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Frequency Analysis of Extreme Rainfall Using 3 Parameter Probability Distributions

3변수 확률분포형에 의한 극치강우의 빈도분석

  • Published : 2004.05.30

Abstract

This research seeks to derive the design rainfalls through the L-moment with the test of homogeneity, independence and outlier of data on annual maximum daily rainfall at 38 rainfall stations in Korea. To select the appropriate distribution of annual maximum daily rainfall data by the rainfall stations, Generalized Extreme Value (GEV), Generalized Logistic (GLO), Generalized Pareto (GPA), Generalized Normal (GNO) and Pearson Type 3 (PT3) probability distributions were applied and their aptness were judged using an L-moment ratio diagram and the Kolmogorov-Smirnov (K-S) test. Parameters of appropriate distributions were estimated from the observed and simulated annual maximum daily rainfall using Monte Carlo techniques. Design rainfalls were finally derived by GEV distribution, which was proved to be more appropriate than the other distributions.

Keywords

References

  1. Greenwood J. A., J. M. Landwehr, N. C. Matalas, and J. R. Wallis. 1979. Probability Weighted Moments : Definition and Relation to Parameters of Several Distributions Expressed in Inverse Form. Water Resources Research 15(5) : 1049- 1064. https://doi.org/10.1029/WR015i005p01049
  2. Hosking J. R. M., J. R. Wallis, E. F. Wood. 1985.. Estimation of the generalized extremevalue distribution by the method of probability-weighted moments. American Statistical Association and the American Society for Quality Control 27(3) : 251-261.
  3. Hosking J. R. M. 1986. The Theory of Probability Weighted Moments. 3-16. RC12210. IBM Research Center: Yorktown Heights.
  4. Hosking J. R. M. 1990. L-moments: Analysis and Estimation of Distributions using Linear Combination of Order Statistics. Journal of the Royal Statistical Society Series B 52(2) : 105-124.
  5. Hosking J. R. M. 1996. Fortran Routines for Use with the Method of L-moments. 1-43. RC2025. IBM Research Center : Yorktown Heights.
  6. Hosking, J. R. M. and J. R. Wallis. 1997. Regional Frequency Analysis. Cambridge University Press.
  7. Lee S. H, S. J. Maeng. 2003. Frequency analysis of extreme rainfall using L-moment. Irrigation and Drainage 52(3) : 219-230. https://doi.org/10.1002/ird.90
  8. Maidment, D. R. 1992. Handbook of Hydrology : McGraw-Hili. Inc.
  9. Naghavi B. and F. X. Yu. 1995. Regional Frequency Analysis of Extreme Precipitation in Louisiana. Journal of Hydraulic Engineering 121(11) : 819-827. https://doi.org/10.1061/(ASCE)0733-9429(1995)121:11(819)
  10. Schaefer M. G. 1990. Regional Analysis of Precipitation Annual Maxima in Washington State. Water Resources Research 26(1) : 119-131. https://doi.org/10.1029/WR026i001p00119
  11. Vogel R. M., T. A. McMahon and F. H. S Chiew. 1993. Flood Flow Frequency Model Selection in Australia. Journal of Hydrology 146 : 421-449. https://doi.org/10.1016/0022-1694(93)90288-K
  12. World Meteorological Organization. 1989. Statistical Distributions for Flood Frequency Analysis. Operational Hydrology Report No.33. Secretariat of the World Meteorological Organization: Geneva, Switzerland; A4.1-A4.14.