Hierarchical asphalt pavement deterioration model for climate impact studies

M. Anyala*, J. B. Odoki, C. J. Baker

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)


Quantification of the impacts of projected climate change on road pavement performance is possible using predictive models that correctly consider key causal factors of pavement deterioration. These factors include climate, traffic, properties of materials and the design of pavements. This paper presents a new model developed to predict rutting in asphalt surfacing. In addition to the key causal factors of road deterioration, the developed model takes into account several sources of uncertainties, particularly those inherent in future climate change predictions and model input parameters. The asphalt surfacing rut depth progression model was developed from a hierarchical road network data structure using a Bayesian regression approach resulting in a model for each surfacing group. The model was applied within a Monte Carlo simulation framework to derive probabilistic outputs of pavement rut depth progression and maintenance costs under the pre-determined future climate scenarios. This model is useful for application at both the network and project levels to develop road management strategies and policies.

Original languageEnglish
Pages (from-to)251-266
Number of pages16
JournalInternational Journal of Pavement Engineering
Issue number3
Early online date14 May 2012
Publication statusPublished - 16 Mar 2014


  • Bayesian regression
  • Climate change
  • Climate impact assessment
  • Pavement deterioration models
  • Rut depth

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Mechanics of Materials


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