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RCP 시나리오별 한반도 가뭄특성 분석

Analysis of drought characteristics depending on RCP scenarios at Korea

  • 김정호 (콜로라도주립대학교 공과대학) ;
  • 김상단 (부경대학교 환경공학과) ;
  • 주진걸 (동신대학교 토목공학과)
  • Kim, Jungho (College of Engineering, Colorado State University) ;
  • Kim, Sangdan (Department of Environmental Engineering, Pukyong National University) ;
  • Joo, Jingul (Department of Civil Engineering, Dongshin University)
  • 투고 : 2015.12.28
  • 심사 : 2016.02.22
  • 발행 : 2016.04.30

초록

본 연구에서는 RCP 시나리오별 표준가뭄지수의 특성을 정량적인 측면과 공간적인 측면에서 상호비교 하였다. 이를 위해, 4개의 RCP 시나리오로부터 산정된 SPI를 기반으로 가뭄 특성을 정량적으로 비교하였고, 가뭄발생 횟수와 지속기간을 공간적으로 분석하였다. 결과적으로, RCP 시나리오별 SPI의 거동 특성은 매우 상이하고, 모든 상관계수가 0.08보다 낮은 것으로 나타났다. 또한 가뭄의 정도, 발생횟수, 그리고 지속기간에 대한 상이한 공간분포 경향을 확인할 수 있었다. RCP 시나리오별 상이한 가뭄발생전망 특성의 가장 큰 배경은 다른 온실가스 배출농도 시나리오 기반의 일 강수량을 들 수 있으나, 온실가스 배출농도 규모에 따른 영향은 명확하지 않았다. 아울러, 본 연구 결과를 통해 단일 RCP 시나리오 자료만 이용한 가뭄발생 전망에는 상당한 불확실성이 따를 것으로 판단된다.

This study implemented a comparison of SPI characteristics in terms of quantitative and spatial analysis depending on four RCP scenarios. For this purpose, we compared quantitative characteristics of drought using standard precipitation index resulted from daily precipitation data reflecting future green gas concentration scenarios, and spatial distribution field of seasonal drought occurrence frequency and its duration, was analyzed to compare drought trends depending on the RCP scenarios. As a result, we found that SPI time series was quite different from each other and correlation coefficients were lower than 0.08. Depending on the RCP scenarios, spatial distribution results showed different trends in drought severity, frequency, and duration. The biggest reason of the difference is daily precipitation data based on the different greenhouse gas concentrations, but we could not find the effect of the concentration extent on drought occurrence projection. In addition, according to the results from this study, drought analysis results using single RCP scenario may have considerable uncertainty.

키워드

참고문헌

  1. Ahn, S.R., Jeong, J.H., and Kim, S.J. (2015). Assessing drought threats to agricultural water supplies under climate change by combining the SWAT and MODSIM models for the Geum River basin, South Korea, Hydrological Sciences Journal, DOI:10.1080/02626667.2015.1112905.
  2. Burke, E.J., Simon, J.B., and Christidis, N. (2006). Modeling the recent evolution of global drought and projections for the twenty-first century with the Hadley Centre climate model. Journal of Hydrometeorology, Vol. 7, No. 5, pp. 1113-1125. https://doi.org/10.1175/JHM544.1
  3. Cook, B.I., Toby R. Ault, and Jason E. Smerdon. (2015). Unprecedented 21st century drought risk in the American Southwest and Central Plains. Science Advances, Vol. 1, No. 1, DOI: 10.1126/sciadv.1400082.
  4. IPCC, (2014). Climate change 2014: synthesis report. contribution of working groups I, II and III to the fifth assessment repozrt of the intergovernmental panel on climate change. IPCC, Geneva, Switzerland.
  5. Joo, J., Kim, S., Park, M., and Kim, J.-H. (2015). Evaluation and calibration method proposal of RCP daily precipitation data. Journal of Korean Society Hazard Mitigation, Vol. 15, No. 2, pp. 79-91.
  6. Kim, B., Park, I., and Ha, S. (2014). Future projection of droughts over South Korea using representative concentration pathways. Terrestrial Atmospheric and Oceanic Sciences, Vol. 25, No. 5, pp. 673-688. https://doi.org/10.3319/TAO.2014.03.13.01(Hy)
  7. Kim, H., Park, J., Yoon, J., and Kim, S. (2010). Application of SAD curve in assessing climate-change impacts on spatio-temporal characteristics of extreme drought events. Journal of Korean Society Civil Engineering, Vol. 30, No. 6B, pp. 561-569.
  8. Kim, J., and Joo, J. (2015). Characteristics of daily precipitation data based on the detailed climate change ensemble scenario depending on the regional climate models and the calibration. Journal of Korean Society Hazard Mitigation, Vol. 15, No. 4, pp. 261-272. https://doi.org/10.9798/KOSHAM.2015.15.4.261
  9. Kim, J., Park, M., and Joo, J. (2015). Comparison of characteristics and spatial distribution tendency of daily precipitation based on the regional climate models for the Korean Peninsula. Journal of Korean Society Hazard Mitigation, Vol. 15, No. 4, pp. 59-70. https://doi.org/10.9798/KOSHAM.2015.15.4.59
  10. Moon, J.W. (2010). Development of drought index based on hydrologic characteristics and water supply system in Korea. Master thesis, Korea University.
  11. Park, M., Sim, H-J., Park, Y., and Kim, S. (2015). Drought severity-duration-frequency analysis based on KMA 1-km resolution RCP scenario. Journal of the Korean Society of Hazard Mitigation, Vol. 15, No. 3, pp. 347-355. https://doi.org/10.9798/KOSHAM.2015.15.3.347
  12. Sheffield, J., and Wood, E.F. (2008). Projected changes in drought occurrence under future global warming from multi-model, multi-scenario, IPCC AR4 simulations. Climate Dynamics, Vol. 31, No. 1, pp. 79-105. https://doi.org/10.1007/s00382-007-0340-z
  13. Svododa, M., Lecomte, D., Hyaes, M., Heim, R., Gleas on, K., Angel, J., Rippey, B., Tinker R., Palecki M., Stooksbury, D., Miskus, D., and Stephens, S. (2002). The drought monitor. Bulletin of the American Meteorological Society, Vol. 83, No. 8, pp. 1181-1190. https://doi.org/10.1175/1520-0477(2002)083<1181:TDM>2.3.CO;2
  14. Yoo, J., Kwon, H., Lee, J., and Kim, T., (2015). Influence of evapotranspiration on future droght risk using bivariate drought frequency curves. KSCE Journal of Civil Engineering, DOI:10.1007/s12205-015-0078-9.

피인용 문헌

  1. A Comparison of Drought Prospection by Future Climate Models vol.16, pp.2, 2016, https://doi.org/10.9798/KOSHAM.2016.16.2.463
  2. Reliability–Resiliency–Vulnerability Approach for Drought Analysis in South Korea Using 28 GCMs vol.10, pp.9, 2018, https://doi.org/10.3390/su10093043