DOI QR코드

DOI QR Code

Regional Frequency Analysis for Rainfall Under Climate Change

기후변화를 고려한 일강우량의 지역빈도해석

  • Song, Chang Woo (Department of Civil Engineering, Inha university) ;
  • Kim, Yon Soo (Department of Civil Engineering, Inha university) ;
  • Kang, Na Rae (Department of Civil Engineering, Inha university) ;
  • Lee, Dong Ryul (Water Resources Research Division, Korea Institute of Construction Technology) ;
  • Kim, Hung Soo (Department of Civil Engineering, Inha university)
  • Received : 2012.11.23
  • Accepted : 2013.02.21
  • Published : 2013.02.28

Abstract

Global warming and climate change have influence on abnormal weather pattern and the rainstorm has a localized and intensive tendency in Korea. IPCC(2007) also reported the rainstorm and typhoon will be more and more stronger due to temperature increase during the 21st century. Flood Estimation Handbook(Institute of Hydrology, 1999) published in United Kingdom, in the case that the data period is shorter than return period, recommends the regional frequency analysis rather than point frequency analysis. This study uses Regional Climate Model(RCM) of Korea Meteorological Administration(KMA) for obtaining the rainfall and for performing the regional frequency analysis. We used the rainfall data from 58 stations managed by KMA and used L-moment algorithm suggested by Hosking and wallis(1993) for the regional frequency analysis considering the climate change. As the results, in most stations, the rainfall amounts in frequencies have an increasing tendency except for some stations. According to the A1B scenario, design rainfall is increased by 7~10% compared with the reference period(1970-2010).

기후변화에 따른 기상변화로 인하여 집중호우 및 돌발홍수 등의 빈도가 증가하고 있다. IPCC 4차 보고서(2007)는 21세기 후반까지 온도상승으로 인한 폭우 및 태풍이 점차 강력해질 것이라는 예측을 하고 있다. 영국에서 발간한 Flood Estimation Handbook(Institute of Hydrology, 1999)에 의하면 대상자료의 기간이 구하려는 재현기간보다 작은 경우에는 지점빈도해석은 적절하지 않으므로, 지역빈도해석을 추천하고 있다. 이에 본 논문은 기후변화를 고려한 빈도해석을 수행하였으며, 이에 앞서 세계기상기구에서 제시한 기후지수를 이용하여 기후변화를 평가하고, 기상청 지역기후모델(KMA-RegCM3)의 강우 자료를 이용하여 기상청 산하 58개 관측소에 대하여 지역빈도해석을 실시하였다. Hosking와 wallis(1993)이 제안한 L-moment 알고리즘을 이용하여 지역빈도해석을 수행하였으며, 그 결과 일부지역을 제외한 대부분의 지역에서 강수량이 증가하였으며, 현재 기간 대비 7~10%의 증가율을 나타내었다. 미래 기후변화의 영향으로 중 남부지방은 상대적으로 강우량이 증가할 것으로 보이며, 미래 강우량에 따른 설계빈도를 재설정 및 강수량이 증가하는 지역에 대한 확률수문량의 적용이 필요할 것으로 판단된다.

Keywords

References

  1. Fowler, HJ, Ekström, M, Kilsby, CG and Jones, PD (2005). New estimates of future change in extreme rainfall across the UK using regional climate model integraiton: 1. Assessment of control climate, J. of Hydrology, 300 (1-4), pp. 212-233. https://doi.org/10.1016/j.jhydrol.2004.06.017
  2. Ganguly, AR (2007). Climate extremes hydro-meteorological extremes and impacts, Fall creek falls 2007 workshop (www.ccs.ornl.gov).
  3. Heo, JH, Lee, YS, Shin HJ and Kim, KD (2007). Application of regional rainfall frequency analysis in South Korea(I) : Rainfall quantile estimation, J. of Korea Society of Civil Engineers, 27(2B), pp. 101-111.
  4. Hosking, JRM (1990). L-moments : Analysis and estimation of distribution using linear combinations of order statistics, J. R. Statist. Soc. B, 52(2), pp. 105- 124.
  5. Hosking, JRM and Wallis, JR (1993). Some Statistics Useful in a Regional Frequency Analysis, Water Resources Research, 29,(2), pp. 271-281. https://doi.org/10.1029/92WR01980
  6. Hosking, JRM and Wallis, JR (1997). Regional frequency analysis, Cambridge University Press.
  7. Institute of Hydrology (1999). Flood estimation handbook.
  8. Kay, AL, Reynard, NS and Jones, RG (2006). RCM rainfall for UK flood frequency estimation: I. Method and validation, J. of Hydrology, 318(1-4), pp. 151-162. https://doi.org/10.1016/j.jhydrol.2005.06.012
  9. Kim, BK, Kim, BS and Kim, HS (2008). On the change of extreme weather event using extreme indices, J. of Korea Society of Civil Engineers, 28(1B), pp. 41-53.
  10. Kim, BS, Kim, BK, Kyoung, MS and Kim, HS (2008). Impact assessment of climate change on extreme rainfall and I-D-F analysis, J. of Korea Water Resources Association, 41(5), pp. 129-141.
  11. Kwon, HH, Kim, BS and Kim, BG (2008). Analysis of precipitation characteristics of regional climate model for climate change impacts on water resources, J. of Korea Society of Civil Engineers, 28(5B), pp. 525-533.
  12. Kyoung, MS, Lee, JK and Kim, HS (2009). Downscaling technique of monthly GCM using daily precipitation generator, J. of Korea Society of Civil Engineers, 29(5), pp. 441-452.
  13. Kyoung, MS (2010). Assesment of Climate Change Effect on Standardized Precipitation Index and Frequency based Precipitation, Doctor's Thesis, Inha University.
  14. Lee, DJ and Heo, JH (2001). Frequency analysis of daily rainfall in Han river basin based on regional L-moments algorithm, J. of Korea Water Resources Association, 34(2), pp. 119-130.
  15. Mailhot, A, Duchesne, S, Caya, D and Talbot, G (2007). Assessment of future change in intensity-duration- frequency (IDF) curves for southern quebec using the canadian regional climate model (CRCM), J. of Hydrology, 347(1-2), pp. 197-210. https://doi.org/10.1016/j.jhydrol.2007.09.019
  16. Ministry of Land, Transport and Maritime Affairs (MLTMA) (2009). Researches on National Water Security in Preparation for Climate Change (2nd).
  17. Ministry of Land, Transport and Maritime Affairs (MLTMA) (2011). Improvement and Supplement of Probability Rainfall in South Korea.
  18. Oh, TS, Moon, YI and Oh, KT (2008). Estimation of probability precipitation by regional frequency analysis using cluster analysis and variable kernel density function, J. of Korea Society of Civil Engineers, 28(2B), pp. 225-236.
  19. STARDEX (STAtistical and Regional dynamical Downscaling of EXtremes for European regions) (2005). http://www. cru.uea.ac.uk/projects/stardex/
  20. Stedinger, JR and Lu, LH (1995). Appraisal of regional and index flood quantile estimators, Stochastic hydrology and hydraulics, 9, pp. 45-75.
  21. Thodsen, H (2007). The influence of climate change on stream flow in danish rivers, J. of Hydrology, 333 (2-4), pp. 226-238. https://doi.org/10.1016/j.jhydrol.2006.08.012
  22. Tinsley Odena, J and Prudhommeb, S (2002). Estimation of modeling error in computational mechanics, J. of Computational Physics, 182(2), pp. 496- 515. https://doi.org/10.1006/jcph.2002.7183
  23. World Meteorological Organization (WMO) (2009). Guidelines on analysis of extremes in a changing climate in support of informed decisions for adaptation, Climate data and monitoring, WCDMP- No. 72.

Cited by

  1. Regional Frequency Analysis for Future Precipitation from RCP Scenarios vol.17, pp.1, 2015, https://doi.org/10.17663/JWR.2015.17.1.080
  2. Geographical Impact on the Annual Maximum Rainfall in Korean Peninsula and Determination of the Optimal Probability Density Function vol.17, pp.3, 2015, https://doi.org/10.17663/JWR.2015.17.3.251