A new method for estimating flood peak discharge and extreme rainfall: Case study of Firat basin

M. Cihat Tuna

Article ID: 683
Vol 3, Issue 1, 2020

VIEWS - 573 (Abstract) 436 (PDF)

Abstract


The commonly-used design parameter for hydraulic structures is the annual maximum instantaneous streamflow recorded by conventional gauging stations. Increased hydroclimatic variability in recent years and the resultant flooding raise questions concerning the flood risk estimations from the short flow records in Turkey. The method described in this study has been selected according to the likely estimates for the peak flow values at different return periods for the gauged basins. Hence, estimation of the peak flow values for regions with poor or rich discharge datasets could be implemented. In theory, this developed method may be used to estimate the peak flow values at any point on a river network, and not only at basin outlets. In this research, a case study has been conducted on the Firat basin, on which the largest dams in Turkey have been built, by employing a novel approach for developing a new method that calculates the peak flood flows and extreme rainfall. The results demonstrate that the approach is sound and can be employed in the prediction of peak rainfall and flow parameters in river basins.

Keywords


Extreme Rainfalls; Goodness-of-fit Test; New Estimation Method; Peak Discharge

Full Text:

PDF


References


1. Gumbel EJ. Statistics of extremes. New York: Columbia University Press; 1958.

2. Chow VT (editor). Handbook of applied hydrology. New York: McGraw-Hill; 1964.

3. Benson MA. Uniform flood frequency estimating methods for federal agencies. Water Resources Research 1968; 4(5): 891–901.

4. Yevjevich V. Probability and statistics in hydrology. Publisher: Fort Collins; 1972.

5. Haan CT. Statistical methods in hydrology. Ames: Iowa State University Press; 1977.

6. Rossi F, Fiorentino M, Versace P. Two-component extreme value distribution for flood frequency analysis. Water Resources Research 1984; 20(7): 847–856.

7. Keim BD, Faiers GE. Heavy rainfall distributions by season in Louisiana: Synoptic interpretations and quantile estimates. Water Resources Bulletin 1996; 32(1): 117–124.

8. Adamowski K. Regional analysis of annual maximum and partial duration flood data by nonparametric and L-moment methods. Journal of Hydrology 2000; 229(3–4): 219–231.

9. Luxemburg WMJ, Savenije HHG, Gelder Van PHJM, et al. Statistical properties of flood runoff of North Eurasian rivers under conditions of climate change. Research Program, Delft University of Technology and Russian research institutes at Vladivostok, Irkutsk and St. Petersburg; 2002.

10. Bakker A, Luxemburg W. Heterogeneous distributions within flood frequency analysis. Paper ISSH-Stochastic Hydraulics 2005, Witteveen en Bos, Deventer, NL and Delft University of Technology, Faculty of Civil Engineering, Delft, NL.

11. Mantje W, Luxemburg W, Gelder van P, et al. Statistical modelling of flood events. Delft University of Technology, Faculty of Civil Engineering, Delft, NL; 2007.

12. Haan CT. Statistical methods in hydrology. Ames, Iowa: Iowa State Press; 2002.

13. D’Agostino RB, Stephens MA. Goodness-of-fit techniques. New York: Marcel Dekker; 1986.

14. EIE. Results for the years of water flow (1938–2010), General Directorate of Electrical Power Resources Survey and Development Administration, Ankara, Turkey; 2010.




DOI: https://doi.org/10.24294/nrcr.v3i1.683

Refbacks

  • There are currently no refbacks.


Copyright (c) 2020 M. Cihat Tuna

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

This site is licensed under a Creative Commons Attribution 4.0 International License.