The main body of research within climate-change induced migration has focused on displacement migration. The "sinking islands" reference is often used to describe island states being in the forefront of climate change impacts, and their inhabitants at risk of becoming the first climate change refugees in history. The aim of this thesis is to understand what circumstances are needed for Kiribati’s ‘Migration with Dignity’ concept to enhance the adaptive capacity of livelihoods. By using the Sustainable Livelihood Approach this thesis examines what impacts climate change has on different aspects of livelihoods in Kiribati. This study uses a case study approach. Data has been collected through 14 semi-structured interviews during an eight weeks long minor field study on the capital atoll South Tarawa. While Kiribati faces many development challenges, being a least developed country with a rent-based economy, climate change puts additional strains on the country’s capacities to cope with the increasing monetization and urbanisation, and abilities to satisfy the growing population’s aspirations. The empirical evidence shows a need among the population to find education and skilled wage employment. Harmonisation between migration, development and adaptation policies can increase livelihoods’ economic conditions and abilities to cope with climate change-related stresses, especially for future generations.

According to the Centre for Research on the Epidemiology of Disasters, the global average number of CID has tripled in less than four decades (from approximately 1,300 Climate-Induced Disasters (CID) between 1975 and 1984 to around 3,900 between 2005 and 2014). In addition, around 1 million deaths and $1.7 trillion damage costs were attributed to CID since 2000, with around $210 billion incurred only in 2020. Consequently, the World Economic Forum identified extreme weather as the top ranked global risk in terms of likelihood and among the top five risks in terms of impact in the last 4 years. These risks are not expected to diminish as: i) the number of CID is anticipated to double during the next 13 years; ii) the annual fatalities due to CID are expected to increase by 250,000 deaths in the next decade; and iii) the annual CID damage costs are expected to increase by around 20% in 2040 compared to those realized in 2020. Given the anticipated increase in CID frequency, the intensification of CID impacts, the rapid growth in the world’s population, and the fact that two thirds of such population will be officially living in urban areas by 2050, it has recently become extremely crucial to enhance both community and city resilience under CID. Resilience, in that context, refers to the ability of a system to bounce back, recover or adapt in the face of adverse events. This is considered a very farfetched goal given both the extreme unpredictability of the frequency and impacts of CID and the complex behavior of cities that stems from the interconnectivity of their comprising infrastructure systems. With the emergence of data-driven machine learning which assumes that models can be trained using historical data and accordingly, can efficiently learn to predict different complex features, developing robust models that can predict the frequency and impacts of CID became more conceivable. Through employing data analytics and machine learning techniques, this work aims at enhancing city resilience by predicting both the occurrence and expected impacts of climate-induced disasters on urban areas. The first part of this dissertation presents a critical review of the research work pertaining to resilience of critical infrastructure systems. Meta-research is employed through topic modelling, to quantitatively uncover related latent topics in the field. The second part aims at predicting the occurrence of CID by developing a framework that links different climate change indices to historical disaster records. In the third part of this work, a framework is developed for predicting the performance of critical infrastructure systems under CID. Finally, the aim of the fourth part of this dissertation is to develop a systematic data-driven framework for the prediction of CID property damages. This work is expected to aid stakeholders in developing spatio-temporal preparedness plans under CID, which can facilitate mitigating the adverse impacts of CID on infrastructure systems and improve their resilience. / Thesis / Doctor of Philosophy (PhD)

Coastal indigenous communities in Keta, Ghana, are experiencing resettlement as a result of slow-onset, climate-induced flooding and erosion. Previous researchers have documented the risk of relocation from rapid-onset events, but little is known about the effectiveness of policies developed in response to slow-onset changes. This phenomenological study investigated the ongoing lived experiences of adult household members in Keta who were relocated by the government. Jun's critical theory provided a constructionist interpretive framework to determine whether Ghana's national policy on climate change resettlement adequately meets Rawls's criteria for distributive social justice. Policy documents and transcriptions of interviews with a purposeful sample of 17 family members were thematically coded and categorized into essence descriptions. Results revealed aligned perceptions of an absence of justice or fairness in the allocation of resources to households relocated by the government. Negative experiences characterized all families' resettlement processes. The government's commitment to ensuring basic community welfare was perceived to be poor. Findings highlight the need for social justice to be the primary policy consideration for future allocation of benefits to resettled households. To avoid reaching a tipping point at which prompt governmental intervention will be either compelled or impossible, quantitative studies are needed to guide policymakers in considering the real costs of relocation and the cumulative effects on families and communities. This study provides evidence for public consideration of the severe consequences of injustice in relocation and the need to prevent human rights abuse in the formulation of social, economic, and cultural policies associated with climate-induced resettlement.