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Development of Real-Time Drought Monitoring and Prediction System on Korea & East Asia Region

한반도·동아시아 지역의 실시간 가뭄 감시 및 전망 시스템 개발

  • Bae, Deg-Hyo (Department of Civil and Environmental Engrg., Sejong Univ.) ;
  • Son, Kyung-Hwan (Department of Civil and Environmental Engrg., Sejong Univ.) ;
  • Ahn, Joong-Bae (Division of Earth Environmental System, Pusan National University) ;
  • Hong, Ja-Young (Division of Earth Environmental System, Pusan National University) ;
  • Kim, Gwang-Soeb (Department of Architecture and Civil Engrg., Kyungbook National University) ;
  • Chung, Jun-Seok (Korea Meteorological Administration) ;
  • Jung, Ui-Seok (Hydrology Engineering & Consulting Center, Korea Inc.) ;
  • Kim, Jong-Khun (Environmental Prediction Research Inc.)
  • Received : 2011.12.19
  • Accepted : 2012.01.20
  • Published : 2012.06.30

Abstract

The objectives of this study are to develop a real-time drought monitoring and prediction system on the East Asia domain and to evaluate the performance of the system by using past historical drought records. The system is mainly composed of two parts: drought monitoring for providing current drought indices with meteorological and hydrological conditions; drought outlooks for suggesting future drought indices and future hydrometeorological conditions. Both parts represent the drought conditions on the East Asia domain (latitude $21.15{\sim}50.15^{\circ}$, longitude $104.40{\sim}149.65^{\circ}$), Korea domain (latitude $30.40{\sim}43.15^{\circ}$, longitude $118.65{\sim}135.65^{\circ}$) and South Korea domain (latitude $30.40{\sim}43.15^{\circ}$, longitude $118.65{\sim}135.65^{\circ}$), respectively. The observed meteorological data from ASOS (Automated Surface Observing System) and AWS (Automatic Weather System) of KMA (Korean Meteorological Administration) and model-driven hydrological data from LSM (Land Surface model) are used for the real-time drought monitoring, while the monthly and seasonal weather forecast information from UM (Unified Model) of KMA are utilized for drought outlooks. For the evaluation of the system, past historical drought records occurred in Korea are surveyed and are compared with the application results of the system. The results demonstrated that the selected drought indices such as KMA drought index, SPI (3), SPI (6), PDSI, SRI and SSI are reasonable, especially, the performance of SRI and SSI provides higher accuracy that the others.

Keywords

References

  1. 건설교통부, 1995: 가뭄기록조사 보고서
  2. 건설교통부, 2002: 2001년 가뭄기록조사 보고서
  3. 기상청, 2007: 산업기상지수 산출기술 개발
  4. 류재희, 이동률, 안재현, 윤용남, 2002: 가뭄평가를 위한 가뭄지수의 비교 연구. 한국수자원학회논문집, 35(4), 397-410.
  5. 손경환, 이종대, 배덕효, 2010: 전지구 수문해석 모형의 국내적용성 평가. 한국수자원학회논문집, 43(12), 1063-1074.
  6. 손경환, 배덕효, 정준석, 2011: 지표수문해석모형을 활용한 국내 가뭄해석 적용성 평가. 한국수자원학회논문집, 40(12), 1063-1074.
  7. 윤성심, 배덕효, 2010: 이류모델을 활용한 초단시간 강우예측의 적용성 평가. 한국수자원학회논문집, 43(8), 695-707.
  8. Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges, 1994: A simple hydrologically based model of land surface water and energy fluxes for general circulation models. Journal of Geophysical Research, 99(7), 14415-14428. https://doi.org/10.1029/94JD00483
  9. Liang, X., G. Jianzhong, and L. Ruby Leung, 2004: Assessment of the effects of spatial resolutions on daily water flux simulations. Journal of Hydrology, 298(1-4), 287-310. https://doi.org/10.1016/j.jhydrol.2003.07.007
  10. Mckee, T.B., N. J. Doesken, and J. Kleist, 1993: The Relationship of Drought Frequency and Duration to Time Scales. 8th Conference on Applied Climatology, 17-22 January, Anaheim, California.
  11. Palmer, W. C., 1965: Meteorological drought, Research paper. 45, U.S. Weather Bureau.
  12. Trenberth, K. E., J. T. Overpeck, and S. Solomon, 2004: Exploring drought and its implications for the future. Eos, Transactions American Geophysical Union, 85(3), 27-27. https://doi.org/10.1029/2004EO030004

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