The increase of the world's population located near areas prone to natural disasters has given rise to new ‘mega risks’; the rebuild after disasters will test the governments’ capabilities to provide appropriate responses to protect the people and businesses. During the aftermath of the Christchurch earthquakes (2010-2012) that destroyed much of the inner city, the government of New Zealand set up a new partnership between the public and private sector to rebuild the city’s infrastructure. The new alliance, called SCIRT, used traditional risk management methods in the many construction projects. And, in hindsight, this was seen as one of the causes for some of the unanticipated problems. This study investigated the risk management practices in the post-disaster recovery to produce a specific risk management model that can be used effectively during future post-disaster situations. The aim was to develop a risk management guideline for more integrated risk management and fill the gap that arises when the traditional risk management framework is used in post-disaster situations. The study used the SCIRT alliance as a case study. The findings of the study are based on time and financial data from 100 rebuild projects, and from surveying and interviewing risk management professionals connected to the infrastructure recovery programme. The study focussed on post-disaster risk management in construction as a whole. It took into consideration the changes that happened to the people, the work and the environment due to the disaster. System thinking, and system dynamics techniques have been used due to the complexity of the recovery and to minimise the effect of unforeseen consequences. Based on an extensive literature review, the following methods were used to produce the model. The analytical hierarchical process and the relative importance index have been used to identify the critical risks inside the recovery project. System theory methods and quantitative graph theory have been used to investigate the dynamics of risks between the different management levels. Qualitative comparative analysis has been used to explore the critical success factors. And finally, causal loop diagrams combined with the grounded theory approach has been used to develop the model itself. The study identified that inexperienced staff, low management competency, poor communication, scope uncertainty, and non-alignment of the timing of strategic decisions with schedule demands, were the key risk factors in recovery projects. Among the critical risk groups, it was found that at a strategic management level, financial risks attracted the highest level of interest, as the client needs to secure funding. At both alliance-management and alliance-execution levels, the safety and environmental risks were given top priority due to a combination of high levels of emotional, reputational and media stresses. Risks arising from a lack of resources combined with the high volume of work and the concern that the cost could go out of control, alongside the aforementioned funding issues encouraged the client to create the recovery alliance model with large reputable construction organisations to lock in the recovery cost, at a time when the scope was still uncertain. This study found that building trust between all parties, clearer communication and a constant interactive flow of information, established a more working environment. Competent and clear allocation of risk management responsibilities, cultural shift, risk prioritisation, and staff training were crucial factors. Finally, the post-disaster risk management (PDRM) model can be described as an integrated risk management model that considers how the changes which happened to the environment, the people and their work, caused them to think differently to ease the complexity of the recovery projects. The model should be used as a guideline for recovery systems, especially after an earthquake, looking in detail at all the attributes and the concepts, which influence the risk management for more effective PDRM. The PDRM model is represented in Causal Loops Diagrams (CLD) in Figure 8.31 and based on 10 principles (Figure 8.32) and 26 concepts (Table 8.1) with its attributes.
Following the 22 February 2011, MW 6.2 earthquake located on a fault beneath the Port Hills of Christchurch, fissuring of up to several hundred metres in length was observed in the loess and loess-colluvium of foot-slope positions in north-facing valleys of the Port Hills. The fissuring was observed in all major valleys, occurred at similar low altitudes, showing a contour-parallel orientation and often accompanied by both lateral compression/extension features and spring formation in the valley floor below. Fissuring locations studied in depth included Bowenvale Valley, Hillsborough Valley, Huntlywood Terrace–Lucas Lane, Bridle Path Road, and Maffeys Road–La Costa Lane. Investigations into loess soil, its properties and mannerisms, as well as international examples of its failure were undertaken, including study of the Loess Plateau of China, the Teton Dam, and palaeo-fissuring on Banks Peninsula. These investigations lead to the conclusion that loess has the propensity to fail, often due to the infiltration of water, the presence of which can lead to its instantaneous disaggregation. Literature study and laboratory analysis of Port Hills loess concluded that is has the ability to be stable in steep, sub-vertical escarpments, and often has a sub-vertically jointed internal structure and has a peak shear strength when dry. Values for cohesion, c (kPa) and the internal friction angle, ϕ (degrees) of Port Hills loess were established. The c values for the 40 Rapaki Road, 3 Glenview Terrace loess samples were 13.4 kPa and 19.7 kPa, respectively. The corresponding ϕ values were thought unusually high, at 42.0° and 43.4°.The analysed loess behaved very plastically, with little or no peak strength visible in the plots as the test went almost directly to residual strength. A geophysics resistivity survey showed an area of low resistivity which likely corresponds to a zone of saturated clayey loess/loess colluvium, indicating a high water table in the area. This is consistent with the appearances of local springs which are located towards the northern end of each distinct section of fissure trace and chemical analysis shows that they are sourced from the Port Hills volcanics. Port Hills fissuring may be sub-divided into three categories, Category A, Category B, and Category C, each characterised by distinctive features of the fissures. Category A includes fissures which display evidence of, spring formation, tunnel-gullying, and lateral spreading-like behaviour or quasi-toppling. These fissures are several metres down-slope of the loess-bedrock interface, and are in valleys containing a loess-colluvium fill. Category B fissures are in wider valleys than those in Category A, and the valleys contain estuarine silty sediments which liquefied during the earthquake. Category C fissures occurred at higher elevations than the fissures in the preceding categories, being almost coincident with bedrock outcropping. It is believed that the mechanism responsible for causing the fissuring is a complex combination of three mechanisms: the trampoline effect, bedrock fracturing, and lateral spreading. These three mechanisms can be applied in varying degrees to each of the fissuring sites in categories A, B, and C, in order to provide explanation for the observations made at each. Toppling failure can describe the soil movement as a consequence of the a three causative mechanisms, and provides insight into the movement of the loess. Intra-loess water coursing and tunnel gullying is thought to have encouraged and exacerbated the fissuring, while not being the driving force per se. Incipient landsliding is considered to be the least likely of the possible fissuring interpretations.
This dissertation addresses several fundamental and applied aspects of ground motion selection for seismic response analyses. In particular, the following topics are addressed: the theory and application of ground motion selection for scenario earthquake ruptures; the consideration of causal parameter bounds in ground motion selection; ground motion selection in the near-fault region where directivity effect is significant; and methodologies for epistemic uncertainty consideration and propagation in the context of ground motion selection and seismic performance assessment. The paragraphs below outline each contribution in more detail. A scenario-based ground motion selection method is presented which considers the joint distribution of multiple intensity measure (IM) types based on the generalised conditional intensity measure (GCIM) methodology (Bradley, 2010b, 2012c). The ground motion selection algorithm is based on generating realisations of the considered IM distributions for a specific rupture scenario and then finding the prospective ground motions which best fit the realisations using an optimal amplitude scaling factor. In addition, using different rupture scenarios and site conditions, two important aspects of the GCIM methodology are scrutinised: (i) different weight vectors for the various IMs considered; and (ii) quantifying the importance of replicate selections for ensembles with different numbers of desired ground motions. As an application of the developed scenario-based ground motion selection method, ground motion ensembles are selected to represent several major earthquake scenarios in New Zealand that pose a significant seismic hazard, namely, Alpine, Hope and Porters Pass ruptures for Christchurch city; and Wellington, Ohariu, and Wairarapa ruptures for Wellington city. A rigorous basis is developed, and sensitivity analyses performed, for the consideration of bounds on causal parameters (e.g., magnitude, source-to-site distance, and site condition) for ground motion selection. The effect of causal parameter bound selection on both the number of available prospective ground motions from an initial empirical as-recorded database, and the statistical properties of IMs of selected ground motions are examined. It is also demonstrated that using causal parameter bounds is not a reliable approach to implicitly account for ground motion duration and cumulative effects when selection is based on only spectral acceleration (SA) ordinates. Specific causal parameter bounding criteria are recommended for general use as a ‘default’ bounding criterion with possible adjustments from the analyst based on problem-specific preferences. An approach is presented to consider the forward directivity effects in seismic hazard analysis, which does not separate the hazard calculations for pulse-like and non-pulse-like ground motions. Also, the ability of ground motion selection methods to appropriately select records containing forward directivity pulse motions in the near-fault region is examined. Particular attention is given to ground motion selection which is explicitly based on ground motion IMs, including SA, duration, and cumulative measures; rather than a focus on implicit parameters (i.e., distance, and pulse or non-pulse classifications) that are conventionally used to heuristically distinguish between the near-fault and far-field records. No ad hoc criteria, in terms of the number of directivity ground motions and their pulse periods, are enforced for selecting pulse-like records. Example applications are presented with different rupture characteristics, source-to-site geometry, and site conditions. It is advocated that the selection of ground motions in the near-fault region based on IM properties alone is preferred to that in which the proportion of pulse-like motions and their pulse periods are specified a priori as strict criteria for ground motion selection. Three methods are presented to propagate the effect of seismic hazard and ground motion selection epistemic uncertainties to seismic performance metrics. These methods differ in their level of rigor considered to propagate the epistemic uncertainty in the conditional distribution of IMs utilised in ground motion selection, selected ground motion ensembles, and the number of nonlinear response history analyses performed to obtain the distribution of engineering demand parameters. These methods are compared for an example site where it is observed that, for seismic demand levels below the collapse limit, epistemic uncertainty in ground motion selection is a smaller uncertainty contributor relative to the uncertainty in the seismic hazard itself. In contrast, uncertainty in ground motion selection process increases the uncertainty in the seismic demand hazard for near-collapse demand levels.
This thesis is concerned with modelling rockfall parameters associated with cliff collapse debris and the resultant “ramp” that formed following the high peak ground acceleration (PGA) events of 22 February 2011 and 13 June 2011. The Christchurch suburb of Redcliffs, located at the base of the Port Hills on the northern side of Banks Peninsula, New Zealand, is comprised of Miocene-age volcanics with valley-floor infilling marine sediments. The area is dominated by basaltic lava flows of the Mt Pleasant Formation, which is a suite of rocks forming part of the Lyttelton Volcanic Group that were erupted 11.0-10.0Ma. Fresh exposure enabled the identification of a basaltic ignimbrite unit at the study site overlying an orange tuff unit that forms a marker horizon spanning the length of the field area. Prior to this thesis, basaltic ignimbrite on Banks Peninsula has not been recorded, so descriptions and interpretations of this unit are the first presented. Mapping of the cliff face by remote observation, and analysis of hand samples collected from the base of the debris slopes, has identified a very strong (>200MPa), columnar-jointed, welded unit, and a very weak (<5MPa), massive, so-called brecciated unit that together represent the end-member components of the basaltic ignimbrite. Geochemical analysis shows the welded unit is picrite basalt, and the brecciated unit is hawaiite, making both clearly distinguishable from the underlying trachyandesite tuff. RocFall™ 4.0 was used to model future rockfalls at Redcliffs. RocFall™ is a two-dimensional (2D), hybrid, probabilistic modelling programme for which topographical profile data is used to generate slope profiles. GNS Science collected the data used for slope profile input in March 2011. An initial sensitivity analysis proved the Terrestrial Laser Scan (TLS)-derived slope to be too detailed to show any results when the slope roughness parameter was tested. A simplified slope profile enabled slope roughness to be varied, however the resulting model did not correlate with field observations as well. By using slope profile data from March 2011, modelled rockfall behaviour has been calibrated with observed rockfall runout at Redcliffs in the 13 June 2011 event to create a more accurate rockfall model. The rockfall model was developed on a single slope profile (Section E), with the chosen model then applied to four other section lines (A-D) to test the accuracy of the model, and to assess future rockfall runout across a wider area. Results from Section Lines A, B, and E correlate very well with field observations, with <=5% runout exceeding the modelled slope, and maximum bounce height at the toe of the slope <=1m. This is considered to lie within observed limits given the expectation that talus slopes will act as a ramp on which modelled rocks travel further downslope. Section Lines C and D produced higher runout percentage values than the other three section lines (23% and 85% exceeding the base of the slope, respectively). Section D also has a much higher maximum bounce height at the toe of the slope (~8.0m above the slope compared to <=1.0m for the other four sections). Results from modelling of all sections shows the significance of the ratio between total cliff height (H) and horizontal slope distance (x), and of maximum drop height to the top of the talus (H*) and horizontal slope distance (x). H/x can be applied to the horizontal to vertical ratio (H:V) as used commonly to identify potential slope instability. Using the maximum value from modelling at Redcliffs, the future runout limit can be identified by applying a 1.4H:1V ratio to the remainder of the cliff face. Additionally, the H*/x parameter shows that when H*/x >=0.6, the percentage of rock runout passing the toe of the slope will exceed 5%. When H*/x >=0.75, the maximum bounce height at the toe of the slope can be far greater than when H*/x is below this threshold. Both of these parameters can be easily obtained, and can contribute valuable guideline data to inform future land-use planning decisions. This thesis project has demonstrated the applicability of a 2D probabilistic-based model (RocFall™ 4.0) to evaluate rockfall runout on the talus slope (or ramp) at the base of ~35-70m high cliff with a basaltic ignimbrite source. Limitations of the modelling programme have been identified, in particular difficulties with adjusting modelled roughness of the slope profile and the inability to consider fragmentation. The runout profile using RocFall™ has been successfully calibrated against actual profiles and some anomalous results have been identified.
In September 2010 and February 2011, the Canterbury region experienced devastating earthquakes with an estimated economic cost of over NZ$40 billion (Parker and Steenkamp, 2012; Timar et al., 2014; Potter et al., 2015). The insurance market played an important role in rebuilding the Canterbury region after the earthquakes. Homeowners, insurance and reinsurance markets and New Zealand government agencies faced a difficult task to manage the rebuild process. From an empirical and theoretic research viewpoint, the Christchurch disaster calls for an assessment of how the insurance market deals with such disasters in the future. Previous studies have investigated market responses to losses in global catastrophes by focusing on the insurance supply-side. This study investigates both demand-side and supply-side insurance market responses to the Christchurch earthquakes. Despite the fact that New Zealand is prone to seismic activities, there are scant previous studies in the area of earthquake insurance. This study does offer a unique opportunity to examine and document the New Zealand insurance market response to catastrophe risk, providing results critical for understanding market responses after major loss events in general. A review of previous studies shows higher premiums suppress demand, but how higher premiums and a higher probability of risk affect demand is still largely unknown. According to previous studies, the supply of disaster coverage is curtailed unless the market is subsidised, however, there is still unsettled discussion on why demand decreases with time from the previous disaster even when the supply of coverage is subsidised by the government. Natural disaster risks pose a set of challenges for insurance market players because of substantial ambiguity associated with the probability of such events occurring and high spatial correlation of catastrophe losses. Private insurance market inefficiencies due to high premiums and spatially concentrated risks calls for government intervention in the provision of natural disaster insurance to avert situations of noninsurance and underinsurance. Political economy considerations make it more likely for government support to be called for if many people are uninsured than if few people are uninsured. However, emergency assistance for property owners after catastrophe events can encourage most property owners to not buy insurance against natural disaster and develop adverse selection behaviour, generating larger future risks for homeowners and governments. On the demand-side, this study has developed an intertemporal model to examine how demand for insurance changes post-catastrophe, and how to model it theoretically. In this intertemporal model, insurance can be sought in two sequential periods of time, and at the second period, it is known whether or not a loss event happened in period one. The results show that period one demand for insurance increases relative to the standard single period model when the second period is taken into consideration, period two insurance demand is higher post-loss, higher than both the period one demand and the period two demand without a period one loss. To investigate policyholders experience from the demand-side perspective, a total of 1600 survey questionnaires were administered, and responses from 254 participants received representing a 16 percent response rate. Survey data was gathered from four institutions in Canterbury and is probably not representative of the entire population. The results of the survey show that the change from full replacement value policy to nominated replacement value policy is a key determinant of the direction of change in the level of insurance coverage after the earthquakes. The earthquakes also highlighted the plight of those who were underinsured, prompting policyholders to update their insurance coverage to reflect the estimated cost of re-building their property. The survey has added further evidence to the existing literature, such as those who have had a recent experience with disaster loss report increased risk perception if a similar event happens in future with females reporting a higher risk perception than males. Of the demographic variables, only gender has a relationship with changes in household cover. On the supply-side, this study has built a risk-based pricing model suitable to generate a competitive premium rate for natural disaster insurance cover. Using illustrative data from the Christchurch Red-zone suburbs, the model generates competitive premium rates for catastrophe risk. When the proposed model incorporates the new RMS high-definition New Zealand Earthquake Model, for example, insurers can find the model useful to identify losses at a granular level so as to calculate the competitive premium. This study observes that the key to the success of the New Zealand dual insurance system despite the high prevalence of catastrophe losses are; firstly the EQC’s flat-rate pricing structure keeps private insurance premiums affordable and very high nationwide homeowner take-up rates of natural disaster insurance. Secondly, private insurers and the EQC have an elaborate reinsurance arrangement in place. By efficiently transferring risk to the reinsurer, the cost of writing primary insurance is considerably reduced ultimately expanding primary insurance capacity and supply of insurance coverage.
