Disaster recovery involves the restoration, repair and rejuvenation of both hard and soft infrastructure. In this report we present observationsfrom seven case studies of collaborative planning from post-earthquake Canterbury, each of which was selected as a means of better understanding ‘soft infrastructure for hard times’. Though our investigation is located within a disaster recovery context, we argue that the lessons learned are widely applicable. Our seven case studies highlighted that the nature of the planning process or journey is as important as the planning objective or destination. A focus on the journey can promote positive outcomes in and of itself through building enduring relationships, fostering diverse leaders, developing new skills and capabilities, and supporting translation and navigation. Collaborative planning depends as much upon emotional intelligence as it does technical competence, and we argue that having a collaborative attitude is more important than following prescriptive collaborative planning formulae. Being present and allowing plenty of time are also key. Although deliberation is often seen as an improvement on technocratic and expertdominated decision-making models, we suggest that the focus in the academic literature on communicative rationality and discursive democracy has led us to overlook other more active forms of planning that occur in various sites and settings. Instead, we offer an expanded understanding of what planning is, where it happens and who is involved. We also suggest more attention be given to values, particularly in terms of their role as a compass for navigating the terrain of decision-making in the collaborative planning process. We conclude with a revised model of a (collaborative) decision-making cycle that we suggest may be more appropriate when (re)building better homes, towns and cities.
      
      
      
        
        
        © 2019, Springer-Verlag GmbH Germany, part of Springer Nature. Prediction of building collapse due to significant seismic motion is a principle objective of earthquake engineers, particularly after a major seismic event when the structure is damaged and decisions may need to be made rapidly concerning the safe occupation of a building or surrounding areas. Traditional model-based pushover analyses are effective, but only if the structural properties are well understood, which is not the case after an event when that information is most useful. This paper combines hysteresis loop analysis (HLA) structural health monitoring (SHM) and incremental dynamic analysis (IDA) methods to identify and then analyse collapse capacity and the probability of collapse for a specific structure, at any time, a range of earthquake excitations to ensure robustness. This nonlinear dynamic analysis enables constant updating of building performance predictions following a given and subsequent earthquake events, which can result in difficult to identify deterioration of structural components and their resulting capacity, all of which is far more difficult using static pushover analysis. The combined methods and analysis provide near real-time updating of the collapse fragility curves as events progress, thus quantifying the change of collapse probability or seismic induced losses very soon after an earthquake for decision-making. Thus, this combination of methods enables a novel, higher-resolution analysis of risk that was not previously available. The methods are not computationally expensive and there is no requirement for a validated numerical model, thus providing a relatively simpler means of assessing collapse probability immediately post-event when such speed can provide better information for critical decision-making. Finally, the results also show a clear need to extend the area of SHM toward creating improved predictive models for analysis of subsequent events, where the Christchurch series of 2010–2011 had significant post-event aftershocks.
      
      
      
        
        
        Predicting building collapse due to seismic motion is critical in design and more so after a major event. Damaged structures can appear sound, but collapse under following major events. There can thus be significant risk in decision making after a major seismic event concerning the safe occupation of a building or surrounding areas, versus the unknown impact of unknown major aftershocks. Model-based pushover analyses are effective if the structural properties are well understood, which is not valid post-event when this risk information is most useful. This research combines Hysteresis Loop Analysis (HLA) structural health monitoring (SHM) and Incremental Dynamic Analysis (IDA) methods to determine collapse capacity and probability of collapse for a specific structure, at any time, a range of earthquake excitations to ensure robustness. The nonlinear dynamic analysis method presented enables constant updating of building performance predictions using post-event SHM results. The resulting combined methods provide near real-time updating of collapse fragility curves as events progress, quantifying the change of collapse probability or seismic induced losses for decision-making - a novel, higher resolution risk analysis than previously available. The methods are not computationally expensive and there is no requirement for a validated numerical model. Results show significant potential benefits and a clear evolution of risk. They also show clear need for extending SHM toward creating improved predictive models for analysis of subsequent events, where the Christchurch series of 2010-2011 had significant post-event aftershocks after each main event. Finally, the overall method is generalisable to any typical engineering demand parameter.
      
      
      
        
        
        Peri-urban environments are critical to the connections between urban and rural ecosystems and their respective communities. Lowland floodplains are important examples that are attractive for urbanisation and often associated with the loss of rural lands and resources. In Christchurch, New Zealand, damage from major earthquakes led to the large-scale abandonment of urban residential properties in former floodplain areas creating a rare opportunity to re-imagine the future of these lands. This has posed a unique governance challenge involving the reassessment of land-use options and a renewed focus on disaster risk and climate change adaptation. Urban-rural tensions have emerged through decisions on relocating residential development, alternative proposals for land uses, and an unprecedented opportunity for redress of degraded traditional values for indigenous (Māori) people. Immediately following the earthquakes, existing statutory arrangements applied to many recovery needs and identified institutional responsibilities. Bespoke legislation was also created to address the scale of impacts. Characteristics of the approach have included attention to information acquisition, iterative assessment of land - use options, and a wide variety of opportunities for community participation. Challenges have included a protracted decision-making process with accompanying transaction costs, and a high requirement for coordination. The case typifies the challenges of achieving ecosystem governance where both urban and rural stakeholders have strong desires and an opportunity to exert influence. It presents a unique context for applying the latest thinking on ecosystem management, adaptation, and resilience, and offers transferable learning for the governance of peri-urban floodplains worldwide.
      
      
      
        
        
        The use of post-earthquake cordons as a tool to support emergency managers after an event has been documented around the world. However, there is limited research that attempts to understand the use, effectiveness, inherent complexities, impacts and subsequent consequences of cordoning once applied. This research aims to fill that gap by providing a detailed understanding of first, the cordons and associated processes, and their implications in a post-earthquake scenario. We use a qualitative method to understand cordons through case studies of two cities where it was used in different temporal and spatial scales: Christchurch (2011) and Wellington (Kaikōura earthquake 2016), New Zealand. Data was collected through 21 expert interviews obtained through purposive and snowball sampling of key informants who were directly or indirectly involved in a decision-making role and/or had influence in relation to the cordoning process. The participants were from varying backgrounds and roles i.e. emergency managers, council members, business representatives, insurance representatives, police and communication managers. The data was transcribed, coded in Nvivo and then grouped based on underlying themes and concepts and then analyzed inductively. It is found that cordons are used primarily as a tool to control access for the purpose of life safety and security. But cordons can also be adapted to support recovery. Broadly, it can be synthesized and viewed based on two key aspects, ‘decision-making’ and ‘operations and management’, which overlap and interact as part of a complex system. The underlying complexity arises in large part due to the multitude of sectors it transcends such as housing, socio-cultural requirements, economics, law, governance, insurance, evacuation, available resources etc. The complexity further increases as the duration of cordon is extended.
      
      
      
        
        
        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.
      
      
      
        
        
        The Canterbury earthquake and aftershock sequence in New Zealand during 2010-2011 subjected the city’s structures to a significant accumulated cyclic demand and raised significant questions regarding the low-cycle fatigue demands imposed upon the structures. There is a significant challenge to quantify the level of cumulative demand imposed on structures and to assess the percentage of a structure's fatigue life that has been consumed as a result of this earthquake sequence. It is important to be able to quantify the cumulative demand to determine how a building will perform in a subsequent large earthquake and inform repair and re-occupancy decisions. This paper investigates the cumulative fatigue demand for a structure located within the Christchurch Central Business District (CBD). Time history analysis and equivalent cycle counting methods are applied across the Canterbury earthquake sequence, using key events from September 4th 2010 and February 22nd , 2011 main shocks. The estimate of the cumulative fatigue demand is then compared to the expected capacity of a case study reinforced concrete bridge pier, to undertake a structure-specific fatigue assessment. The analysis is undertaken to approximate the portion of the structural fatigue capacity that has been consumed, and how much residual capacity remains. Results are assessed for recordings at the four Christchurch central city strong motion recording sites installed by the GeoNet programme, to provide an estimate of variation in results. The computed cyclic demand results are compared to code-based design methods and as assessment of the inelastic displacement demand of the reinforcing steel. Results are also presented in a fragility context where a de minimis (inconsequential), irreparable damage and full fatigue fracture are defined to provide a probabilistic assessment of the fatigue damage incurred. This methodology can provide input into the overall assessment of fatigue demands and residual capacity.
      
      
      
        
        
        This thesis documents the development and demonstration of an assessment method for analysing earthquake-related damage to concrete waste water gravity pipes in Christchurch, New Zealand, following the 2010-2011 Canterbury Earthquake Sequence (CES). The method is intended to be internationally adaptable to assist territorial local authorities with improving lifelines infrastructure disaster impact assessment and improvements in resilience. This is achieved through the provision of high-resolution, localised damage data, which demonstrate earthquake impacts along the pipe length. The insights gained will assist decision making and the prioritisation of resources following earthquake events to quickly and efficiently restore network function and reduce community impacts. The method involved obtaining a selection of 55 reinforced concrete gravity waste water pipes with available Closed-Circuit Television (CCTV) inspection footage filmed before and after the CES. The pipes were assessed by reviewing the recordings, and damage was mapped to the nearest metre along the pipe length using Geographic Information Systems. An established, systematic coding process was used for reporting the nature and severity of the observed damage, and to differentiate between pre-existing and new damage resulting from the CES. The damage items were overlaid with geospatial data such as Light Detection and Ranging (LiDAR)-derived ground deformation data, Liquefaction Resistance Index data and seismic ground motion data (Peak Ground acceleration and Peak Ground Velocity) to identify potential relationships between these parameters and pipe performance. Initial assessment outcomes for the pipe selection revealed that main pipe joints and lateral connections were more vulnerable than the pipe body during a seismic event. Smaller diameter pipes may also be more vulnerable than larger pipes during a seismic event. Obvious differential ground movement resulted in increased local damage observations in many cases, however this was not obvious for all pipes. Pipes with older installation ages exhibited more overall damage prior to a seismic event, which is likely attributable to increased chemical and biological deterioration. However, no evidence was found relating pipe age to performance during a seismic event. No evidence was found linking levels of pre-CES damage in a pipe with subsequent seismic performance, and seismic performance with liquefaction resistance or magnitude of seismic ground motion. The results reported are of limited application due to the small demonstration sample size, but reveal the additional level of detail and insight possible using the method presented in this thesis over existing assessment methods, especially in relation to high resolution variations along the length of the pipe such as localised ground deformations evidenced by LiDAR. The results may be improved by studying a larger and more diverse sample pool, automating data collection and input processes in order to improve efficiency and consider additional input such as pipe dip and cumulative damage over a large distance. The method is dependent on comprehensive and accurate pre-event CCTV assessments and LIDAR data so that post-event data could be compared. It is proposed that local territorial authorities should prioritise acquiring this information as a first important step towards improving the seismic resilience of a gravity waste water pipe network.
      
      
      
        
        
        This thesis documents the development and demonstration of an assessment method for analysing earthquake-related damage to concrete waste water gravity pipes in Christchurch, New Zealand, following the 2010-2011 Canterbury Earthquake Sequence (CES). The method is intended to be internationally adaptable to assist territorial local authorities with improving lifelines infrastructure disaster impact assessment and improvements in resilience. This is achieved through the provision of high-resolution, localised damage data, which demonstrate earthquake impacts along the pipe length. The insights gained will assist decision making and the prioritisation of resources following earthquake events to quickly and efficiently restore network function and reduce community impacts. The method involved obtaining a selection of 55 reinforced concrete gravity waste water pipes with available Closed-Circuit Television (CCTV) inspection footage filmed before and after the CES. The pipes were assessed by reviewing the recordings, and damage was mapped to the nearest metre along the pipe length using Geographic Information Systems. An established, systematic coding process was used for reporting the nature and severity of the observed damage, and to differentiate between pre-existing and new damage resulting from the CES. The damage items were overlaid with geospatial data such as Light Detection and Ranging (LiDAR)-derived ground deformation data, Liquefaction Resistance Index data and seismic ground motion data (Peak Ground acceleration and Peak Ground Velocity) to identify potential relationships between these parameters and pipe performance. Initial assessment outcomes for the pipe selection revealed that main pipe joints and lateral connections were more vulnerable than the pipe body during a seismic event. Smaller diameter pipes may also be more vulnerable than larger pipes during a seismic event. Obvious differential ground movement resulted in increased local damage observations in many cases, however this was not obvious for all pipes. Pipes with older installation ages exhibited more overall damage prior to a seismic event, which is likely attributable to increased chemical and biological deterioration. However, no evidence was found relating pipe age to performance during a seismic event. No evidence was found linking levels of pre-CES damage in a pipe with subsequent seismic performance, and seismic performance with liquefaction resistance or magnitude of seismic ground motion. The results reported are of limited application due to the small demonstration sample size, but reveal the additional level of detail and insight possible using the method presented in this thesis over existing assessment methods, especially in relation to high resolution variations along the length of the pipe such as localised ground deformations evidenced by LiDAR. The results may be improved by studying a larger and more diverse sample pool, automating data collection and input processes in order to improve efficiency and consider additional input such as pipe dip and cumulative damage over a large distance. The method is dependent on comprehensive and accurate pre-event CCTV assessments and LIDAR data so that post-event data could be compared. It is proposed that local territorial authorities should prioritise acquiring this information as a first important step towards improving the seismic resilience of a gravity waste water pipe network.
      
      
      
        
        
        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.