A decision support system for scour management of road and railway bridges based on Bayesian networks

Andrea Maroni, Enrico Tubaldi, Dimitri Val, Hazel McDonald, Stewart Lothian, Oliver Riches, Daniele Zonta

Research output: Contribution to conferencePaperpeer-review

3 Citations (Scopus)
12 Downloads (Pure)


Flood-induced scour is the excavation of material around bridge foundations due to the erosive action of flowing water and it is by far the leading cause of bridge failures worldwide. In the United States, scour is the cause of 22 bridges fail every year whereas in the UK, it contributed significantly to the 138 collapses of bridges in the last century. Monitoring an entire infrastructure network against scour is not economically feasible. A way to overcome this limitation is to install scour monitoring systems (SMSs) at critical bridge locations, and then extend information gained to the entire asset through a probabilistic approach. In this paper, we propose a Decision Support System (DSS) for road and railway bridge scour management that exploits information from a limited number of scour monitoring systems to achieve a more confined estimate of the scour risk for a bridge network. A Bayesian network (BN) is used to describe conditional dependencies among the random variables involved. It allows estimating the present and future scour depth distribution using real-time information from monitoring of scour depth and river flow characteristics. Data collected by SMSs and BN’s outcomes are then used to inform a decision model and thus support transport agencies’ decision frameworks. The idea is to use this information to update the scour threshold after which bridges are closed. A case study consisting of several road bridges in Scotland is built to demonstrate the functioning of the DDS. They cross the same river and only one of them is instrumented with a SMS. The BN is found to estimate accurately the scour depth at unmonitored bridges and the decision model provides higher values of scour threshold compared to the ones implicitly chosen by transport agencies.
Original languageEnglish
Number of pages8
Publication statusPublished - 12 Sept 2019
EventThe 12th International Workshop on Structural Health Monitoring - University of Stanford, Stanford, United States
Duration: 10 Sept 201912 Sept 2019


ConferenceThe 12th International Workshop on Structural Health Monitoring
Abbreviated titleIWSHM 2019
Country/TerritoryUnited States
Internet address


  • scour
  • road and rail bridges
  • structural health monitoring
  • Bayesian network
  • Decision Support System


Dive into the research topics of 'A decision support system for scour management of road and railway bridges based on Bayesian networks'. Together they form a unique fingerprint.

Cite this