Abstract
Scour is one of the most widespread causes of bridge failure worldwide. The magnitude of the river flow at the bridge location is a key factor which directly affects the scour hole depth. Climate change may cause changes in the flow characteristics in a river due to changes in the precipitation patterns and catchment characteristics. In this paper, statistical analysis of the expected maximum annual flow of rivers is combined with the Monte Carlo simulation to estimate the probability of local scour failure. Climate change is assumed to manifest itself through gradual changes in the statistical characteristics of the expected maximum annual flow distributions. Results are presented from a case study using a bridge in the UK, which revealed that a time-dependent increase in the mean of the expected maximum annual flow has a more pronounced effect on scour performance as compared to an increase of its variability alone. Amongst the cases examined, however, the most adverse effect on local scour performance is observed from the simultaneous increase in both mean and variability of the expected maximum annual flow. The results also highlighted the significance of the foundation depth and local scour model parameter in relation to the changing flow characteristics.