한국수자원학회논문집 (Journal of Korea Water Resources Association)

  • 제46권3호
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  • Pages.229-243
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  • 2013
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  • 2799-8746(pISSN)
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  • 2799-8754(eISSN)
한국수자원학회 (Korea Water Resources Association)
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기후모형(GCMs)에 기반한 2018년 평창 동계올림픽 적설량 및 수문모의

GCMs-Driven Snow Depth and Hydrological Simulation for 2018 Pyeongchang Winter Olympics

  • 김정진 (미국 아이다호대학교 농생공학과) ;
  • 류재현 (미국 아이다호대학교 농생공학과)
  • Kim, Jung Jin (Department of Biological & Agricultural Eng., Univ. of Idaho) ;
  • Ryu, Jae Hyeon (Department of Biological & Agricultural Eng., Univ. of Idaho)
  • 투고 : 2012.09.13
  • 심사 : 2012.10.22
  • 발행 : 2013.03.31
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초록

평창유역의 적설량을 모의하기 위하여 HSPF 모형을 적용하였다. 미래 적설량을 평가하기 위해 CIMIP3에서 제공하는 A1, A1B, B1의 온실가스 배출시나리오에 기반한 GCMs를 이용하였으며, HSPF 모형과 GCMs의 통계학적 오류를 최소화 하기 위해 편의보정(Bias-correction)과 시간적 분해모형(Temporal disaggregation)을 적용하였다. 모형의 검 보정 결과 모의된 유출량과 적설량의 경우 모형 효율이 높게 나타났으며, 특히 모형의 검정 후 상관계수를 분석한 결과 월별 유출량의 상관계수는 0.94로 나타났다. 월별 적설량, 또한, 상관계수가 0.91로 나타나 보정된 HSPF 모형이 평창지역에 대한 유출량과 적설량을 잘 모의하고 있는 것으로 판단된다. GCMs를 이용한 2018년 평창올림픽 경기장의 적설량을 분석한 결과 1월에는 17.62%, 2월에는 9.38%, 3월에는 7.25%의 적설량이 감소되는 것으로 나타났다.

Hydrological simulation Program-Fortran (HSPF) model was used to simulate streamflow and snow depth at Pyengchang watershed. The selected Global Climate Models (GCMs) provided by the Coupled Model Intercomparision Project Phase 3 (CMIP3) were utilized to evaluate streamflow and snow depth driven by future climate scenarios, including A1, A1B, and B1. Bias-correlation and temporal downscaling processes have been performed to minimize systematic errors between GCMs and HSPF. Based on simulated monthly streamflow and snow depth after calibration, the results indicate that HSPF performs well. The correlation coefficient between the observed and simulated monthly streamflow is 0.94. Snow depth simulations also show high correlation coefficient, which is 0.91. The results indicate that snow depth in 2018 at Pyongchang winter olympic venues will decrease by 17.62%, 9.38%, and 7.25% in January, February, and March respectively, based on streamflow realizations induced by all GCMs ensembles.

키워드

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피인용 문헌

  1. Projection of Climate Change with Uncertainties: 1. GCM and RCP Uncertainties vol.14, pp.5, 2014, https://doi.org/10.9798/KOSHAM.2014.14.5.317