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Development of climate change uncertainty assessment method for projecting the water resources

기후변화에 따른 수자원 전망의 불확실성 평가기법 개발

  • Lee, Moon-Hwan (Dept. of Civil and Environmental Engrg., Sejong University) ;
  • So, Jae-Min (Dept. of Civil and Environmental Engrg., Sejong University) ;
  • Bae, Deg-Hyo (Dept. of Civil and Environmental Engrg., Sejong University)
  • 이문환 (세종대학교 공과대학 건설환경공학과) ;
  • 소재민 (세종대학교 공과대학 건설환경공학과) ;
  • 배덕효 (세종대학교 공과대학 건설환경공학과)
  • Received : 2016.05.13
  • Accepted : 2016.06.29
  • Published : 2016.08.31

Abstract

It is expected that water resources will be changed spatially and temporally due to the global climate change. The quantitative assessment of change in water availability and appropriate water resources management measures are needed for corresponding adaptation. However, there are large uncertainties in climate change impact assessment on water resources. For this reason, development of technology to evaluate the uncertainties quantitatively is required. The objectives of this study are to develop the climate change uncertainty assessment method and to apply it. The 5 RCMs (HadGEM3-RA, RegCM4, MM5, WRF, and RSM), 5 statistical post-processing methods (SPP) and 2 hydrological models (HYM) were applied for evaluation. The results of the uncertainty analysis showed that the RCM was the largest sources of uncertainty in Spring, Summer, Autumn (29.3~68.9%), the hydrological model was the largest source of uncertainty in Winter (46.5%). This method can be possible to analyze the changes in the total uncertainty according to the specific RCM, SPP, HYM model. And then it is expected to provide the method to reduce the total uncertainty.

전지구적으로 발생하는 기후변화로 인해 수자원의 시공간적 변화를 야기할 것으로 전망된다. 기후변화에 따른 수자원의 영향을 정량적으로 평가하고 그에 적응할 수 있는 수자원 관리 방안이 필요하다. 하지만 영향평가 시 많은 불확실성이 발생하기 때문에 평가 시 발생하는 불확실성을 정량적으로 평가할 수 있는 기술 개발이 요구된다. 본 연구에서는 기후변화에 따른 수자원 영향평가 시 발생하는 불확실성을 단계별로 평가할 수 있는 기법을 개발하였으며, 지역기후모형, 통계적 후처리기법, 수문모형에 따른 불확실성을 분석하였다. 평가를 위해 5개 지역기후모형, 5개 통계적 후처리기법과 2개 수문모형을 이용하였다. 불확실성의 요인을 분석한 결과 유출량의 경우 겨울철을 제외한 모든 계절에서 RCM의 불확실성이 29.3~8.9%로 가장 큰 비중을 차지하는 것으로 나타났으나, 겨울철은 수문모형의 불확실성이 46.5%를 차지하는 것으로 나타났다. 증발산량의 경우 가을철을 제외하고 수문모형의 불확실성이 28.5~5.1%로 가장 큰 비중을 차지하였다. 따라서 이수기는 수문모형에 더욱 영향이 큰 것으로 나타났으며, 홍수기는 기후 모델링 부분의 영향이 큰 것으로 사료된다. 이 기법을 통해 특정 RCM이나 통계적 후처리기법, 수문모형 등의 선정에 따라 전체 불확실성이 어떻게 변화될 수 있는지를 분석할 수 있으며, 이를 통해 불확실성을 저감할 수 있는 방안을 마련할 수 있을 것으로 기대된다.

Keywords

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