Active faults capable of generating highly damaging earthquakes may not cause surface rupture (i.e., blind faults) or cause surface ruptures that evade detection due to subsequent burial or erosion by surface processes. Fault populations and earthquake frequency-‐magnitude distributions adhere to power laws, implying that faults too small to cause surface rupture but large enough to cause localized strong ground shaking densely populate continental crust. The rupture of blind, previously undetected faults beneath Christchurch, New Zealand in a suite of earthquakes in 2010 and 2011, including the fatal 22 February 2011 moment magnitude (Mw) 6.2 Christchurch earthquake and other large aftershocks, caused a variety of environmental impacts, including major rockfall, severe liquefaction, and differential surface uplift and subsidence. All of these effects occurred where geologic evidence for penultimate effects of the same nature existed. To what extent could the geologic record have been used to infer the presence of proximal, blind and / or unidentified faults near Christchurch? In this instance, we argue that phenomena induced by high intensity shaking, such as rock fragmentation and rockfall, revealed the presence of proximal active faults in the Christchurch area prior to the recent earthquake sequence. Development of robust earthquake shaking proxy datasets should become a higher scientific priority, particularly in populated regions.
Since the early 1980s seismic hazard assessment in New Zealand has been based on Probabilistic Seismic Hazard Analysis (PSHA). The most recent version of the New Zealand National Seismic Hazard Model, a PSHA model, was published by Stirling et al, in 2012. This model follows standard PSHA principals and combines a nation-wide model of active faults with a gridded point-source model based on the earthquake catalogue since 1840. These models are coupled with the ground-motion prediction equation of McVerry et al (2006). Additionally, we have developed a time-dependent clustering-based PSHA model for the Canterbury region (Gerstenberger et al, 2014) in response to the Canterbury earthquake sequence. We are now in the process of revising that national model. In this process we are investigating several of the fundamental assumptions in traditional PSHA and in how we modelled hazard in the past. For this project, we have three main focuses: 1) how do we design an optimal combination of multiple sources of information to produce the best forecast of earthquake rates in the next 50 years: can we improve upon a simple hybrid of fault sources and background sources, and can we better handle the uncertainties in the data and models (e.g., fault segmentation, frequency-magnitude distributions, time-dependence & clustering, low strain-rate areas, and subduction zone modelling)? 2) developing revised and new ground-motion predictions models including better capturing of epistemic uncertainty – a key focus in this work is developing a new strong ground motion catalogue for model development; and 3) how can we best quantify if changes we have made in our modelling are truly improvements? Throughout this process we are working toward incorporating numerical modelling results from physics based synthetic seismicity and ground-motion models.
Natural disasters are increasingly disruptive events that affect livelihoods, organisations, and economies worldwide. Research has identified the impacts and responses of organisations to different types of natural disasters, and have outlined factors, such as industry sector, that are important to organisational vulnerability and resilience. One of the most costly types of natural disasters in recent years has been earthquakes, and yet to date, the majority of studies have focussed on the effects of earthquakes in urban areas, while rural organisational impact studies have primarily focused on the effects of meteorological and climatic driven hazards. As a result, the likely impacts of an earthquake on rural organisations in a developed context is unconstrained in the literature. In countries like New Zealand, which have major earthquakes and agricultural sectors that are significant contributors to the economy, it is important to know what impacts an earthquake event would have on the rural industries, and how these impacts compare to that of a more commonly analysed, high-frequency event. In September of 2010, rural organisations in Canterbury experienced the 4 September 2010 Mw 7.1 `Darfield' earthquake and the associated aftershocks, which came to be known as the Canterbury earth- quake sequence. The earthquake sequence caused intense ground shaking, creating widespread critical service outages, structural and non-structural damage to built infrastructure, as well as ground surface damage from ooding, liquefaction and surface rupture. Concurrently on September 18 2010, rural organisations in Southland experienced an unseasonably late snowstorm and cold weather snap that brought prolonged sub-zero temperatures, high winds and freezing rain, damaging structures in the City of Invercargill and causing widespread livestock losses and production decreases across the region. This thesis documents the effects of the Canterbury earthquake sequence and Southland snowstorm on farming and rural non-farming organisations, utilizing comparable methodologies to analyse rural organisational impacts, responses and recovery strategies to natural disasters. From the results, a short- term impact assessment methodology is developed for multiple disasters. Additionally, a regional asset repair cost estimation model is proposed for farming organisations following a major earthquake event, and the use of social capital in rural organisational recovery strategies following natural disasters is analysed.
