EGU23-882
https://doi.org/10.5194/egusphere-egu23-882
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Design flood estimation for flood disaster Resilient bridges exposed to climate change

Rakesh Kumar
Rakesh Kumar
  • Sharda University, School of Engineering and Technology, Civil Engineering, India (rakesh.kumar@sharda.ac.in)

Flood disaster resilient design of the bridges is the lifeline of the transport infrastructure. Design of flood disaster resilient bridges is the major requirement for construction of the main highways and railway networks as well as for developing the transport networks in hilly regions and remote areas. Inadequate hydrologic and hydraulic design of the bridges results in failure of the bridges and during the current rainy season, a number of bridges were washed away in the India and other parts of the world, mainly due to it. In the present era, the construction technology is in fairly well advanced state and a major challenge associated in construction of the disaster resilient bridge infrastructure is to estimate the accurate design flood and using it for determination of the highest flood level (HFL) of the bridges incorporating the growing climate-change-induced threats of the intensifying extreme weather events. In this research, a procedure for design flood estimation for the bridges will be developed based on the L-moments approach of flood frequency analysis and its superiority will be demonstrated over the existing procedures. The data will be screened using the discordancy measure (Di) in terms of the L-moments. Homogeneity of the region will be tested using the L-moments based heterogeneity measure, H. For computing the heterogeneity measure H, 500 simulations will be  performed using the four parameter Kappa distribution. Comparative regional flood frequency analysis studies ill be performed using the L-moments based frequency distributions: viz. Extreme value, General extreme value, Logistic, Generalized logistic, Normal, Generalized normal, Uniform, Pearson Type-III, Exponential, Generalized Pareto, Kappa, and five parameter Wakeby. Based on the L-moment ratio diagram and Zidist -statistic criteria, the robust distribution will be identified and design flood will be estimated using the robust frequency distribution. Effect of climate change will be studied using the CMIP-5 scenarios and the fixed percentage increases in the design flood. The research will create a climate-resilience-centred procedure leading to policy framework comprising of exhaustive methodology, guidelines and tools for design of flood disaster resilient bridges for the road and railway networks to make the transport infrastructure more resilient in the face of future climate change induced uncertainties of the extreme rainfall events.

How to cite: Kumar, R.: Design flood estimation for flood disaster Resilient bridges exposed to climate change, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-882, https://doi.org/10.5194/egusphere-egu23-882, 2023.