Étant donné que les catastrophes sont un phénomène spatial, l’application de systèmes d’information géographique (SIG) est un outil pratique et fiable pour le processus de réduction des risques de catastrophe (RRC). Les SIG peuvent servir le processus de RRC en tant que base de données pour la collecte et l’intégration de données, ainsi que pour l’incorporation de données multi‐sources, en tant que systèmes d’observation, en tant qu’outil pour la production de cartes de risques, en tant que calculateur d’exposition, constructeur de modèles déterminant les vulnérabilités des éléments, en temps quasi réel, traqueur de crise, etc… Mais ces applications SIG ont été intégrées de manière inégale à travers les différentes phases du cycle de RRC. De plus, l'utilisation efficace de ces technologies nécessite des recherches et des développements plus poussés, en particulier dans les pays en développement où de nombreux obstacles entravent l'utilisation des SIG pour la protection civile. Cette tâche devient encore plus compliquée au niveau local en région rurale comme dans notre zone d’étude Baalbek‐Hermel, Gouvernorat du Liban. Le manque de ressources humaines et financières et des données spatiales critiques lacunaires limitent l’utilisation des SIG pour améliorer la décision en matière de RRC ? Dans quelle mesure le SIG pourrait‐il être efficace dans les actions de RRC dans un pays en développement comme le Liban, où le nombre d’enjeux exposés augmentent sans cesse et où le gouvernement a d'autres priorités urgentes que de s'engager dans un plan de RRC? Plusieurs études de cas menées à Baalbek‐Hermel servent à tester les hypothèses retenues et à discuter de l’adoption et de l’adaptation de techniques SIG afin de les rendre efficaces et capables de servir tout le cycle de RRC ; évaluation des dangers, de la vulnérabilité et des dommages, planification d’urgence et d’évacuation, systèmes d’alerte précoce, zonage des terres, données en temps quasi réel pour l’intervention, rétablissement et renforcement de la résilience. Les défis posés par le déploiement de ces technologies SIG dans chacune des phases susmentionnées du cycle de la RRC et la manière dont ils peuvent être surmontés sont discutés, en considérant les approches autochtones pour l’application de technologies et d’innovations en matière de RRC. Les résultats de cette thèse offrent le potentiel de surmonter certains des obstacles qui entravent l'utilisation des SIG pour une RRC efficace dans les pays en développement. Ainsi, les praticiens de RRC au Liban et dans d'autres pays en développement pourraient exploiter ce potentiel pour tenter de réduire la vulnérabilité aux dangers et améliorer la capacité de prévention des catastrophes. / Given that natural disasters are spatial phenomenon, the application of geographical information systems (GIS) has proven to be a convenient and reliable tool for the Disaster Risk Reduction (DRR) process. GIS can serve DRR as a database for data gathering, integration and incorporation,an output viewer, a tool for hazard maps production, a calculator for exposure, a model builderfor determining assets’ vulnerabilities, a near real time crisis tracker, etc… Nevertheless, GIS applications have been integrated unevenly across the different phases of the DRR cycle.Moreover, the effective use of these technologies requires further research and development,especially in developing countries where numerous barriers hamper the use of GIS for civil protection. The task is further complicated at the local level in rural areas such as our study area Baalbek‐Hermel, Governorate of Lebanon. Restrictions include limited human and financial resources and a lack of critical spatial data required to support GIS application to DRR. To what extent could GIS be efficient in DRR actions in a developing country like Lebanon where themajority of assets at risk is ever‐growing and the government has other urgent priorities than tocommit to DRR plans? Several case‐studies in Baalbek‐Hermel were taken to test these assumptions and discuss the adaptation of GIS techniques to make them effective and to be able to serve the whole DRR cycle; hazard, vulnerability, risk and damage assessment, emergency and evacuation planning, land‐use zoning, recovery and resilience building. Challenges in the deployment of GIS technologies in each afore mentioned phase of the DRR cycle and how they may be overcome were discussed, considering indigenous approaches for the application of technologies and innovations in DRR. The results of this dissertation suggested ways to control some of the barriers hampering the effective use of GIS for DRR in developing countries. Thus,DRR practitioners in Lebanon and other developing countries could harness this potential in anattempt to reduce hazard vulnerability and improve disaster reduction capacity.

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One of the great challenges facing human systems today is how to prepare for, manage, and adapt successfully to the profound and rapid changes wreaked by disasters. Wellington, New Zealand, is a capital city at significant risk of devastating earthquake and tsunami, potentially requiring mass evacuations with little or short notice. Subsequent hardship and suffering due to widespread property damage and infrastructure failure could cause large areas of the Wellington Region to become uninhabitable for weeks to months. Previous research has shown that positive health and well-being are associated with disaster-resilient outcomes. Preventing adverse outcomes before disaster strikes, through developing strengths-based skill sets in health-protective attitudes and behaviours, is increasingly advocated in disaster research, practise, and management. This study hypothesised that well-being constructs involving an affective heuristic play vital roles in pathways to resilience as proximal determinants of health-protective behaviours. Specifically, this study examined the importance of health-related quality of life and subjective well-being in motivating evacuation preparedness, measured in a community sample (n=695) drawn from the general adult population of Wellington’s isolated eastern suburbs. Using a quantitative epidemiological approach, the study measured the prevalence of key quality of life indicators (physical and mental health, emotional well-being or “Sense of Coherence”, spiritual well-being, social well-being, and life satisfaction) using validated psychometric scales; analysed the strengths of association between these indicators and the level of evacuation preparedness at categorical and continuous levels of measurement; and tested the predictive power of the model to explain the variance in evacuation preparedness activity. This is the first study known to examine multi-dimensional positive health and global well-being as resilient processes for engaging in evacuation preparedness behaviour. A cross-sectional study design and quantitative survey were used to collect self-report data on the study variables; a postal questionnaire was fielded between November 2008 and March 2009 to a sampling frame developed through multi-stage cluster randomisation. The survey response rate was 28.5%, yielding a margin of error of +/- 3.8% with 95% confidence and 80% statistical power to detect a true correlation coefficient of 0.11 or greater. In addition to the primary study variables, data were collected on demographic and ancillary variables relating to contextual factors in the physical environment (risk perception of physical and personal vulnerability to disaster) and the social environment (through the construct of self-determination), and other measures of disaster preparedness. These data are reserved for future analyses. Results of correlational and regression analyses for the primary study variables show that Wellingtonians are highly individualistic in how their well-being influences their preparedness, and a majority are taking inadequate action to build their resilience to future disaster from earthquake- or tsunami-triggered evacuation. At a population level, the conceptual multi-dimensional model of health-related quality of life and global well-being tested in this study shows a positive association with evacuation preparedness at statistically significant levels. However, it must be emphasised that the strength of this relationship is weak, accounting for only 5-7% of the variability in evacuation preparedness. No single dimension of health-related quality of life or well-being stands out as a strong predictor of preparedness. The strongest associations for preparedness are in a positive direction for spiritual well-being, emotional well-being, and life satisfaction; all involve a sense of existential meaningfulness. Spiritual well-being is the only quality of life variable making a statistically significant unique contribution to explaining the variance observed in the regression models. Physical health status is weakly associated with preparedness in a negative direction at a continuous level of measurement. No association was found at statistically significant levels for mental health status and social well-being. These findings indicate that engaging in evacuation preparedness is a very complex, holistic, yet individualised decision-making process, and likely involves highly subjective considerations for what is personally relevant. Gender is not a factor. Those 18-24 years of age are least likely to prepare and evacuation preparedness increases with age. Multidimensional health and global well-being are important constructs to consider in disaster resilience for both pre-event and post-event timeframes. This work indicates a need for promoting self-management of risk and building resilience by incorporating a sense of personal meaning and importance into preparedness actions, and for future research into further understanding preparedness motivations.

Atmospheric features, such as tropical cyclones, act as a driving mechanism for many of the major hazards affecting coastal areas around the world. Accurate and efficient quantification of tropical cyclone surge hazard is essential to the development of resilient coastal communities, particularly given continued sea level trend concerns. Recent major tropical cyclones that have impacted the northeastern portion of the United States have resulted in devastating flooding in New York City, the most densely populated city in the US. As a part of national effort to re-evaluate coastal inundation hazards, the Federal Emergency Management Agency used the Joint Probability Method to re-evaluate surge hazard probabilities for Flood Insurance Rate Maps in the New York – New Jersey coastal areas, also termed the New York Bight. As originally developed, this method required many combinations of storm parameters to statistically characterize the local climatology for numerical model simulation. Even though high-performance computing efficiency has vastly improved in recent years, researchers have utilized different “Optimal Sampling” techniques to reduce the number of storm simulations needed in the traditional Joint Probability Method. This manuscript presents results from the simulation of over 350 synthetic tropical cyclones designed to produce significant surge in the New York Bight using the hydrodynamic Advanced Circulation numerical model, bypassing the need for Optimal Sampling schemes. This data set allowed for a careful assessment of joint probability distributions utilized for this area and the impacts of current assumptions used in deriving new flood-risk maps for the New York City area.