Well-validated liquefaction constitutive models are increasingly important as non-linear time history analyses become relatively more common in industry for key projects. Previous validation efforts of PM4Sand, a plasticity model specifically for liquefaction, have generally focused on centrifuge tests; however, pore pressure transducers installed at several free-field sites during the Canterbury Earthquake Sequence (CES) in Christchurch, New Zealand provide a relatively unique dataset to validate against. This study presents effective stress site response analyses performed in the finite difference software FLAC to examine the capability of PM4Sand to capture the generation of excess pore pressures during earthquakes. The characterization of the subsurface is primarily based on extensive cone penetration tests (CPT) carried out in Christchurch. Correlations based on penetration resistances are used to estimate soil parameters, such as relative density and shear wave velocity, which affect liquefaction behaviour. The resulting free-field FLAC model is used to estimate time histories of excess pore pressure, which are compared with records during several earthquakes in the CES to assess the suitability of PM4Sand.
Liquefaction-induced lateral spreading during the 2011 Christchurch earthquake in New Zealand was severe and extensive, and data regarding the displacements associated with the lateral spreading provides an excellent opportunity to better understand the factors that influence these movements. Horizontal displacements measured from optical satellite imagery and subsurface data from the New Zealand Geotechnical Database (NZGD) were used to investigate four distinct lateral spread areas along the Avon River in Christchurch. These areas experienced displacements between 0.5 and 2 m, with the inland extent of displacement ranging from 100 m to over 600 m. Existing empirical and semi-empirical displacement models tend to under estimate displacements at some sites and over estimate at others. The integrated datasets indicate that the areas with more severe and spatially extensive displacements are associated with thicker and more laterally continuous deposits of liquefiable soil. In some areas, the inland extent of displacements is constrained by geologic boundaries and geomorphic features, as expressed by distinct topographic breaks. In other areas the extent of displacement is influenced by the continuity of liquefiable strata or by the presence of layers that may act as vertical seepage barriers. These observations demonstrate the need to integrate geologic/geomorphic analyses with geotechnical analyses when assessing the potential for lateral spreading movements.
Research indicates that aside from the disaster itself, the next major source of adverse outcomes during such events, is from errors by either the response leader or organisation. Yet, despite their frequency, challenge, complexity, and the risks involved; situations of extreme context remain one of the least researched areas in the leadership field. This is perhaps surprising. In the 2010 and 2011 (Christchurch) earthquakes alone, 185 people died and rebuild costs are estimated to have been $40b. Add to this the damage and losses annually around the globe arising from natural disasters, major business catastrophes, and military conflict; there is certainly a lot at stake (lives, way of life, and our well-being). While over the years, much has been written on leadership, there is a much smaller subset of articles on leadership in extreme contexts, with the majority of these focusing on the event rather than leadership itself. Where leadership has been the focus, the spotlight has shone on the actions and capabilities of one person - the leader. Leadership, however, is not simply one person, it is a chain or network of people, delivering outcomes with the support of others, guided by a governance structure, contextualised by the environment, and operating on a continuum across time (before, during, and after an event). This particular research is intended to examine the following: • What are the leadership capabilities and systems necessary to deliver more successful outcomes during situations of extreme context; • How does leadership in these circumstances differ from leadership during business as usual conditions; • Lastly, through effective leadership, can we leverage these unfortunate events to thrive, rather than merely survive?
Tsunami events including the 2004 Indian Ocean Tsunami and the 2011 Tohoku Earthquake and Tsunami confirmed the need for Pacific-wide comprehensive risk mitigation and effective tsunami evacuation planning. New Zealand is highly exposed to tsunamis and continues to invest in tsunami risk awareness, readiness and response across the emergency management and science sectors. Evacuation is a vital risk reduction strategy for preventing tsunami casualties. Understanding how people respond to warnings and natural cues is an important element to improving evacuation modelling techniques. The relative rarity of tsunami events locally in Canterbury and also globally, means there is limited knowledge on tsunami evacuation behaviour, and tsunami evacuation planning has been largely informed by hurricane evacuations. This research aims to address this gap by analysing evacuation behaviour and movements of Kaikōura and Southshore/New Brighton (coastal suburb of Christchurch) residents following the 2016 Kaikōura earthquake. Stage 1 of the research is engaging with both these communities and relevant hazard management agencies, using a survey and community workshops to understand real-event evacuation behaviour during the 2016 Kaikōura earthquake and subsequent tsunami evacuations. The second stage is using the findings from stage 1 to inform an agent-based tsunami evacuation model, which is an approach that simulates of the movement of people during an evacuation response. This method improves on other evacuation modelling approaches to estimate evacuation times due to better representation of local population characteristics. The information provided by the communities will inform rules and interactions such as traffic congestion, evacuation delay times and routes taken to develop realistic tsunami evacuation models. This will allow emergency managers to more effectively prepare communities for future tsunami events, and will highlight recommended actions to increase the safety and efficiency of future tsunami evacuations.
