Pavement infrastructure is experiencing unanticipated climate conditions caused by global warming. Extreme weather events, such as extreme precipitations, are increasing in intensity and frequency, creating rising concern in pavement vulnerability and resilience analysis. Previous design approaches based on historical climate data may no longer be adequate for addressing future conditions. To promote pavement resilience under climate change, assessing pavement risk for extreme events is essential for prioritizing vulnerable infrastructure and developing adaptation strategies. The objective of this study is to develop a quantitative evaluation methodology for assessing pavement risk from extreme precipitations under climate change. Hazard analysis, fragility modeling, and cost estimation are the three major components for risk evaluation. An ensemble of 24 global climate models is used for predicting future extreme precipitations under various climate-forcing scenarios. The Mechanistic-Empirical Pavement Design Guide is employed to simulate performance change for performing fragility modeling. Risk assessment models considering a full range of hazards were used to quantify risk of asset value loss over specified analysis periods. Results indicate that future extreme precipitation events are expected to cause an increased medium risk of asset value loss. However, high uncertainties are involved in the estimation owing to variations in predicted climates. Major pavement damages do not necessarily equate with highest risk because the probability of occurrence of major damage is relatively lower. The proposed approach provides a practical tool for analyzing the interaction among extreme precipitation levels, pavement designs, damage states, occurrence probability, and asset value at risk.


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    Title :

    Pavement Risk Assessment for Future Extreme Precipitation Events under Climate Change


    Additional title:

    Transportation Research Record: Journal of the Transportation Research Board


    Contributors:


    Publication date :

    2018-06-06




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



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