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A regional shear-wave velocity (V S) model has been developed for the Groningen gas field in the Netherlands as the basis for seismic microzonation of an area of more than 1000 km 2. The V S model, extending to a depth of almost 1 km, is an essential input to the modelling of hazard and risk due to induced earthquakes in the region. The detailed V S profiles are constructed from a novel combination of three data sets covering different, partially overlapping depth ranges. The uppermost 50 m of the V S profiles are obtained from a high-resolution geological model with representative V S values assigned to the sediments. Field measurements of V S were used to derive representative V S values for the different types of sediments. The profiles from 50 to 120 m are obtained from inversion of surface waves recorded (as noise) during deep seismic reflection profiling of the gas reservoir. The deepest part of the profiles is obtained from sonic logging and V P-V S relationships based on measurements in deep boreholes. Criteria were established for the splicing of the three portions to generate continuous models over the entire depth range for use in site response calculations, for which an elastic half-space is assumed to exist below a Electronic supplementary material The online version of this article (

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Aleatory variability in ground-motion prediction, represented by the standard deviation (sigma) of a ground-motion prediction equation, exerts a very strong influence on the results of probabilistic seismic-hazard analysis (PSHA). This is especially so at the low annual exceedance frequencies considered for nuclear facilities; in these cases, even small reductions in sigma can have a marked effect on the hazard estimates. Proper separation and quantification of aleatory variability and epistemic uncertainty can lead to defensible reductions in sigma. One such approach is the single-station sigma concept, which removes that part of sigma corresponding to repeatable site-specific effects. However, the site-to-site component must then be constrained by site-specific measurements or else modeled as epistemic uncertainty and incorporated into the modeling of site effects. The practical application of the single-station sigma concept, including the characterization of the dynamic properties of the site and the incorporation of site-response effects into the hazard calculations, is illustrated for a PSHA conducted at a rock site under consideration for the potential construction of a nuclear power plant.

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The potential for building damage and personal injury due to induced earthquakes in the Groningen gas field is being modeled in order to inform risk management decisions. To facilitate the quantitative estimation of the induced seismic hazard and risk, a ground motion prediction model has been developed for response spectral accelerations and duration due to these earthquakes that originate within the reservoir at 3 km depth. The model is consistent with the motions recorded from small-magnitude events and captures the epistemic uncertainty associated with extrapolation to larger magnitudes. In order to reflect the conditions in the field, the model first predicts accelerations at a rock horizon some 800 m below the surface and then convolves these motions with frequency-dependent nonlinear amplification factors assigned to zones across the study area. The variability of the ground motions is modeled in all of its constituent parts at the rock and surface levels.

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The Kiban-Kyoshin network (KiK-net) database is an important resource for ground motion (GM) studies. The processing of the KiK-net records is a necessary first step to enable their use in engineering applications. In this manuscript we present a step-by-step automated protocol used to systematically process about 157,000 KiK-net strong ground motion records. The automated protocol includes the selection of the corner frequency for high-pass filtering. In addition, a comprehensive set of metadata was compiled for each record. As a part of the metadata collection, two algorithms were used to identify dependent and independent earthquakes. Earthquakes are also classified into active crustal or subduction type events; most of the GM records correspond to subduction type earthquakes. A flatfile with all the metadata and the spectral acceleration of the processed records is uploaded to NEEShub ( https://nees.org/resources/7849 , Dawood et al. 2014 ).