한국수자원학회논문집 (Journal of Korea Water Resources Association)

  • 제55권3호
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  • Pages.177-189
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  • 2022
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  • 2799-8746(pISSN)
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  • 2799-8754(eISSN)
한국수자원학회 (Korea Water Resources Association)
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극한강우량 산정을 위한 대규모 기후 앙상블 모의자료의 적용

Application of a large-scale ensemble climate simulation database for estimating the extreme rainfall

  • 김영규 (충남대학교 토목공학과) ;
  • 손민우 (충남대학교 토목공학과)
  • Kim, Youngkyu (Department of Civil Engineering, Chungnam National University) ;
  • Son, Minwoo (Department of Civil Engineering, Chungnam National University)
  • 투고 : 2021.10.21
  • 심사 : 2022.01.27
  • 발행 : 2022.03.31
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초록

본 연구는 저빈도·고강도의 확률강우량 산정을 위해, 대규모 기후 앙상블 모의실험으로 생성된 d4PDF (Data for Policy Decision Making for Future Change)를 적용하는 것을 목적으로 수행되었다. 또한, d4PDF를 이용하여 산정된 확률강우량과 관측 자료 및 빈도해석을 통해서 산정된 확률강우량을 비교함으로써 빈도해석 과정의 적용에 따라 발생하는 불확실성을 분석하였다. 이와 같은 연구는 금산, 임실, 전주, 장수 관측소를 대상으로 수행되었다. d4PDF 자료는 총 50개의 앙상블로 구성되어있으며, 하나의 앙상블은 60년동안의 기상자료를 제공하기 때문에 한 지점에서 3,000개의 연 최대 일 강우량을 수집하는 것이 가능했다. 이와 같은 d4PDF의 특징을 토대로 본 연구는 빈도해석 방법을 적용하지 않고, 3000개의 연 최대 일강수량을 비모수적 접근법(Non-parametric approach)에 따라 규모별로 나열하여, 10년부터 1000년의 재현기간을 갖는 확률강우량을 산정했다. 그 후, 관측 자료와 Gumbel 및 GEV (General extreme value) 분포를 토대로 산정된 확률강우량과의 편차를 산정하였다. 그 결과, 재현기간과 관측 기간의 차이가 증가할수록 이 편차가 증가하였으며, 이 결과는 짧은 관측 기간과 빈도해석의 적용은 재현기간이 증가할수록 신뢰하기 어려운 확률강우량을 제시한다는 것을 의미한다. 반면에, d4PDF는 대규모 표본을 이용함으로써 이와 같은 불확실성을 최소화시켜 합리적인 저빈도·고강도의 확률강우량을 제시하였다.

The purpose of this study is to apply the d4PDF (Data for Policy Decision Making for Future Change) constructed from a large-scale ensemble climate simulation to estimate the probable rainfall with low frequency and high intensity. In addition, this study analyzes the uncertainty caused by the application of the frequency analysis by comparing the probable rainfall estimated using the d4PDF with that estimated using the observed data and frequency analysis at Geunsam, Imsil, Jeonju, and Jangsu stations. The d4PDF data consists of a total of 50 ensembles, and one ensemble provides climate and weather data for 60 years such as rainfall and temperature. Thus, it was possible to collect 3,000 annual maximum daily rainfall for each station. By using these characteristics, this study does not apply the frequency analysis for estimating the probability rainfall, and we estimated the probability rainfall with a return period of 10 to 1000 years by distributing 3,000 rainfall by the magnitude based on a non-parametric approach. Then, the estimated probability rainfall using d4PDF was compared with those estimated using the Gumbel or GEV distribution and the observed rainfall, and the deviation between two probability rainfall was estimated. As a result, this deviation increased as the difference between the return period and the observation period increased. Meanwhile, the d4PDF reasonably suggested the probability rainfall with a low frequency and high intensity by minimizing the uncertainty occurred by applying the frequency analysis and the observed data with the short data period.

키워드

과제정보

이 논문은 2022년도 정부(교육부)의 재원으로 한국연구재단의 지원을 받아 수행된 기초연구사업임(No. 2021R1I1A3060354).

참고문헌

  1. Alam, M.S., and Elshorbagy, A. (2015). "Quantification of the climate change-induced variations in Intensity - Duration - Frequency curves in the Canadian Prairies." Journal of Hydrology, Elsevier, Vol. 527, pp. 990-1005. https://doi.org/10.1016/j.jhydrol.2015.05.059
  2. Bandaru, S., Sano, S., Shimizu, Y., Seki, Y., Okano, Y., Sasaki, T., Wada, H., Otsuki, T., and Ito, T. (2020). "Impact of heavy rains of 2018 in western Japan: disaster-induced health outcomes among the population of Innoshima Island." Heliyon, Elsevier, Vol. 6, No. 5, e03942. https://doi.org/10.1016/j.heliyon.2020.e03942
  3. Ben Alaya, M.A., Zwiers, F., and Zhang, X. (2018). "Probable maximum precipitation: Its estimation and uncertainty quantification using bivariate extreme value analysis." Journal of Hydrometeorology, Vol. 19, No. 4, pp. 679-694. https://doi.org/10.1175/JHM-D-17-0110.1
  4. Bobee, B., Cavadias, G., Ashkar, F., Bernier, J., and Rasmussen, P. (1993). "Towards a systematic approach to comparing distributions used in flood frequency analysis." Journal of Hydrology, Elsevier Vol. 142, No. 1-4, pp. 121-136. https://doi.org/10.1016/0022-1694(93)90008-W
  5. Christidis, N., Jones, G.S., and Stott, P.A. (2015). "Dramatically increasing chance of extremely hot summers since the 2003 European heatwave." Nature Climate Change, Vol. 5, No. 1, pp. 46-50. https://doi.org/10.1038/nclimate2468
  6. Cunnane, C. (1989). Statistical distributions for flood frequency analysis. Operational Hydrological Report. No. 33, Word Meteorological Organization, Geneva, Switzerland.
  7. Doll, P., Trautmann, T., Gerten, D., Schmied, H.M., Ostberg, S., Saaed, F., and Schleussner, C.F. (2018). "Risks for the global freshwater system at 1.5℃ and 2℃ global warming." Environmental Research Letters, IOP Publishing, Vol. 13, No. 4, pp. 1-15.
  8. Duan, W., Hanasaki, N., Shiogama, H., Chen, Y., Zou, S., Nover, D., Zhou, B., and Wang, Y. (2019). "Evaluation and future projection of Chinese precipitation extremes using large ensemble high-resolution climate simulations." Journal of Climate, Vol. 32, No. 8, pp. 2169-2183. https://doi.org/10.1175/JCLI-D-18-0465.1
  9. Faye. B, Webber, H., Naab, J.B., MacCarthy, D.S., Adam, M., Ewert, F., Lamers, J.P.A., Schleussner, C.F., Ruane, A., Gessner, U., Hoogenboom, G., Boote, K., Shelia, V., Saeed, F., Wisser, D., Hadir, S., Laux, P., and Gaiser, T. (2018). "Impacts of 1.5 versus 2.0℃ on cereal yields in the West African Sudan Savanna." Environmental Research Letters, IOP Publishing, Vol. 13, No. 3, pp. 1-13.
  10. Felix, M.L., Kim, Y., Choi, M., Kim, J.-C., Do, X.K., Nguyen, T. H., and Jung, K. (2021). "Detailed trend analysis of extreme climate indices in the upper Geum River Basin." Water, MDPI, Vol. 13, No. 22, 3171. https://doi.org/10.3390/w13223171
  11. Fischer, E.M., and Knutti, R. (2015). "Anthropogenic contribution to global occurrence of heavy-precipitation and high-temperature extremes." Nature Climate Change, Vol. 5, No. 6, pp. 560-564. https://doi.org/10.1038/nclimate2617
  12. Gumbel, E.J. (1958). Statics of extremes. Columbia University Press, New York, N.Y., U.S.
  13. Haddad, K., and Rahman, A. (2011). "Selection of the best fit flood frequency distribution and parameter estimation procedure: A case study for Tasmania in Australia." Stochastic Environmental Research and Risk Assessment, Springer, Vol. 25, No. 3, pp. 415-428. https://doi.org/10.1007/s00477-010-0412-1
  14. Haddad, K., Johnson, F., Rahman, A., Green, J., and Kuczera, G. (2015). "Comparing three methods to form regions for design rainfall statistics: two case studies in Australia." Journal of Hydrology, Elsevier, Vol. 527, pp. 62-76. https://doi.org/10.1016/j.jhydrol.2015.04.043
  15. Hanittinan, P., Tachikawa, Y., and Ram-Indra, T. (2020). "Projection of hydroclimate extreme indices over the indochina region under climate change using a large single-model ensemble." International Journal of Climatology, RMetS, Vol. 40, No. 6, pp. 2924-2952. https://doi.org/10.1002/joc.6374
  16. Hirota, K., Konagai, K., Sassa, K., Dang, K., Yoshinaga, Y., and Wakita, E.K. (2019). "Landslides triggered by the West Japan Heavy Rain of July 2018, and geological and geomorphological features of soaked mountain slopes." Landslides, Springer, Vol. 16, pp. 189-194. https://doi.org/10.1007/s10346-018-1100-3
  17. Hwang, J., Ahn, J., Jeong, C., and Heo, J.-H. (2018). "A study on the variation of design flood due to climate change in the ungauged urban catchment." Journal of Korea Water Resources Association, KWRA, Vol. 51, No. 5, pp. 395-404. https://doi.org/10.3741/JKWRA.2018.51.5.395
  18. Ishii, M., and Mori, N. (2020). "d4PDF: Large-ensemble and highresolution climate simulations for global warming risk assessment." Progress in Earth and Planetary Science, Springer, Vol. 7, No. 1, pp. 1-22. https://doi.org/10.1186/s40645-019-0311-0
  19. Ji, Z., and Kang, S. (2015). "Evaluation of extreme climate events using a regional climate model for China." International Journal of Climatology, Vol. 35, pp. 888-902. https://doi.org/10.1002/joc.4024
  20. Johnson, F., Haddad, K., Rahman, A., and Green, J. (2012). "Application of Bayesian GLSR to estimate sub daily rainfall parameters for the IFD revision project." Hydrology and Water Resources Symposium 2012, EA, Australia, p. 800.
  21. Kay, J.E., Deser, C., Phillips, A., Mai, A., Hannay, C., Strand, G., Arblaster, J.M., Bates, S.C., Danabasoglu, G., Edwards, J., Holland, M., Kushner, P., Lamarque, J.F., Lawrence, D., Lindsay, K. Middleton, A., Munoz, E., Neale, R., Oleson, K., Polvani, L., and Vertenstein, M. (2015). "The community earth system model (CESM) large ensemble project: A community resource for studying climate change in the presence of internal climate variability." Bulletin of the American Meteorological Society, AMS, Vol. 96, No. 8, pp. 1333-1349. https://doi.org/10.1175/BAMS-D-13-00255.1
  22. Kendall, M.G. (1975). Rank correlation methods (4th edn.) charles griffin. Griffin, London, UK.
  23. Klemes, V. (1986). "Dilettantism in hydrology: Transition or destiny?" Water Resources Research, WOL, Vol. 22, No. 9S, pp. 177S-188S.
  24. Klemes, V. (1987). "Hydrological and engineering relevance of flood frequency analysis." Hydrologic Frequency Modeling, Springer, pp. 1-18.
  25. Klemes, V. (2000). "Tall tales about tails of hydrological distributions. I." Journal of Hydrologic Engineering, Vol. 5, No. 3, pp. 227-231. https://doi.org/10.1061/(ASCE)1084-0699(2000)5:3(227)
  26. Kumar, N., Poonia, V., Gupta, B.B., and Goyal, M.K. (2021). "A novel framework for risk assessment and resilience of critical infrastructure towards climate change." Technological Forecasting and Social Change, Elsevier, Vol. 165, 120532. https://doi.org/10.1016/j.techfore.2020.120532
  27. Lavender, S.L., E Walsh, K.J., Caron, L.-P., King, M., Monkiewicz, S., Guishard, M., Zhang, Q., and Hunt, B. (2018). "Estimation of the maximum annual number of North Atlantic tropical cyclones using climate models." Science Advances, Vol. 4, No. 8, eaat6509. https://doi.org/10.1126/sciadv.aat6509
  28. Li, S., Mote, P. W., Rupp, D. E., Vickers, D., Mera, R., and Allen, M. (2015). "Evaluation of a regional climate modeling effort for the western United States using a superensemble from weather @home." Journal of Climate, Vo. 28, pp. 7470-7488. https://doi.org/10.1175/JCLI-D-14-00808.1
  29. Mann, H.B. (1945). "Nonparametric tests against trend." Econometrica, Vol. 13, No. 3, pp. 245-259. https://doi.org/10.2307/1907187
  30. Mizuta, R., Murata, A., Ishii, M., Shiogama, H., Hibino, K., Mori, N., Arakawa, O., Imada, Y., Yoshida, K., Aoyagi, T., Kawase, H., Mori, M., Okada, Y., Shimura, T., Nagatomo, T., Ikeda, M., Endo, H., Masaya, N., Arai, M., Takahashi, C., Tanaka, K., Takemi, T., Tachikawa, Y., Temur, K., Kamae, Y., Watanabe, M., Sasaki, H., Kitoh, A., Takayabu, I., Nakakita, E., and Kimoto, M. (2017). "Over 5,000 years of ensemble future climate simulations by 60-km global and 20-km regional atmospheric models." Bulletin of the American Meteorological Society, AMS, Vol. 98, No. 7, pp. 1383-1398.
  31. Mori, N., Shimura, T., Yoshida, K., Mizuta, R., Okada, Y., Fujita, M., Khujanazarov, T., and Nakakita, E. (2019). "Future changes in extreme storm surges based on mega-ensemble projection using 60-km resolution atmospheric global circulation model." Coastal Engineering Journal, T&F, Vol. 61, No. 3, pp. 295-307. https://doi.org/10.1080/21664250.2019.1586290
  32. Mote, P.W., Allen, M.R., Jones, R.G., Li, S., Mera, R., Rupp, D.E., Salahuddin, A., and Vickers, D. (2016). "Superensemble regional climate modeling for the western United States." Bulletin of the American Meteorological Society, Vol. 97, pp. 203-215. https://doi.org/10.1175/BAMS-D-14-00090.1
  33. Sasaki, H., Kurihara, K., Takayabu, I., and Uchiyama, T. (2008). "Preliminary experiments of reproducing the present climate using the non-hydrostatic regional climate model." Sola, MSJ, Vol. 4, pp. 25-28. https://doi.org/10.2151/sola.2008-007
  34. Seneviratne, S., Nicholls, N., Easterling, D., Goodess, C., Kanae, S., Kossin, J., Luo, Y., Marengo, J., McInnes, K., and Rahimi, M. (2012). Changes in climate extremes and their impacts on the natural physical environment. Cambridge University Press, Cambridge, UK.
  35. Sharma, M.A., and Singh, J.B. (2010). "Use of probability distribution in rainfall analysis." New York Science Journal, Vol. 3, No. 9, pp. 40-49.
  36. Shimpo, A., Takemura, K., Wakamatsu, S., Togawa, H., Mochizuki, Y., Takekawa, M., Tanaka, S., Yamashita, K., Maeda, S., and Kurora, R. (2019). "Primary factors behind the heavy rain event of July 2018 and the subsequent heat wave in Japan." Sola, MSJ, Vol. 15A, pp. 13-18. https://doi.org/10.2151/sola.15A-003
  37. Smith, L.C. (2000). "Trends in Russian Arctic river-ice formation and breakup, 1917 to 1994." Physical Geography, Vol. 21, No. 1, pp. 46-56. https://doi.org/10.1080/02723646.2000.10642698
  38. Tanaka, T., Kiyohara, K., and Tachikawa, Y. (2020). "Comparison of fluvial and pluvial flood risk curves in urban cities derived from a large ensemble climate simulation dataset: A case study in Nagoya, Japan." Journal of Hydrology, Elsevier, Vol. 584, No. February, 124706. https://doi.org/10.1016/j.jhydrol.2020.124706
  39. Tanaka, T., Kobayashi, K., and Tachikawa, Y. (2021). "Simultaneous flood risk analysis and its future change among all the 109 class-A river basins in Japan using a large ensemble climate simulation database d4PDF." Environmental Research Letters, IOP Publishing, Vol. 16, No. 7, 74059. https://doi.org/10.1088/1748-9326/abfb2b
  40. Tanaka, T., Tachikawa, Y., Ichikawa, Y., and Yorozu, K. (2018). "Flood risk curve development with probabilistic rainfall modelling and large ensemble climate simulation data: A case study for the Yodo river basin." Hydrological Research Letters, Vol. 12, No. 4, pp. 28-33. https://doi.org/10.3178/hrl.12.28
  41. Tang, J., Niu, X., Wang, S., Gao, H., Wang, X., and Wu, J. (2016). "Statistical downscaling and dynamical downscaling of regional climate in China: Present climate evaluations and future climate projections." Journal of Geophysical Research, Vol. 121, pp. 2110-2129.
  42. Yang, J.A., Kim, S., Mori, N., and Mase, H. (2018). "Assessment of long-term impact of storm surges around the Korean Peninsula based on a large ensemble of climate projections." Coastal Engineering, Elsevier, Vol. 142, pp. 1-8. https://doi.org/10.1016/j.coastaleng.2018.09.008
  43. Zhang, Y., Xu, Y., Dong, W., Cao, L., and Sparrow, M. (2006). "A future climate scenario of regional changes in extreme climate events over China using the PRECIS climate model." Geophysical Research Letter, Vol. 33, L24702. https://doi.org/10.1029/2006GL027229