Pumice materials, which are problematic from an engineering viewpoint, are widespread in the central part of the North Island. Considering the impacts of the 2010-2011 Christchurch earthquakes, a clear understanding of their properties under earthquake loading is necessary. For example, the 1987 Edgecumbe earthquake showed evidence of localised liquefaction of sands of volcanic origin. To elucidate on this, research was undertaken to investigate whether existing empirical field-based methods to evaluate the liquefaction potential of sands, which were originally developed for hard-grained soils, are applicable to crushable pumice-rich deposits. For this purpose, two sites, one in Whakatane and another in Edgecumbe, were selected where the occurrence of liquefaction was reported following the Edgecumbe earthquake. Manifestations of soil liquefaction, such as sand boils and ejected materials, have been reported at both sites. Field tests, including cone penetration tests (CPT), shear-wave velocity profiling, and screw driving sounding (SDS) tests were performed at the sites. Then, considering estimated peak ground accelerations (PGAs) at the sites based on recorded motions and possible range of ground water table locations, liquefaction analysis was conducted at the sites using available empirical approaches. To clarify the results of the analysis, undisturbed soil samples were obtained at both sites to investigate the laboratory-derived cyclic resistance ratios and to compare with the field-estimated values. Research results clearly showed that these pumice-rich soils do not fit existing liquefaction assessment frameworks and alternate methods are necessary to characterise them.
There is a growing awareness of the need for the earthquake engineering practice to incorporate in addition to empirical approaches in evaluation of liquefaction hazards advanced methods which can more realistically represent soil behaviour during earthquakes. Currently, this implementation is hindered by a number of challenges mainly associated with the amount of data and user-experience required for such advanced methods. In this study, we present key steps of an advanced seismic effective-stress analysis procedure, which on the one hand can be fully automated and, on the other hand, requires no additional input (at least for preliminary applications) compared to simplified cone penetration test (CPT)-based liquefaction procedures. In this way, effective-stress analysis can be routinely applied for quick, yet more robust estimations of liquefaction hazards, in a similar fashion to the simplified procedures. Important insights regarding the dynamic interactions in liquefying soils and the actual system response of a deposit can be gained from such analyses, as illustrated with the application to two sites from Christchurch, New Zealand.
Soil-structure interaction (SSI) has been widely studied during the last decades. The influence of the properties of the ground motion, the structure and the soil have been addressed. However, most of the studies in this field consider a stand-alone structure. This assumption is rarely justifiable in dense urban areas where structures are built close to one another. The dynamic interaction between adjacent structures has been studied since the early 1970s, mainly using numerical and analytical models. Even though the early works in this field have significantly contributed to understanding this problem, they commonly consider important simplifications such as assuming a linear behaviour of the structure and the soil. Some experimental works addressing adjacent structures have recently been conducted using geotechnical centrifuges and 1g shake tables. However, further research is needed to enhance the understanding of this complex phenomenon. A particular case of SSI is that of structures founded in fine loose saturated sandy soil. An iconic example was the devastating effects of liquefaction in Christchurch, New Zealand, during the Canterbury earthquake in 2011. In the case of adjacent structures on liquefiable soil, the experimental evidence is even scarcer. The present work addresses the dynamic interaction between adjacent structures by performing multiple experimental studies. The work starts with two-adjacent structures on a small soil container to expose the basics of the problem. Later, results from tests considering a more significant number of structures on a big laminar box filled with sand are presented. Finally, the response of adjacent structures on saturated sandy soil is addressed using a geotechnical centrifuge and a large 1g shake table. This research shows that the acceleration, lateral displacement, foundation rocking, damping ratio, and fundamental frequency of the structure of focus are considerably affected by the presence of neighbouring buildings. In general, adjacent buildings reduced the dynamic response of the structure of focus on dry sand. However, the acceleration was amplified when the structures had a similar fundamental frequency. In the case of structures on saturated sand, the presence of adjacent structures reduced the liquefaction potential. Neighbouring structures on saturated sand also presented larger rotation of the footing and lateral displacement of the top mass than that of the stand-alone case.
The Canterbury Earthquake Sequence (CES), induced extensive damage in residential buildings and led to over NZ$40 billion in total economic losses. Due to the unique insurance setting in New Zealand, up to 80% of the financial losses were insured. Over the CES, the Earthquake Commission (EQC) received more than 412,000 insurance claims for residential buildings. The 4 September 2010 earthquake is the event for which most of the claims have been lodged with more than 138,000 residential claims for this event only. This research project uses EQC claim database to develop a seismic loss prediction model for residential buildings in Christchurch. It uses machine learning to create a procedure capable of highlighting critical features that affected the most buildings loss. A future study of those features enables the generation of insights that can be used by various stakeholders, for example, to better understand the influence of a structural system on the building loss or to select appropriate risk mitigation measures. Previous to the training of the machine learning model, the claim dataset was supplemented with additional data sourced from private and open access databases giving complementary information related to the building characteristics, seismic demand, liquefaction occurrence and soil conditions. This poster presents results of a machine learning model trained on a merged dataset using residential claims from the 4 September 2010.
Global biodiversity is threatened by human actions, including in urban areas. Urbanisation has removed and fragmented indigenous habitats. As one of the 25 biodiversity ’hot spots’, New Zealand is facing the problems of habitat loss and indigenous species extinction. In New Zealand cities, as a result of the land clearance and imported urban planning precepts, many urban areas have little or no original native forest remaining. Urbanisation has also been associated with the introduction of multitudes of species from around the world.
Two large earthquakes shook Christchurch in 2010 and 2011 and caused a lot of damage. Parts of the city suffered from soil liquefaction after the earthquakes. In the most damaged parts of Christchurch, particularly in the east, whole neighbourhoods were abandoned and later demolished except for larger trees.
Christchurch offers an excellent opportunity to study the biodiversity responses to an urban area with less intensive management, and to learn more about the conditions in urban environments that are most conducive to indigenous plant biodiversity.
This study focuses on natural woody plant regeneration of forested sites in Christchurch city, many of which were also surveyed prior to the earthquakes. By repeating the pre-earthquake surveys, I am able to describe the natural regeneration occurring in Christchurch forested areas. By combining this with the regeneration that has occurred in the Residential Red Zone, successional trajectories can be described under a range of management scenarios. Using a comprehensive tree map of the Residential Red Zone, I was also able to document minimum dispersal distances of a range of indigenous trees in Christchurch. This is important for planning reserve connectivity. Moreover, I expand and improve on a previous analysis of the habitat connectivity of Christchurch (made before the earthquakes) to incorporate the Residential Red Zone, to assess the importance for habitat connectivity of restoring the indigenous forest in this area. In combination, these data sets are used to provide patch scenarios and some management options for biodiversity restoration in the Ōtākaro-Avon Red Zone post-earthquake.
