Recent tsunami events have highlighted the importance of effective tsunami risk management strategies (including land-use planning, structural and natural mitigation, warning systems, education and evacuation planning). However, the rarity of tsunami means that empirical data concerning reactions to tsunami warnings and evacuation behaviour is rare when compared to findings for evacuations from other hazards. More knowledge is required to document the full evacuation process, including responses to warnings, pre-evacuation actions, evacuation dynamics, and the return home. Tsunami evacuation modelling has the potential to inform evidence-based tsunami risk planning and response. However, to date, tsunami evacuation models have largely focused on the timings of evacuations, rather than behaviours of those evacuating. In this research, survey data was gathered from coastal communities in Banks Peninsula and Christchurch, New Zealand, relating to behaviours and actions during the November 14th 2016 Kaikōura earthquake tsunami. Survey questions asked about immediate actions following the earthquake shaking, reactions to tsunami warnings, pre-evacuation actions, evacuation dynamics and details on congestion. This data was analysed to characterise trends and identify factors that influenced evacuation actions and behaviour, and was further used to develop a realistic evacuation model prototype to evaluate the capacity of the roading network in Banks Peninsula during a tsunami evacuation. The evacuation model incorporated tsunami risk management strategies that have been implemented by local authorities, and exposure and vulnerability data, alongside the empirical data collected from the survey. This research enhances knowledge of tsunami evacuation behaviour and reactions to tsunami warnings, and can be used to refine evacuation planning to ensure that people can evacuate efficiently, thereby reducing their tsunami exposure and personal risk.
After a high-intensity seismic event, inspections of structural damages need to be carried out as soon as possible in order to optimize the emergency management, as well as improving the recovery time. In the current practice, damage inspections are performed by an experienced engineer, who physically inspect the structures. This way of doing not only requires a significant amount of time and high skilled human resources, but also raises the concern about the inspector’s safety. A promising alternative is represented using new technologies, such as drones and artificial intelligence, which can perform part of the damage classification task. In fact, drones can safely access high hazard components of the structures: for instance, bridge piers or abutments, and perform the reconnaissance by using highresolution cameras. Furthermore, images can be automatically processed by machine learning algorithms, and damages detected. In this paper, the possibility of applying such technologies for inspecting New Zealand bridges is explored. Firstly, a machine-learning model for damage detection by performing image analysis is presented. Specifically, the algorithm was trained to recognize cracks in concrete members. A sensitivity analysis was carried out to evaluate the algorithm accuracy by using database images. Depending on the confidence level desired,i.e. by allowing a manual classification where the alghortim confidence is below a specific tolerance, the accuracy was found reaching up to 84.7%. In the second part, the model is applied to detect the damage observed on the Anzac Bridge (GPS coordinates -43.500865, 172.701138) in Christchurch by performing a drone reconnaissance. Reults show that the accuracy of the damage detection was equal to 88% and 63% for cracking and spalling, respectively.
Recent global tsunami events have highlighted the importance of effective tsunami risk management strategies (including land-use planning, structural and natural defences, warning systems, education and evacuation measures). However, the rarity of tsunami means that empirical data concerning reactions to tsunami warnings and tsunami evacuation behaviour is rare when compared to findings about evacuations to avoid other sources of hazard. To date empirical research into tsunami evacuations has focused on evacuation rates, rather than other aspects of the evacuation process. More knowledge is required about responses to warnings, pre-evacuation actions, evacuation dynamics and the return home after evacuations. Tsunami evacuation modelling has the potential to inform evidence-based tsunami risk planning and response. However to date tsunami evacuation models have largely focused on timings of evacuations, rather than evacuation behaviours. This Masters research uses a New Zealand case study to reduce both of these knowledge gaps. Qualitative survey data was gathered from populations across coastal communities in Banks Peninsula and Christchurch, New Zealand, required to evacuate due to the tsunami generated by the November 14th 2016 Kaikōura Earthquake. Survey questions asked about reactions to tsunami warnings, actions taken prior to evacuating and movements during the 2016 tsunami evacuation. This data was analysed to characterise trends and identify factors that influenced evacuation actions and behaviour. Finally, it was used to develop an evacuation model for Banks Peninsula. Where appropriate, the modelling inputs were informed by the survey data. Three key findings were identified from the results of the evacuation behaviour survey. Although 38% of the total survey respondents identified the earthquake shaking as a natural cue for the tsunami, most relied on receiving official warnings, including sirens, to prompt evacuations. Respondents sought further official information to inform their evacuation decisions, with 39% of respondents delaying their evacuation in order to do so. Finally, 96% of total respondents evacuated by car. This led to congestion, particularly in more densely populated Christchurch city suburbs. Prior to this research, evacuation modelling had not been completed for Banks Peninsula. The results of the modelling showed that if evacuees know how to respond to tsunami warnings and where and how to evacuate, there are no issues. However, if there are poor conditions, including if people do not evacuate immediately, if there are issues with the roading network, or if people do not know where or how to evacuate, evacuation times increase with there being more bottlenecks leading out of the evacuation zones. The results of this thesis highlight the importance of effective tsunami education and evacuation planning. Reducing exposure to tsunami risk through prompt evacuation relies on knowledge of how to interpret tsunami warnings, and when, where and how to evacuate. Recommendations from this research outline the need for public education and engagement, and the incorporation of evacuation signage, information boards and evacuation drills. Overall these findings provide more comprehensive picture of tsunami evacuation behaviour and decision making based on empirical data from a recent evacuation, which can be used to improve tsunami risk management strategies. This empirical data can also be used to inform evacuation modelling to improve the accuracy and realism of the evacuation models.
Coastal margins are exposed to rising sea levels that present challenging circumstances for natural resource management. This study investigates a rare example of tectonic displacement caused by earthquakes that generated rapid sea-level change in a tidal lagoon system typical of many worldwide. This thesis begins by evaluating the coastal squeeze effects caused by interactions between relative sea-level (RSL) rise and the built environment of Christchurch, New Zealand, and also examples of release from similar effects in areas of uplift where land reclamations were already present. Quantification of area gains and losses demonstrated the importance of natural lagoon expansion into areas of suitable elevation under conditions of RSL rise and showed that they may be necessary to offset coastal squeeze losses experienced elsewhere. Implications of these spatial effects include the need to provide accommodation space for natural ecosystems under RSL rise, yet other land-uses are likely to be present in the areas required. Consequently, the resilience of these environments depends on facilitating transitions between human land-uses either proactively or in response to disaster events. Principles illustrated by co-seismic sea-level change are generally applicable to climate change adaptation due to the similarity of inundation effects. Furthermore, they highlight the potential role of non-climatic factors in determining the overall trajectory of change. Chapter 2 quantifies impacts on riparian wetland ecosystems over an eight year period post- quake. Coastal wetlands were overwhelmed by RSL rise and recovery trajectories were surprisingly slow. Four risk factors were identified from the observed changes: 1) the encroachment of anthropogenic land-uses, 2) connectivity losses between areas of suitable elevation, 3) the disproportionate effect of larger wetland vulnerabilities, and 4) the need to protect new areas to address the future movement of ecosystems. Chapter 3 evaluates the unique context of shoreline management on a barrier sandspit under sea-level rise. A linked scenario approach was used to evaluate changes on the open coast and estuarine shorelines simultaneously and consider combined effects. The results show dune loss from a third of the study area using a sea-level rise scenario of 1 m over 100 years and with continuation of current land-uses. Increased exposure to natural hazards and accompanying demand for seawalls is a likely consequence unless natural alternatives can be progressed. In contrast, an example of managed retreat following earthquake-induced subsidence of the backshore presents a new opportunity to restart saltmarsh accretion processes seaward of coastal defences with the potential to reverse decades of degradation and build sea-level rise resilience. Considering both shorelines simultaneously highlights the existence of pinch-points from opposing forces that result in small land volumes above the tidal range. Societal adaptation is delicately poised between the paradigms of resisting or accommodating nature and challenged by the long perimeter and confined nature of the sandspit feature. The remaining chapters address the potential for salinity effects caused by tidal prism changes with a focus on the conservation of īnanga (Galaxias maculatus), a culturally important fish that supports New Zealand‘s whitebait fishery. Methodologies were developed to test the hypothesis that RSL changes would drive a shift in the distribution of spawning sites with implications for their management. Chapter 4 describes a new practical methodology for quantifying the total productivity and spatiotemporal variability of spawning sites at catchment scale. Chapter 5 describes the novel use of artificial habitats as a detection tools to help overcome field survey limitations in degraded environments where egg mortality can be high. The results showed that RSL changes resulted in major shifts in spawning locations and these were associated with new patterns of vulnerability due to the continuation of pre-disturbance land-uses. Unexpected findings includes an improved understanding of the spatial relationship between salinity and spawning habitat, and identification of an invasive plant species as important spawning habitat, both with practical management implications. To conclude, the design of legal protection mechanisms was evaluated in relation to the observed habitat shifts and with a focus on two new planning initiatives that identified relatively large protected areas (PAs) in the lower river corridors. Although the larger PAs were better able to accommodate the observed habitat shifts inefficiencies were also apparent due to spatial disparities between PA boundaries and the values requiring protection. To reduce unnecessary trade-offs with other land-uses, PAs of sufficient size to cover the observable spatiotemporal variability and coupled with adaptive capacity to address future change may offer a high effectiveness from a network of smaller PAs. The latter may be informed by both monitoring and modelling of future shifts and these are expected to include upstream habitat migration driven by the identified salinity relationships and eustatic sea-level rise. The thesis concludes with a summary of the knowledge gained from this research that can assist the development of a new paradigm of environmental sustainability incorporating conservation and climate change adaptation. Several promising directions for future research identified within this project are also discussed.
