한국수자원학회논문집 (Journal of Korea Water Resources Association)

  • 제49권3호
  • /
  • Pages.253-262
  • /
  • 2016
  • /
  • 2799-8746(pISSN)
  • /
  • 2799-8754(eISSN)
한국수자원학회 (Korea Water Resources Association)
권호 표지
DOI QR코드

DOI QR Code

Bayesian 기반 Multi-Segmented 곡선식을 활용한 수위-유량 곡선의 불확실성 분석

A development of rating-curve using Bayesian Multi-Segmented model

  • 김진영 (전북대학교 토목공학과 방재연구센터) ;
  • 김진국 (전북대학교 토목공학과 방재연구센터) ;
  • 이재철 (충남도립대학교 건설정보과) ;
  • 권현한 (전북대학교 토목공학과 방재연구센터)
  • Kim, Jin-Young (Department of Civil Engineering, Chonbuk National University) ;
  • Kim, Jin-Guk (Department of Civil Engineering, Chonbuk National University) ;
  • Lee, Jae Chul (Department of Civil Engineering and Informatics, Chungnam State University) ;
  • Kwon, Hyun-Han (Department of Civil Engineering, Chonbuk National University)
  • 투고 : 2016.01.04
  • 심사 : 2016.02.05
  • 발행 : 2016.03.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

수위-유량 관계곡선(rating curve)은 수위표에서 관측된 수위 및 유량을 이용하여 만들어진 회귀분석식을 의미하며, 하천의 수위를 유량으로 환산하는 방법으로 일반적으로 활용되고 있다. 그러나 수위-유량 관계곡선식에서 저수위와 고수위와 분리 및 매개변수 추정에 있어 불확실성을 고려한 해석은 이루어지지 않고 있다. 이러한 이유로 본 연구에서는 수위-유량 관계곡선식에서 매개변수 추정 및 저 고수위 분리시 발생하는 문제점을 개선하기 위해 Bayesian 기법을 도입하였으며, 수위-유량 관계곡선식의 매개변수의 추정과 더불어 불확실성을 정량화 하는데 목적을 두었다. 이와 더불어 Bayesian 모형 기반 Multi-Segmented 수위-유량 관계곡선(Bayesian M-S)을 활용하여 저 고수위를 분리할 수 있는 새로운 수위-유량 관계곡선을 개발하고 기존 수위-유량 관계곡선과 비교 분석을 실시하였다. 그 결과 본 연구에서 개발한 Bayesian M-S 기법이 기존 수위-유량 관계곡선식 보다 개선된 결과를 도출할 수 있었으며, 수위-유량 관계곡선식의 신뢰구간을 제시하는데 유리한 것을 확인할 수 있었다.

A Rating curve is a regression equation of discharge versus stage for a given point on a stream where the stream discharge is measured across the stream channel with a stage and discharge measurement. The curve is generally used to calculate discharge based on the stage. However, the existing approach showed problems in terms of estimating uncertainty associated with regression parameters including the separation parameter for low and high flow. In this regard, this study aimed to develop a new method for the aforementioned problems based on Bayesian approach, which can better estimate the parameter and its uncertainty. In addition, this study used a Bayesian Multi-Segmented (Bayesian M-S) model which is provided a comparison between the existing and proposed scheme. The proposed model showed better results for the parameter estimation than the existing approach, and provided better performance in terms of estimating uncertainty range.

키워드

참고문헌

  1. Block, P.J., Filho, F.A.S., and Kwon, H.-H. (2009). "A Streamflow Forecasting Framework using Multiple Climate and Hydrological Models." Journal of The American Water Resources Association, Vol. 45, No. 4, pp. 828-843. https://doi.org/10.1111/j.1752-1688.2009.00327.x
  2. Kim, J.-Y., Kwon, H.-H., and Lim, J.-Y. (2014). "Development of Hierarchical Bayesian Spatial Regional Frequency Analysis Model Considering Geographical Characteristics." Journal of Korea Water Resources Association, KWRA, Vol. 47, No. 5, pp. 469-482. https://doi.org/10.3741/JKWRA.2014.47.5.469
  3. Kim, S.U., and Lee,. K.S. (2008). "Identification of Uncertainty in Fitting Rating Curve with Bayesian Regression." Journal of Korea Water Resources Association, KWRA, Vol. 41, No. 9, pp. 943-958. https://doi.org/10.3741/JKWRA.2008.41.9.943
  4. Kwon, H.-H., Filho, F., Block, P., Sun, L., Lall, U., and Reis Jr, D. S. (2012a). "Uncertainty Assessment of Hydrologic and Climate Forecast Models in Northeatern Brazil." Hydrological Processes, Vol. 26, pp. 3875-3885. https://doi.org/10.1002/hyp.8433
  5. Kwon, H.-H., Kim, J.-G., Lee, J.S., and Na, B.-K. (2012b). "Uncertainty Assessment of Single Event Rainfall-Runoff Model using Bayesian Model." Journal of Korea Water Resources Association, KWRA, Vol. 45, NO. 5, pp. 505-516. https://doi.org/10.3741/JKWRA.2012.45.5.505
  6. Kwon, H.-H., Moon, Y.-I., Kim, B.-S., and Yoon, S-Y. (2008). "Parameter Optimization and Uncertainty Analysis of the NWS-PC Rainfall-Runoff Model Coupled with Bayesian Markov Chain Monte Carlo Inference Scheme." Journal of Korean Society of Civil Engineer, Vol. 28 No. 4B, pp. 363-467.
  7. Lee, W.S., Kim, S.U., Chung, E.-S., and Lee, K.S. (2008). "Improvement of Rating Curve Fitting Considering Variance Function with Pseudo-likelihood Estimation." Journal of Korea Water Resources Association, KWRA, Vol. 41, No. 8, pp. 807-823. https://doi.org/10.3741/JKWRA.2008.41.8.807
  8. Li, P.-H., Kwon, H.-H., Sun, L., Lall, U., and Kao, J.-J. (2010). "A Modified Support Vector Machine based Prediction Model on Streamflow at the Shihmen Reservoir, Taiwan." International Journal of Climatology, Vol. 30, pp. 1256-1268.
  9. Ministry of Land, Infrastructure and Transport. (2010). "Korea Annual hydrological report."
  10. Ministry of Land, Infrastructure and Transport. (2011). "Korea Annual hydrological report."
  11. Ministry of Land, Infrastructure and Transport. (2012). "Korea Annual hydrological report."
  12. Nash, J.E., and Sutcliffe, J.V. (1970). "River Flow Forecasting through Conceptual Models Part I-A Discussion of Principles." Journal of Hydrology, Vol. 10, pp. 282-290. https://doi.org/10.1016/0022-1694(70)90255-6
  13. Petersen-Overleir, A. (2005). "A Hydraulics Perspective on the Power-law Stage-discharge Rating Curve." NVE report 05-05, Norwegian Water Resources and Energy Directorate, pp. 28.
  14. Petersen-Overleir, A. and Reitan, T. (2005) "Objective Segmentation in Compound Rating Curves." Journal of Hydrology, Vol. 311, Issues 1-4, pp. 188-201. https://doi.org/10.1016/j.jhydrol.2005.01.016
  15. Reitan, T., and Petersen-Overleir, A. (2006). "Existence of the Frequentistic Regression Estimate of a Power-law with a Location Parameter, with Applications for Making Discharge Rating Curves." Stoch. Environ. Res. Risk Asses/, Vol. 20, No. 6, pp. 445-453. https://doi.org/10.1007/s00477-006-0037-6
  16. Reitan, T., and Petersen-Overleir, A. (2008). "Bayesian methods for estimating multi-segment discharge rating curves", Stochastic Environmental Research and Risk Assessment, Vol. 23, No. 5, pp. 627-642. https://doi.org/10.1007/s00477-008-0248-0
  17. Seber, G.A.F., and Wild, C.J. (1989). "Nonlinear Regression." New York: John Wiley and Sons.
  18. White, H. (1980). "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity." Econometrica, Vol. 48, No. 4, pp. 817-838. https://doi.org/10.2307/1912934
  19. Xu, K., Brown, C., Kwon, H.-H., Lall, U., Zhang, J., Hayashi, S., and Chen, Z. (2007). "Climate Teleconnections to Yangtze River Seasonal Steamflow at the Three Gorges Dam, China." International Journal of Climatology, Vol. 27, pp. 771-780. https://doi.org/10.1002/joc.1437
  20. Yoon, Y.N. (2007). "Hydrology - Basics and Application." CheongMoonGak