Comparison of L-moments of Probability Distributions for Extreme Value Analysis of Rainfall for Estimation of Peak Flood Discharge for Ungauged Catchments

Authors

  • N. Vivekanandan  Central Water and Power Research Station, Pune, Maharashtra, India

Keywords:

Chi-square, Extreme Value, Kolmogorov-Smirnov, Mean Square Error, Rainfall, Peak Flood

Abstract

Estimation of Peak Flood Discharge (PFD) at a desired location on a river is important for planning, design and management of hydraulic structures. For ungauged catchment, rainfall depth becomes an important input in derivation of PFD. So, rainfall depth can be estimated through frequency analysis by fitting of probability distributions to the rainfall data. In this paper, the series of annual 1-day maximum rainfall derived from daily rainfall data recorded at Una district is used to estimate the 1-day maximum rainfall adopting six probability distributions. Method of L-moments is used for determination of parameters of distributions. Goodness-of-Fit tests viz., Chi-square and Kolmogorov-Smirnov are applied for checking the adequacy of fitting of probability distributions to the recorded data. Root Mean Square Error (RMSE) is used for the selection of most suitable probability distribution for estimation of rainfall. Based on GoF test results and RMSE values, the study identifies the Extreme Value Type-1 (EV1) is better suited distribution for rainfall estimation. By applying the procedures, as described in CWC guidelines, the 1-hour value of distributed rainfall is computed from the estimated 1-day maximum rainfall using EV1 distribution and adopted for computation of PFD for ungauged catchment. The study suggests the computed PFD from rational formula could be considered for design of flood protection measures for river Swan and its tributaries joining the Beas river basin, Himachal Pradesh.

References

  1. Badreldin, G.H.H. and Feng, P., Regional rainfall frequency analysis for the Luanhe Basin using L-moments and cluster techniques, International Conference on Environmental Science and Development, 5-7 January 2012, Hong Kong, Vol. 1, pp. 126–135.
  2. Charles Annis, P.E., Goodness-of-Fit tests for statistical distributions, http://www.statistical engineering. com/goodness.html], 2009.
  3. Central Water Commission (CWC), Flood estimation report for Western Himalayas-Zone 7, CWC Design Office Report No.: WH/22/1994, New Delhi, 1994.
  4. Di Balldassarre, G., Castellarin, A. and Brath, A., Relationships between statistics of rainfall extremes and mean annual precipitation: an application for design-storm estimation in northern central Italy, Hydrology and Earth System Sciences, 2006, Vol. 10, No. 2, pp. 589–601.
  5. Eslamian, S.S, and Feizi, H,, Maximum monthly rainfall analysis using L-Moments for an arid region in Isfahan Province, Iran, Applied Meteorology and Climatology, 2007, Vol. 46, No. 4, pp. 494-503.
  6. Gonzalez, J. and Valdes, J.B., A regional monthly precipitation simulation model based on an L-moment smoothed statistical regionalization approach, Journal of Hydrology, 2008, Vol. 348, No. 1, pp. 27-39.
  7. Gubareva, T.S. and Gartsman, B.I., Estimating distribution parameters of extreme hydrometeorological characteristics by L-Moment method, Water Resources, 2010, Vol. 37, No. 4, pp. 437–445.
  8. Guevara, E., “Engineering design parameters of storms in Venezuela”, Hydrology Days, pp. 80-91, 2003.
  9. Hosking, J.R.M, L-moments: Analysis and estimation of distributions using linear combinations of order statistics, Royal Statistical Society, Series-B, 1990, Vol. 52, No. 1, pp. 105-124.
  10. Hosking, J.R.M. and Wallis, J.R., Some statistics useful in regional frequency analysis”, Water Resources Research, 1993, Vol. 29, No. 2, pp. 271-281.
  11. Hosking, J.R.M. and Wallis, J.R., Regional frequency analysis: an approach based on L-moments, Cambridge University Press, 1997.
  12. Kumar, R. and Chatterjee, C., Regional flood frequency analysis using L-Moments for north Barhamputra region of India, Hydrologic Engineering, 2005, Vol. 10, No. 1, pp. 1–7.
  13. National Institute of Hydrology (NIH), Technical note on hydrological process in an ungauged catchment, 2011, pp. 1-163.
  14. Neslihan, S., Recep, Y., Tefaruk, H. and Ahmet, D., Comparison of probability weighted moments and maximum likeli-hood methods used in flood frequency analysis for Ceyhan river basin, Arabian Journal of Science and Engineering, 2010, Vol. 35, No. 1, pp. 49-69.
  15. Singh, R.D., Mishra, S.K. and Chowdhary, H., Regional flow duration models for 1200 ungauged Himalayan watersheds for planning micro-hydro projects, ASCE Journal of. Hydrologic Engineering, 2001, Vol. 6, No. 4, pp. 310-316.
  16. Topaloglu, F., Determining suitable probability distribution models for flow and precipitation series of the Seyhan River basin, Turkish Journal of Agriculture and Forestry, 2002, Vol. 26, No. 1, pp. 189 – 194.
  17. Yurekli, K., Modarres, R. and Ozturk, F., Regional daily maximum rainfall estimation for Cekerek Watershed by L-moments, Meteorological Applications, 2009, Vol. 16, No. 4, pp. 435-444.
  18. Zhang, J., Powerful goodness-of-fit tests based on the likelihood ratio, Journal of Royal Statistical Society, 2002,Vol. 64, No. 2, pp. 281-294.Cajori, Florian; "A History of Mathematical Notations", vol. I & II. Open Court Publishing Co., La Salle Illinois, 1928 & 1929; republished Dover Publications Inc., New York, 1993, xxviii + 820 pp. ISBN 0-486-67766-4 (pbk.)
  19. Lie, Håkon Wium  and  Bert Bos; Cascading Style Sheets, level 1, W3C Recommendation, 17 Dec  1996
  20. F. Damerau, A technique for computer detection and correction of spelling errors. Communications of the ACM, 1964, Vol. 7, Issue 3, pp. 659-664.

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Published

2015-12-25

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Section

Research Articles

How to Cite

[1]
N. Vivekanandan, " Comparison of L-moments of Probability Distributions for Extreme Value Analysis of Rainfall for Estimation of Peak Flood Discharge for Ungauged Catchments, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 1, Issue 5, pp.35-41, November-December-2015.