DOI QR코드

DOI QR Code

Regional Frequency Analysis for Rainfall using L-Moment

L-모멘트법에 의한 강우의 지역빈도분석

  • Published : 2008.03.31

Abstract

This study was conducted to derive the optimal regionalization of the precipitation data which can be classified on the basis of climatologically and geographically homogeneous regions all over the regions except Cheju and Ulreung islands in Korea. A total of 65 rain gauges were used to regional analysis of precipitation. Annual maximum series for the consecutive durations of 1, 3, 6, 12, 24, 36, 48 and 72hr were used for various statistical analyses. K-means clustering mettled is used to identify homogeneous regions all over the regions. Five homogeneous regions for the precipitation were classified by the K-means clustering. Using the L-moment ratios and Kolmogorov-Smirnov test, the underlying regional probability distribution was identified to be the generalized extreme value (GEV) distribution among applied distributions. The regional and at-site parameters of the generalized extreme value distribution were estimated by the linear combination of the probability weighted moments, L-moment. The regional and at-site analysis for the design rainfall were tested by Monte Carlo simulation. Relative root-mean-square error (RRMSE), relative bias (RBIAS) and relative reduction (RR) in RRMSE were computed and compared with those resulting from at-site Monte Carlo simulation. All show that the regional analysis procedure can substantially reduce the RRMSE, RBIAS and RR in RRMSE in the prediction of design rainfall. Consequently, optimal design rainfalls following the regions and consecutive durations were derived by the regional frequency analysis.

본 연구에서는 L-모멘트법에 의한 지역화 빈도분석에 따른 설계강우량 추정에 관한 연구를 수행하였다. 제주도와 울릉도의 강우관측소를 제외한 분석에 사용된 65개 강우관측소의 강우자료 수집과 선정된 강우관측지점의 강우자료의 지속시간, 즉 1, 3, 6, 12, 24, 36, 48 및 72시간 지속의 연최대치 계열을 구성하였다. 관측지점을 대상으로 Cluster분석을 실시한 결과 우리나라의 강우관측지점에 대한 합리적인 지역화로 5개의 지역으로 구분되었다. 지역화된 지역에 대한 지속기간별 극치강우자료의 적정분포모형 결정을 위한 6가지 분포모형의 적용하고 적용분포의 L-모멘트비를 산정하여 L-모멘트비도를 도시하고 K-S 검정에 의한 적정분포모형을 선정하였다. 선정된 적정분포는 GEV 분포이며 이 분포에 의해 강우관측치의 점빈도 및 지역빈도분석에 의한 설계강우량을 유도하였다. Monte Carlo 기법에 의해 모의발생된 강우량의 점빈도 및 지역빈도분석에 의한 설계강우량을 유도하였다. 실측치 및 모의발생치의 점빈도 및 지역빈도분석에 의한 설계강우량의 비교분석을 위해 상대제곱근오차와 상대편의오차에 의해 분석한 결과 점빈도 분석에 의한 설계강우량보다 지역빈도분석에 의한 설계강우량의 사용이 적정한 것으로 나타났다.

Keywords

References

  1. J. R. M. Hosking, J. R. Wallis, and E. F. Wood, "Estimation of the generalized extreme-value distribution by the method of probability- weighted moments," American Statistical Association and the American Society for Quality Control Vol.27, No.3, pp.251-261, 1985.
  2. J. R. M. Hosking, The Theory of Probability Weighted Moments, RC12210. IBM Research Center: Yorktown Heights, pp.3-16, 1986.
  3. J. R. M. Hosking, "L-moments: Analysis and Estimation of Distributions Using Linear Combination of Order Statistics," Journal Royal Statistical Society Series B, Vol.52, No.1, pp.105-124, 1990.
  4. J. R. M. Hosking, Fortran Routines for Use with the Method of L-moments, RC2025. IBM Research Center: Yorktown Heights, pp.1-43, 1996.
  5. J. R. M. Hosking and J. R. Wallis, The U.S. National Electronic Drought Atlas: Statistical Data Analysis with GIS-Based Presentation of Results, RC20499. IBM Research Center: Yorktown Heights, pp.1-16, 1996.
  6. J. R. M. Hosking and J. R. Wallis, Regional Frequency Analysis, Cambridge University Press: Cambridge, UK, 1997.
  7. S. H. Lee and S. J. Maeng, "Frequency analysis of extreme rainfall using L-moment," Irrigation and Drainage Vol.52, No.3, pp.219-230, 2003. https://doi.org/10.1002/ird.90
  8. B. Naghavi and F. X. Yu, "Regional Frequency Analysis of Extreme Precipitation in Louisiana," Journal of Hydraulic Engineering Vol.121, No.11, pp.819-827, 1995. https://doi.org/10.1061/(ASCE)0733-9429(1995)121:11(819)
  9. M. G. Schaefer, "Regional Analysis of Precipitation Annual Maxima in Washington State," Water Resources Research Vol.26, No.1, pp.119-131, 1990. https://doi.org/10.1029/WR026i001p00119
  10. SYSTAT, SYSTAT 8.0 Statistics, SPSS Inc., 1998.
  11. World Meteorological Organization, Statistical Distributions for Flood Frequency Analysis. Operational Hydrology Report No.33. Secretariat of the World Meteorological Organization: Geneva, Switzerland; pp.A4.1- A4.14, 1989.

Cited by

  1. Development of Hierarchical Bayesian Spatial Regional Frequency Analysis Model Considering Geographical Characteristics vol.47, pp.5, 2014, https://doi.org/10.3741/JKWRA.2014.47.5.469