TY - JOUR A1 - Händel, Annabel A1 - von Specht, Sebastian A1 - Kuehn, Nicolas M. A1 - Scherbaum, Frank T1 - Mixtures of ground-motion prediction equations as backbone models for a logic tree: an application to the subduction zone in Northern Chile JF - Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering N2 - In probabilistic seismic hazard analysis, different ground-motion prediction equations (GMPEs) are commonly combined within a logic tree framework. The selection of appropriate GMPEs, however, is a non-trivial task, especially for regions where strong motion data are sparse and where no indigenous GMPE exists because the set of models needs to capture the whole range of ground-motion uncertainty. In this study we investigate the aggregation of GMPEs into a mixture model with the aim to infer a backbone model that is able to represent the center of the ground-motion distribution in a logic tree analysis. This central model can be scaled up and down to obtain the full range of ground-motion uncertainty. The combination of models into a mixture is inferred from observed ground-motion data. We tested the new approach for Northern Chile, a region for which no indigenous GMPE exists. Mixture models were calculated for interface and intraslab type events individually. For each source type we aggregated eight subduction zone GMPEs using mainly new strong-motion data that were recorded within the Plate Boundary Observatory Chile project and that were processed within this study. We can show that the mixture performs better than any of its component GMPEs, and that it performs comparable to a regression model that was derived for the same dataset. The mixture model seems to represent the median ground motions in that region fairly well. It is thus able to serve as a backbone model for the logic tree. KW - Mixture model KW - Backbone model KW - Ground-motion prediction equation KW - Logic tree KW - Chile subduction zone Y1 - 2015 U6 - https://doi.org/10.1007/s10518-014-9636-7 SN - 1570-761X SN - 1573-1456 VL - 13 IS - 2 SP - 483 EP - 501 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Dahm, Torsten A1 - Kuehn, Daniela A1 - Ohrnberger, Matthias A1 - Kroeger, Jens A1 - Wiederhold, Helga A1 - Reuther, Claus-Dieter A1 - Dehghani, Ali A1 - Scherbaum, Frank T1 - Combining geophysical data sets to study the dynamics of shallow evaporites in urban environments : application to Hamburg, Germany N2 - Shallowly situated evaporites in built-up areas are of relevance for urban and cultural development and hydrological regulation. The hazard of sinkholes, subrosion depressions and gypsum karst is often difficult to evaluate and may quickly change with anthropogenic influence. The geophysical exploration of evaporites in metropolitan areas is often not feasible with active industrial techniques. We collect and combine different passive geophysical data as microgravity, ambient vibrations, deformation and hydrological information to study the roof morphology of shallow evaporites beneath Hamburg, Northern Germany. The application of a novel gravity inversion technique leads to a 3-D depth model of the salt diapir under study. We compare the gravity-based depth model to pseudo-depths from H/V measurements and depth estimates from small-scale seismological array data. While the general range and trend of the diapir roof is consistent, a few anomalous regions are identified where H/V pseudo-depths indicate shallower structures not observed in gravity or array data. These are interpreted by shallow residual caprock floaters and zones of increased porosity. The shallow salt structure clearly correlates with a relative subsidence in the order of 2 mm yr(-1). The combined interpretation of roof morphology, yearly subsidence rates, chemical analyses of groundwater and of hydraulic head in aquifers indicates that the salt diapir beneath Hamburg is subject to significant ongoing dissolution that may possibly affect subrosion depressions, sinkhole distribution and land usage. The combined analysis of passive geophysical data may be exemplary for the study of shallow evaporites beneath other urban areas. Y1 - 2010 UR - http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1365-246X U6 - https://doi.org/10.1111/j.1365-246X.2010.04521.x SN - 0956-540X ER - TY - JOUR A1 - Delavaud, Elise A1 - Cotton, Fabrice A1 - Akkar, Sinan A1 - Scherbaum, Frank A1 - Danciu, Laurentiu A1 - Beauval, Celine A1 - Drouet, Stephane A1 - Douglas, John A1 - Basili, Roberto A1 - Sandikkaya, M. Abdullah A1 - Segou, Margaret A1 - Faccioli, Ezio A1 - Theodoulidis, Nikos T1 - Toward a ground-motion logic tree for probabilistic seismic hazard assessment in Europe JF - Journal of seismology N2 - The Seismic Hazard Harmonization in Europe (SHARE) project, which began in June 2009, aims at establishing new standards for probabilistic seismic hazard assessment in the Euro-Mediterranean region. In this context, a logic tree for ground-motion prediction in Europe has been constructed. Ground-motion prediction equations (GMPEs) and weights have been determined so that the logic tree captures epistemic uncertainty in ground-motion prediction for six different tectonic regimes in Europe. Here we present the strategy that we adopted to build such a logic tree. This strategy has the particularity of combining two complementary and independent approaches: expert judgment and data testing. A set of six experts was asked to weight pre-selected GMPEs while the ability of these GMPEs to predict available data was evaluated with the method of Scherbaum et al. (Bull Seismol Soc Am 99:3234-3247, 2009). Results of both approaches were taken into account to commonly select the smallest set of GMPEs to capture the uncertainty in ground-motion prediction in Europe. For stable continental regions, two models, both from eastern North America, have been selected for shields, and three GMPEs from active shallow crustal regions have been added for continental crust. For subduction zones, four models, all non-European, have been chosen. Finally, for active shallow crustal regions, we selected four models, each of them from a different host region but only two of them were kept for long periods. In most cases, a common agreement has been also reached for the weights. In case of divergence, a sensitivity analysis of the weights on the seismic hazard has been conducted, showing that once the GMPEs have been selected, the associated set of weights has a smaller influence on the hazard. KW - Logic trees KW - Ground-motion prediction equations KW - Expert judgment KW - Model selection KW - Seismic hazard assessment Y1 - 2012 U6 - https://doi.org/10.1007/s10950-012-9281-z SN - 1383-4649 VL - 16 IS - 3 SP - 451 EP - 473 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Douglas, John A1 - Akkar, Sinan A1 - Ameri, Gabriele A1 - Bard, Pierre-Yves A1 - Bindi, Dino A1 - Bommer, Julian J. A1 - Bora, Sanjay Singh A1 - Cotton, Fabrice A1 - Derras, Boumediene A1 - Hermkes, Marcel A1 - Kuehn, Nicolas Martin A1 - Luzi, Lucia A1 - Massa, Marco A1 - Pacor, Francesca A1 - Riggelsen, Carsten A1 - Sandikkaya, M. Abdullah A1 - Scherbaum, Frank A1 - Stafford, Peter J. A1 - Traversa, Paola T1 - Comparisons among the five ground-motion models developed using RESORCE for the prediction of response spectral accelerations due to earthquakes in Europe and the Middle East JF - Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering N2 - This article presents comparisons among the five ground-motion models described in other articles within this special issue, in terms of data selection criteria, characteristics of the models and predicted peak ground and response spectral accelerations. Comparisons are also made with predictions from the Next Generation Attenuation (NGA) models to which the models presented here have similarities (e.g. a common master database has been used) but also differences (e.g. some models in this issue are nonparametric). As a result of the differing data selection criteria and derivation techniques the predicted median ground motions show considerable differences (up to a factor of two for certain scenarios), particularly for magnitudes and distances close to or beyond the range of the available observations. The predicted influence of style-of-faulting shows much variation among models whereas site amplification factors are more similar, with peak amplification at around 1s. These differences are greater than those among predictions from the NGA models. The models for aleatory variability (sigma), however, are similar and suggest that ground-motion variability from this region is slightly higher than that predicted by the NGA models, based primarily on data from California and Taiwan. KW - Strong-motion data KW - Ground-motion models KW - Ground-motion prediction equations KW - Style of faulting KW - Site amplification KW - Aleatory variability KW - Epistemic uncertainty KW - Europe KW - Middle East Y1 - 2014 U6 - https://doi.org/10.1007/s10518-013-9522-8 SN - 1570-761X SN - 1573-1456 VL - 12 IS - 1 SP - 341 EP - 358 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Molkenthin, Christian A1 - Scherbaum, Frank A1 - Griewank, Andreas A1 - Leovey, Hernan A1 - Kucherenko, Sergei A1 - Cotton, Fabrice T1 - Derivative-Based Global Sensitivity Analysis: Upper Bounding of Sensitivities in Seismic-Hazard Assessment Using Automatic Differentiation JF - Bulletin of the Seismological Society of America N2 - Seismic-hazard assessment is of great importance within the field of engineering seismology. Nowadays, it is common practice to define future seismic demands using probabilistic seismic-hazard analysis (PSHA). Often it is neither obvious nor transparent how PSHA responds to changes in its inputs. In addition, PSHA relies on many uncertain inputs. Sensitivity analysis (SA) is concerned with the assessment and quantification of how changes in the model inputs affect the model response and how input uncertainties influence the distribution of the model response. Sensitivity studies are challenging primarily for computational reasons; hence, the development of efficient methods is of major importance. Powerful local (deterministic) methods widely used in other fields can make SA feasible, even for complex models with a large number of inputs; for example, automatic/algorithmic differentiation (AD)-based adjoint methods. Recently developed derivative-based global sensitivity measures can combine the advantages of such local SA methods with efficient sampling strategies facilitating quantitative global sensitivity analysis (GSA) for complex models. In our study, we propose and implement exactly this combination. It allows an upper bounding of the sensitivities involved in PSHA globally and, therefore, an identification of the noninfluential and the most important uncertain inputs. To the best of our knowledge, it is the first time that derivative-based GSA measures are combined with AD in practice. In addition, we show that first-order uncertainty propagation using the delta method can give satisfactory approximations of global sensitivity measures and allow a rough characterization of the model output distribution in the case of PSHA. An illustrative example is shown for the suggested derivative-based GSA of a PSHA that uses stochastic ground-motion simulations. Y1 - 2017 U6 - https://doi.org/10.1785/0120160185 SN - 0037-1106 SN - 1943-3573 VL - 107 SP - 984 EP - 1004 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Esfahani, Reza Dokht Dolatabadi A1 - Vogel, Kristin A1 - Cotton, Fabrice A1 - Ohrnberger, Matthias A1 - Scherbaum, Frank A1 - Kriegerowski, Marius T1 - Exploring the dimensionality of ground-motion data by applying autoencoder techniques JF - Bulletin of the Seismological Society of America : BSSA N2 - In this article, we address the question of how observed ground-motion data can most effectively be modeled for engineering seismological purposes. Toward this goal, we use a data-driven method, based on a deep-learning autoencoder with a variable number of nodes in the bottleneck layer, to determine how many parameters are needed to reconstruct synthetic and observed ground-motion data in terms of their median values and scatter. The reconstruction error as a function of the number of nodes in the bottleneck is used as an indicator of the underlying dimensionality of ground-motion data, that is, the minimum number of predictor variables needed in a ground-motion model. Two synthetic and one observed datasets are studied to prove the performance of the proposed method. We find that mapping ground-motion data to a 2D manifold primarily captures magnitude and distance information and is suited for an approximate data reconstruction. The data reconstruction improves with an increasing number of bottleneck nodes of up to three and four, but it saturates if more nodes are added to the bottleneck. Y1 - 2021 U6 - https://doi.org/10.1785/0120200285 SN - 0037-1106 SN - 1943-3573 VL - 111 IS - 3 SP - 1563 EP - 1576 PB - Seismological Society of America CY - El Cerito, Calif. ER - TY - JOUR A1 - Al Atik, Linda A1 - Abrahamson, Norman A. A1 - Bommer, Julian J. A1 - Scherbaum, Frank A1 - Cotton, Fabrice A1 - Kuehn, Nicolas T1 - The variability of ground-motion prediction models and its components Y1 - 2010 UR - http://srl.geoscienceworld.org/ U6 - https://doi.org/10.1785/gssrl.81.5.794 SN - 0895-0695 ER - TY - JOUR A1 - Bommer, Julian J. A1 - Douglas, John A1 - Scherbaum, Frank A1 - Cotton, Fabrice A1 - Bungum, Hilmar A1 - Faeh, Donat T1 - On the selection of ground-motion prediction equations for seismic hazard analysis Y1 - 2010 UR - http://srl.geoscienceworld.org/ U6 - https://doi.org/10.1785/gssrl.81.5.783 SN - 0895-0695 ER - TY - JOUR A1 - Schroeter, Kai A1 - Kreibich, Heidi A1 - Vogel, Kristin A1 - Riggelsen, Carsten A1 - Scherbaum, Frank A1 - Merz, Bruno T1 - How useful are complex flood damage models? JF - Water resources research N2 - We investigate the usefulness of complex flood damage models for predicting relative damage to residential buildings in a spatial and temporal transfer context. We apply eight different flood damage models to predict relative building damage for five historic flood events in two different regions of Germany. Model complexity is measured in terms of the number of explanatory variables which varies from 1 variable up to 10 variables which are singled out from 28 candidate variables. Model validation is based on empirical damage data, whereas observation uncertainty is taken into consideration. The comparison of model predictive performance shows that additional explanatory variables besides the water depth improve the predictive capability in a spatial and temporal transfer context, i.e., when the models are transferred to different regions and different flood events. Concerning the trade-off between predictive capability and reliability the model structure seem more important than the number of explanatory variables. Among the models considered, the reliability of Bayesian network-based predictions in space-time transfer is larger than for the remaining models, and the uncertainties associated with damage predictions are reflected more completely. KW - floods KW - damage KW - model validation KW - Bayesian networks KW - regression tree Y1 - 2014 U6 - https://doi.org/10.1002/2013WR014396 SN - 0043-1397 SN - 1944-7973 VL - 50 IS - 4 SP - 3378 EP - 3395 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Molkenthin, Christian A1 - Scherbaum, Frank A1 - Griewank, Andreas A1 - Kühn, Nicolas A1 - Stafford, Peter J. A1 - Leovey, Hernan T1 - Sensitivity of Probabilistic Seismic Hazard Obtained by Algorithmic Differentiation: A Feasibility Study JF - Bulletin of the Seismological Society of America N2 - Probabilistic seismic-hazard analysis (PSHA) is the current tool of the trade used to estimate the future seismic demands at a site of interest. A modern PSHA represents a complex framework that combines different models with numerous inputs. It is important to understand and assess the impact of these inputs on the model output in a quantitative way. Sensitivity analysis is a valuable tool for quantifying changes of a model output as inputs are perturbed, identifying critical input parameters, and obtaining insight about the model behavior. Differential sensitivity analysis relies on calculating first-order partial derivatives of the model output with respect to its inputs; however, obtaining the derivatives of complex models can be challenging. In this study, we show how differential sensitivity analysis of a complex framework such as PSHA can be carried out using algorithmic/automatic differentiation (AD). AD has already been successfully applied for sensitivity analyses in various domains such as oceanography and aerodynamics. First, we demonstrate the feasibility of the AD methodology by comparing AD-derived sensitivities with analytically derived sensitivities for a basic case of PSHA using a simple ground-motion prediction equation. Second, we derive sensitivities via AD for a more complex PSHA study using a stochastic simulation approach for the prediction of ground motions. The presented approach is general enough to accommodate more advanced PSHA studies of greater complexity. Y1 - 2015 U6 - https://doi.org/10.1785/0120140294 SN - 0037-1106 SN - 1943-3573 VL - 105 IS - 3 SP - 1810 EP - 1822 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Molkenthin, Christian A1 - Scherbaum, Frank A1 - Griewank, Andreas A1 - Kuehn, Nicolas A1 - Stafford, Peter T1 - A Study of the sensitivity of response spectral amplitudes on seismological parameters using algorithmic differentiation JF - Bulletin of the Seismological Society of America N2 - Response spectra are of fundamental importance in earthquake engineering and represent a standard measure in seismic design for the assessment of structural performance. However, unlike Fourier spectral amplitudes, the relationship of response spectral amplitudes to seismological source, path, and site characteristics is not immediately obvious and might even be considered counterintuitive for high oscillator frequencies. The understanding of this relationship is nevertheless important for seismic-hazard analysis. The purpose of the present study is to comprehensively characterize the variation of response spectral amplitudes due to perturbations of the causative seismological parameters. This is done by calculating the absolute parameter sensitivities (sensitivity coefficients) defined as the partial derivatives of the model output with respect to its input parameters. To derive sensitivities, we apply algorithmic differentiation (AD). This powerful approach is extensively used for sensitivity analysis of complex models in meteorology or aerodynamics. To the best of our knowledge, AD has not been explored yet in the seismic-hazard context. Within the present study, AD was successfully implemented for a proven and extensively applied simulation program for response spectra (Stochastic Method SIMulation [SMSIM]) using the TAPENADE AD tool. We assess the effects and importance of input parameter perturbations on the shape of response spectra for different regional stochastic models in a quantitative way. Additionally, we perform sensitivity analysis regarding adjustment issues of groundmotion prediction equations. Y1 - 2014 U6 - https://doi.org/10.1785/0120140022 SN - 0037-1106 SN - 1943-3573 VL - 104 IS - 5 SP - 2240 EP - 2252 PB - Seismological Society of America CY - Albany ER - TY - JOUR A1 - Schmelzbach, C. A1 - Scherbaum, Frank A1 - Tronicke, Jens A1 - Dietrich, P. T1 - Bayesian frequency-domain blind deconvolution of ground-penetrating radar data JF - Journal of applied geophysics N2 - Enhancing the resolution and accuracy of surface ground-penetrating radar (GPR) reflection data by inverse filtering to recover a zero-phased band-limited reflectivity image requires a deconvolution technique that takes the mixed-phase character of the embedded wavelet into account. In contrast, standard stochastic deconvolution techniques assume that the wavelet is minimum phase and, hence, often meet with limited success when applied to GPR data. We present a new general-purpose blind deconvolution algorithm for mixed-phase wavelet estimation and deconvolution that (1) uses the parametrization of a mixed-phase wavelet as the convolution of the wavelet's minimum-phase equivalent with a dispersive all-pass filter, (2) includes prior information about the wavelet to be estimated in a Bayesian framework, and (3) relies on the assumption of a sparse reflectivity. Solving the normal equations using the data autocorrelation function provides an inverse filter that optimally removes the minimum-phase equivalent of the wavelet from the data, which leaves traces with a balanced amplitude spectrum but distorted phase. To compensate for the remaining phase errors, we invert in the frequency domain for an all-pass filter thereby taking advantage of the fact that the action of the all-pass filter is exclusively contained in its phase spectrum. A key element of our algorithm and a novelty in blind deconvolution is the inclusion of prior information that allows resolving ambiguities in polarity and timing that cannot be resolved using the sparseness measure alone. We employ a global inversion approach for non-linear optimization to find the all-pass filter phase values for each signal frequency. We tested the robustness and reliability of our algorithm on synthetic data with different wavelets, 1-D reflectivity models of different complexity, varying levels of added noise, and different types of prior information. When applied to realistic synthetic 2-D data and 2-D field data, we obtain images with increased temporal resolution compared to the results of standard processing. KW - Deconvolution KW - Inverse filtering KW - Ground penetrating radar KW - GPR KW - Data processing KW - Vertical resolution Y1 - 2011 U6 - https://doi.org/10.1016/j.jappgeo.2011.08.010 SN - 0926-9851 VL - 75 IS - 4 SP - 615 EP - 630 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Scherbaum, Frank A1 - Mzhavanadze, Nana A1 - Rosenzweig, Sebastian A1 - Müller, Meinard T1 - Tuning systems of traditional Georgian singing determined from a new corpus of field recordings JF - Musicologist N2 - In this study we examine the tonal organization of the 2016 GVM dataset, a newly-created corpus of high-quality multimedia field recordings of traditional Georgian singing with a focus on Svaneti. For this purpose, we developed a new processing pipeline for the computational analysis of non-western polyphonic music which was subsequently applied to the complete 2016 GVM dataset. To evaluate under what conditions a single tuning system is representative of current Svan performance practice, we examined the stability of the obtained tuning systems from an ensemble-, a song-, and a corpus-related perspective. Furthermore, we compared the resulting Svan tuning systems with the tuning systems obtained for the Erkomaishvili dataset (Rosenzweig et al., 2020) in the study by Scherbaum et al. (2020). In comparison to a 12-TET (12-tone-equal-temperament) system, the Erkomaishvili and the Svan tuning systems are surprisingly similar. Both systems show a strong presence of pure fourths (500 cents) and fifths (700 cents), and 'neutral' thirds (peaking around 350 cents) as well as 'neutral' sixths. In addition, the sizes of the melodic and the harmonic seconds in both tuning systems differ systematically from each other, with the size of the harmonic second being systematically larger than the melodic one. KW - traditional Georgian music KW - tuning KW - computational ethnomusicology Y1 - 2022 U6 - https://doi.org/10.33906/musicologist.1068947 SN - 2618-5652 VL - 6 IS - 2 SP - 142 EP - 168 PB - Trabzon Univ State Conservatory CY - Trabzon ER - TY - JOUR A1 - Scherbaum, Frank A1 - Cotton, Fabrice A1 - Staedtke, Helmut T1 - The estimation of minimum-misfit stochastic models from empirical ground-motion prediction equations N2 - In areas of moderate to low seismic activity there is commonly a lack of recorded strong ground motion. As a consequence, the prediction of ground motion expected for hypothetical future earthquakes is often performed by employing empirical models from other regions. In this context, Campbell's hybrid empirical approach (Campbell, 2003, 2004) provides a methodological framework to adapt ground-motion prediction equations to arbitrary target regions by using response spectral host-to-target-region-conversion filters. For this purpose, the empirical ground-motion prediction equation has to be quantified in terms of a stochastic model. The problem we address here is how to do this in a systematic way and how to assess the corresponding uncertainties. For the determination of the model parameters we use a genetic algorithm search. The stochastic model spectra were calculated by using a speed-optimized version of SMSIM (Boore, 2000). For most of the empirical ground-motion models, we obtain sets of stochastic models that match the empirical models within the full magnitude and distance ranges of their generating data sets fairly well. The overall quality of fit and the resulting model parameter sets strongly depend on the particular choice of the distance metric used for the stochastic model. We suggest the use of the hypocentral distance metric for the stochastic Simulation of strong ground motion because it provides the lowest-misfit stochastic models for most empirical equations. This is in agreement with the results of two recent studies of hypocenter locations in finite-source models which indicate that hypocenters are often located close to regions of large slip (Mai et al., 2005; Manighetti et al., 2005). Because essentially all empirical ground-motion prediction equations contain data from different geographical regions, the model parameters corresponding to the lowest-misfit stochastic models cannot necessarily be expected to represent single, physically realizable host regions but to model the generating data sets in an average way. In addition, the differences between the lowest-misfit stochastic models and the empirical ground-motion prediction equation are strongly distance, magnitude, and frequency dependent, which, according to the laws of uncertainty propagation, will increase the variance of the corresponding hybrid empirical model predictions (Scherbaum et al., 2005). As a consequence, the selection of empirical ground-motion models for host-to-target-region conversions requires considerable judgment of the ground-motion analyst Y1 - 2006 U6 - https://doi.org/10.1785/0120050015 ER - TY - JOUR A1 - Scherbaum, Frank A1 - Bommer, Julian J. A1 - Bungum, Hilmar A1 - Cotton, Fabrice A1 - Abrahamson, Norman A. T1 - Composite ground-motion models and logic trees: Methodology, sensitivities, and uncertainties N2 - Logic trees have become a popular tool in seismic hazard studies. Commonly, the models corresponding to the end branches of the complete logic tree in a probabalistic seismic hazard analysis (PSHA) are treated separately until the final calculation of the set of hazard curves. This comes at the price that information regarding sensitivities and uncertainties in the ground-motion sections of the logic tree are only obtainable after disaggregation. Furthermore, from this end-branch model perspective even the designers of the logic tree cannot directly tell what ground-motion scenarios most likely would result from their logic trees for a given earthquake at a particular distance, nor how uncertain these scenarios might be or how they would be affected by the choices of the hazard analyst. On the other hand, all this information is already implicitly present in the logic tree. Therefore, with the ground-motion perspective that we propose in the present article, we treat the ground-motion sections of a complete logic tree for seismic hazard as a single composite model representing the complete state-of-knowledge-and-belief of a particular analyst on ground motion in a particular target region. We implement this view by resampling the ground-motion models represented in the ground-motion sections of the logic tree by Monte Carlo simulation (separately for the median values and the sigma values) and then recombining the sets of simulated values in proportion to their logic-tree branch weights. The quantiles of this resampled composite model provide the hazard analyst and the decision maker with a simple, clear, and quantitative representation of the overall physical meaning of the ground-motion section of a logic tree and the accompanying epistemic uncertainty. Quantiles of the composite model also provide an easy way to analyze the sensitivities and uncertainties related to a given logic-tree model. We illustrate this for a composite ground- motion model for central Europe. Further potential fields of applications are seen wherever individual best estimates of ground motion have to be derived from a set of candidate models, for example, for hazard rnaps, sensitivity studies, or for modeling scenario earthquakes Y1 - 2005 SN - 0037-1106 ER - TY - JOUR A1 - Musson, R. M. W. A1 - Toro, G. R. A1 - Coppersmith, Kevin J. A1 - Bommer, Julian J. A1 - Deichmann, N. A1 - Bungum, Hilmar A1 - Cotton, Fabrice A1 - Scherbaum, Frank A1 - Slejko, Dario A1 - Abrahamson, Norman A. T1 - Evaluating hazard results for Switzerland and how not to do it : a discussion of "Problems in the application of the SSHAC probability method for assessing earthquake hazards at Swiss nuclear power plants" by J-U Klugel N2 - The PEGASOS project was a major international seismic hazard study, one of the largest ever conducted anywhere in the world, to assess seismic hazard at four nuclear power plant sites in Switzerland. Before the report of this project has become publicly available, a paper attacking both methodology and results has appeared. Since the general scientific readership may have difficulty in assessing this attack in the absence of the report being attacked, we supply a response in the present paper. The bulk of the attack, besides some misconceived arguments about the role of uncertainties in seismic hazard analysis, is carried by some exercises that purport to be validation exercises. In practice, they are no such thing; they are merely independent sets of hazard calculations based on varying assumptions and procedures, often rather questionable, which come up with various different answers which have no particular significance. (C) 2005 Elsevier B.V. All rights reserved Y1 - 2005 ER - TY - JOUR A1 - Bommer, Julian J. A1 - Abrahamson, Norman A. A1 - Strasser, F. O. A1 - Pecker, Alain A1 - Bard, Pierre-Yves A1 - Bungum, Hilmar A1 - Cotton, Fabrice A1 - Fäh, Donat A1 - Sabetta, F. A1 - Scherbaum, Frank A1 - Studer, Jost T1 - The challenge of defining upper bounds on earthquake ground motions Y1 - 2004 SN - 0895-0695 ER - TY - JOUR A1 - Scherbaum, Frank A1 - Cotton, Fabrice A1 - Smit, P. T1 - On the use of response spectral-reference data for the selection and ranking of ground-motion models for seismic-hazard analysis in regions of moderate seismicity : the case of rock motion N2 - The use of ground-motion-prediction equations to estimate ground shaking has become a very popular approach for seismic-hazard assessment, especially in the framework of a logic-tree approach. Owing to the large number of existing published ground-motion models, however, the selection and ranking of appropriate models for a particular target area often pose serious practical problems. Here we show how observed around-motion records can help to guide this process in a systematic and comprehensible way. A key element in this context is a new, likelihood based, goodness-of-fit measure that has the property not only to quantify the model fit but also to measure in some degree how well the underlying statistical model assumptions are met. By design, this measure naturally scales between 0 and 1, with a value of 0.5 for a situation in which the model perfectly matches the sample distribution both in terms of mean and standard deviation. We have used it in combination with other goodness-of-fit measures to derive a simple classification scheme to quantify how well a candidate ground-rnotion-prediction equation models a particular set of observed-response spectra. This scheme is demonstrated to perform well in recognizing a number of popular ground-motion models from their rock-site- recording, subsets. This indicates its potential for aiding the assignment of logic-tree weights in a consistent and reproducible way. We have applied our scheme to the border region of France, Germany, and Switzerland where the M-w 4.8 St. Die earthquake of 22 February 2003 in eastern France recently provided a small set of observed-response spectra. These records are best modeled by the ground-motion-prediction equation of Berge-Thierry et al. (2003), which is based on the analysis of predominantly European data. The fact that the Swiss model of Bay et al. (2003) is not able to model the observed records in an acceptable way may indicate general problems arising from the use of weak-motion data for strong-motion prediction Y1 - 2004 SN - 0037-1106 ER - TY - JOUR A1 - Scherbaum, Frank A1 - Schmedes, J. A1 - Cotton, Fabrice T1 - On the conversion of source-to-site distance measures for extended earthquake source models N2 - One of the major challenges in engineering seismology is the reliable prediction of site-specific ground motion for particular earthquakes, observed at specific distances. For larger events, a special problem arises, at short distances, with the source-to-site distance measure, because distance metrics based on a point-source model are no longer appropriate. As a consequence, different attenuation relations differ in the distance metric that they use. In addition to being a source of confusion, this causes problems to quantitatively compare or combine different ground- motion models; for example, in the context of Probabilistic Seismic Hazard Assessment, in cases where ground-motion models with different distance metrics occupy neighboring branches of a logic tree. In such a situation, very crude assumptions about source sizes and orientations often have to be used to be able to derive an estimate of the particular metric required. Even if this solves the problem of providing a number to put into the attenuation relation, a serious problem remains. When converting distance measures, the corresponding uncertainties map onto the estimated ground motions according to the laws of error propagation. To make matters worse, conversion of distance metrics can cause the uncertainties of the adapted ground-motion model to become magnitude and distance dependent, even if they are not in the original relation. To be able to treat this problem quantitatively, the variability increase caused by the distance metric conversion has to be quantified. For this purpose, we have used well established scaling laws to determine explicit distance conversion relations using regression analysis on simulated data. We demonstrate that, for all practical purposes, most popular distance metrics can be related to the Joyner-Boore distance using models based on gamma distributions to express the shape of some "residual function." The functional forms are magnitude and distance dependent and are expressed as polynomials. We compare the performance of these relations with manually derived individual distance estimates for the Landers, the Imperial Valley, and the Chi-Chi earthquakes Y1 - 2004 SN - 0037-1106 ER - TY - JOUR A1 - Bora, Sanjay Singh A1 - Cotton, Fabrice A1 - Scherbaum, Frank T1 - NGA-West2 Empirical Fourier and Duration Models to Generate Adjustable Response Spectra JF - Earthquake spectra : the professional journal of the Earthquake Engineering Research Institute N2 - Adjustment of median ground motion prediction equations (GMPEs) from one region to another region is one of the major challenges within the current practice of seismic hazard analysis. In our approach of generating response spectra, we derive two separate empirical models for a) Fourier amplitude spectrum (FAS) and b) duration of ground motion. To calculate response spectra, the two models are combined within the random vibration theory (RVT) framework. The models are calibrated on recordings obtained from shallow crustal earthquakes in active tectonic regions. We use a subset of NGA-West2 database with M3.2-7.9 earthquakes at distances 0-300 km. The NGA-West2 database expanded over a wide magnitude and distance range facilitates a better constraint over derived models. A frequency-dependent duration model is derived to obtain adjustable response spectral ordinates. Excellent comparison of our approach with other NGA-West2 models implies that it can also be used as a stand-alone model. Y1 - 2019 U6 - https://doi.org/10.1193/110317EQS228M SN - 8755-2930 SN - 1944-8201 VL - 35 IS - 1 SP - 61 EP - 93 PB - Sage Publ. CY - Thousand Oaks ER -