Browse > Article
http://dx.doi.org/10.3741/JKWRA.2018.51.9.747

Bivariate regional frequency analysis of extreme rainfalls in Korea  

Shin, Ju-Young (Department of Civil and Environmental Engineering, Yonsei University)
Jeong, Changsam (Department of Civil and Environmental Engineering, Induk University)
Ahn, Hyunjun (Department of Civil and Environmental Engineering, Yonsei University)
Heo, Jun-Haeng (Department of Civil and Environmental Engineering, Yonsei University)
Publication Information
Journal of Korea Water Resources Association / v.51, no.9, 2018 , pp. 747-759 More about this Journal
Abstract
Multivariate regional frequency analysis has advantages of regional and multivariate framework as adopting a large number of regional dataset and modeling phenomena that cannot be considered in the univariate frequency analysis. To the best of our knowledge, the multivariate regional frequency analysis has not been employed for hydrological variables in South Korea. Applicability of the multivariate regional frequency analysis should be investigated for the hydrological variable in South Korea in order to improve our capacity to model the hydrological variables. The current study focused on estimating parameters of regional copula and regional marginal models, selecting the most appropriate distribution models, and estimating regional multivariate growth curve in the multivariate regional frequency analysis. Annual maximum rainfall and duration data observed at 71 stations were used for the analysis. The results of the current study indicate that Frank and Gumbel copula models were selected as the most appropriate regional copula models for the employed regions. Several distributions, e.g. Gumbel and log-normal, were the representative regional marginal models. Based on relative root mean square error of the quantile growth curves, the multivariate regional frequency analysis provided more stable and accurate quantiles than the multivariate at-site frequency analysis, especially for long return periods. Application of regional frequency analysis in bivariate rainfall-duration analysis can provide more stable quantile estimation for hydraulic infrastructure design criteria and accurate modelling of rainfall-duration relationship.
Keywords
Multivariate regional frequency analysis; Annual maximum rainfall-duration; Regional growth curve; Regional copula;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
1 Song, H.-K., Joo, K., Jeong, J., and Heo, J.-H. (2016). "A comparative study on the inter-event time with the time-resolution of rainfall data." Proceedings Korea Water Resources Association Conference 2016, KWRA, p. 167.
2 Chebana, F., and Ouarda, T. B. M. J., (2007). "Multivariate L-moment homogeneity test." Water Resources Researches, AGU, Vol. 43, No. 8.
3 Chebana, F., and Ouarda, T. B. M. J. (2009), "Index flood-based multivariate regional frequency analysis." Water Resource Researches, AGU, Vol. 45, No. 10.
4 Heo, J.-H., Lee, Y. S., Nam, W. S., and Kim, K.-D. (2007b). "Application of regional rainfall frequency analysis in South Korea (II): Monte Carlo simulation and determination of appropriate method." Journal of Korean Society of Civil Engineering, KSCE, Vol. 27 No. 2B, pp. 113-123.
5 Heo, J.-H., Lee, Y. S., Shin, H., and Kim, K.-D. (2007a). "Application of regional rainfall frequency analysis in South Korea (I): Rainfall quantile estimation." Journal of Korean Society of Civil Engineering, KSCE, Vol. 27, No. 2B, pp. 101-111.
6 Hosking, J. R. M., and Wallis, J .R. (2005). Regional frequency analysis: an approach based on L-moments. Cambridge University Press.
7 Joo, K., Shin, J.-Y., and Heo, J.-H., (2012). "Bivariate frequency analysis of rainfall using copula model." Journal of the Korea Water Resources Association, KWRA, Vol. 45, No. 8, pp. 827-837.   DOI
8 Kim, J. W., Nam, W. S., Shin, J.-Y., and Heo, J.-H. (2008). "Regional frequency analysis of South Korean rainfall data using FORGEX method." Journal of the Korea Water Resources Association, KWRA, Vol. 41, No. 4, pp. 405-412.   DOI
9 Kim, J.-Y., So, B.-J., Kim, T.-W., Kwon, H.-H., (2016a). "A development of trivariate drought frequency analysis approach using copula function." Journal of the Korea Water Resources Association, KWRA, Vol. 49, No. 10, pp. 823-833.   DOI
10 Kim, S., Ahn, H., Shin, H., and Heo, J.-H. (2016b). "Development of spatial dependence formula of FORGEX method using rainfall data in Korea" Journal of the Korea Water Resources Association, KWRA, Vol. 49, No. 12, pp. 1007-1014.   DOI
11 Lee, J.-Y., Park, D.-H., Shin, J.-Y., and Kim, T.-W. (2016). "Estimating design floods for ungauged basins in the geumriver basin through regional flood frequency analysis using L-moments method." Journal of Korea Water Resources Association, KWRA, Vol. 49, No. 8, pp. 646-656.
12 Nam, W. S., Kim, T., Shin, J.-Y., and Heo, J.-H. (2008). "Regional rainfall frequency analysis by multivariate techniques." Journal of Korea Water Resources Association, KWRA, Vol. 41, No. 5, pp. 517-525.   DOI
13 Nelsen, R. B. (2006). An introduction to copulas. Springer.
14 Requena, A. I., Chebana, F., and Mediero, L. (2016). "A complete procedure for multivariate index-flood model application." Journal of Hydrology, Vol. 535, pp. 559-580.   DOI
15 Shin, J.-Y., Jeong, C., Joo, K., and Heo, J.-H. (2018). "Hydrological homogeneous region delineation for bivariate frequency analysis of extreme rainfalls in Korea." Journal of the Korea Water Resources Association, KWRA, Vol. 51, No. 1, pp. 49-60.   DOI
16 Brahimi, B., Chebana, F., and Necir, A. (2015). "Copula representation of bivariate L-moments: a new estimation method for multiparameter twodimensional copula models." Statistics, Vol. 49, No. 3, pp. 497-521.   DOI
17 Abdi, A., Hassanzadeh, Y., Talatahari, S., Fakheri-Fard, A., Mirabbasi, R., and Ouarda, T .B. M. J. (2017). "Multivariate regional frequency analysis: Two new methods to increase the accuracy of measures." Advances in Water Resources, Vol. 107, pp. 290-300.   DOI
18 Bellman, R., Corporation, R., and Collection, K. M. R. (1957). Dynamic programming. Princeton University Press.
19 Ben Aissia, M. A., Chebana, F., Ouarda, T .B. M. J., Bruneau, P., and Barbet, M. (2015). "Bivariate index-flood model: case study in Quebec, Canada." Hydrological Sciences Journal, IAHS, Vol. 60, No. 2, pp. 247-268.   DOI