한국수자원학회논문집 (Journal of Korea Water Resources Association)

  • 제43권12호
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  • Pages.1011-1027
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  • 2010
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  • 2799-8746(pISSN)
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  • 2799-8754(eISSN)
한국수자원학회 (Korea Water Resources Association)
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다중최적화기법을 이용한 강우-유사-유출 예측 불확실성 평가

Assessment of Rainfall-Sediment Yield-Runoff Prediction Uncertainty Using a Multi-objective Optimization Method

  • 이기하 (충남대학교 건설방재연구소) ;
  • 유완식 (충남대학교 공과대학 토목공학과) ;
  • 정관수 (충남대학교 공과대학 토목공학과) ;
  • 조복환 (한국종합기술 수자원부)
  • Lee, Gi-Ha (Research Associate., Construction and Disaster Research Center, Chungnam National Univ.) ;
  • Yu, Wan-Sik (Dept. of Civil Eng., Chungnam National Univ.) ;
  • Jung, Kwan-Sue (Dept. of Civil Eng., Chungnam National Univ.) ;
  • Cho, Bok-Hwan (Div. of Water Resources, Korean Engineering Consultants Corp.)
  • 투고 : 2010.10.04
  • 심사 : 2010.11.11
  • 발행 : 2010.12.31
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초록

모형의 구조, 모델링에 사용되는 자료, 매개변수 등에 포함된 다양한 불확실성 원인들은 수문모의 및 예측결과에 있어 불확실성을 야기한다. 본 연구에서는 강우-유출 및 강우-유사유출 모의가 가능한 분포형 강우-유사-유출 모형을 용담댐 상류유역인 천천유역에 적용하여 수문곡선 및 유사량곡선의 재현성을 평가하고, 다중최적화기법인 MOSCEM을 이용하여 강우-유출 모듈, 강우-유사유출 모듈의 매개변수를 독립적으로 보정한 경우(Case I과 II), 그리고 두 모듈이 결합된 강우-유사-유출 모형의 매개변수를 동시에 보정한 경우(Case III)에 대하여 Pareto 최적해를 추정하고, 이에 따른 수문 예측결과의 불확실성을 평가한다. 매개변수 불확실성의 전이에 따른 수문곡선의 불확실성 평가 결과(Case I), 모의기간 동안 고유량보다는 저유량 부분에서 불확실성 범위가 두드러졌으며, 이에 반해, 유사량곡선의 경우(Case II) 저농도보다는 고농도 부분에서 불확실성 범위가 넓게 분포하였다. 강우-유사-유출 모형의 매개변수의 불확실성을 동시에 추정한 경우 수문곡선 및 유사량곡선 모두 Case I과 II에 비해 모의기간 전반에 걸쳐 불확실성 범위가 넓게 분포되었으며, 매개 변수의 불확실성으로 인해 대상유역내 격자별 침식 및 퇴적 공간분포 양상이 상이하게 나타났다.

In hydrologic modeling, prediction uncertainty generally stems from various uncertainty sources associated with model structure, data, and parameters, etc. This study aims to assess the parameter uncertainty effect on hydrologic prediction results. For this objective, a distributed rainfall-sediment yield-runoff model, which consists of rainfall-runoff module for simulation of surface and subsurface flows and sediment yield module based on unit stream power theory, was applied to the mesoscale mountainous area (Cheoncheon catchment; 289.9 $km^2$). For parameter uncertainty evaluation, the model was calibrated by a multi-objective optimization algorithm (MOSCEM) with two different objective functions (RMSE and HMLE) and Pareto optimal solutions of each case were then estimated. In Case I, the rainfall-runoff module was calibrated to investigate the effect of parameter uncertainty on hydrograph reproduction whereas in Case II, sediment yield module was calibrated to show the propagation of parameter uncertainty into sedigraph estimation. Additionally, in Case III, all parameters of both modules were simultaneously calibrated in order to take account of prediction uncertainty in rainfall-sediment yield-runoff modeling. The results showed that hydrograph prediction uncertainty of Case I was observed over the low-flow periods while the sedigraph of high-flow periods was sensitive to uncertainty of the sediment yield module parameters in Case II. In Case III, prediction uncertainty ranges of both hydrograph and sedigraph were larger than the other cases. Furthermore, prediction uncertainty in terms of spatial distribution of erosion and deposition drastically varied with the applied model parameters for all cases.

키워드

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