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Arnau Bayón

Publications and source records attributed to Arnau Bayón.

2 recordsLinked to original sources

Urban Flood Drifters (UFDs): identification, classification and characterisation

Extreme floods threaten lives, assets and ecosystems, with the largest impacts occurring in urbanised areas. However, flood mitigation schemes generally neglect the fact that urban floods carry a considerable amount of solid load. In this study, we define Urban Flood Drifters (UFDs) as loose objects present in the urban landscape that can become mobile under certain flow conditions, thereafter blocking drainage infrastructure and endangering both downstream and upstream communities. Based on 270 post-flood photographic records from 63 major inundations of the past quarter-century across 46 countries, we provide a comprehensive analysis of UFDs and their flood-hazard implications. We show that a variety of vehicles, furniture and a heterogeneous mixture of drifters are present in post-flooding scenarios. Plastic, construction debris and wood (natural or anthropogenic) dominate the statistics of transported drifters in urban floods (with frequencies of roughly 50-60% each), followed by cars (present in 31.5% of post-flood images). Other heavy vehicles are readily observed in post-flood imagery and furniture such as bins, garden sheds or water tanks also appear occasionally, therefore suggesting that they can play a relevant role in extreme floods.

physics.flu-dyn↗

Urban Flood Drifters (UFDs): Onset of Movement

Despite their catastrophic implications in flood events, the mobilization and transport of large, loose objects - termed Urban Flood Drifters (UFDs) - are often overlooked in flood management. This oversight stems from our limited understanding of how flowing water interacts with these heterogeneous objects. To bridge this knowledge gap, we introduce a mechanistic stability model that predicts the onset of UFD mobilization across a diverse array of loose objects, from plastics to heavy vehicles. Built on an inventory of key physical properties of UFDs, this model is also validated against existing mobilization studies. Our model generates stability curves that delineate flow conditions leading to their mobilization. We further enhance the reliability of our model by incorporating a Monte Carlo-based probabilistic framework that accounts for uncertainties and interdependencies among the input parameters. These probabilistic stability curves enable us to estimate the likelihood of mobilization for specific categories of UFDs under certain flow conditions. When integrated with flood maps or two-dimensional (2D) hydrodynamic models, our stability curves can guide urban planning efforts to predict and mitigate the impacts of UFDs during extreme flood events.

physics.flu-dyn↗