Flash flood simulation for Tabuk City catchment, Saudi Arabia

Original Paper

Abstract

In January 2013, the city of Tabuk, Saudi Arabia suffered a huge flash flood that caused damage to infrastructure and the death of many people. Reliable predictions are one of the key challenges for successful flash flood management in the Tabuk area. In this research paper, two state-of-the-art hydrological models, that is, the Identification of unit Hydrograph and Component flows from Rainfall, Evaporation and Streamflow (IHACRES) and Soil Conservation Service (SCS) lumped models, have been used and compared based on ensemble mode to reduce modelling uncertainty. A successful approach to reducing uncertainty in the hydrological models in this paper is to implement a modern video technique using a camera installed in the field. The suitability of the models is then ranked according to their performance regarding different aspects of flash floods. The average flow rate estimated based on the video record technique at Wadi Abu Nishayfah Bridge was 2.35 m3/s, while the average flow rates from IHACRES and SCS simulations were 3.1 and 1.7 m3/s, respectively. The IHACRES and SCS simulations can be reasonably applied for the Tabuk area to predict floods in the wadis. Video imagery for flood records needs to be validated to minimise uncertainty. However, video techniques can be a very effective tool in arid areas.

Keywords

Arid region Tabuk area Flash flood IHACRES SCS Video technique 

Notes

Acknowledgments

The authors would like to acknowledge the financial support for this work from the Deanship of Scientific Research (DSR), University of Tabuk, Tabuk, Saudi Arabia, under grant no. S-0039/1435, and the on-going project entitled “Flash Floods Assessment and Management over Tabuk Area: Causes, Dangers and Solutions (Field Study).”

References

  1. Abushandi E, Merkel B (2011) Application of IHACRES rainfall-runoff model to the wadi Dhuliel arid catchment, Jordan. J Water Clim Change 2(1):56–71. doi: 10.2166/wcc.2011.048 CrossRefGoogle Scholar
  2. Arnold JG et al (2012) SWAT: model use, calibration, and validation. Trans ASABE 55(4):1491–1508. doi: 10.13031/2013.42256 CrossRefGoogle Scholar
  3. Aziz K, Rahman A, Fang G, Shrestha S (2014) Application of artificial neural networks in regional flood frequency analysis: a case study for Australia. Stoch Environ Res Risk Assess 28(3):541–554. doi: 10.1007/s00477-013-0771-5 CrossRefGoogle Scholar
  4. Bradley AA, Kruger A, Meselhe EA, Muste MVI (2002) Flow measurement in streams using video imagery. Water Resour Res 38(12):51-1–51-8. doi: 10.1029/2002WR001317 CrossRefGoogle Scholar
  5. Croke BFW, Andrews F, Jakeman AJ, Cuddy SM, Luddy A (2006) IHACRES classic plus: a redesign of the IHACRES rainfall-runoff model. Environ Model Softw 21(3):426–427. doi: 10.1016/j.envsoft.2005.07.003 CrossRefGoogle Scholar
  6. Davis RS (2001) Flash flood forecast and detection methods. Meteorol Monogr 28(50):481–526. doi: 10.1175/0065-9401-28.50.481 CrossRefGoogle Scholar
  7. El Kenawy A, McCabe MF (2015) A multi-decadal assessment of the performance of gauge- and model-based rainfall products over Saudi Arabia: climatology, anomalies and trends. International Journal of Climatology, doi: 10.1002/joc.4374.Google Scholar
  8. Foote B (2008) Research applications laboratory's (RAL) annual report for FY2008. The National Center for Atmospheric Research, Boulder, CO, USAGoogle Scholar
  9. Ghoneim E, Foody GM (2013) Assessing flash flood hazard in an arid mountainous region. Arab J Geosci 6(4):1191–1202. doi: 10.1007/s12517-011-0411-7 CrossRefGoogle Scholar
  10. Jackisch C, Zehe E, Samaniego L, Singh AK (2014) An experiment to gauge an ungauged catchment: rapid data assessment and eco-hydrological modelling in a data-scarce rural catchment. Hydrol Sci J 59(12):2103–2125. doi: 10.1080/02626667.2013.870662 CrossRefGoogle Scholar
  11. Kite GW, Pietroniro A (1996) Remote sensing application in hydrological modelling. Hydrol Sci J 41(4):563–591. doi: 10.1080/02626669609491526 CrossRefGoogle Scholar
  12. Krysanova V, Hattermann F, Wechsung F (2005) Development of the ecohydrological model SWIM for regional impact studies and vulnerability assessment. Hydrol Process 19(3):763–783. doi: 10.1002/hyp.5619 CrossRefGoogle Scholar
  13. Littlewood IG, Jakeman AJ (1994) A new method of rainfall-runoff modelling and its applications in catchment hydrology. In: Zanetti P (ed) Environmental modeling, volume 2: computer methods and software for simulating environmental pollution and its adverse effects. Computational Mechanics Publications, Billerica, MA, USA, pp 143–171Google Scholar
  14. Mahmoud SH (2014) Investigation of rainfall–runoff modeling for Egypt by using remote sensing and GIS integration. CATENA 120:111–121. doi: 10.1016/j.catena.2014.04.011 CrossRefGoogle Scholar
  15. Mishra SK, Singh VP (2004) Long-term hydrological simulation based on the Soil Conservation Service curve number. Hydrol Process 18(7):1291–1313. doi: 10.1002/hyp.1344 CrossRefGoogle Scholar
  16. Mulvany TJ (1851) On the use of self-registering rain and flood gauges in making observations of the relations of rain fall and of flood discharges in a given catchment. Proc Inst Civ Eng Ireland 4(2):19–33Google Scholar
  17. Patel DP, Srivastava PK (2013) Flood hazards mitigation analysis using remote sensing and GIS: correspondence with town planning scheme. Water Resour Manag 27(7):2353–2368. doi: 10.1007/s11269-013-0291-6 CrossRefGoogle Scholar
  18. Post DA, Jakeman AJ (1999) Predicting the daily streamflow of ungauged catchments in S.E. Australia by regionalising the parameters of a lumped conceptual rainfall-runoff model. Ecol Model 123(2–3):91–104. doi: 10.1016/S0304-3800(99)00125-8 CrossRefGoogle Scholar
  19. Pressey HA (1903) Methods of measuring velocity in river channels. Sci Am Suppl 56:23140–23142. doi: 10.1038/scientificamerican09051903-23140supp CrossRefGoogle Scholar
  20. Rallison RE (1980) Origin and evolution of the SCS runoff equation. Proceeding of the Symposium on Watershed Management’80, July 21–23, 1980, American Society of Civil Engineering, Boise, ID, USA, pp. 912–924Google Scholar
  21. Rallison RE, Miller N (1981) Past, present and future SCS runoff procedure. Proceedings of the International Symposium on Rainfall-Runoff Modeling, May 18–21, 1981, Mississippi State University, Mississippi State, MI, USA, pp. 353–364Google Scholar
  22. Soil Conservation Service (1986) Urban hydrology for small watersheds. Technical Release TR-55. USDA Soil Conservation Service, Hydrology Unit, Washington, DC, USAGoogle Scholar
  23. Tehrany MS, Pradhan B, Mansor S, Ahmad N (2015) Flood susceptibility assessment using GIS-based support vector machine model with different kernel types. CATENA 125:91–101. doi: 10.1016/j.catena.2014.10.017 CrossRefGoogle Scholar
  24. Van Dam JC, Groenendijk P, Hendriks RFA, Kroes JG (2008) Advances of modeling water flow in variably saturated soils with SWAP. Vadose Zone J 7(2):640–653. doi: 10.2136/vzj2007.0060 CrossRefGoogle Scholar
  25. Wheater H, Sorooshian S, Sharma KD (eds) (2008) Hydrological modelling in arid and semi-arid areas. Cambridge University Press, Cambridge, UKGoogle Scholar

Copyright information

© Saudi Society for Geosciences 2016

Authors and Affiliations

  1. 1.Civil Engineering Department, Faculty of EngineeringSohar UniversitySoharOman

Personalised recommendations