DOI QR코드

DOI QR Code

A development of trivariate drought frequency analysis approach using copula function

Copula 함수를 활용한 삼변량 가뭄빈도해석 기법 개발

  • Kim, Jin-Young (Department of Civil Engineering, Chonbuk National University) ;
  • So, Byung-Jin (Department of Civil Engineering, Chonbuk National University) ;
  • Kim, Tae-Woong (Department of Civil and Environmental Engineering, Hanyang University) ;
  • Kwon, Hyun-Han (Department of Civil Engineering, Chonbuk National University)
  • Received : 2016.07.25
  • Accepted : 2016.08.26
  • Published : 2016.10.31

Abstract

This study developed a trivariate Copula function based drought frequency analysis model to better evaluate the recent 2014~2015 drought event. The bivariate frequency analysis has been routinely used for the drought variables of interest (e.g. drought duration and severity). However, the recent drought patterns showed that the intensity can be regarded as an important factor which is being characterized by short duration and severe intensity. Thus, we used the trivariate Copula function approach to incorporate the trivariate drought characteristics into the drought frequency analysis. It was found that the return periods based on the trivariate frequency analysis are, in general, higher than the existing bivariate frequency analysis. In addition, this study concludes that the increase in drought frequency claimed by the Gumbel copula function has been overestimated compared to the Student t Copula function. In other words, the selection of copula functions is rather sensitive to the estimation of trivariate drought return periods at a given duration, magnitude and intensity.

본 연구에서는 최근 발생한 2014~2015 가뭄 사상을 보다 정확하게 분석하기 위해 삼변량 Copula 함수를 도입하여 연구를 진행하였다. 기존 연구에서는 일반적으로 가뭄 분석시 이변량(가뭄 지속시간, 심도)를 활용한 연구가 다수 진행되었다. 그러나 최근 강우자료의 패턴을 살펴보면 두 변량 이외의 가뭄 강도가 중요한 인자로 평가되어 이를 함께 고려한 삼변량 Copula 분석을 수행하였으며, 기상청 관측소 중 서울 관측소를 대상으로 연구를 진행하였다. 기본적으로, 이변량 빈도해석 결과에 비해 삼변량 해석 결과는 동일한 가뭄 사상에 대해서 다소 증가된 재현기간을 나타내는 것으로 파악됐다. 이와 더불어, Gumbel Copula 함수의 경우 Student t Copula 함수보다 가뭄 위험도 평가 시 다소 과대 추정하는 것으로 확인되었다. 즉, 삼변량 빈도해석 시 고려되는 Copula 함수의 선택이 가뭄의 재현기간을 추정하는데 있어 매우 민감한 사항으로 평가되었다.

Keywords

References

  1. Bonaccorse, B., Cancelliere, A., and Rossi, G. (2003). "An analytical formulation of return period of drought severity." Vol. 17, No. 3, pp. 157-174. https://doi.org/10.1007/s00477-003-0127-7
  2. Cancelliere, A., and Salas, J. D. (2010). "Drought probabilities and return period for annual streamflows series." Journal of Hydrology, Vol. 391, No. 1-2, pp. 77-89. https://doi.org/10.1016/j.jhydrol.2010.07.008
  3. Chen, L., Singh, V. P., Guo, S., Mishra, A. K., and Gou, J. (2013). "Drougth analysis based on copulas." Journal of Hydrologic Engineering, Vol. 18, No. 7, pp. 797-808. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000697
  4. Chun, S.-Y., Kim, Y.-T., and Kwon, H.-H. (2015). "Drought frequency analysis using hidden markov chain model and bivariate copula function." Journal of Korea Water Resource Associate, Vol. 48, No. 12, pp. 969-979. https://doi.org/10.3741/JKWRA.2015.48.12.969
  5. Dai, A., Trenberth, K. E., and Qian, T. (2004). "A global dataset of palmer drought severity index: Relationship with soil moisture and effects of surface warming." Journal of Hydrometeorology, Vol. 5, pp. 1117-1129. https://doi.org/10.1175/JHM-386.1
  6. Favre, A.-C., Adluni, S. E., Perreault, L., Thiemonge, N., and Bobee, B. (2004). "Multivariate hydrological frequency analysis using copulas." Water Resources Research, Vol. 40, No. 1, doi: 10.1029/2003WR002456.
  7. Fernandez, B., and Salas, J. D. (1999). "Return period and risk of hydrologic events. I: Mathematical Formulation." Journal of Hyrologic engineering, Vol. 4, No. 4, pp. 297-307. https://doi.org/10.1061/(ASCE)1084-0699(1999)4:4(297)
  8. Grimaldi, S., and Serinaldi, F. (2006). "Design hyetograph analysis with 3-copula function." Hydrological Sciences Journal, Vol. 51, No. 2, pp. 223-238. https://doi.org/10.1623/hysj.51.2.223
  9. Joe, H. (1997). "Multivariate models and dependence concept." Chapman & Hall, London.
  10. Kim, J.-Y., Kim, J.-G., Choi, B.-H., and Kwon, H.-H. (2015). "A development of hydrologic dam risk analysis model using bayesian network(BN)." Journal of Korea Water Resource Associate, Vol. 48, No. 10, pp. 781-791. https://doi.org/10.3741/JKWRA.2015.48.10.781
  11. Kim, T.-W., Valdes, J. B., and Yoo, C. S. (2003). "Nonparametric approach for estimating return periods of droughts in arid regions." Journal of Hydrologic engineering, Vol. 8, No. 5, pp. 237-246. https://doi.org/10.1061/(ASCE)1084-0699(2003)8:5(237)
  12. Kim, T.-W., Valdes, J. B., and Yoo, C. S. (2006). "Nonparametric approach for bivariate drought characterization using palmer drought index." Journal of Hydrologic Engineering, Vol. 11, No. 2, pp. 134-143. https://doi.org/10.1061/(ASCE)1084-0699(2006)11:2(134)
  13. Kumar, M. N., Murthy, C. S., Sai, M. V. R. S., and Roy, P. S. (2009). "On the use of standardized precipitation index (SPI) for drought intensity assessment." Meteorological Appocations, Vol. 16, No. 3, pp. 381-389. https://doi.org/10.1002/met.136
  14. Kwon, H.-H., and Lall, U. (2016). "A copula-based nonstationary frequency analysis for the 2012-2015 drought in California." Water Resources Research, doi:10.1002/2016WR018959.
  15. Laird, K. R., Fritz, S. C., and Cumming, B. F. (1998). "A diatombased reconstruction of drought intensity, duration, and frequency from moon lake, north dakota: a sub-decadal record of the last 2300 years." Journal of Paleolimnology, Vol. 19, pp. 161-179. https://doi.org/10.1023/A:1007929006001
  16. Lee, T. S., and Son, C. Y. (2016). "Analyzing the drought event in 2015 through statistical drought frequency analysis." Journal of Korea Water Resource Associate, Vol. 49, No. 3, pp. 177-186. https://doi.org/10.3741/JKWRA.2016.49.3.177
  17. Ma, M. W., Song, S. B., Ren, L., Jaing, S. H., and Song, J. L. (2013). "Multivariate drought characteristics using trivariate Gaussian and Student t copulas." Hydrological processes, Vol. 27, pp. 1175-1190. https://doi.org/10.1002/hyp.8432
  18. Nelssen, R. B. (2006). "An Introduction to Copula." Springer, New York, pp. 109-115.
  19. Radice, R., Marra, G., and Wojtys, M. (2015). "Copula regression spline models for binary outcomes." Statistics and Computing, doi:10.1007/s11222-015-9581-6.
  20. Requena, A. L., Mediero O., and Marcos, L. G. (2013). "A bivariate return period based on copulas for hydrologic dam design: accounting for reservoir routing in risk estimation", Hydrology and Earth System Sciences, Vol. 17, No. 8, pp. 3023-3038. https://doi.org/10.5194/hess-17-3023-2013
  21. Salvadori, G., and Michele, C. (2004). "Frequency analysis via copulas: Theoretical aspects and applications to hydrological events." Water Resources Research, Vol. 40, No. 12.
  22. Salvatierra, I. D. L., and Patton, A. J. (2015). "Dynamic copula models and high frequency data." Journal of Empirical Finance, Vol. 30, pp. 120-135. https://doi.org/10.1016/j.jempfin.2014.11.008
  23. Sheffield, J., and Wood, E. F. (2008). "Projected changes in drought occurrence under future global warming from multimodel, multi-scenario, IPCC AR4 simulations." Climate Dynamics, Vol. 31, pp. 79-105. https://doi.org/10.1007/s00382-007-0340-z
  24. Shiau, J. T. (2006). "Fitting drought duration and severity with two-dimensional copulas." Water Resources Management, Vol. 20, pp. 795-815. https://doi.org/10.1007/s11269-005-9008-9
  25. Shiau, J. T., and Modarres, R. (2009). "Copula-based drought severityduration-frequency analysis in Iran." Meteorological Applacations, Vol. 16, pp. 481-489. https://doi.org/10.1002/met.145
  26. Shiau, J.-T., and Shen, H. W. (2001). "Recurrence analysis of hydrologic droughts of differing severity." Journal of water resources planning and management, Vol. 127, No. 1, pp. 30-40. https://doi.org/10.1061/(ASCE)0733-9496(2001)127:1(30)
  27. Shiau, J.-T., Feng, S., and Nadarajah, S. (2007). "Assessment of hydrological droughts for the Yellow River, China, using copulas." Hydrological processes, Vol. 21, pp. 2157-2163. https://doi.org/10.1002/hyp.6400
  28. Sklar, K. (1959). "Fontions de reprartition a n dimensions et leurs marge." Publ. Inst. Statis. Univ. Paris 8, p. 11.
  29. Yevjevich, V. (1967). "On objective approach to derinitions and investigations of continental hydrologic droughts." Hydrology Paper, No. 23, Colorado State University, Fort Collins, pp. 4-18.
  30. Yoo, J. Y., Shin, J. Y., Kim, D. K., and Kim, T.-W. (2013). "Drought risk analysis using stochastic rainfall generation model and copula functions." Journal of Korea water resources association, Vol. 46, No. 4, pp. 425-437. https://doi.org/10.3741/JKWRA.2013.46.4.425
  31. Yu, J. S., Yoo, J. Y., Lee, J.-H., and Kim, T.-W. (2016). "Estimation of drought risk through the bivariate drought frequency analysis using copula functions." Journal of Korea Water Resource Associate, Vol. 49, No. 3, pp. 217-225. https://doi.org/10.3741/JKWRA.2016.49.3.217
  32. Zhang, L., and Singh, V. P. (2007). "Gumbel-hougaard copula for trivariate rainfall frequency analysis." Journal of Hydrologic engineering, Vol. 12, No. 4, pp. 409-419. https://doi.org/10.1061/(ASCE)1084-0699(2007)12:4(409)