Advertisement

Natural Hazards

, Volume 87, Issue 1, pp 383–394 | Cite as

Use of LSPIV in assessing urban flash flood vulnerability

  • Nicolás Federico GuillénEmail author
  • Antoine Patalano
  • Carlos Marcelo García
  • Juan Carlos Bertoni
Original Paper

Abstract

The probability of the occurrence of urban flash floods has increased appreciably in recent years. Scientists have published various articles related to the estimation of the vulnerability of people and vehicles in urban areas resulting from flash floods. However, most published works are based on research performed using numerical models and laboratory experiments. This paper presents a novel approach that combines the implementation of image velocimetry technique (large-scale particle image velocimetry—LSPIV) using a flash flood video recorded by the public locally and the estimation of the vulnerability of people and vehicles to high water velocities in urban areas. A numerical one‐dimensional hydrodynamic model has also been used in this approach for water velocity characterization. The results presented in this paper correspond to a flash flood resulting on November 29, 2012, in the city of Asunción in Paraguay. During this flash flood, people and vehicles were observed being carried away because of high water velocities. Various sequences of the recorded flash flood video were characterized using LSPIV. The results obtained in this work validate the existing vulnerability criterion based on the effect of the flash flood and resulting high water velocities on people and vehicles.

Keywords

LSPIV Surface water velocity measurement Urban floods Experimental techniques 

Abbreviations

LSPIV

Large-scale particle image velocimetry

Notes

Acknowledgements

The authors acknowledge Angel M. Martin, Jr., USGS retired, for his technical edit and constructive comments on the manuscript; Kevin A. Oberg, USGS—Office of Surface Water, for helping in the final edition of this work; and two anonymous reviewers provided useful comments and suggestions for improving the manuscript.

References

  1. Australia Institute of Engineers (1987) Australian rainfall and runoff, vol 1&2. (Ed: Pilgrim, D.H.) Institution of Engineers, AustraliaGoogle Scholar
  2. Chow VT (1959) Open-channel hydraulics. McGraw-Hill, New York, p 680Google Scholar
  3. Creutin J-D, Muste M, Bradley A, Kim SC, Kruger A (2003) River gauging using PIV techniques: a proof of concept experiment on the Iowa River. J Hydrol 277(3–4):182–194CrossRefGoogle Scholar
  4. Engineers Australia (2010) Australian rainfall and runoff revision projects. PROJECT 10 appropriate safety criteria for people. STAGE 1 REPORT P10/S1/006. April 2010Google Scholar
  5. Federal Emergency Management Agency (FEMA) (1979) The floodway: a guide for community permit officials. EEUUGoogle Scholar
  6. Fujita I, Muste M, Kruger A (1998) Large-scale particle image velocimetry for flow analysis in hydraulic engineering applications. J Hydraul Res 36(3):397–414CrossRefGoogle Scholar
  7. Fujita I, Kunita Y, Tsubaki R (2013) Image analysis and reconstruction of the 2008 Toga River flash flood in an urbanized area. Aust J Water Resour 16(2):12CrossRefGoogle Scholar
  8. Hauet A, Muste M, Ho HC (2009) Digital mapping of riverine waterway hydrodynamic and geomorphic features. Earth Surf Proc Land 34(2):242–252CrossRefGoogle Scholar
  9. Le Boursicaud R, Pénard L, Hauet A, Thollet T, Le Coz J (2016) Gauging extreme floods on YouTube: application of LSPIV to home movies for the post-event determination of stream discharges. Hydrol Process 30:90–105CrossRefGoogle Scholar
  10. Le Coz J, Magali Jodeau, Hauet A, Marchand B, Le Boursicaud R (2014) Image-based velocity and discharge measurements in field and laboratory river engineering studies using the free FUDAA-LSPIV software. River Flow, LausanneGoogle Scholar
  11. Le Coz J, Patalano A, Collins D, Guillén NF, García CM, Smart GM, Bind J, Chiaverini A, Le Boursiqueau R, Dramais G, Braud I (2016) Crowd-sourced data for flood hydrology: feedback from recent citizen science projects in Argentina, France and New Zealand. J Hydrol. Available online 26 July 2016, ISSN 0022-1694, http://dx.doi.org/10.1016/j.jhydrol.2016.07.036. (http://www.sciencedirect.com/science/article/pii/S0022169416304668)
  12. Martínez-Gomariz E, Gómez M, Russo B (2016) Experimental study of the stability of pedestrians exposed to urban pluvial flooding. Nat Hazards 1–20Google Scholar
  13. Milanesi L, Pilotti M, Ranzi R (2015) A conceptual model of people’s vulnerability to floods. Water Resour Res 51:182–197. doi: 10.1002/2014WR016172 CrossRefGoogle Scholar
  14. Muste M, Schöne J, Creutin J-D (2005) Measurement of free-surface flow velocity using controlled surface waves. Flow Meas Instrum 16(1):47–55CrossRefGoogle Scholar
  15. Muste M, Fujita I, Hauet A (2008) Large-scale particle image velocimetry for measurements in riverine environments. Water Resour Res 44:1–14CrossRefGoogle Scholar
  16. Nanía LS (1999) Metodología numérico experimental para el análisis del riesgo asociado a la escorrentía pluvial en una red de calles. Tesis doctoral. Universitat Politècnica de Catalunya, Barcelona, EspañaGoogle Scholar
  17. Patalano A, García CM (2006) RIVeR—towards affordable, practical and user-friendly toolbox for large scale PIV and PTV techniques. In: IAHR RiverFlow Conference, St. Louis, Missouri, USAGoogle Scholar
  18. Rooseboom A, Basson MS, Loots CH, Wiggett JH, Bosman J (1986) Manual on road drainage, 2nd edn. National Transport Commission, Chief Director of National Road, Republic of South AfricaGoogle Scholar
  19. Russo B (2009) Design of surface drainage systems according to hazard criteria related to flooding of urban areas. Tesis doctoral. Universitat Politècnica de Catalunya, Barcelona, EspañaGoogle Scholar
  20. Stumpf A, Augereau E, Delacourt C, Bonnier J (2016) Photogrammetric discharge monitoring of small tropical mountain rivers: a case study at Rivière des Pluies, Réunion Island. Water Resour Res 52(6):4550–4570CrossRefGoogle Scholar
  21. Témez JR (1992) Control del desarrollo urbano en las zonas inundables. Monografías del Colegio de Ingenieros de Caminos, Canales y Puertos, vol 10, pp 105–115. Madrid, SpainGoogle Scholar
  22. Thielicke W, Stamhuis EJ (2014) PIVlab—towards user-friendly, affordable and accurate digital particle image velocimetry in MATLAB. J Open Res Softw 2(1):e30. doi: 10.5334/jors.bl Google Scholar
  23. USACE [US Army Corps of Engineers] (2008) HEC-RAS Version 4.1. Davis, CA Institute for Water Resources, Hydrologic Engineering CenterGoogle Scholar
  24. WMO [World Meteorological Organization] (2009) Flood management in a changing climate. APFM technical document no. 9, Flood management tools series, associated programme on flood management (WMO), Geneva. Switzerland. www.apfm.info/pdf/ifm_tools/Tools_FM_in_a_changing_climate.pdf
  25. Wright-Mc Laughlin Engineers (1969) Urban drainage and flood control district, vol 861. Denver, Colorado, USAGoogle Scholar
  26. Xia J, Teo FY, Lin B, Falconer RA (2011) Formula of incipient velocity for flooded vehicles. Nat Hazards 58(1):1–14CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2017

Authors and Affiliations

  • Nicolás Federico Guillén
    • 1
    Email author
  • Antoine Patalano
    • 1
  • Carlos Marcelo García
    • 1
  • Juan Carlos Bertoni
    • 1
  1. 1.Institute for Advanced Studies for Engineering and Technology (IDIT CONICET/UNC), CETA–FCEFyNUniversidad Nacional de CórdobaCórdobaArgentina

Personalised recommendations