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Research papers, University of Canterbury Library

Background and methodology The Mw 7.8, 14th November 2016 earthquake centred (item b, figure 1) in the Hurunui District of the South Island, New Zealand, damaged critical infrastructure across North Canterbury and Marlborough. We investigate the impacts to infrastructure and adaptations to the resulting service disruption in four small rural towns (figure 1): Culverden (a), Waiau (c), Ward (d) and Seddon (e). This is accomplished though literary research, interviews and geospatial analysis. Illustrating our methods, we have displayed here a Hurunui District hazard map (figure 2b) and select infrastructure inventories (figures 2a, 3).

Research papers, University of Canterbury Library

We present ground motion simulations of the Porters Pass (PP) fault in the Canterbury region of New Zealand; a major active source near Christchurch city. The active segment of the PP fault has an inferred length of 82 km and a mostly strike-slip sense of movement. The PP fault slip makes up approximately 10% of the total 37 mm/yr margin-parallel plate motion and also comprises a significant proportion of the total strain budget in regional tectonics. Given that the closest segment of the fault is less than 45 km from Christchurch city, the PP fault is crucial for accurate earthquake hazard assessment for this major population centre. We have employed the hybrid simulation methodology of Graves and Pitarka (2010, 2015), which combines low (f<1 Hz) and high (f>1 Hz) frequencies into a broadband spectrum. We have used validations from three moderate magnitude events (𝑀𝑀4.6 Sept 04, 2010; 𝑀𝑀4.6 Nov 06, 2010; 𝑀𝑀4.9 Apr 29, 2011) to build confidence for the 𝑀𝑀 > 7 PP simulations. Thus far, our simulations include multiple rupture scenarios which test the impacts of hypocentre location and the finite-fault stochastic rupture representation of the source itself. In particular, we have identified the need to use location-specific 1D 𝑉𝑠/𝑉𝑝 models for the high frequency part of the simulations to better match observations.