Results from a series of 1D seismic effective stress analyses of natural soil deposits from Christchurch are summarized. The analysed soil columns include sites whose performance during the 2010-2011 Canterbury earthquakes varied significantly, from no liquefaction manifestation at the ground surface to very severe liquefaction, in which case a large area of the site was covered by thick soil ejecta. Key soil profile characteristics and response mechanisms affecting the severity of surface liquefaction manifestation and subsequent damage are explored. The influence of shaking intensity on the triggering and contribution of these mechanisms is also discussed. Careful examination of the results highlights the importance of considering the deposit as a whole, i.e. a system of layers, including interactions between layers in the dynamic response and through pore water pressure redistribution and water flow.
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.
Developing a holistic understanding of social, cultural, and economic impacts of disasters can help in building disaster risk knowledge for policy making and planning. Many methods can help in developing an understanding of the impacts of a disaster, including interviews and surveys with people who have experienced disaster, which may be invasive at times and create stress for the participants to relive their experiences. In the past decade, social media, blog posts, video blogs (i.e. “vlogs”), and crowdsourcing mechanisms such as Humanitarian OpenStreetMap and Ushahidi, have become prominent platforms for people to share their experiences and impacts of an event from the ground. These platforms allow for the discovery of a range of impact information, from physical impacts, to social, cultural, and psychological impacts. It can also reveal interesting behavioural information such as their decision to heed a warning or not, as people tend to share their experiences and their reactions online. This information can help researchers and authorities understand both the impacts as well as behavioural responses to hazards, which can then shape how early warning systems are designed and delivered. It can also help to identify gaps in desired behavioural responses. This poster presents a selection of cases identified from the literature and grey literature, such as the Haiti earthquake, the Christchurch earthquake, Hurricane Sandy, and Hurricane Harvey, where online platforms were widely used during and after a disaster to document impacts, experiences, and behavioural responses. A summary of key learnings and areas for future research is provided.
This study explicitly investigates uncertainties in physics-based ground motion simulation validation for earthquakes in the Canterbury region. The simulations utilise the Graves and Pitarka (2015) hybrid methodology, with separately quantified parametric uncertainties in the comprehensive physics and simplified physics components of the model. The study is limited to the simulation of 148 small magnitude (Mw 3.5 – 5) earthquakes, with a point source approximation for the source rupture representations, which also enables a focus on a small number of relevant uncertainties. The parametric uncertainties under consideration were selected through sensitivity analysis, and specifically include: magnitude, Brune stress parameter and high frequency rupture velocity. Twenty Monte Carlo realisations were used to sample parameter uncertainties for each of the 148 events. Residuals associated with the following intensity measures: spectral acceleration, peak ground velocity, arias intensity and significant duration, were ascertained. Using these residuals, validation was performed through assessment of systematic biases in site and source terms from mixed-effects regression. Based on the results to date, initial standard deviation recommendations for parameter uncertainties, based on the Canterbury simulations have been obtained. This work ultimately provides an initial step toward explicit incorporation of modelling uncertainty in simulated ground motion predictions for future events, which will improve the use of simulation models in seismic hazard analysis. We plan to subsequently assess uncertainties for larger magnitude events with more complex ruptures, and events across a larger geographic region, as well as uncertainties due to path attenuation, site effects, and more general model epistemic uncertainties.
Natural hazards continue to have adverse effects on communities and households worldwide, accelerating research on proactively identifying and enhancing characteristics associated with resilience. Although resilience is often characterized as a return to normal, recent studies of postdisaster recovery have highlighted the ways in which new opportunities can emerge following disruption, challenging the status quo. Conversely, recovery and reconstruction may serve to reinforce preexisting social, institutional, and development pathways. Our understanding of these dynamics is limited however by the small number of practice examples, particularly for rural communities in developed nations. This study uses a social–ecological inventory to document the drivers, pathways, and mechanisms of resilience following a large-magnitude earthquake in Kaikōura, a coastal community in Aotearoa New Zealand. As part of the planning and implementation phase of a multiyear project, we used the tool as the basis for indepth and contextually sensitive analysis of rural resilience. Moreover, the deliberate application of social–ecological inventory was the first step in the research team reengaging with the community following the event. The inventory process provided an opportunity for research partners to share their stories and experiences and develop a shared understanding of changes that had taken place in the community. Results provide empirical insight into reactions to disruptive change associated with disasters. The inventory also informed the design of targeted research collaborations, established a platform for longer-term community engagement, and provides a baseline for assessing longitudinal changes in key resilience-related characteristics and community capacities. Findings suggest the utility of social–ecological inventory goes beyond natural resource management, and that it may be appropriate in a range of contexts where institutional, social, and economic restructuring have developed out of necessity in response to felt or anticipated external stressors.
