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Research papers, University of Canterbury Library

Introduction This poster presents the inferred initial performance and recovery of the water supply network of Christchurch following the 22 February 2011 Mw 6.2 earthquake. Results are presented in a geospatial and temporal fashion. This work strengthens the current understanding of the restoration of such a system after a disaster and quantifies the losses caused by this earthquake in respect with the Christchurch community. Figure 1 presents the topology of the water supply network as well as the spatial distribution of the buildings and their use.

Research papers, University of Canterbury Library

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.

Research papers, University of Canterbury Library

essential systems upon which the well-being and functioning of societies depend. They deliver a service or a good to the population using a network, a combination of spatially-distributed links and nodes. As they are interconnected, network elements’ functionality is also interdependent. In case of a failure of one component, many others could be momentarily brought out-of-service. Further problems arise for buried infrastructure when it comes to buried infrastructure in earthquake and liquefaction-prone areas for the following reasons: • Technically more demanding inspections than those required for surface horizontal infrastructure • Infrastructure subject to both permanent ground displacement and transient ground deformation • Increase in network maintenance costs (i.e. deterioration due to ageing material and seismic hazard) These challenges suggest careful studies on network resilience will yield significant benefits. For these reasons, the potable water network of Christchurch city (Figure 1) has been selected for its well-characterized topology and its extensive repair dataset.

Research papers, University of Canterbury Library

Earthquake-triggered soil liquefaction caused extensive damage and heavy economic losses in Christchurch during the 2010-2011 Canterbury earthquakes. The most severe manifestations of liquefaction were associated with the presence of natural deposits of clean sands and silty sands of fluvial origin. However, liquefaction resistance of fines-containing sands is commonly inferred from empirical relationships based on clean sands (i.e. sands with less than 5% fines). Hence, existing evaluation methods have poor accuracy when applied to silty sands. Also, existing methods do not quantify appropriately the influence on liquefaction resistance of soil fabric and structure, which are unique to a specific depositional environment. This study looks at the influence of fines content, soil fabric (i.e. arrangement of soil particles) and structure (e.g. layering, segregation) on the undrained cyclic behaviour and liquefaction resistance of fines-containing sandy soils from Christchurch using Direct Simple Shear (DSS) tests on soil specimens reconstituted in the laboratory with the water sedimentation technique. The poster describes experimental procedures and presents early test results on two sands retrieved at two different sites in Christchurch.

Research papers, University of Canterbury Library

Earthquake-triggered soil liquefaction caused extensive damage and heavy economic losses in Christchurch during the 2010-2011 Canterbury earthquakes. The most severe manifestations of liquefaction were associated with the presence of natural deposits of clean sands and silty sands of fluvial origin. However, liquefaction resistance of fines-containing sands is commonly inferred from empirical relationships based on clean sands (i.e. sands with less than 5% fines). Hence, existing evaluation methods have poor accuracy when applied to silty sands. The liquefaction behaviour of Christchurch fines-containing (silty) sands is investigated through a series of Direct Simple Shear (DSS) tests. This type of test better resembles earthquake loading conditions in soil deposits compared to cyclic triaxial tests. Soil specimens are reconstituted in the laboratory with the water sedimentation technique. This preparation method yields soil fabrics similar to those encountered in fluvial soil deposits, which are common in the Christchurch area. Test results provide preliminary indications on how void ratio, relative density, preparation method and fines content influence the cyclic liquefaction behaviour of sand-silt mixtures depending on the properties of host sand and silt.

Research papers, University of Canterbury Library

The Canterbury Earthquake Sequence 2010-2011 (CES) induced widespread liquefaction in many parts of Christchurch city. Liquefaction was more commonly observed in the eastern suburbs and along the Avon River where the soils were characterised by thick sandy deposits with a shallow water table. On the other hand, suburbs to the north, west and south of the CBD (e.g. Riccarton, Papanui) exhibited less severe to no liquefaction. These soils were more commonly characterised by inter-layered liquefiable and non-liquefiable deposits. As part of a related large-scale study of the performance of Christchurch soils during the CES, detailed borehole data including CPT, Vs and Vp have been collected for 55 sites in Christchurch. For this subset of Christchurch sites, predictions of liquefaction triggering using the simplified method (Boulanger & Idriss, 2014) indicated that liquefaction was over-predicted for 94% of sites that did not manifest liquefaction during the CES, and under-predicted for 50% of sites that did manifest liquefaction. The focus of this study was to investigate these discrepancies between prediction and observation. To assess if these discrepancies were due to soil-layer interaction and to determine the effect that soil stratification has on the develop-ment of liquefaction and the system response of soil deposits.

Research papers, University of Canterbury Library

The greater Wellington region, New Zealand, is highly vulnerable to large earthquakes. While attention has been paid to the consequences of earthquake damage to road, electricity and water supply networks, the consequences of wastewater network damage for public health, environmental health and habitability of homes remain largely unknown for Wellington City. The Canterbury and Kaikōura earthquakes have highlighted the vulnerability of sewerage systems to disruption during a disaster. Management of human waste is one of the critical components of disaster planning to reduce faecal-oral transmission of disease and exposure to disease-bearing vectors. In Canterbury and Kaikōura, emergency sanitation involved a combination of Port-a-loos, chemical toilets and backyard long-drops. While many lessons may be learned from experiences in Canterbury earthquakes, it is important to note that isolation is likely to be a much greater factor for Wellington households, compared to Christchurch, due to the potential for widespread landslides in hill suburbs affecting road access. This in turn implies that human waste may have to be managed onsite, as options such as chemical toilets and Port-a-loos rely completely on road access for delivering chemicals and collecting waste. While some progress has been made on options such as emergency composting toilets, significant knowledge gaps remain on how to safely manage waste onsite. In order to bridge these gaps, laboratory tests will be conducted through the second half of 2019 to assess the pathogen die-off rates in the composting toilet system with variables being the type of carbon bulking material and the addition of a Bokashi composting activator.

Research papers, University of Canterbury Library

Geospatial liquefaction models aim to predict liquefaction using data that is free and readily-available. This data includes (i) common ground-motion intensity measures; and (ii) geospatial parameters (e.g., among many, distance to rivers, distance to coast, and Vs30 estimated from topography) which are used to infer characteristics of the subsurface without in-situ testing. Since their recent inception, such models have been used to predict geohazard impacts throughout New Zealand (e.g., in conjunction with regional ground-motion simulations). While past studies have demonstrated that geospatial liquefaction-models show great promise, the resolution and accuracy of the geospatial data underlying these models is notably poor. As an example, mapped rivers and coastlines often plot hundreds of meters from their actual locations. This stems from the fact that geospatial models aim to rapidly predict liquefaction anywhere in the world and thus utilize the lowest common denominator of available geospatial data, even though higher quality data is often available (e.g., in New Zealand). Accordingly, this study investigates whether the performance of geospatial models can be improved using higher-quality input data. This analysis is performed using (i) 15,101 liquefaction case studies compiled from the 2010-2016 Canterbury Earthquakes; and (ii) geospatial data readily available in New Zealand. In particular, we utilize alternative, higher-quality data to estimate: locations of rivers and streams; location of coastline; depth to ground water; Vs30; and PGV. Most notably, a region-specific Vs30 model improves performance (Figs. 3-4), while other data variants generally have little-to-no effect, even when the “standard” and “high-quality” values differ significantly (Fig. 2). This finding is consistent with the greater sensitivity of geospatial models to Vs30, relative to any other input (Fig. 5), and has implications for modeling in locales worldwide where high quality geospatial data is available.