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Modification of the Fixed Coefficient Method for the Parameter Estimation of Storage Function Method

저류함수법의 매개변수 추정을 위한 상수고정법의 개선

  • Chung, Gunhui (Water Resources Research Division, Korea Institute of Construction Technology) ;
  • Park, Hee-Seong (Water Resources Research Division, Korea Institute of Construction Technology)
  • 정건희 (한국건설기술연구원 수자원연구실) ;
  • 박희성 (한국건설기술연구원 수자원연구실)
  • Received : 2012.08.01
  • Accepted : 2012.09.27
  • Published : 2013.01.31

Abstract

The researches on the parameter estimation for storage function method have been conducted for a long time using different methods. However, the determination of the optimal parameters takes a long time and there is a controversy that the proposed optimal parameters do not likely represent the physical characteristics of watershed. In this study, the characteristics of the continuity and storage function equation was analyzed and sensitivities were evaluated. As the result, the only optimal solution is suggested among several local optimums. It is also shown that the lag time is able to be determined using the direct runoff starting time of the watershed. From the sensitivity analysis, it is also proved that the determination of the lag time is very important and the only optimal solution could be found easily after selecting the lag time. Therefore, unlike the traditional optimization method, the proposed method does not take a long time to find the optimal solution which is depending on the characteristics of the rainfall events. The fixed coefficient method which is a method to estimate the optimal parameters of storage function method has been modified using the proposed method. Therefore, the practical efficiency to apply storage function method could be enhanced by applying the proposed method. While the traditional method takes care only the error of the runoff hydrograph, it is very important that the proposed method considers the characteristics of the watershed.

저류함수법의 최적 매개변수를 추정하기 위한 연구는 오랜 동안 여러 가지 방법으로 수행되어왔다. 그러나 여전히 최적 매개변수를 결정하는 것은 시간이 오래 걸리는 일이며, 유역의 물리적인 특성과 상관없는 매개변수가 결과로 제시되는 경우가 잦다는 인식이 팽배하다. 본 구에서는 저류함수모형의 연속방정식과 저류함수식을 충실히 분석하고 민감도 분석을 수행하였다. 그 결과, 많은 수의 국지해 중에서 유일해를 결정하는 방법을 제안할 수 있었다. 또한 유역의 직접유출 시작 시간을 고려하여 저류함수법의 지체시간을 결정할 수 있다는 것을 보였으며, 매개변수의 민감도 분석 결과, 모형의 지체시간을 결정하는 것이매우 중요하다는 것을 알수 있었다. 지체시간을 결정한 후에는 유일한해를 비교적 쉽게 찾을 수 있었다. 그러므로 제안된 방법은 기존의 최적화 방법과 같이 시간이 오래 걸리지 않으며, 강우사상별로 비교적 정확한 매개변수를 산정할 수 있다는 장점이 있다. 제안된 방법을 이용하여 기존의 저류함수법의 매개변수를 추정하기 위한 다양한 방법 중 상수고정법을 수정하였으며, 그 결과 실무에서 업무효율을 높일 수 있을 것으로 기대된다. 또한 제안된 방법은 기존의 유출수문곡선의 계산오차에만 의지하여 매개변수를 최적화하는 방법과는 다르게 유역의 특성을 고려할 수 있다는 점에서 그 의미가 있다.

Keywords

References

  1. Bae, D.H., and Jung, I.M. (2000) "Development of Stochastic-Dynamic Channel Routing Model by Storage Function Method." Journal of Korea Water Resources Association, KWRA, Vol. 33, No. 3, pp. 341-350.
  2. Bae, D.H., Lee, B.J., and Georgakakos, K.P. (2009a). "Stochastic Continuous Storage Function Model with Ensemble Kalman Filtering (I): Model Development." Journal of KoreaWater Resources Association, KWRA, Vol. 42, No. 11, pp. 953-961. https://doi.org/10.3741/JKWRA.2009.42.11.953
  3. Fujita, M., and Kudo, M. (1995). "Stochastic response of a storage function model for flood runoff estimation of higher-order moments." Environment International, Vol. 21, No. 5, pp. 523-531. https://doi.org/10.1016/0160-4120(95)00052-M
  4. Kim, J.R., Kim, J.C., Jeong, D.K., and Kim, J.H. (2006). "The optiaml parameter estimation of storage function model based on the dynamic effect." Journal of Korea Water Resources Association, KWRA, Vol. 39, No. 7, pp. 593-603.
  5. Kim, W.H., Im, Y.C., and Ryu, J.W. (1998). "An Adaptive Storage Function Method for Rainfall-Runoff Forecasting." Journal of Electrical Engineering & Technology, KIEE, Vol. 47, No. 2, pp. 231-236.
  6. Kimura, T. (1961). "The Flood Runoff Analysis Method by the Storage Function Model." The Public Works Research Institute, Ministry of Construction
  7. Lee, B.J., Bae, D.H., and Shamir, E. (2009b). "Stochastic Continuous Storage Function Model with Ensemble Kalman Filtering (II): Application and Verification." Journal of Korea Water Resources Association, KWRA, Vol. 42, No. 11, pp. 963-972. https://doi.org/10.3741/JKWRA.2009.42.11.963
  8. Lee, J.K., and Lee, C.H. (1996). "A Study on the Introduction of Fuzzy Theory to the Adjustment of Time-Variant Parameter of Storage Function Method." Journal of Korea Water Resources Association, KWRA, Vol. 29, No. 4, pp. 149-160.
  9. Nam, K.T. (1985). "Parameter Determination of Rainfall Runoff Model by Storage Function Model." Journal of Korea Water Resources Association, KWRA, Vol. 18, No. 2, pp. 185-185.
  10. 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, No. 3, pp. 282-290. https://doi.org/10.1016/0022-1694(70)90255-6
  11. Shamir, E., Lee, B., Bae, D., and Georgakakos, K. P. (2010). "Flood forecasting in regulated basins using the ensemble extended kalman filter with the storage function method." Journal of Hydrologic Engineering, ASCE, Vol. 15, No. 12, pp. 1030-1044.
  12. Song, J.H., Kim, H.S., Hong, I.P., and Kim, S.U. (2006). "Parameter Calibration of Storage Function Model and Flood Forecasting (1) Calibration Methods and Envaluation of Simulated Flood Hydrograph." The KSCE Journal of Civil Engineering, KSCE, Vol. 26, No. 1B, pp. 27-38.
  13. Sugiyama, H., Kadoya, M., Nagai, A., and Lansey, K. (1999). "Verification and application of regional equations for the storage function runoff model." Journal of the American Water Resources Association, Vol. 35, No. 5, pp. 1147-1157. https://doi.org/10.1111/j.1752-1688.1999.tb04202.x
  14. Sugiyama, H., Kadoya, M., Nagai, A., and Lausey, K. (1997). "Evaluation of the storage function model parameter characteristics." Journal of Hydrology, Vol. 191, pp. 332-348. https://doi.org/10.1016/S0022-1694(96)03026-0
  15. Yi, J.E., and Choi, C.W. (2008). "Flood Forcasting and Warning Using Neuro-Fuzzy Inference Technique." Journal of Korea Water Resources Association, KWRA, Vol. 41, No. 3, pp. 341-351. https://doi.org/10.3741/JKWRA.2008.41.3.341

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