Geology topics

Brendon A. Bradley

Publications and source records attributed to Brendon A. Bradley.

5 recordsLinked to original sources

USGS2022

Hybrid broadband ground-motion simulation validation of small magnitude active shallow crustal earthquakes in New Zealand

This article presents a comprehensive validation of the hybrid broadband ground-motion simulation approach (via the commonly used Graves and Pitarka method) in a New Zealand context with small magnitude point source ruptures using an extensive set of 5218 ground motions recorded at 212 sites from 479 active shallow crustal earthquakes across the country. Modifications to the simulation method inferred from a previous New Zealand validation are implemented, and the improvements are explicitly quantified. Empirical ground-motion models are also considered to provide a benchmark for simulation prediction accuracy and precision. Examination of intensity measure residuals identifies that the simulation method modifications lead to reduced model prediction bias and within-event variability and provides evidence toward the use of spatially varying coefficient models for simulation parameters, such as the high-frequency Brune stress parameter. Additional biases identified include, among others, underprediction of significant durations at soft soil sites and overprediction of short-period pseudo-spectral accelerations at stiff alluvial gravel and rock sites due to low-estimated 30 m time-averaged shear-wave velocity values.

Earthquake Spectra↗

USGS2020

Hybrid broadband ground motion simulation validation of small magnitude earthquakes in Canterbury, New Zealand

Ground motion simulation validation is an important and necessary task toward establishing the efficacy of physics-based ground motion simulations for seismic hazard analysis and earthquake engineering applications. This article presents a comprehensive validation of the commonly used Graves and Pitarka hybrid broadband ground motion simulation methodology with a recently developed three-dimensional (3D) Canterbury Velocity Model. This is done through simulation of 148 small magnitude earthquake events in the Canterbury, New Zealand, region in order to supplement prior validation efforts directed at several larger magnitude events. Recent empirical ground motion models are also considered to benchmark the simulation predictive capability, which is examined by partitioning the prediction residuals into the various components of ground motion variability. Biases identified in source, path, and site components suggest that improvements to the predictive capabilities of the simulation methodology can be made by using a longer high-frequency path duration model, reducing empirical V s 30 -based low-frequency site amplification, and utilizing site-specific velocity models in the high-frequency simulations.

Canterbury↗

USGS2018

Broadband ground‐motion simulation of the 2011 Mw 6.2 Christchurch, New Zealand, earthquake

This study presents the details and results of hybrid broadband (0–10 Hz) ground‐motion simulations for the 2011 M w "> M w Mw 6.2 Christchurch, New Zealand, earthquake. The simulations utilize a 3D velocity model and a kinematic source model with stochastic realizations of the slip amplitude, rise time, and rake angle. The resulting ground motions capture the salient basin amplification effects that are seen in the observed ground motions in central Christchurch city. Quantitative comparisons of the simulations with both observed recordings and empirical ground‐motion models (GMMs), considering peak ground acceleration, 5% damped pseudospectral acceleration, and 5%–95% significant duration, indicate that the simulations exhibit lower bias than empirical GMMs over the T = 1 – 10    s "> T = 1 – 10 s T=1–10 s period range, and are comparable at short periods ( ⁠ T < 1    s "> T < 1 s T<1 s ⁠ ). Sensitivity analyses suggest that the effect of stochastic realizations of different slip distributions is relatively small because of the fault dimensions. It is also illustrated that the effect of slip distribution variability is only a small component of the total uncertainty in ground‐motion simulation. As well as the important implications toward ground‐motion simulation validation, the presented simulations provide ground‐motion time series that can be used for forensic structural and geotechnical case histories that are located sufficiently far from strong‐motion station recordings.

Christchurch↗

USGS2018

Landslides triggered by the 14 November 2016 Mw 7.8 Kaikōura Earthquake, New Zealand

The 14 November 2016 M w "> M w Mw 7.8 Kaikōura earthquake generated more than 10,000 landslides over a total area of about 10 , 000    km 2 "> 10 , 000 km 2 10,000 km2 , with the majority concentrated in a smaller area of about 3600    km 2 "> 3600 km 2 3600 km2 . The largest landslide triggered by the earthquake had an approximate volume of 20 ( ± 2 )    M   m 3 "> 20 ( ± 2 ) M m 3 20(±2) M m3 , with a runout distance of about 2.7 km, forming a dam on the Hapuku River. In this article, we present version 1.0 of the landslide inventory we have created for this event. We use the inventory presented in this article to identify and discuss some of the controls on the spatial distribution of landslides triggered by the Kaikōura earthquake. Our main findings are (1) the number of medium to large landslides (source area ≥ 10 , 000    m 2 "> ≥ 10 , 000 m 2 ≥10,000 m2 ) triggered by the Kaikōura earthquake is smaller than for similar‐sized landslides triggered by similar magnitude earthquakes in New Zealand; (2) seven of the largest eight landslides (from 5 to 20    M   m 3 "> 20 M m 3 20 M m3 ) occurred on faults that ruptured to the surface during the earthquake; (3) the average landslide density within 200 m of a mapped surface fault rupture is three times that at a distance of 2500 m or more from a mapped surface fault rupture; (4) the “distance to fault” predictor variable, when used as a proxy for ground‐motion intensity, and when combined with slope angle, geology, and elevation variables, has more power in predicting landslide probability than the modeled peak ground acceleration or peak ground velocity; and (5) for the same slope angles, the coastal slopes have landslide point densities that are an order of magnitude greater than those in similar materials on the inland slopes, but their source areas are significantly smaller.

Bulletin of the Seismological Society of America↗

USGS2018

Spatial and spectral interpolation of ground-motion intensity measure observations

Following a significant earthquake, ground‐motion observations are available for a limited set of locations and intensity measures (IMs). Typically, however, it is desirable to know the ground motions for additional IMs and at locations where observations are unavailable. Various interpolation methods are available, but because IMs or their logarithms are normally distributed, spatially correlated, and correlated with each other at a given location, it is possible to apply the conditional multivariate normal (MVN) distribution to the problem of estimating unobserved IMs. In this article, we review the MVN and its application to general estimation problems, and then apply the MVN to the specific problem of ground‐motion IM interpolation. In particular, we present (1) a formulation of the MVN for the simultaneous interpolation of IMs across space and IM type (most commonly, spectral response at different oscillator periods) and (2) the inclusion of uncertain observation data in the MVN formulation. These techniques, in combination with modern empirical ground‐motion models and correlation functions, provide a flexible framework for estimating a variety of IMs at arbitrary locations.

Bulletin of the Seismological Society of America↗