Incorporating climate adaptation into future road infrastructure maintenance costs

Abstract

The effects of climate change, such as increasing temperatures and changing precipitation patterns, significantly affect road infrastructure’s structural integrity and longevity, requiring a reevaluation of maintenance standards. Previous research on pavement performance did not incorporate climate adaptation into maintenance standards. This study develops a scenario-based road infrastructure maintenance cost prediction approach integrating climate and traffic scenarios. Using high-resolution data on pavement depth and materials, it evaluates future impacts on maintenance costs in Western Australia, and advances sustainable spatial planning under climate change through geospatial, decision-oriented analysis. The results show that without intervention, traffic and climate change could significantly increase road maintenance costs by 2050. Under an equivalent service-improvement target of a 1.0-point reduction in network-average International Roughness Index, adopting climate-adaptive pavement standards reduces life-cycle maintenance costs by 16.1 % relative to the baseline scenario, while traffic-management-based redistribution reduces costs by 17.0 % relative to the same baseline scenario. Integrating climate adaptation into road maintenance standards provides more accurate, actionable recommendations for policymakers and engineers to enhance infrastructure resilience, reduce long-term costs, and safeguard against the adverse climate change impacts on transportation networks.

Keywords

Climate adaptation / Road maintenance / Predictive modeling / Life-cycle cost analysis / Traffic management

Data availability statement

Please refer to https://doi.org/10.6084/m9.figshare.31566121.

Declaration of competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

CRediT authorship contribution statement

Pengcheng Zhang: Writing – original draft, Visualization, Validation, Methodology, Formal analysis, Data curation, Conceptualization. Wen Yi: Writing – review & editing, Supervision, Funding acquisition. Yongze Song: Writing – review & editing, Supervision, Methodology, Formal analysis, Conceptualization. Zhi Cao: Writing – review & editing, Methodology. Peng Wang: Writing – review & editing. Weiqiang Chen: Writing – review & editing. Peng Wu: Writing – review & editing, Supervision. Ammar Shemery: Writing – review & editing, Data curation. Keith Hampson: Writing – review & editing.

Acknowledgements

This research work was supported by the National Natural Science Foundation of China (Grants No. 72201229 and 72361137006 ) and Centre for Infrastructure Delivery Research Funding (Grant No. P0055981 ).

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