Resilience Through Infrastructure Asset Management Long-term Planning

Infrastructure systems worldwide face increasing threats from climate change, manifested in intensified and more frequent natural hazards such as flooding, sea-level rise, and extreme weather events. Effective long-term planning and resilience-building measures are crucial to mitigate these risks and ensure sustainable development, economic stability, and societal well-being. In response to these challenges, this thesis advances infrastructure resilience planning by developing innovative methodologies tailored to manage uncertainty and complexity arising from climate change impacts to natural hazard frequencies. The application of Investment Logic Mapping (ILM) provided a novel qualitative lens that integrates societal well-being into infrastructure adaptation and asset management (IAM). Traditionally utilised for strategic investment planning, ILM uniquely illustrates how infrastructure interventions yield comprehensive benefits across social, economic, environmental, and cultural dimensions, reinforcing a socio-technical resilience perspective. This approach extends beyond physical robustness and emphasises quality of life in line with the New Zealand Living Standard Framework. Geographic Information System (GIS)-based analysis is performed following the ILM analysis to spatially illustrate the intersections between climate hazards and vulnerable infrastructure assets. The spatial overlay method utilised in this thesis provided an informed risk in the study area of Thames-Coromandel. The geospatial analysis provided insights into a localised area of interest based on hazard exposure and vulnerability. Using the location of interest provided practical insights into risks in the area and into prioritising localised interventions. The GIS-based analysis in this thesis is considered to provide a micro-regional vulnerability map. Furthermore, this spatial analysis facilitates targeted resilience strategies that are adaptable across diverse geographic contexts and data availabilities. A further methodological contribution involves constructing a criteria matrix to evaluate decision-support tools, including cost-benefit analysis, multi-criteria decision analysis, and robust planning. The matrix systematically assesses the effectiveness of the tools in multi-hazard scenarios, their integration of well-being indicators, and their robustness under uncertainty. Such structured comparative analysis provides planners and researchers with clear guidelines for choosing appropriate methodologies aligned with resilience objectives and data constraints. This thesis introduced a multi-stage, multi-objective Robust Decision Making (RDM) framework that enables the evaluation of infrastructure strategies across multiple plausible periods. This research enhances the capacity of long-term planning by identifying interventions and how they may vary under different scenarios, such as budget and objectives. The methodology used in this chapter provides a dynamic approach to stress-test infrastructure decisions under deep uncertainty, thereby enabling forecasted infrastructure strategies beyond a single-scenario setting. Despite these advancements, the Author acknowledges several limitations, including reliance on proxy or broad-scale data, which affects the precision of local outcomes; limited case-study explorations outside the study area; and a primarily conceptual integration of well-being due to the absence of extensive stakeholder validation. Data unavailability and modelling limitations also constrain the scalability of the RDM approach, particularly for detailed power network analysis. Lastly, the practical implementation of advanced methodologies remained a work in progress. In summary, while the methodologies proposed in this thesis significantly enhance theoretical and practical frameworks for infrastructure resilience, their full operationalisation requires ongoing refinement, stakeholder engagement, and comprehensive empirical testing. Thus, this research meets its initial objectives and identifies pathways for future exploration and detailed development within the resilience and long-term infrastructure planning domain.

Name thesis:degree_name

PhD

Level thesis:degree_level

Doctoral

Discipline thesis:degree_discipline

Civil and Environmental Engineering

Grantor dc:publisher

ResearchSpace@Auckland

Year dc:date.issued

2026

Author dc:creator

• Hasanah, Annisa Nur

Advisors dc:contributor.advisor

• Henning, Theuns
• Wotherspoon, Liam

• Infrastructure resilience
• Infrastructure asset management
• Long-term planning
• Robust decision-making
• Climate change adaptation
• Interdependent infrastructure
• Natural hazards
• Investment decision-making

Statement dc:rights

• Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Licence dc:rights.uri

• https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm

Handle dc:identifier.uri

https://hdl.handle.net/2292/75039

OAI identifier oai:identifier

oai:researchspace.auckland.ac.nz:2292/75039