Stormwater Infrastructure Resilience Assessment against Seismic Hazard Using Bayesian Belief Network

Maryam Garshasbi, Golam Kabir () and Subhrajit Dutta
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Maryam Garshasbi: Industrial Systems Engineering, University of Regina, Regina, SK S4S 0A2, Canada
Golam Kabir: Industrial Systems Engineering, University of Regina, Regina, SK S4S 0A2, Canada
Subhrajit Dutta: Department of Civil Engineering, National Institute of Technology Silchar, Silchar 781017, India

IJERPH, 2023, vol. 20, issue 16, 1-19

Abstract: Resilient stormwater infrastructure is one of the fundamental components of resilient and sustainable cities. For this, the resilience assessment of stormwater infrastructure against earthquake hazards is crucial for municipal authorities. The objective of this study is to develop a resilience assessment framework for stormwater pipe infrastructure against seismic hazards. A Bayesian belief network (BBN)-based stormwater infrastructure resilience model is constructed based on the published literature and expert knowledge. The developed framework is implemented in the city of Regina, Canada, to assess the city’s stormwater pipe infrastructure resilience. The outcome of the model indicates that proposed BBN-based stormwater infrastructure resilience model can effectively quantify uncertainties and handle the nonlinear relationships between several reliability and recovery factors. The model is also capable of identifying the most sensitive and vulnerable stormwater pipes within the network.

Keywords: resilience; stormwater pipe infrastructure; seismic hazard; Bayesian belief network; sensitivity analysis (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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