Risk-informed and data-driven adaptation : quantitative advancements in spatial risk analysis at the intersection of built and human systems.
| dc.contributor.author | Anderson, Mitchell | |
| dc.date.accessioned | 2025-02-20T21:09:39Z | |
| dc.date.available | 2025-02-20T21:09:39Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | The increasing frequency and severity of climate-related natural hazards worldwide threatens the lives and wellbeing of billions. It is this notion that underscores the urgent need for equitable and effective adaptation planning, which, as described in this thesis, requires accessible and advanced spatial risk assessment methodologies. This thesis explores and advances methodologies for modelling quantitative impacts on infrastructure and communities during and after natural hazard events. The research aims to improve the effectiveness of spatial risk assessments and subsequent decision-making in climate adaptation, infrastructure management, land use planning, and emergency response. The overarching objective is to enhance the understanding of how risks cascade between built and human systems. This is achieved through a systematic examination and strengthening of methodologies used within climate risk and adaptation assessments to date. Specifically, this research integrates the modelling of natural hazards with social vulnerability, interconnected infrastructure networks, supply chain disruptions, and community access to essential services. Key methodological advancements include the development of techniques for modelling residents and assets that become isolated during hazard events, the introduction of the concept of functional isolation, and the incorporation of distributional justice considerations into direct and indirect risk assessments. These innovations address critical gaps identified in a systematic review of 86 global climate risk and adaptation assessments, particularly in addressing indirect impacts and equity considerations. Case studies in New Zealand and the United States demonstrate the practical utility of these methodologies in real-world scenarios. Analysis of coastal flooding in New Zealand reveals that including indirect impacts increases the at-risk population from 61,993 to 217,002 in a present-day event, with disproportionate effects on Māori communities. In Christchurch, the concept of functional isolation uncovers a three-fold increase in affected residential buildings when considering cascading infrastructure failures on critical amenities such as health-related and educational facilities. By addressing critical gaps in current risk analysis practices, this research contributes to a more comprehensive understanding of community resilience in the face of increasing climate-related risks. The findings have significant implications for equitable and effective climate adaptation strategies, emergency preparedness, and long-term urban planning. As climate change escalates global risks, the approaches and insights presented become increasingly critical for building resilient communities worldwide. The thesis concludes by discussing future research directions and the potential for wider application of these methodologies in future risk assessments and adaptation plans around the world. | |
| dc.identifier.uri | https://hdl.handle.net/10092/108106 | |
| dc.identifier.uri | https://doi.org/10.26021/15665 | |
| dc.language | English | |
| dc.language.iso | en | |
| dc.rights | All Right Reserved | |
| dc.rights.uri | https://canterbury.libguides.com/rights/theses | |
| dc.title | Risk-informed and data-driven adaptation : quantitative advancements in spatial risk analysis at the intersection of built and human systems. | |
| dc.type | Theses / Dissertations | |
| thesis.degree.discipline | Civil Engineering | |
| thesis.degree.grantor | University of Canterbury | |
| thesis.degree.level | Doctoral | |
| thesis.degree.name | Doctor of Philosophy | |
| uc.bibnumber | in1406389 | |
| uc.college | Faculty of Engineering |