-tailed distributions applied to air permeabilities of fractured tuff

Earth and environmental variables are commonly taken to have multivariate Gaussian or heavy-tailed distributions in space and/or time. This is based on the observation that univariate frequency distributions of corresponding samples appear to be Gaussian or heavy-tailed. Of particular interest to us is the well-documented but heretofore little noticed and unexplained phenomenon that whereas the frequency distribution of log permeability data often seems to be Gaussian, that of corresponding increments tends to exhibit heavy tails. The tails decay as powers of ? $ \alpha $ where 1 <  $ \alpha $  < 2 is either constant or grows monotonically toward an asymptote with increasing separation distance or lag. We illustrate the latter phenomenon on 1-m scale log air permeabilities from pneumatic tests in 6 vertical and inclined boreholes completed in unsaturated fractured tuff near Superior, Arizona. We then show theoretically and demonstrate numerically, on synthetically generated signals, that whereas the case of constant $ \alpha $ is consistent with a collection of samples from truncated sub-Gaussian fractional Lévy noise, a random field (or process) subordinated to truncated fractional Gaussian noise, the case of variable $ \alpha $ is consistent with a collection of samples from truncated sub-Gaussian fractional Lévy motion (tfLm), a random field subordinated to truncated fractional Brownian motion. Whereas the first type of signal is relatively regular and characterized by Lévy index $ \alpha $ , the second is highly irregular (punctuated by spurious spikes) and characterized by the asymptote of $ \alpha $ values associated with its increments. We describe a procedure to estimate the parameters of univariate distributions characterizing such signals and apply it to our log air permeability data. The latter are found to be consistent with a collection of samples from tfLm with $ \alpha $ slightly smaller than 2, which is easily confused with a Gaussian field (characterized by constant $ \alpha $  = 2). The irregular (spiky) nature of this signal is typical of observed fractured rock properties. We propose that distributions of earth and environmental variable be inferred jointly from measured values and their increments in a way that insures consistency between these two sets of data.     

Empirical ground-motion relations using moderate earthquakes recorded by Medellín–Aburrá Valley (Colombia) strong-motion networks

We tested attenuation relations obtained for different regions of the world to verify their suitability to predict strong-motion data recorded by Medellín and Aburrá Valley Accelerographic Networks. We used as comparison criteria, the average of the difference between the observed and the predicted data as a function of epicenter distance and its standard deviation. We also used the approach developed by Sherbaum et al. (Bull Seism Soc Am 94:2164–2185, 2004) that provides a method to evaluate the overall goodness-of-fit of ground-motion prediction equations. The predictive models selected use a generic focal depth. We found that this parameter has an important influence in the ground-motion predictions and must be taken into account as an independent variable. We also found important to characterize the local soil amplification to improve the attenuation relations. We found empirical relations for peak horizontal acceleration PGA and velocity PGV based on the Kamiyama and Yanagisawa (Soils Found 26:16–32, 1986) approach. $$\begin{aligned} \log _{10} (PGA)=0.5886M_L -1.0902\log _{10}(R)-0.0035H+C_{st}\pm 0.\text{29} \end{aligned}$$ $$\begin{aligned} \log _{10} (PGV)=0.7255M_L -1.8812\log _{10}(R)-0.0016H+C_{st}\pm 0.36 \end{aligned}$$ where PGA is measured in cm/s $^{2}$ and PGV in cm/s, $M_{L}$ is local magnitude in the range 2.8–6.5, $R$ is epicentral distance up to 290 km, $H$ is focal depth in km and $C_{st}$ is a coefficient that accounts for the site response due to soil conditions of each recording station. The introduction of focal depth and local site conditions as independent variables, minimize the residuals and the dispersion of the predicted data. We conclude that $H$ and $C_{st}$ are sensitive parameters, having a strong influence on the strong-motion predictions. Using the same functional form, we also propose an empirical relation for the root mean square acceleration a $_\mathrm{rms}$ : $$\begin{aligned} \log _{10} \left( {a_{rms} } \right)=0.4797M_L -1.1665\log _{10} (R)-0.00201H+C_{st}\pm 0.40 \end{aligned}$$ where a $_\mathrm{rms}$ is measured in cm/s $^{2}$ , from the S-wave arrival and using a window length equal to the rupture duration. The other variables are the same as those for PGA and PGV. The site correction coefficients $C_{st}$ found for PGA, PGV and a $_\mathrm{rms}$ show a similar trend indicating a good correlation with the soil conditions of the recording sites.     

Compatible ground-motion prediction equations for damping scaling factors and vertical-to-horizontal spectral amplitude ratios for the broader Europe region

In a companion article Akkar et al. (Bull Earthq Eng, doi:10.1007/s10518-013-9461-4, 2013a; Bull Earthq Eng, doi:10.1007/s10518-013-9508-6, 2013b) present a new ground-motion prediction equation (GMPE) for estimating 5 %-damped horizontal pseudo-acceleration spectral (PSA) ordinates for shallow active crustal regions in Europe and the Middle East. This study provides a supplementary viscous damping model to modify 5 %-damped horizontal spectral ordinates of Akkar et al. (Bull Earthq Eng, doi:10.1007/s10518-013-9461-4 2013a; Bull Earthq Eng, doi:10.1007/s10518-013-9508-6, 2013b) for damping ratios ranging from 1 to 50 %. The paper also presents another damping model for scaling 5 %-damped vertical spectral ordinates that can be estimated from the vertical-to-horizontal (V/H) spectral ratio GMPE that is also developed within the context of this study. For consistency in engineering applications, the horizontal and vertical damping models cover the same damping ratios as noted above. The article concludes by introducing period-dependent correlation coefficients to compute horizontal and vertical conditional mean spectra (Baker in J Struct Eng 137:322–331, 2011). The applicability range of the presented models is the same as of the horizontal GMPE proposed by Akkar et al. (Bull Earthq Eng, doi:10.1007/s10518-013-9461-4 2013a; Bull Earthq Eng, doi:10.1007/s10518-013-9508-6, 2013b): as for spectral periods $0.01 \hbox { s}\le \,\hbox {T}\le \,4\hbox { s}$ as well as PGA and PGV for V/H model; and in terms of seismological estimator parameters $4\le \hbox {M}_\mathrm{w} \le 8, \hbox { R} \le 200 \hbox { km}, 150\hbox { m/s}\le \hbox { V}_\mathrm{S30}\le $ 1,200 m/s, for reverse, normal and strike-slip faults. The source-to-site distance measures that can be used in the computations are epicentral $(\hbox {R}_\mathrm{epi})$ , hypocentral $(\hbox {R}_\mathrm{hyp})$ and Joyner–Boore $(\hbox {R}_\mathrm{JB})$ distances. The implementation of the proposed GMPEs will facilitate site-specific adjustments of the spectral amplitudes predicted from probabilistic seismic hazard assessment in Europe and the Middle East region. They can also help expressing the site-specific design ground motion in several formats. The consistency of the proposed models together with the Akkar et al. (Bull Earthq Eng, doi:10.1007/s10518-013-9461-4 2013a; Bull Earthq Eng, doi:10.1007/s10518-013-9508-6, 2013b) GMPE may be advantageous for future modifications in the ground-motion definition in Eurocode 8 (CEN in Eurocode 8, Design of structures for earthquake resistance—part 1: general rules, seismic actions and rules for buildings. European Standard NF EN 1998-1, Brussels, 2004).     

Quantifying influence of weather indices on PM_{2.5} based on relation map

Many researches have been conducted on the health influence of Particle Matter with diameters less than 2.5 microns (PM \(_{2.5}\) ). There are also some researches on the cause of PM \(_{2.5}\) . However, such research generally focuses on the economic and political aspect of the environment issue. In this paper, a data-analysis approach of the PM \(_{2.5}\) issue is raised to offer a new viewpoint of this problem. The applied method extracts the relations of air quality system record as a relation map, which illustrates the influence among the parameters in a graph. The method successfully fitted the weather record, and derived from it the influencers of PM \(_{2.5}\) . The result shows that the average temperature, average barometric pressure and concentration of Ozone are all factors that have an influence on the concentration of PM \(_{2.5}.\) A short justification of it is also provided.     

Assessment of expected damage on buildings subjected to Lorca earthquake through an energy-based seismic index method and nonlinear dynamic response analyses

The city of Lorca (Spain) was hit on May 11th, 2011, by two consecutive earthquakes of magnitudes 4.6 and 5.2 M \(_\mathrm{w}\) , causing casualties and important damage in buildings. Many of the damaged structures were reinforced concrete frames with wide beams. This study quantifies the expected level of damage on this structural type in the case of the Lorca earthquake by means of a seismic index \(I_{v}\) that compares the energy input by the earthquake with the energy absorption/dissipation capacity of the structure. The prototype frames investigated represent structures designed in two time periods (1994–2002 and 2003–2008), in which the applicable codes were different. The influence of the masonry infill walls and the proneness of the frames to concentrate damage in a given story were further investigated through nonlinear dynamic response analyses. It is found that (1) the seismic index method predicts levels of damage that range from moderate/severe to complete collapse; this prediction is consistent with the observed damage; (2) the presence of masonry infill walls makes the structure very prone to damage concentration and reduces the overall seismic capacity of the building; and (3) a proper hierarchy of strength between beams and columns that guarantees the formation of a strong column-weak beam mechanism (as prescribed by seismic codes), as well as the adoption of counter-measures to avoid the negative interaction between non-structural infill walls and the main frame, would have reduced the level of damage from \(I_{v}\) \(\,=\,\) 1 (collapse) to about \(I_{v}\) \(\,=\,\) 0.5 (moderate/severe damage).     

Assessing interpolation error for space–time monitoring data

In Europe, since 1990, a survey on environmental monitoring has been taking place every 5 years, using moss samples to study the distribution of heavy metal concentration and assess contamination sources, resulting on the identification of statistical association of several heavy metal concentrations in mosses. With this work, we propose an extension of an existing spatio-temporal model, introduced in Høst et al. (JASA 90(431):853–861, 1995), allowing for prediction at unsampled locations of pollution data in the presence of covariates related to each country specificities, when separately modelling the spatial mean field, the spatial variance field and the space–time residual field. Moreover, this model allows to estimate an interpolation error, as an accuracy measure, derived dependently on the case study. For a validation purpose, a simulation study is conducted, showing that the use of the proposed model leads to more accurate prediction values. Results obtained by the proposed methodology for the most recent available survey, are compared with results obtained with no temporal information, namely when Ordinary Kriging, according to the definition in Cressie (Statistics for spatial data, Wiley, New York, 1993), is used to derive illustrative prediction maps based only on the most recent data. An exercise of cross-validation is performed relative to each of the scenarios considered and the average interpolation errors are presented. While assessing interpolation errors, we conclude that the monitoring specificities of each country and the information of preceding surveys allow for more accurate prediction results.     

Some aspects of volcanic rocks of the valley of Mexico

Three periods of volcanic activity connected with tectonic events form the geological history of the Valley of Mexico (Mooser 1963, 1969). An igneous rock suite from rhyodacites to andesites (but lacking rhyolites and basalts) can be observed in each period. During the Tertiary epochs — in the Oligo-Miocene and Upper Miocene-Pliocene — we have a more dacitic volcanism, in the Quaternary epoch a more andesitic volcanism. This result was verified by calculating the average of all available and stratigraphically datable chemical analyses byGunn &Mooser (1971) andNegendank (1972). Using the average chemical composition of the Oligo-Miocene, Upper Miocene-Pliocene and Quaternary products the equivalent igneous rocks were computed using theRittmann-norms in theStreckeisen-Q-A-P-F double triangle with the following result (names in parenthesis are those using the classification ofMiddlemost (1973): Quaternary : quartz-latite-andesite (andesite) Upper Miocene-Pliocene : leuco-quartz-latite-andesite (high lime dacite) Oligo-Miocene : leuco-quartz-latite-andesite (high lime dacite) The equal average composition of the two groups of Tertiary volcanic rocks seems to support the theory of a uniform primary andesite magma apart from which of the two possible theories of petrogenesis one favors. The calculated average trace element abundances show high Cr- and Ni-values which suggests that mantle material was involved if we consider the Tertiary products as partial melting products of the lower crust. A more elegant hypothesis seems to be the model ofGunn &Mooser (1971), who consider these volcanic rocks as partial melting products of oceanic tholeiites or their high pressure derivatives in the sense ofRaleigh &Lee (1969).     

On the seismic response of under-designed caisson foundations

The seismic behaviour of caisson foundations supporting typical bridge piers is analysed with 3D finite elements, with due consideration to soil and interface nonlinearities. Single-degree-of freedom oscillators of varying mass and height, simulating heavily and lightly loaded bridge piers, founded on similar caissons are studied. Four different combinations of the static ( $\text{ FS }_\mathrm{V}$ FS V ) and seismic ( $\text{ FS }_\mathrm{E}$ FS E ) factors of safety are examined: (1) a lightly loaded ( $\text{ FS }_\mathrm{V}= 5$ FS V = 5 ) seismically under-designed ( $\text{ FS }_\mathrm{E} < 1$ FS E < 1 ) caisson, (2) a lightly loaded seismically over-designed ( $\text{ FS }_\mathrm{E} >1$ FS E > 1 ) caisson, (3) a heavily loaded ( $\text{ FS }_\mathrm{V} = 2.5$ FS V = 2.5 ) seismically under-designed ( $\text{ FS }_\mathrm{E} < 1$ FS E < 1 ) caisson and (4) a heavily loaded seismically over-designed caisson. The analysis is performed with use of seismic records appropriately modified so that the effective response periods (due to soil-structure-interaction effects) of the studied systems correspond to the same spectral acceleration, thus allowing their inelastic seismic performance to be compared on a fair basis. Key performance measures of the systems are then contrasted, such as: accelerations, displacements, rotations and settlements. It is shown that the performance of the lightly loaded seismically under-designed caisson is advantageous: not only does it reduce significantly the seismic load to the superstructure, but it also produces minimal residual displacements of the foundation. For heavily loaded foundations, however ( $\text{ FS }_{V} = 2.5$ FS V = 2.5 ), the performance of the two systems (over and under designed) is similar.