Liquefaction-induced lateral spreading during earthquakes poses a significant hazard to the built environment, as observed in Christchurch during the 2010 to 2011 Canterbury Earthquake Sequence (CES). It is critical that geotechnical earthquake engineers are able to adequately predict both the spatial extent of lateral spreads and magnitudes of associated ground movements for design purposes. Published empirical and semi-empirical models for predicting lateral spread displacements have been shown to vary by a factor of <0.5 to >2 from those measured in parts of Christchurch during CES. Comprehensive post- CES lateral spreading studies have clearly indicated that the spatial distribution of the horizontal displacements and extent of lateral spreading along the Avon River in eastern Christchurch were strongly influenced by geologic, stratigraphic and topographic features.
Semi-empirical models based on in-situ geotechnical tests have become the standard of practice for predicting soil liquefaction. Since the inception of the “simplified” cyclic-stress model in 1971, variants based on various in-situ tests have been developed, including the Cone Penetration Test (CPT). More recently, prediction models based soley on remotely-sensed data were developed. Similar to systems that provide automated content on earthquake impacts, these “geospatial” models aim to predict liquefaction for rapid response and loss estimation using readily-available data. This data includes (i) common ground-motion intensity measures (e.g., PGA), which can either be provided in near-real-time following an earthquake, or predicted for a future event; and (ii) geospatial parameters derived from digital elevation models, which are used to infer characteristics of the subsurface relevent to liquefaction. However, the predictive capabilities of geospatial and geotechnical models have not been directly compared, which could elucidate techniques for improving the geospatial models, and which would provide a baseline for measuring improvements. Accordingly, this study assesses the realtive efficacy of liquefaction models based on geospatial vs. CPT data using 9,908 case-studies from the 2010-2016 Canterbury earthquakes. While the top-performing models are CPT-based, the geospatial models perform relatively well given their simplicity and low cost. Although further research is needed (e.g., to improve upon the performance of current models), the findings of this study suggest that geospatial models have the potential to provide valuable first-order predictions of liquefaction occurence and consequence. Towards this end, performance assessments of geospatial vs. geotechnical models are ongoing for more than 20 additional global earthquakes.
Based on a qualitative study of four organisations involving 47 respondents following the extensive 2010 – 2011 earthquakes in Christchurch, New Zealand, this paper presents some guidance for human resource practitioners dealing with post-disaster recovery. A key issue is the need for the human resource function to reframe its practices in a post-disaster context, developing a specific focus on understanding and addressing changing employee needs, and monitoring the leadership behaviour of supervisors. This article highlights the importance of flexible organisational responses based around a set of key principles concerning communication and employee perceptions of company support.
Background Liquefaction induced land damage has been identified in more than 13 notable New Zealand earthquakes within the past 150 years, as presented on the timeline below. Following the 2010-2011 Canterbury Earthquake Sequence (CES), the consequences of liquefaction were witnessed first-hand in the city of Christchurch and as a result the demand for understanding this phenomenon was heightened. Government, local councils, insurers and many other stakeholders are now looking to research and understand their exposure to this natural hazard.
We present the initial findings from a study of adaptive resilience of lifelines organisations providing essential infrastructure services, in Christchurch, New Zealand following the earthquakes of 2010-2011. Qualitative empirical data was collected from 200 individuals in 11 organisations. Analysis using a grounded theory method identified four major factors that aid organisational response, recovery and renewal following major disruptive events. Our data suggest that quality of top and middle-level leadership, quality of external linkages, level of internal collaboration, ability to learn from experience, and staff well-being and engagement influence adaptive resilience. Our data also suggest that adaptive resilience is a process or capacity, not an outcome and that it is contextual. Post-disaster capacity/resources and post-disaster environment influence the nature of adaptive resilience.
