This thesis presents a new GIS-based scenario volcanic risk assessment model called RiskScape Volcano (RSV) that has been designed for the RiskScape program to advance the field of volcanic risk assessment. RiskScape is a natural hazards risk assessment software tool being developed in New Zealand by GNS Science and NIWA. When integrated into RiskScape, RSV will add proximal volcanic hazard risk assessment capability, and enhanced inventory design; it presently operates outside of RiskScape by combining volcanic hazard models’ output spatial hazard intensity (hazard maps) with inventory databases (asset maps) in GIS software to determine hazard exposure, which is then combined with fragility functions (relationships between hazard intensity and expected damage ratios) to estimate risk. This thesis consists of seven publications, each of which comprises a part of the development and testing of RSV: 1) results of field investigation of impacts to agriculture and infrastructure of the 2006 eruption of Merapi Volcano, Indonesia; 2) agricultural fragility functions for tephra damage in New Zealand based on the observations made at Merapi; 3) examination of wind patterns above the central North Island, New Zealand for better modeling of tephra dispersal with the ASHFALL model; 4) a description of the design, components, background, and an example application of the RSV model; 5) test of RSV via a risk assessment of population, agriculture, and infrastructure in the Rotorua District from a rhyolite eruption at the Okataina Volcanic Centre; 6) test of RSV via a comparison of risk to critical infrastructure in Mammoth Lakes, California from an eruption at Mammoth Mountain volcano versus an eruption from the Inyo craters; and 7) a survey of volcanic hazard awareness in the tourism sector in Mammoth Lakes. Tests of the model have demonstrated that it is capable of providing valid and useful risk assessments that can be used by local government and emergency management to prioritise eruption response planning and risk mitigation efforts. RSV has provided the RiskScape design team with a more complete quantitative volcanic risk assessment model that can be integrated into RiskScape and used in New Zealand and potentially overseas.

This thesis presents a new GIS-based scenario volcanic risk assessment model called RiskScape Volcano (RSV) that has been designed for the RiskScape program to advance the field of volcanic risk assessment. RiskScape is a natural hazards risk assessment software tool being developed in New Zealand by GNS Science and NIWA. When integrated into RiskScape, RSV will add proximal volcanic hazard risk assessment capability, and enhanced inventory design; it presently operates outside of RiskScape by combining volcanic hazard models’ output spatial hazard intensity (hazard maps) with inventory databases (asset maps) in GIS software to determine hazard exposure, which is then combined with fragility functions (relationships between hazard intensity and expected damage ratios) to estimate risk. This thesis consists of seven publications, each of which comprises a part of the development and testing of RSV: 1) results of field investigation of impacts to agriculture and infrastructure of the 2006 eruption of Merapi Volcano, Indonesia; 2) agricultural fragility functions for tephra damage in New Zealand based on the observations made at Merapi; 3) examination of wind patterns above the central North Island, New Zealand for better modeling of tephra dispersal with the ASHFALL model; 4) a description of the design, components, background, and an example application of the RSV model; 5) test of RSV via a risk assessment of population, agriculture, and infrastructure in the Rotorua District from a rhyolite eruption at the Okataina Volcanic Centre; 6) test of RSV via a comparison of risk to critical infrastructure in Mammoth Lakes, California from an eruption at Mammoth Mountain volcano versus an eruption from the Inyo craters; and 7) a survey of volcanic hazard awareness in the tourism sector in Mammoth Lakes. Tests of the model have demonstrated that it is capable of providing valid and useful risk assessments that can be used by local government and emergency management to prioritise eruption response planning and risk mitigation efforts. RSV has provided the RiskScape design team with a more complete quantitative volcanic risk assessment model that can be integrated into RiskScape and used in New Zealand and potentially overseas.

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.