1. Background and Objectives This poster presents results from ground motion simulations of small-to-moderate magnitude (3.5≤Mw≤5.0) earthquake events in the Canterbury, New Zealand region using the Graves and Pitarka (2010,2015) methodology. Subsequent investigation of systematic ground motion effects highlights the prediction bias in the simulations which are also benchmarked against empirical ground motion models (e.g. Bradley (2013)). In this study, 144 earthquake ruptures, modelled as point sources, are considered with 1924 quality-assured ground motions recorded across 45 strong motion stations throughout the Canterbury region, as shown in Figure 1. The majority of sources are Mw≥4.0 and have centroid depth (CD) 10km or shallower. Earthquake source descriptions were obtained from the GeoNet New Zealand earthquake catalogue. The ground motion simulations were performed within a computational domain of 140km x 120km x 46km with a finite difference grid spacing of 0.1km. The low-frequency (LF) simulations utilize the 3D Canterbury Velocity Model while the high-frequency (HF) simulations utilize a generic regional 1D velocity model. In the LF simulations, a minimum shear wave velocity of 500m/s is enforced, yielding a maximum frequency of 1.0Hz.
Critical infrastructure networks are highly relied on by society such that any disruption to service can have major social and economic implications. Furthermore, these networks are becoming increasingly dependent on each other for normal operation such that an outage or asset failure in one system can easily propagate and cascade across others resulting in widespread disruptions in terms of both magnitude and spatial reach. It is the vulnerability of these networks to disruptions and the corresponding complexities in recovery processes which provide direction to this research. This thesis comprises studies contributing to two areas (i) the modelling of national scale in-terdependent infrastructure systems undergoing major disruptions, and (ii) the tracking and quantification of infrastructure network recovery trajectories following major disruptions. Firstly, methods are presented for identifying nationally significant systemic vulnerabilities and incorporating expert knowledge into the quantification of infrastructure interdependency mod-elling and simulation. With application to the interdependent infrastructures networks across New Zealand, the magnitudes and spatial extents of disruption are investigated. Results high-light the importance in considering interdependencies when assessing disruptive risks and vul-nerabilities in disaster planning applications and prioritising investment decisions for enhancing resilience of national networks. Infrastructure dependencies are further studied in the context of recovery from major disruptions through the analysis of curves measuring network functionality over time. Continued studies into the properties of recovery curves across a database of global natural disasters produce statistical models for predicting the trajectory and expected recovery times. Finally, the use of connectivity based metrics for quantifying infrastructure system functionality during recovery are considered with a case study application to the Christchurch Earthquake (February 22, 2011) wastewater network response.
Damage distribution maps from strong earthquakes and recorded data from field experiments have repeatedly shown that the ground surface topography and subsurface stratigraphy play a decisive role in shaping the ground motion characteristics at a site. Published theoretical studies qualitatively agree with observations from past seismic events and experiments; quantitatively, however, they systematically underestimate the absolute level of topographic amplification up to an order of magnitude or more in some cases. We have hypothesized in previous work that this discrepancy stems from idealizations of the geometry, material properties, and incident motion characteristics that most theoretical studies make. In this study, we perform numerical simulations of seismic wave propagation in heterogeneous media with arbitrary ground surface geometry, and compare results with high quality field recordings from a site with strong surface topography. Our goal is to explore whether high-fidelity simulations and realistic numerical models can – contrary to theoretical models – capture quantitatively the frequency and amplitude characteristics of topographic effects. For validation, we use field data from a linear array of nine portable seismometers that we deployed on Mount Pleasant and Heathcote Valley, Christchurch, New Zealand, and we compute empirical standard spectral ratios (SSR) and single-station horizontal-to-vertical spectral ratios (HVSR). The instruments recorded ambient vibrations and remote earthquakes for a period of two months (March-April 2017). We next perform two-dimensional wave propagation simulations using the explicit finite difference code FLAC. We construct our numerical model using a high-resolution (8m) Digital Elevation Map (DEM) available for the site, an estimated subsurface stratigraphy consistent with the geomorphology of the site, and soil properties estimated from in-situ and non-destructive tests. We subject the model to in-plane and out-of-plane incident motions that span a broadband frequency range (0.1-20Hz). Numerical and empirical spectral ratios from our blind prediction are found in very good quantitative agreement for stations on the slope of Mount Pleasant and on the surface of Heathcote Valley, across a wide range of frequencies that reveal the role of topography, soil amplification and basin edge focusing on the distribution of ground surface motion.
