After the Christchurch earthquakes, the government declared about 8000 houses as Red Zoned, prohibiting further developments in these properties, and offering the owners to buy them out. The government provided two options for owners: the first was full payment for both land and dwelling at the 2007 property evaluation, the second was payment for land, and the rest to be paid by the owner’s insurance. Most people chose the second option. Using data from LINZ combined with data from StatNZ, this project empirically investigates what led people to choose this second option, and what were the implications of these choices for the owners’ wealth and income.
Within four weeks of the September 4 2010 Canterbury Earthquake a new, loosely-knit community group appeared in Christchurch under the banner of “Greening the Rubble.” The general aim of those who attended the first few meetings was to do something to help plug the holes that had already appeared or were likely to appear over the coming weeks in the city fabric with some temporary landscaping and planting projects. This article charts the first eighteen months of Greening the Rubble and places the initiative in a broader context to argue that although seismic events in Christchurch acted as a “call to palms,” so to speak, the city was already in need of some remedial greening. It concludes with a reflection on lessons learned to date by GTR and commentary on the likely issues ahead for this new mini-social-environmental movement in the context of a quake-affected and still quake-prone major New Zealand city. One of the key lessons for GTR and all of those involved in Christchurch recovery activities to date is that the city is still very much in the middle of the event and is to some extent a laboratory for seismic and agency management studies alike.
The city of Christchurch has experienced over 10,000 aftershocks since the 4th of September 2010 earthquake of which approximately 50 have been greater than magnitude 5. The damage caused to URM buildings in Christchurch over this sequence of earthquakes has been well documented. Due to the similarity in age and construction of URM buildings in Adelaide, South Australia and Christchurch (they are sister cities, of similar age and heritage), an investigation was conducted to learn lessons for Adelaide based on the Christchurch experience. To this end, the number of URM buildings in the central business districts of both cities, the extent of seismic strengthening that exists in both cities, and the relative earthquake hazards for both cities were considered. This paper will report on these findings and recommend strategies that the city of Adelaide could consider to significantly reduce the seismic risk posed by URM buildings in future earthquake.
The rapid classification of building damage states or placards after an earthquake is vital for enabling an efficient emergency response and informed decision-making for rehabilitation and recovery purposes. Traditional methods rely heavily on inspector-led on-site surveys, which are often time-consuming, resource-intensive, and susceptible to human error. This study introduces a machine learning-supported surrogate model designed to streamline the assessment of building damage, focusing on the automated assignment of damage placards within the context of New Zealand's post-earthquake evaluation frameworks. The study evaluates two key safety evaluation protocols—Rapid Building Assessment (RBA) and Detailed Damage Evaluation (DDE)—and integrates corresponding databases derived from the 2010–2011 Canterbury Earthquake Sequence (CES) in Christchurch. Six ML classifiers—Multilayer Perceptron (MLP), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbours (KNN), Gradient Boosting Classifier (GBC), and Gradient Bagging (GBag)—were rigorously tested across both databases. The results indicate that the RF-based surrogate model outperforms the other classifiers across both RBA and DDE protocols. Two distinct sets of critical predictors have been further identified for each protocol, allowing for the rapid retrieval of essential data for future on-site surveys, while retaining the RF model's predictive accuracy. The developed surrogate model provides a pragmatic tool for practising engineers to rapidly assign placards to damaged structures and for policymakers and building owners to make informed recovery decisions for earthquake-affected buildings.
The greater Wellington region, New Zealand, is highly vulnerable to large earthquakes. While attention has been paid to the consequences of earthquake damage to road, electricity and water supply networks, the consequences of wastewater network damage for public health, environmental health and habitability of homes remain largely unknown for Wellington City. The Canterbury and Kaikōura earthquakes have highlighted the vulnerability of sewerage systems to disruption during a disaster. Management of human waste is one of the critical components of disaster planning to reduce faecal-oral transmission of disease and exposure to disease-bearing vectors. In Canterbury and Kaikōura, emergency sanitation involved a combination of Port-a-loos, chemical toilets and backyard long-drops. While many lessons may be learned from experiences in Canterbury earthquakes, it is important to note that isolation is likely to be a much greater factor for Wellington households, compared to Christchurch, due to the potential for widespread landslides in hill suburbs affecting road access. This in turn implies that human waste may have to be managed onsite, as options such as chemical toilets and Port-a-loos rely completely on road access for delivering chemicals and collecting waste. While some progress has been made on options such as emergency composting toilets, significant knowledge gaps remain on how to safely manage waste onsite. In order to bridge these gaps, laboratory tests will be conducted through the second half of 2019 to assess the pathogen die-off rates in the composting toilet system with variables being the type of carbon bulking material and the addition of a Bokashi composting activator.
