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Research papers, University of Canterbury Library

One of the current challenges in physics-based ground-motion simulations is to refine the modeling of local site effects. These effects require a finer spatial resolution in the material modeling than that generally considered in regional-scale simulations. Because of this, empirical amplification factors are typically applied to capture these unmodeled phenomena. The ergodic nature of this approach suggests that there is room for improvement. In this study, the predictive capability of simulations is evaluated using alternative methods for capturing local site effects. In addition to the conventional empirical approach, two methods are examined that allow for more site-specific information to be incorporated: the square-root impedance method and the 1D time domain site-response analysis. The three approaches are tested using 1000+ observed ground motions from 150+ small-magnitude events (3.5 ≤ Mw ≤ 5.0), recorded at 20 strong-motion stationsin the Canterbury, New Zealand, region. These 20 well-characterized sites represent a wide range of soil conditions, including stiff gravels with Vs30 values greater than 500 m/s, and sand and silt deposits with Vs30 valuesless than 200 m/s. Multiple intensity measures are computed and prediction residuals are partitioned using mixed-effects regression to rigorously assess the relative performance of the different approaches considered. The results indicate that the benefit of using more sophisticated methods is highly dependent on the characteristics of the site. Key site parameters and trends are identified and discussed in light of the assumptions and limitations of each approach.

Research papers, University of Canterbury Library

This paper provides a summary of initial research results investigating systematic site effects from the prediction residuals of empirical- and physics-based ground-motion models (GMMs) for small magnitude (i.e., 3.5 ≤ MW ≤ 5) active shallow crustal earthquakes in New Zealand (NZ). Advancing ground-motion predictability through physics-based GMMs is an iterative process and requires addressing fundamental questions like: Is there salient physics which has been overlooked? Which geographic regions have predictions that significantly deviate from observations and why? Which sites exhibit systematic prediction residuals and how can the attributes influencing them be identified? This preliminary study examines these questions by classifying 171 sites from the Canterbury and Wellington regions into four geomorphic categories: basin, basin-edge, hill, and valley, following the categorisation by Nweke et al. (2022). Trends in the site-to-site residuals for each geomorphic category indicate apparent differences between the four categories, with residuals for valley sites illustrating a clear dependence with the inferred fundamental site period. Computed residuals from both empirical- and physics-based GMMs also provided insight into the role of site-specific attributes vs. the different prediction methods, assisting to understand the salient causes of these residuals.