Vulnerability of road bridge infrastructure under extreme flood events — ASN Events

Vulnerability of road bridge infrastructure under extreme flood events (#67)

Sujeeva Setunge 1 , Weena Lokuge 2
  1. RMIT University, Melbourne, VIC, Australia
  2. Civil and Environmental Engineering, University of Southern Queensland, Toowoomba, Qld, Australia

Road network and critical road structures such as bridges, culverts and floodways have a vital role before, during and after extreme events to reduce the vulnerability of the community being served. Understanding the resilience of existing structures to known natural hazards empowers the road authorities in risk mitigation and emergency management. Major resources available to researchers to address the complex problem include the recent case studies of extreme events where failures of infrastructure and resultant impact on community have been captured by some road authorities. For example, 2010-2011 floods in Queensland, Australia, had a huge impact particularly on central and southern Queensland resulting in the state owned properties such as 9170 km road network, 4748 km rail network, 89 severely damaged bridges and culverts, 411 schools and 138 national parks.

The paper presents a detailed analysis of the case study of 2013 floods in Lockyer valley region in Australia to identify the critical failure mechanisms of road bridge structures exposed to flood events. In the region, 43 out 46 bridges were damaged due to the 2013 flood. Major failure mechanisms of bridge structures have been identified as scouring of abutments and piers, damage to bridge decks due to urban debris impact and severe damages to bridge approach ramps. A subsequent analysis of the current design standards for bridge structures indicated the possible gaps in design practices which may have led to the observed failures. A methodology of quantifying the vulnerability of bridge structures has been identified through a detailed analysis of the case studies and an extensive review of published research. Application of the methodology is demonstrated using the Queensland case study.