ALBERT

Description: We present a quantitative procedure for constraining probabilistic seismic hazard analysis results at a given site, based on the existence of fragile geologic structures at that site. We illustrate this procedure by analyzing precarious rocks and undamaged lithophysae at Yucca Mountain, Nevada. The key metric is the probability that the feature would have survived to the present day, assuming that the hazard results are correct. If the fragile geologic structure has an extremely low probability of having survived (which would be inconsistent with the observed survival of the structure), then the calculations illustrate how much the hazard would have to be reduced to result in a nonnegligible survival probability. The calculations are able to consider structures the predicted failure probabilities of which are a function of one or more ground-motion parameters, as well as structures that either rapidly or slowly evolved to their current state over time. These calculations are the only way to validate seismic hazard curves over long periods of time.

Description: We estimate the a rms -stress drop, , ( Hanks, 1979 ) using acceleration time records of 59 earthquakes from two earthquake sequences in eastern Honshu, Japan. These acceleration-based static stress drops compare well to stress drops calculated for the same events by Baltay et al. (2011) using an empirical Green’s function (eGf) approach. This agreement supports the assumption that earthquake acceleration time histories in the bandwidth between the corner frequency and a maximum observed frequency can be considered white, Gaussian, noise. Although the is computationally simpler than the eGf-based -stress drop, and is used as the "stress parameter" to describe the earthquake source in ground-motion prediction equations, we find that it only compares well to the at source-station distances of ~20 km or less because there is no consideration of whole-path anelastic attenuation or scattering. In these circumstances, the correlation between the and is strong. Events with high and low stress drops obtained through the eGf method have similarly high and low . We find that the inter-event standard deviation of stress drop, for the population of earthquakes considered, is similar for both methods, 0.40 for the method and 0.42 for the , in log 10 units, provided we apply the ~20 km distance restriction to . This indicates that the observed variability is inherent to the source, rather than attributable to uncertainties in stress-drop estimates. Online Material: Earthquake catalog including additional source parameters.

Description: INTRODUCTION Large earthquakes strike infrequently and close-in recordings are uncommon. This situation makes it difficult to predict the ground motion very close to earthquake-generating faults, if the prediction is to be based on readily available observations. A solution might be to cover the Earth with seismic instruments so that one could rely on the data from previous events to predict future shaking. However, even in the case of complete seismic data coverage for hundreds of years, there would still be one type of earthquake that would be difficult to predict: those very rare earthquakes that produce very large ground motion. These extreme-ground-motion events are so unlikely that most engineers would not even consider designing facilities to withstand the possibility of their occurrence. An exception would be a structure that needs to remain functional for an unusually long period of time. One example of a planned long-life structure has been the high-level nuclear waste repository at Yucca Mountain, Nevada. This structure has been envisioned as one that would perform reliably over tens of thousands of years (CRWMS M&O, 1998). The problem of predicting the maximum possible ground motion in the Yucca Mountain region has been studied using two approaches: a geological approach that examines evidence from the past, and a seismological approach that predicts possibilities for the future via computer simulations. Both strategies are described in detail in Hanks et al. (forthcoming). The seismological approach involved computer simulations that invoked a "physical limits" perspective. Calculations were performed to numerically simulate the largest possible earthquake-generated ground motions that could occur, while remaining faithful to the current state of knowledge about rock physics and wave propagation. These "physical limit" simulations were specifically applied to scenario earthquakes on the faults on and near Yucca Mountain (Andrews et al. 2007). In...

Description: Magnitude ( M )–log area ( A ) relations have been the focus of considerable research in the past two decades because of their importance in estimating moment magnitude M for earthquake probability calculations and seismic-hazard analysis. For M 〈6.5 earthquakes, with source dimensions less than the seismogenic width W , there is a strong consensus for constant stress-drop scaling. For the larger earthquakes ( M 〉7) that dominate the moment balancing in continental crust, the L -model scaling employed by Hanks and Bakun (2002 , 2008 ) involves fault slip growing with fault length L when L 〉 W ~15 km or so, requiring that static stress drops increase with increasing fault slip. Constant stress-drop representations of the same larger-earthquake data, such as Shaw (2009 , 2013 ), require slip at depths significantly greater than W ~15 km. Available evidence supports neither of these requirements leaving us perplexed as to how large-earthquake ruptures initiate and propagate in continental crust. Deep slip M –log A models that involve an unknown amount of seismic moment/earthquake slip at unknown depths〉 W are not appropriate for use in earthquake probability studies governed by shallow-slip (depths≤ W ) seismic moment/earthquake slip balancing, such as those in California during the twenty-first century.

Description: The Next Generation Attenuation-West 2 (NGA-West 2) 2014 ground-motion prediction equations (GMPEs) model ground motions as a function of magnitude and distance, using empirically derived coefficients (e.g., Bozorgnia et al. , 2014 ); as such, these GMPEs do not clearly employ earthquake source parameters beyond moment magnitude ( M ) and focal mechanism. To better understand the magnitude-dependent trends in the GMPEs, we build a comprehensive earthquake source-based model to explain the magnitude dependence of peak ground acceleration and peak ground velocity in the NGA-West 2 ground-motion databases and GMPEs. Our model employs existing models ( Hanks and McGuire, 1981 ; Boore, 1983 , 1986 ; Anderson and Hough, 1984 ) that incorporate a point-source Brune model, including a constant stress drop and the high-frequency attenuation parameter 0 , random vibration theory, and a finite-fault assumption at the large magnitudes to describe the data from magnitudes 3 to 8. We partition this range into four different magnitude regions, each of which has different functional dependences on M . Use of the four magnitude partitions separately allows greater understanding of what happens in any one subrange, as well as the limiting conditions between the subranges. This model provides a remarkably good fit to the NGA data for magnitudes from 3〈 M 〈8 at close rupture distances ( R rup ≤20 km). We explore the trade-offs between and 0 in ground-motion models and data, which play an important role in understanding small-magnitude data, for which the corner frequency is masked by the attenuation of high frequencies. That this simple, source-based model matches the NGA-West 2 GMPEs and data so well suggests that considerable simplicity underlies the parametrically complex NGA GMPEs. Online Material: Figures providing detail on the V S 30 distribution in the subset of the Next Generation Attenuation-West 2 (NGA-West 2) data used, the quarter-wavelength amplifications used in the model, the statistical test for the large magnitude portion of the model, and the magnitude dependence.

Description: The basic physics of earthquakes is such that strong ground motion cannot be expected from an earthquake unless the earthquake itself is very close or has grown to be very large. We use simple seismological relationships to calculate the minimum time that must elapse before such ground motion can be expected at a distance from the earthquake, assuming that the earthquake magnitude is not predictable. Earthquake early warning (EEW) systems are in operation or development for many regions around the world, with the goal of providing enough warning of incoming ground shaking to allow people and automated systems to take protective actions to mitigate losses. However, the question of how much warning time is physically possible for specified levels of ground motion has not been addressed. We consider a zero-latency EEW system to determine possible warning times a user could receive in an ideal case. In this case, the only limitation on warning time is the time required for the earthquake to evolve and the time for strong ground motion to arrive at a user’s location. We find that users who wish to be alerted at lower ground motion thresholds will receive more robust warnings with longer average warning times than users who receive warnings for higher ground motion thresholds. EEW systems have the greatest potential benefit for users willing to take action at relatively low ground motion thresholds, whereas users who set relatively high thresholds for taking action are less likely to receive timely and actionable information.

Description: Residuals between ground‐motion data and ground‐motion prediction equations (GMPEs) can be decomposed into terms representing earthquake source, path, and site effects. These terms can be cast in terms of repeatable (epistemic) residuals and the random (aleatory) components. Identifying the repeatable residuals leads to a GMPE with reduced uncertainty for a specific source, site, or path location, which in turn can yield a lower hazard level at small probabilities of exceedance. We illustrate a schematic framework for this residual partitioning with a dataset from the ANZA network, which straddles the central San Jacinto fault in southern California. The dataset consists of more than 3200 1.15≤M≤3 earthquakes and their peak ground accelerations (PGAs), recorded at close distances (⁠ R≤20  km ⁠). We construct a small‐magnitude GMPE for these PGA data, incorporating VS30 site conditions and geometrical spreading. Identification and removal of the repeatable source, path, and site terms yield an overall reduction in the standard deviation from 0.97 (in ln units) to 0.44, for a nonergodic assumption, that is, for a single‐source location, single site, and single path. We give examples of relationships between independent seismological observables and the repeatable terms. We find a correlation between location‐based source terms and stress drops in the San Jacinto fault zone region; an explanation of the site term as a function of kappa, the near‐site attenuation parameter; and a suggestion that the path component can be related directly to elastic structure. These correlations allow the repeatable source location, site, and path terms to be determined a priori using independent geophysical relationships. Those terms could be incorporated into location‐specific GMPEs for more accurate and precise ground‐motion prediction.