In the past few years across the world, the increases in frequency and intensity of floods, primarily resulting from climate change and extreme weather conditions, have significantly caused damage to property and infrastructure, particularly riverine bridges. Such flood events result in the erosion of soil around the foundation of the bridges (known as scouring), which is widely identified as a leading cause of bridge failures. The exposure of bridge foundations to hydraulic forces results in the reduction of the lateral load-carrying capacity of the pile foundation and bridge system. According to reports, the failure of bridges due to floods and flood-induced scouring is 51.89% in India, and in the USA, it is 54.85%. These statistics highlight the significant impact of floods and flood-induced scouring on the vulnerability of the bridges. Therefore, it is crucial to assess the vulnerability of riverine bridges situated in high-flow rivers incorporating the influence of time-dependent scouring during design service life.
To address existing research gaps, this study focuses on evaluating the flood vulnerability assessment of riverine bridges by incorporating the effect of time-dependent scour through fragility curves. To achieve this, a case study bridge is selected, and temporal scour depth is calculated over the bridge service life using regional discharge data for various flood scenarios. A detailed three-dimensional finite element model of the case-study bridge is developed incorporating soil-foundation-structure interaction effects through a series of zerolength nonlinear soil spring elements positioned at various depths along the pile length. Considering different sources of uncertainties and utilizing Latin hypercube sampling, a set of multiple bridge models is generated, and the fragility curves are developed. The findings of this study highlight the substantial effect of scouring on bridge vulnerability during flood events, providing essential insights for improving infrastructure resilience and developing effective risk mitigation strategies.