Water Resources Management

, Volume 24, Issue 7, pp 1425–1439 | Cite as

Development of a Regional Non-dimensional Return Period Flood Model

  • Pradeep K. Bhunya
  • Niranjan Panigrahy
  • Rakesh Kumar
  • Ronny Berndtsson
Article

Abstract

Based on the non-dimensional approach, this study focuses on developing a model to compute design flood for specific return periods whose parameter estimations are done using the Marquardt algorithm considering peak flood data of 100 Indian catchments. The selected flood data varies for majority of the sites for a period of 10 years, and for a few sites up to 36 years; and as a preliminary processing these data are checked for outliers, discordancy, and other errors. The model is calibrated for a variety of situations, and validated on selected gauged catchments. Both the descriptive and predictive goodness-of-fit measures are computed considering the floods of specific return periods estimated from the observed data. The model is found to perform well for the whole study area. Investigations reveal the model to be useful to any catchment within the hydrologically homogeneous region with limited or no flood data conditions.

Keywords

Hydrologically homogeneous region Design flood Regional flood frequency L-moment ratios Dimensional analysis 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Black PE (1972) Hydrograph response to geomorphic model watershed characteristics and precipitation variables. J Hydrol 17:309–129CrossRefGoogle Scholar
  2. Calver A, Wood WL (1991) Dimensionless hillslope hydrology. Proc Inst Civ Eng, Part 2 91:593–602Google Scholar
  3. Central Water Commission (1982a) Flood estimation report for Lower Narmada and Tapi sub-zone-3b. Directorate of Hydrology (Small Catchments), CWC, New Delhi, IndiaGoogle Scholar
  4. Central Water Commission (1982b) Flood Estimation Report for Mahanadi sub-zone-3d. Directorate of hydrology (Small Catchments), CWC, New Delhi, IndiaGoogle Scholar
  5. Central Water Commission (1987) Flood estimation report for Mahi and Sabarmati (sub-zone-3A). Directorate of hydrology (Small Catchments), CWC, New Delhi, IndiaGoogle Scholar
  6. Cheng Y (2000) Non-dimensional Peak Breach Outflow Analysis with Dam Breach Parameters, section 23, chapter 2. In: Proceedings of Joint Conference on Water Resources Engineering and Water Resources Planning & Management held in Minneapolis, Minnesota, sponsored by EWRI of ASCE, 30 July–2 August 2000Google Scholar
  7. Edson CG (1951) Parameters for relating unit hydrograph to watershed characteristics. Trans Am Geophys Union 32:591–596Google Scholar
  8. Gidas NK, Constantinou T (1983) Non dimensional numbers associated with evaporation from capillary porous medium. J Hydrol Sci 28(14):539–549CrossRefGoogle Scholar
  9. Grace RA, Eagleson PS (1966) The modeling of overland flow. Water Resour Res 2:393–403CrossRefGoogle Scholar
  10. Grace RA, Eagleson PS (1967) Scale model of urban runoff from storm rainfall. J Hydrol Eng ASCE 93(13):161–167Google Scholar
  11. Grover PL, Burn DH, Cunderlik JM (2002) A comparison of index flood estimation procedures for ungauged catchments. Can J Civ Eng 29(15):734–741CrossRefGoogle Scholar
  12. Hosking JRM (1990) L-moment: analysis and estimation of distribution using linear combination of order statistics. J R Stat Soc B 52(1):105–124Google Scholar
  13. Hosking JRM (1991) Fortran routines for use with the method of L-moments. Res. Report, RC 17097, IBM Res., NYGoogle Scholar
  14. Hosking JRM, Wallis JR (1993) Some statistics useful in regional frequency analysis. Water Resour Res 29(12):271–275CrossRefGoogle Scholar
  15. Hosking JRM, Wallis JR (1997) Regional frequency analysis: an approach based on L-moments. Cambridge University Press, UKCrossRefGoogle Scholar
  16. Kumar R, Singh RD, Seth SM (1999) Regional flood formulas for seven subzones of zone-3 of India. J Hydrol Eng ASCE 4(13):240–256CrossRefGoogle Scholar
  17. Landwehr JM, Metalas NC, Wallis JR (1979a) Estimation of parameters and quantiles of Wakeby distributions 1. Known lower bounds. Water Resour Res 15:1361CrossRefGoogle Scholar
  18. Landwehr JM, Metalas NC, Wallis JR (1979b) Estimation of parameters and quantiles of Wakeby distributions: 2. Unknown lower bounds. Water Resour Res 15(16):1373CrossRefGoogle Scholar
  19. Langhaar HL (1951) Dimensional analysis and theory of models. Wiley, New YorkGoogle Scholar
  20. Maidment DR (ed) (1993) Handbook of hydrology. McGraw-Hill, New YorkGoogle Scholar
  21. Marquardt DW (1962) An algorithm for least-square estimation of nonlinear parameters. J Soc Ind Appl Math 11(12):431–441Google Scholar
  22. Montgomery DC, Runger GC (1994) Applied statistics and probability for engineers. Wiley, NYGoogle Scholar
  23. Rao AR, Ahmed KH (1997) Regional frequency analysis of Wabash river flood data by L-moments. J Hydrol Eng ASCE 2(14):169–179CrossRefGoogle Scholar
  24. Singh VP (1988) Hydrologic systems: rainfall-runoff modeling, vol 1. Prentice Hall. Englewood Cliffs, New JerseyGoogle Scholar
  25. Stedinger JR, Lu L-H (1995) Appraisal of regional and index quantile estimators. Stoch Hydrol Hydraul 9(1):49–75CrossRefGoogle Scholar
  26. Swamee PK, Ojha CSP, Abbas A (1995) Mean annual flood estimation. J Water Resour Plan Manage ASCE 121(16):403–407CrossRefGoogle Scholar
  27. Wong ST (1979) A dimensionally homogeneous and statistically optimal model for predicting mean annual flood. J Hydrol 42:269–279CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • Pradeep K. Bhunya
    • 1
  • Niranjan Panigrahy
    • 1
  • Rakesh Kumar
    • 1
  • Ronny Berndtsson
    • 2
  1. 1.National Institute of HydrologyRoorkeeIndia
  2. 2.Department of Water Resources EngineeringLund UniversityLundSweden

Personalised recommendations