Journal of Korea Water Resources Association (한국수자원학회논문집)

Korea Water Resources Association (한국수자원학회)
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Analysis of the effect of climate change on IDF curves using scale-invariance technique: focus on RCP 8.5

Scale-Invariance 기법을 이용한 IDF 곡선의 기후변화 영향 분석: RCP 8.5를 중심으로

  • Choi, Jeonghyeon (Division of Earth Environmental System Science, Pukyong National University) ;
  • Lee, Okjeong (Division of Earth Environmental System Science, Pukyong National University) ;
  • Kim, Sangdan (Department of Environmental Engineering, Pukyong National University)
  • 최정현 (부경대학교 지구환경시스템과학부) ;
  • 이옥정 (부경대학교 지구환경시스템과학부) ;
  • 김상단 (부경대학교 환경공학과)
  • Received : 2016.09.05
  • Accepted : 2016.11.09
  • Published : 2016.12.31
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Abstract

According to 5th IPCC Climate Change Report, there is a very high likelihood that the frequency and intensity of extreme rainfall events will increase. In reality, flood damage has increased, and it is necessary to estimate the future probabilistic design rainfall amount that climate change is reflected. In this study, the future probabilistic design precipitation amount is estimated by analyzing trends of future annual maximum daily rainfall derived by RCP 8.5 scenarios and using the scale-invariance technique. In the first step, after reviewing the time-scale characteristics of annual maximum rainfall amounts for each duration observed from 60 sites operating in Korea Meterological Administration, the feasibility of the scale-invariance technique are examined using annual daily maximum rainfall time series simulated under the present climate condition. Then future probabilistic design rainfall amounts for several durations reflecting the effects of climate change are estimated by applying future annual maximum daily rainfall time series in the IDF curve equation derived by scale-invariance properties. It is shown that the increasing trend on the probabilistic design rainfall amount has resulted on most sites, but the decreasing trend in some regions has been projected.

IPCC 제5차 평가보고서에 따르면 극한강우의 빈도 및 강도가 증가할 가능성이 매우 높을 것으로 예측되고 있다. 실제로 극한강우에 따른 침수피해가 증가하고 있으며, 이에 따라 기후변화의 영향을 반영한 미래 확률강우량 추정이 필요하다. 본 연구에서는 기후변화 RCP 8.5 시나리오로부터 도출된 미래 연 최대 일강수량 자료의 추세분석과 scale-invariance 기법을 이용하여 미래 확률강우량을 추정하였다. 먼저, 기상청 관할 60개 기상관측소의 관측 강우자료를 이용하여 관측소별로 스케일 특성을 검토한 후, 현재기후 모의자료를 이용하여 scale-invariance 기법의 적용가능성을 검증하였다. 그 후, 미래 일 강수량 시계열을 scale-invariance 특성에 따라 유도된 IDF 곡선식에 적용하여 기후변화의 영향을 반영한 지속시간별 확률강우량을 추정하였다. 대부분의 지점에서 확률강우량이 증가할 것으로 예측되었으나, 일부 지역의 경우에는 감소할 가능성도 있음을 살펴볼 수 있다.

Keywords

References

  1. Burlando, P. and Rosso, R. (1996). "Scaling and multiscaling models of depth-duration-frequency curves for storm precipitation." Journal of Hydrology, Vol. 187, No. 1, pp. 45-64. https://doi.org/10.1016/S0022-1694(96)03086-7
  2. Donat, M. G., Alexander, L. V., Yang, H., Durre, I., Vose, R., Dunn, R. J. H., Willett, K. M., Aguilar, E., Brunet, M., Caesar, J., Hewitson, B., Jack, C., Klein Tank, A. M. G., Kruger, A. C., Marengo, J., Peterson, T. C., Renom, M., Oria Rojas, C., Rusticucci, M., Salinger, J., Elrayah, A. S., Sekele, S. S., Srivastava, A. K., Trewin, B., Villarroel, C., Vincent, L. A., Zhai, P., Zhang, X., and Kitching, S. (2013). "Updated analyses of temperature and precipitation extreme indices since the beginning of the twentieth century: The HadEX2 dataset." Journal of Geophysical Research: Atmospheres, Vol. 118, No. 5, pp. 2098-2118. https://doi.org/10.1002/jgrd.50150
  3. Gregersen, I. B., Sorup, H. J. D., Madsen, H., Rosbjerg, D., Mikkelsen, P. S., and Arnbjerg-Nielsen, K. (2013). "Assessing future climatic changes of rainfall extremes at small spatio-temporal scales." Climatic Change, Vol. 118, No. 3, pp. 783-797. https://doi.org/10.1007/s10584-012-0669-0
  4. Groisman, P. Y., Knight, R. W., Easterling, D. R., Karl, T. R., Hegerl, G. C., and Razuvaev, V. N. (2005). "Trends in intense precipitation in the climate record." Journal of Climate, Vol. 18, No. 9, pp. 1326-1350. https://doi.org/10.1175/JCLI3339.1
  5. Hawkins, E., Osborne, T. M., Ho, C. K., and Challinor, A. J. (2012). "Calibration and bias correction of climate projections for crop modelling: An idealised case study over Europe." Agricultural and Forest Meteorology, Vol. 170, pp. 19-31.
  6. IPCC (2014). "Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change." IPCC, Geneva, Switzerland.
  7. Jung, Y., Kim, S., Kim, T., and Heo, J. (2008). "Rainfall quantile estimation using scaling property in Korea." Journal of Korea Water Resources Association, Vol. 41, No. 9, pp. 873-884. https://doi.org/10.3741/JKWRA.2008.41.9.873
  8. Kim, E., Choi, H. I., Park, M. J., Cho, S. J., and Kim, S. (2011). "The effect of climate change on Korean drought occurrences using a stochastic soil water balance model." Scientific Research and Essays, Vol. 6, No. 13, pp. 2771-2783.
  9. Krige, D. G. (1951). "A statistical approach to some mine valuations and allied problems at the Witwatersrand." Master's thesis, University of Witwatersrand, p. 272.
  10. Kwon, Y., Park, J., and Kim, T. (2009). "Estimation of design rainfalls considering an increasing trend in rainfall data." Journal of The Korean Society of Civil Engineers, Vol. 29, No. 2B, pp. 131-139.
  11. Lee, M., Shin, S., and Bae, D. (2012). "The application assessment of future design rainfall estimation method using scale properties." Journal of Korea Water Resources Association, Vol. 45, No. 3, pp. 253-262. https://doi.org/10.3741/JKWRA.2012.45.3.253
  12. Lee, O., and Kim, S. (2016). "Future PMPs projection under future dew point temperature variation of RCP 8.5 climate change scenario." Journal of Korean Society of Hazard Mitigation, Vol. 16, No. 2, pp. 505-514. https://doi.org/10.9798/KOSHAM.2016.16.2.505
  13. Liuzzo, L., and Freni, G. (2015). "Analysis of extreme rainfall trends in sicily for the evaluation of depth-duration-frequency curves in climate change scenarios." Journal of Hydrologic Engineering, Vol. 20, No. 12.
  14. Mailhot, A., and Duchesne, S. (2010). "Design criteria of urban drainage infrastructures under climate change." Journal of Water Resources Planning and Management, Vol. 136, No. 2, pp. 201-208. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000023
  15. Ministry of Construction and Transport (2000). "1999 Report of research and investigation of water resources management method development. Vol 1. Probability Rainfall Map." Ministry of Construction and Transport.
  16. Ministry of Land, Transport and Maritime Affairs (2012). "Design flood estimation tips." Ministry of Land, Transport and Maritime Affairs.
  17. Perkins, S. E., Alexander, L. V., and Nairn, J. R. (2012). "Increasing frequency, intensity and duration of observed global heatwaves and warm spells." Geophysical Research Letters, Vol. 39, No. 20.
  18. Rodriguez, R., Navarro, X., Casas, M. C., Ribalaygua, J., Russo, B., Pouget, L., and Redano, A. (2014). "Influence of climate change on IDF curves for the metropolitan area of Barcelona." International Journal of Climatology, Vol. 34, No. 3, pp. 643-654. https://doi.org/10.1002/joc.3712
  19. Willems, P. (2013). "Adjustment of extreme rainfall statistics accounting for multidecadal climate oscillations." Journal of Hydrology, Vol. 490, pp. 126-133. https://doi.org/10.1016/j.jhydrol.2013.03.034

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