The Kaikōura Earthquake ruptured a complex network of at least 20 faults in the northeastern South Island, with variable geometries, slip and slip rates. Ground shaking and surface fault rupture generated a tsunami, thousands of landslides, and many dammed rivers. The earthquake damaged farmland, buildings and infrastructure in the northeastern South Island and Wellington regions, closing critical transport networks for over a year. This special issue presents a collection of 12 papers on the earthquake. These papers cover a range of topics, including, the geometries and paleoearthquake histories of faults that ruptured, seismic hazards, the tsunami and coastal geomorphology, together with the societal impact and communication of the earthquake. They incorporate our understanding of the earthquake 5–6 years since it occurred. Despite an unprecedented amount of data and thousands of published papers referring to the earthquake, many key questions remain. These include: is the Hikurangi subduction interface capable of producing great earthquakes beneath the northeastern South Island? Why did the Hope Fault not accommodate significant slip in the earthquake? Has the earthquake changed the seismic hazard in central Aotearoa New Zealand? Addressing these questions will improve understanding of seismic processes and hazards helping to build resilience to future earthquakes.
Transportation networks are critical infrastructure in urban environments. Before, during and following volcanic activity, these networks can incur direct and indirect impacts, which subsequently reduces the Level-of-Service available to transportation end-users. Additionally, reductions in service can arise from management strategies including evacuation zoning, causing additional complications for transportation end-users and operators. Here, we develop metrics that incorporate Level-of-Service for transportation end-users as the key measure of vulnerability for multi-hazard volcanic impact and risk assessments. A hypothetical eruption scenario recently developed for the Auckland Volcanic Field, New Zealand, is applied to describe potential impacts of a small basaltic eruption on different transportation modes, namely road, rail, and activities at airports and ports. We demonstrate how the new metrics can be applied at specific locations worldwide by considering the geophysical hazard sequence and evacuation zones in this scenario, a process that was strongly informed by consultation with transportation infrastructure providers and emergency management officials. We also discuss the potential implications of modified hazard sequences (e.g. different wind profiles during the scenario, and unrest with no resulting eruption) on transportation vulnerability and population displacement. The vent area of the eruption scenario used in our study is located north of the Māngere Bridge suburb of Auckland. The volcanic activity in the scenario progresses from seismic unrest, through phreatomagmatic explosions generating pyroclastic surges to a magmatic phase generating a scoria cone and lava flows. We find that most physical damage to transportation networks occurs from pyroclastic surges during the initial stages of the eruption. However, the most extensive service reduction across all networks occurs ~ 6 days prior to the eruption onset, largely attributed to the implementation of evacuation zones; these disrupt crucial north-south links through the south eastern Auckland isthmus, and at times cause up to ~ 435,000 residents and many businesses to be displaced. Ash deposition on road and rail following tephra-producing eruptive phases causes widespread Level-of-Service reduction, and some disruption continues for > 1 month following the end of the eruption until clean-up and re-entry to most evacuated zones is completed. Different tephra dispersal and deposition patterns can result in substantial variations to Level-of-Service and consequences for transportation management. Additional complexities may also arise during times of unrest with no eruption, particularly as residents are potentially displaced for longer periods of time due to extended uncertainties on potential vent location. The Level-of-Service metrics developed here effectively highlight the importance of considering transportation end-users when developing volcanic impact and risk assessments. We suggest that the metrics are universally applicable in other urban environments.
Tephra falls can cause a range of impacts to communities by disrupting, contaminating and damaging buildings and infrastructure systems, as well as posing a potential health hazard. Coordinated clean-up operations minimise the impacts of tephra on social and economic activities. However, global experience suggests clean-up operations are one of the most challenging aspects of responding to and recovering from tephra falls in urban environments. Here, we present a method for modelling coordinated municipal-led (town/district level authorities) tephra clean-up operations to support pre-event response and recovery planning. The model estimates the volume of tephra to be removed, clean-up duration, and direct costs. The underpinning component of the model is a scalable clean-up response framework, which identifies and progressively includes more urban surfaces (e.g., roofs, and roads) requiring clean-up with increasing tephra thickness. To demonstrate model applicability, we present four clean-up scenarios for the city of Auckland, New Zealand: 1 mm and 10 mm distal tephra fall across the city, along with two local 'wet' eruption scenarios (low and high volume tephra deposition) from within the Auckland Volcanic Field. Depending on the modelled scenario, outputs suggest that coordinated clean-up operations in Auckland could require the removal of tens of thousands to millions of cubic metres of tephra. The cost of these operations are estimated to be NZ$0.6–1.1 million (US$0.4–0.7 million) for the 1 mm distal tephra scenario and NZ$13.4–25.6 million (US$9–17 million) for the 10 mm distal tephra scenario. Estimated clean-up costs of local eruptions range from tens of millions to hundreds of millions of dollars. All eruption scenarios indicate clean-up operations lasting weeks to months, but clean-up in some areas impacted by local eruptions could last for years. The model outputs are consistent with documented historic tephra clean-up operations. Although we use Auckland as a proof-of-concept example, the method may be adapted for any city exposed to a tephra hazard.
Understanding the potential impacts of a large tsunami on a coastal region enables better planning of disaster management strategies. Potential housing damage, habitability, human displacement and sheltering needs are key concerns for emergency managers following tsunami events. This article presents a novel approach to address these requirements. We first review available literature on factors influencing residential habitability, human displacement and sheltering needs following disasters. Existing models are reviewed to identify lessons, gaps and opportunities that can inform the development of a new model. We then present a new model for estimating habitability, displacement and sheltering needs for tsunami (HDS-T). The model uses an additive scoring system incorporating both physical and demographic factors, weighted according to their relative influence. We demonstrate application of HDS-T through the case study of three tsunami scenarios affecting the coastal city of Christchurch, New Zealand. The results are time-varying, reflecting the response and early recovery phase of the tsunami events. For the largest scenario, 14,695 residents are displaced on the first day, with 1795 displaced residents requiring sheltering assistance. The number of displaced residents reduces to 9014 on Day 4, 7131 on Day 7, and 4366 at the time point of one month. HDS-T is designed to be adaptable to other natural hazards and contexts, such as earthquakes.
Abstract Auckland is the largest city in New Zealand (pop. 1.5 million) and is situated atop an active monogenetic volcanic field. When volcanic activity next occurs, the most effective means of protecting the people who reside and work in the region will be to evacuate the danger zone prior to the eruption. This study investigates the evacuation demand throughout the Auckland Volcanic Field and the capacity of the transportation network to fulfil such a demand. Diurnal movements of the population are assessed and, due to the seemingly random pattern of eruptions in the past, a non-specific approach is adopted to determine spatial vulnerabilities at a micro-scale (neighbourhoods). We achieve this through the calculation of population-, household- and car-to-exit capacity ratios. Following an analysis of transportation hub functionality and the susceptibility of motorway bridges to a new eruption, modelling using dynamic route and traffic assignment was undertaken to determine various evacuation attributes at a macro-scale and forecast total network clearance times. Evacuation demand was found to be highly correlated to diurnal population movements and neighbourhood boundary types, a trend that was also evident in the evacuation capacity ratio results. Elevated population to evacuation capacity ratios occur during the day in and around the central city, and at night in many of the outlying suburbs. Low-mobility populations generally have better than average access to public transportation. Macro-scale vulnerability was far more contingent upon the destination of evacuees, with favourable results for evacuation within the region as opposed to outside the region. Clearance times for intra-regional evacuation ranged from one to nine hours, whereas those for inter-regional evacuation were found to be so high, that the results were unrealistic. Therefore, we conclude that, from a mobility standpoint, there is considerable merit to intra-regional evacuation.
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