Transurban FY26 Corporate Report Section C: Strategy
Key assumptions
Summary output
Modelling of asset damage and traffic disruptions • The assessment used third-party modelling software to evaluate climate- related hazards across the Group’s road network. A selection of representative locations across open roads, tunnels and bridges was used, given the impracticality of assessing every part of the Group’s road network. While these locations were chosen to reflect a range of potential climate-related hazard exposures, they may not capture all asset characteristics or location-specific risks across the network. • The assessment methodology focused on road assets. Buildings, tolling systems and other non-road assets representing approximately 10% of total insured asset value were excluded. Assessment of tolling systems was not supported by relevant asset types within the modelling software, and the modelling methodology was not designed to assess buildings. • Assessed climate-related hazards include coastal inundation, extreme heat, extreme wind, forest fire, freeze-thaw, landslide, riverine flood, soil movement, surface water flood, tropical cyclone storm surge, and tropical cyclone wind. • Impact estimates are based on generic asset assumptions for open roads, tunnels and bridges and may not fully reflect the Group’s asset designs, engineering controls or resilience measures. As a result, soil movement risks were excluded from the assessment, as the methodology was not considered sufficiently representative of the Group’s assets. • Disruption to any part of a road segment is assumed to render the entire segment non-operational for the event duration. • Traffic disruption results are based on estimates of asset inoperability due to hazard events and do not take customer behaviour into account. • Risks are assessed independently, without accounting for potential interactions or differing asset-level responses. • Estimates represent potential maximum exposure based on inherent risk, excluding management actions or mitigation measures, and are derived using a probability-weighted value-at-risk framework. • Underlying asset damage calculations reflect 100% of asset values as per Group property insurance coverage.
• Scenario analysis indicates that physical climate risks are not expected to have a material financial effect through to 2050. Under RCP 8.5, estimated impacts remain modest, with average annual long-term cashflow effects of approximately $11 million, reaching around $13 million by FY50. • Sea level rise may increase the risk of coastal inundation (for example, during extreme high or king tides), potentially resulting in localised flooding and associated revenue loss due to disruption to asset operations. • Identified impacts are driven by bushfire affecting assets in New South Wales and Queensland, coastal inundation caused by sea level rise affecting assets in Victoria, and landslide risks associated with changes in precipitation (including extreme rainfall and flooding) affecting assets in Australia and GWA. The Group maintains CCAP and maintenance programs to manage and mitigate these risks. • Modelled impacts continue to increase beyond 2050, reflecting the longer-term effects of climate change. These projections are subject to heightened uncertainty, including variability in the frequency, severity and geographic distribution of climate-related risks. • Notwithstanding the relatively modest average annual impacts, actual impacts in any given year may vary and could be higher due to the episodic and non-linear nature of physical climate risks, with outcomes influenced by the timing and occurrence of individual climate events.
The results of this analysis help inform the Group’s strategy by supporting decision-making across asset design and engineering practices, capital allocation, and lifecycle planning. This includes the application of best-practice sustainable infrastructure design and construction standards and reinforces the Group’s disciplined approach to maintenance, resilience planning, and long-term asset management.
Key judgements and uncertainties Scenario analysis of weather related impacts to infrastructure and operations
The scenario analysis relies on third-party modelling of asset damage and traffic disruptions, including climate hazard damage functions applied to generic asset types. These approaches may not fully capture asset-specific characteristics, resilience measures or operational controls, and therefore involve a high degree of estimation uncertainty. The Group has applied judgement in validating and interpreting the outputs against the Group’s assets, operating conditions, design characteristics and historical experience. Modelling limitations include the use of representative geographic points, generic asset design and engineering attributes, independent hazard modelling, and the exclusion of asset-specific resilience measures or controls. ¢
c. R2 Safety and wellbeing of customers, communities, employees and contractors Qualitative assessment indicates that the increasing frequency and intensity of extreme heat and heavy precipitation events may adversely affect the safety and wellbeing of employees, contractors, customers and communities through heightened exposure to heat stress, hazardous road conditions and increased incident risk. These impacts may also contribute to operational disruptions, reduced workforce productivity, service delays, potential increases in workforce and operational costs, and reputational impacts where stakeholder expectations regarding safety and community outcomes are not met. Quantitative analysis has not been undertaken for these risks as the Group has not historically experienced material operational and safety effects directly attributable to climate-related heat stress, unsafe road
conditions or associated incidents. While these risks are recognised qualitatively, the feasibility of developing robust quantitative estimates is currently limited by the complexity of isolating climate-related factors from other contributing factors, including traffic volumes, driver behaviour, road design, asset condition and operational practices. In particular, the relationship between long-term climate change and incident frequency or severity is subject to significant uncertainty and relies on multiple assumptions that cannot currently be supported by sufficiently granular historical data. As a result, any quantitative estimates would have a high degree of uncertainty and may not provide a sufficiently representative or decision-useful assessment of potential financial effects.
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