Liquefaction assessment of highway networks using geospatial models

Assessment of liquefaction hazard across infrastructure networks using in-situ investigation data and simplified liquefaction evaluation procedures can be costly due to the volume of data required. In these cases, geospatial methods can be used as an alternative approach. This paper applies a geospatial methodology to assess the liquefaction susceptibility of New Zealand’s State Highways, allowing for quantification of the overall exposure of this network. Ground motion simulation was used to assess the probability of liquefaction for an Alpine Fault earthquake across the South Island of New Zealand, and, in conjunction with indicators for infrastructure criticality, suggested that areas with the highest liquefaction probability during an Alpine Fault earthquake may have significant local impacts, but only minor impacts on the wider network across the South Island. Using this proof of concept, a wider suite of earthquake scenarios will be used in combination with criticality frameworks to inform wide scale national infrastructure liquefaction assessment. Island was incorporated into the assessment to estimate the probability of liquefaction damage for this specific event. These outputs are discussed and linked with several indicators for infrastructure criticality, such as movement of people, to evaluate the consequences of liquefaction damage to the economy and society. The combination of both exposure and criticality assessment provides a multi-disciplinary understanding of potential liquefaction impacts to inform decision making, with further research needed to characterise the framework for infrastructure criticality aspects. 2 NEW ZEALAND STATE HIGHWAYS The functionality of national infrastructure networks is essential to provide services such as transportation of people and goods, as well as electricity supply. Because of their geographic distribution, infrastructure networks are often exposed to a range of natural hazards. In New Zealand, another important factor is the rugged topography and limited network redundancy across much of the country, meaning that disruption in one location can often have widespread implications across the network. In the event of an earthquake, liquefaction induced lateral spreading and ground deformation are one of the main causes of infrastructure damage. Impacts can vary from superficial changes, which do not interfere with the network’s functionality, to total failure of the system components and subsequent widespread outages (Mian et al., 2013; Ministry of Business, Innovation & Employment, 2017). Facing a growing population, increasing freight transport and tourist travel needs, the State Highway network is New Zealand’s most valuable asset being worth NZD 26 billion (NZ Transport Agency, 2018a). It represents only 12% of the entire road system, but accounts for up to 50% of all motor vehicle travel distance and facilitate long distance trips across the country (Ministry of Transport, 2011). For national freight movement, State Highways remain the primary transport mode covering 91% of cargo handling (measured by freight tonnes). Compared to rail and coastal shipping, they are more cost efficient and provide flexibility as well as accessibility in terms of space and time (Ministry of Transport, 2014). 3 GEOSPATIAL LIQUEFACTION MODEL The Zhu et al. (2017) geospatial model relies on a set of 18 variables which are related to factors most relevant to liquefaction: soil properties (relative density), water table depth (saturation), and ground shaking (load). To correlate these variables with liquefaction occurrence, case history data from 22 different earthquakes in the United States, New Zealand and Asia were obtained. Five events where liquefaction did not manifest within the same areas were also assessed to account for low intensity shaking events, in which liquefaction is unlikely to occur. Since most liquefaction manifestation has been observed in coastal areas, the primary model was biased, making it less applicable to non-coastal regions. Therefore, a modified version with a different arrangement of variables was introduced for global implementation (Zhu et al., 2015; Zhu et al., 2017). For relative density and saturation, the best-performing variables were slope-derived VS30 (time averaged shear-wave velocity over the first 30m), water table depth, distance to coast, distance to river, distance to closest water body, and precipitation. Peak ground velocity (PGV) proved to be most suitable for characterizing ground shaking intensity. Interaction effects among variables, for instance between distance to coast and distance to rivers, were also considered and improved the overall performance of the model (Zhu et al., 2017). Comparing the predictions of both models with the actual observations showed several discrepancies, revealing the limitations of the Zhu et al. (2017) approach. One reason for inaccurate results was the fact that site specific characteristics and other contributing factors (e.g. soil plasticity) were not included due to their restricted accessibility. Beyond that, the global model did not perform as well as the regional (coastal) model, indicating that variables related to soil saturation were the driving factor for liquefaction occurrence. Despite its limitations, the model of Zhu et al. (2017) provides useful results, especially considering the cost and time required to collate traditional in-situ methods across such a broad area (Maurer, 2017). It is therefore a reasonable tool to assess liquefaction on a national scale and to estimate potential liquefaction induced damage of New Zealand’s State Highway network. 3.1 Application to the State Highway network In order to apply the approach of Zhu et al. (2017) and to perform the assessment, the first step involved the geospatial modelling of the State Highway network in ArcGIS using a publically available dataset from the NZ Transport Agency (2012) (Fig. 1a). Since values for liquefaction susceptibility and probability were calculated for specific points, the format of the State Highway data set (polylines) needed to be adjusted by splitting the lines into sections of 100m and identifying centre points for each section. The spacing of 100m allows a detailed South Island-wide analysis of geospatial characteristics without creating issues regarding the data volume. Liquefaction susceptibility was calculated for each data point using the geospatial proxies described in the previous section. However, instead of the global slope-derived VS30 variable, a recently developed New Zealand-specific VS30 model (currently unpublished) was used. In order to calculate the probability of liquefaction occurrence and to estimate the potential damage, ground shaking data for a modelled Alpine Fault earthquake (rupture propagating northwards) was used. The Alpine Fault is a 600km long fault on the South Island which marks the boundary of the Pacific and Australian plates. According to recent studies of historic data, there is 30% chance that the Alpine Fault will rupture in the next 50 years (Berryman & Cochran, 2012, Howarth et al., 2018). Because of the severe consequences, ground shaking scenarios along the Alpine Fault have become a frequently discussed topic in current research, e.g. Sutherland et al. (2007), Cox et al. (2012) and Orchiston et al. (2018), and were used as a showcase event to estimate liquefaction probability in this paper. However, considering that the extent of the fault ruptures is not entirely predictable and that the potential impact is based on simplified estimation procedures, the outcome has to be interpreted with caution – the actual degree of liquefaction impact could be higher or lower (Bradley et al., 2017; Robinson, 2018). Figure 1. (a) New Zealand state highway network (South Island) including locations of major cities, airports and seaports. (b) Liquefaction susceptibility based on the geospatial model of Zhu et al. (2017).