Monitoring-based adaptive water level thresholds for bridge scour risk management

Abstract

Riverbed scour is the leading cause of bridge failure worldwide. Recent developments in sensor technology for structures have resulted in more bridges being instrumented and monitored. However, alongside scour monitoring systems, there is a need of techniques to handle the data obtained and exploit them to inform the management of the bridge scour risk. This paper illustrates the development of a decision support system (DSS) for bridge scour risk management, which is based on a probabilistic framework for scour risk estimation, enhanced by real-time information from scour monitoring systems and in line with current risk procedures used by transport agencies. The proposed DSS provides bridge operators with adaptive measurement-informed water level thresholds triggering bridge closure to traffic under heavy floods. The application of the DSS is illustrated by considering a case study of three bridges at risk of scour managed by Transport Scotland. It is shown that information from scour sensors within the proposed DSS allows reducing the uncertainty in the scour estimates and yields adaptive water level thresholds triggering bridge closure to traffic that can differ significantly from those currently considered by transport agencies. This can ultimately result in a reduction of false alarms and unnecessary bridge closures.