Articles | Volume 25, issue 2
https://doi.org/10.5194/hess-25-885-2021
https://doi.org/10.5194/hess-25-885-2021
Research article
 | 
24 Feb 2021
Research article |  | 24 Feb 2021

Assessing different imaging velocimetry techniques to measure shallow runoff velocities during rain events using an urban drainage physical model

Juan Naves, Juan T. García, Jerónimo Puertas, and Jose Anta

Related subject area

Subject: Urban Hydrology | Techniques and Approaches: Instruments and observation techniques
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Cited articles

Aberle, J., Rennie, C., Admiraal, D., and Muste, M.: Experimental Hydraulics: Methods, Instrumentation, Data Proce and Management: Volume II: Instrumentation and Measurement Techniques, CRC Press, London, UK, 2017. 
Adrian, L., Adrian, R. J., and Westerweel, J.: Particle image velocimetry (No. 30), Cambridge University Press, Cambridge, 2011. 
Anta, J., Peña, E., Suárez, J., and Cagiao, J.: A BMP selection process based on the granulometry of runoff solids in a separate urban catchment, Water Sa., 32, 419–428, https://doi.org/10.4314/wsa.v32i3.5268, 2006. 
Apel, H., Thieken, A. H., Merz, B., and Blöschl, G.: Flood risk assessment and associated uncertainty, Nat. Hazards Earth Syst. Sci., 4, 295–308, https://doi.org/10.5194/nhess-4-295-2004, 2004. 
Arnbjerg-Nielsen, K., Willems, P., Olsson, J., Beecham, S., Pathirana, A., Bülow Gregersen, I., Madsen, H., and Nguyen, V. T. V.: Impacts of climate change on rainfall extremes and urban drainage systems: a review, Water Sci. Technol., 68, 16–28, https://doi.org/10.2166/wst.2013.251, 2013. 
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Short summary
Surface water velocities are key in the calibration of physically based urban drainage models, but the shallow depths developed during non-extreme rainfall and the risks during floods limit the availability of this type of data. This study proves the potential of different imaging velocimetry techniques to measure water runoff velocities in urban catchments during rain events, highlighting the importance of considering rain properties to interpret and assess the results obtained.