Deterioration of Flexible Pavements Induced by Flooding: Case Study Using Stochastic Monte Carlo Simulations in Discrete-Time Markov Chains

Flooding is and has historically been the most frequent natural disaster in the globe. There is strong evidence that the frequency of flooding is increasing. Pavements, however, are currently designed based on historic climatic conditions assuming a stationary climate, which no longer seems to be a good proxy for future conditions. The goal of this study is to characterize the performance of flooded pavement and quantify the impact of flooding on pavement deterioration and service life. To achieve this goal, the study analyzes the floods occurring in Colorado, United States, in 2013, and uses empirical data on pavement conditions to (1) quantify whether flooding impacts pavement deterioration, (2) define a conceptual model to characterize the deterioration of flooded pavements, and (3) quantify the loss of service life derived from flooding. To address these inquiries, the study used statistical analysis, stochastic Markov deterioration modeling, and Monte Carlo simulations. The study found that flooding accelerates pavement deterioration. Specifically, flooding induces a sudden drop in condition, followed by an accelerated long-term (i.e., multiyear) deterioration that reduces the pavement service life. The better the condition before flooding, the higher the loss of pavement service life. This new understanding of the impact of flooding on pavement conditions will help transportation agencies in the design of resilience programs and postflood strategies. Further research is recommended to analyze other flood events using similar methodologies to understand the influence of factors such as flood characteristics, location, and climate conditions in this phenomenon.