2019
DOI: 10.1016/j.jhydrol.2019.05.003
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Using a 2D shallow water model to assess Large-Scale Particle Image Velocimetry (LSPIV) and Structure from Motion (SfM) techniques in a street-scale urban drainage physical model

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Cited by 33 publications
(33 citation statements)
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“…The experimental dataset obtained is described and openly available at the Zenodo [43] repository, where the quality of the experimental results obtained using this rainfall simulator can be confirmed. In addition, these experimental results were used to obtain a detailed representation of the overland runoff though a 2D shallow water model [44] and to analyze the performance of a novel physically-based urban wash-off model [45].…”
Section: Discussionmentioning
confidence: 99%
“…The experimental dataset obtained is described and openly available at the Zenodo [43] repository, where the quality of the experimental results obtained using this rainfall simulator can be confirmed. In addition, these experimental results were used to obtain a detailed representation of the overland runoff though a 2D shallow water model [44] and to analyze the performance of a novel physically-based urban wash-off model [45].…”
Section: Discussionmentioning
confidence: 99%
“…First, an accurate hydraulic characterization was performed, measuring flows and depths generated by three different rain intensities, additionally obtaining runoff velocity distributions and elevations using visualization techniques. In Naves et al 27 , these data have been used to assess Large-Scale Particle Image Velocimetry (LSPIV) and Structure from Motion (SfM) techniques to accurately represent overland flow obtaining surface velocity distributions and surface elevations respectively. The videos and images provided can be of reuse as a means of optimizing visualization techniques for hydraulic modelling purposes.…”
Section: Background and Summarymentioning
confidence: 99%
“…Finally, the resulted velocity distributions that are provided correspond to the surface flow velocity and not to the depth-average velocities. Some authors use a flow velocity correction factor from 0.6 to 1 based on the log-law velocity profile 24,42 , and in Naves et al 27 the classical value of 0.85 was applied. However, due to the very shallow flow conditions, this assumption is not expected to add significant uncertainties.…”
Section: Surface Velocitiesmentioning
confidence: 99%
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“…In Naves et al (2019a), a variation of the LSPIV technique was applied to measure the surface velocity fields generated by three different rain intensities in a full-scale urban drainage physical model. That study used UV illumination and fluorescent particles as artificial tracers to satisfactorily address the problems caused by the presence of raindrops in the experiments, which are the interference of raindrops in the visualization of images and the disturbances generated in the flow because of https://doi.org/10.5194/hess-2020-136 Preprint.…”
Section: Introductionmentioning
confidence: 99%