The city of Christchurch and its surrounds experienced widespread damage due to soil liquefaction induced by seismic shaking during the Canterbury earthquake sequence that began in September 2010 with the Mw7.1 Darfield earthquake. Prior to the start of this sequence, the city had a large network of strong motion stations (SMSs) installed, which were able to record a vast database of strong ground motions. This paper uses this database of strong ground motion recordings, observations of liquefaction manifestation at the ground surface, and data from a recently completed extensive geotechnical site investigation program at each SMS to assess a range of liquefaction evaluation procedures at the four SMSs in the Christchurch Central Business District (CBD). In general, the characteristics of the accelerograms recorded at each SMS correlated well with the liquefaction evaluation procedures, with low liquefaction factors of safety predicted at sites with clear liquefaction identifiers in the ground motions. However, at sites that likely liquefied at depth (as indicated by evaluation procedures and/or inferred from the characteristics of the recorded surface accelerograms), the presence of a non-liquefiable crust layer at many of the SMS locations prevented the manifestation of any surface effects. Because of this, there was not a good correlation between surface manifestation and two surface manifestation indices, the Liquefaction Potential Index (LPI) and the Liquefaction Severity Number (LSN).
None
None
This paper presents a methodology by which both site-specific and spatially distributed ground motion intensity can be obtained immediately following an earthquake event. The methodology makes use of both prediction models for ground motion intensity and its correlation over spatial distances. A key benefit of the methodology is that the ground motion intensity at a given location is not a single value but a distribution of values. The distribution is comprised of both a mean and also standard deviation, with the standard deviation being a function of the distance to nearby strong motion stations. The methodology is illustrated for two applications. Firstly, maps of conditional peak ground acceleration (PGA) have been developed for the major events in the Canterbury earthquake sequence. It is illustrated how these conditional maps can be used for post-event evaluation of liquefaction triggering criteria which have been adopted by the Department of Building and Housing (DBH). Secondly, the conditional distribution of response spectral ordinates is obtained at a specific location for the purposes of determining appropriate ground motion records for use in seismic response analyses of important structures at locations where direct recordings are absent.
Novel Gel-push sampling was employed to obtain high quality samples of Christchurch sands from the Central Business District, at sites where liquefaction was observed in 22 February 2011, and 13 June 2011 earthquakes. The results of cyclic triaxial testing on selected undisturbed specimens of typical Christchurch sands are presented and compared to empirical procedures used by practitioners. This comparison suggests cyclic triaxial data may be conservative, and the Magnitude Scaling Factor used in empirical procedures may be unconservative for highly compressible soils during near source moderate to low magnitude events. Comparison to empirical triggering curves suggests the empirical method generally estimates the cyclic strength of Christchurch sands within a reasonable degree of accuracy as a screening evaluation tool for liquefaction hazard, however for sands with moderate to high fines content it may be significantly unconservative, highlighting the need for high quality sampling and testing on important projects where seismic performance is critical.
The potential for a gastroenteritis outbreak in a post-earthquake environment may increase because of compromised infrastructure services, contaminated liquefaction (lateral spreading and surface ejecta), and the presence of gastroenteritis agents in the drinking water network. A population in a post-earthquake environment might be seriously affected by gastroenteritis because it has a short incubation period (about 10 hours). The potential for a gastroenteritis outbreak in a post-earthquake environment may increase because of compromised infrastructure services, contaminated liquefaction (lateral spreading and surface ejecta), and the presence of gastroenteritis agents in the drinking water network. A population in a post-earthquake environment might be seriously affected by gastroenteritis because it has a short incubation period (about 10 hours). The aim of this multidisciplinary research was to retrospectively analyse the gastroenteritis prevalence following the February 22, 2011 earthquake in Christchurch. The first focus was to assess whether earthquake-induced infrastructure damage, liquefaction, and gastroenteritis agents spatially explained the recorded gastroenteritis cases over the period of 35 days following the February 22, 2011 earthquake in Christchurch. The gastroenteritis agents considered in this study were Escherichia coli found in the drinking water supply (MPN/100mL) and Non-Compliant Free Associated Chlorine (FAC-NC) (less than <0.02mg/L). The second focus was the protocols that averted a gastroenteritis outbreak at three Emergency Centres (ECs): Burnside High School Emergency Centre (BEC); Cowles Stadium Emergency Centre (CEC); and Linwood High School Emergency Centre (LEC). Using a mixed-method approach, gastroenteritis point prevalence and the considered factors were quantitatively analysed. The qualitative analysis involved interviewing 30 EC staff members. The data was evaluated by adopting the Grounded Theory (GT) approach. Spatial analysis of considered factors showed that highly damaged CAUs were statistically clustered as demonstrated by Moran’s I statistic and hot spot analysis. Further modelling showed that gastroenteritis point prevalence clustering could not be fully explained by infrastructure damage alone, and other factors influenced the recorded gastroenteritis point prevalence. However, the results of this research suggest that there was a tenuous, indirect relationship between recorded gastroenteritis point prevalence and the considered factors: earthquake-induced infrastructure damage, liquefaction and FAC-NC. Two ECs were opened as part of the post-earthquake response in areas with severe infrastructure damage and liquefaction (BEC and CEC). The third EC (CEC) provided important lessons that were learnt from the previous September 4, 2010 earthquake, and implemented after the February 22, 2011 earthquake. Two types of interwoven themes identified: direct and indirect. The direct themes were preventive protocols and indirect themes included type of EC building (school or a sports stadium), and EC staff. The main limitations of the research were Modifiable Areal Units (MAUP), data detection, and memory loss. This research provides a practical method that can be adapted to assess gastroenteritis risk in a post-earthquake environment. Thus, this mixed method approach can be used in other disaster contexts to study gastroenteritis prevalence, and can serve as an appendage to the existing framework for assessing infectious diseases. Furthermore, the lessons learnt from qualitative analysis can inform the current infectious disease management plans, designed for a post-disaster response in New Zealand and internationally Using a mixed-method approach, gastroenteritis point prevalence and the considered factors were quantitatively analysed. A damage profile was created by amalgamating different types of damage for the considered factors for each Census Area Unit (CAU) in Christchurch. The damage profile enabled the application of a variety of statistical methods which included Moran’s I , Hot Spot (HS) analysis, Spearman’s Rho, and Besag–York–Mollié Model using a range of software. The qualitative analysis involved interviewing 30 EC staff members. The data was evaluated by adopting the Grounded Theory (GT) approach. Spatial analysis of considered factors showed that highly damaged CAUs were statistically clustered as demonstrated by Moran’s I statistic and hot spot analysis. Further modelling showed that gastroenteritis point prevalence clustering could not be fully explained by infrastructure damage alone, and other factors influenced the recorded gastroenteritis point prevalence. However, the results of this research suggest that there was a tenuous, indirect relationship between recorded gastroenteritis point prevalence and the considered factors: earthquake-induced infrastructure damage, liquefaction and FAC-NC. Two ECs were opened as part of the post-earthquake response in areas with severe infrastructure damage and liquefaction (BEC and CEC). The third EC (CEC) provided important lessons that were learnt from the previous September 4, 2010 earthquake, and implemented after the February 22, 2011 earthquake. The ECs were selected to represent the Christchurch area, and were situated where potential for gastroenteritis was high. BEC represented the western side of Christchurch; whilst, CEC and LEC represented the eastern side, where the potential for gastroenteritis was high according to the outputs of the quantitative spatial modelling. Qualitative analysis from the interviews at the ECs revealed that evacuees were arriving at the ECs with gastroenteritis-like symptoms. Participants believed that those symptoms did not originate at the ECs. Two types of interwoven themes identified: direct and indirect. The direct themes were preventive protocols that included prolific use of hand sanitisers; surveillance; and the services offered. Indirect themes included the EC layout, type of EC building (school or a sports stadium), and EC staff. Indirect themes governed the quality and sustainability of the direct themes implemented, which in turn averted gastroenteritis outbreaks at the ECs. The main limitations of the research were Modifiable Areal Units (MAUP), data detection, and memory loss. It was concluded that gastroenteritis point prevalence following the February 22, 2011 earthquake could not be solely explained by earthquake-induced infrastructure damage, liquefaction, and gastroenteritis causative agents alone. However, this research provides a practical method that can be adapted to assess gastroenteritis risk in a post-earthquake environment. Creating a damage profile for each CAU and using spatial data analysis can isolate vulnerable areas, and qualitative data analysis provides localised information. Thus, this mixed method approach can be used in other disaster contexts to study gastroenteritis prevalence, and can serve as an appendage to the existing framework for assessing infectious diseases. Furthermore, the lessons learnt from qualitative analysis can inform the current infectious disease management plans, designed for a post-disaster response in New Zealand and internationally.
