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http://dx.doi.org/10.3741/JKWRA.2006.39.7.593

The optimal parameter estimation of storage function model based on the dynamic effect  

Kim Jong-Rae (Korea Water Resources Corporation)
Kim Joo-Cheal (Industrial Technology Research Institute, Chungnam National Univ.)
Jeong Dong-Kook (Dept. of Civil and Environ, Engrg., Hannam Univ.)
Kim Jae-Han (Dept. of Civil Engrg., Chungnam National Univ.)
Publication Information
Journal of Korea Water Resources Association / v.39, no.7, 2006 , pp. 593-603 More about this Journal
Abstract
The basin response to storm is regarded as nonlinearity inherently. In addition, the consistent nonlinearity of hydrologic system response to rainfall has been very tough and cumbersome to be treated analytically. The thing is that such nonlinear models have been avoided because of computational difficulties in identifying the model parameters from recorded data. The parameters of nonlinear system considered as dynamic effects in the conceptual model are optimized as the sum of errors between the observed and computed runoff is minimized. For obtaining the optimal parameters of functions, the historical data for the Bocheong watershed in the Geum river basin were tested by applying the numerical methods, such as quasi-linearization technique, Runge-Kutta procedure, and pattern-search method. The estimated runoff carried through from the storage function with dynamic effects was compared with the one of 1st-order differential equation model expressing just nonlinearity, and also done with Nash model. It was found that the 2nd-order model yields a better prediction of the hydrograph from each storm than the 1st-order model. However, the 2nd-order model was shown to be equivalent to Nash model when it comes to results. As a result, the parameters of nonlinear 2nd-order differential equation model performed from the present study provided not only a considerable physical meaning but also a applicability to Korean watersheds.
Keywords
dynamic effects of storage; storage function; model parameters; quasi-linearization technique; Runge-Kutta procedure; pattern-search method;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 남궁달 (1985). '저류함수볍에 의한 강우-유출모형의 변수추정', 한국수자원학희지, 18(2), pp. 175-185
2 윤재홍, 고석구, 김양일 (1991) '최적화 기법에 의한 저류함수 유출 모델의 자동 보정', 수공학논총, 한국수자원학회, 제33권, pp. 88-101
3 김주철, 정관수, 김재한 (2004). '신집수형상디스크립터 와 Nash 모형의 지체시간 사이의 상관성 분석', 한국수자원학회논문집, 37(12), pp. 1065-1074
4 정창삼, 허준행 (2002). '패턴 인식기법을 이용한 유출 모형의 매개변수 최적화', 한국수자원학회 2002 학술발표회논문집, pp. 1316-1321
5 박봉진, 차형선, 김주환 (1997). '유전자 알고리듬을 이용한 저류함수모형의 매개변수 추정에 관한 연구', 한국수자원학회논문집, 30(4), pp. 347-355
6 송재현, 김형수, 홍일표, 김상욱 (2006). '저류함수모형의 매개변수 보정과 홍수예측(1) 보정 방법론과 모의 홍수수문곡선의 평가', 대한토목학회논문집, 26 (1B), pp. 27-38
7 이정규, 이창해 (1996). '저류함수법의 시변성 매개변수 조정에 퍼지이론 도입에 관한 연구', 한국수자원학회지, 29(4), pp. 149-160
8 한국수자원공사 (2003). KOWACO 홍수분석모형 개발 보고서, pp. 445-557
9 Doege, J.C.I. and 0' Kane, J.P. (2003). Deterministic methods in system hydrology, A. A. Balkerm Publishers
10 Kaplan, W. (1964). Elements of ordinary differential equations, Addison-Wesley
11 Jain, M. K. (1979). Numerical solution of differential equations, Wiley Eastern Limited
12 Labadie, J.W. and Dracup, J. A. (1969). 'Optimal identification of lumped watershed model', Water Resources Research, 5(3), pp. 583-590   DOI
13 Prasad, R (1967). 'A nonlinear hydrologic system response model' , Journal of the Hydraulics Division, pp. 201-221
14 日野幹雄 (1975). '非線型流出解析および適應據測', 1975 年度(第十一-回)水I學に關する夏期研修會講義集 A コ-ス, 日本士木學會 水理委員會, A-8-1-A-8-31
15 日野幹雄, 太田猛彦, 砂田憲吾, 渡辺邦夫(1989). 洪水 の数値務報, 森北出版柱式會杜
16 김한섭, 이정규 (2000). '통합저류함수모형에 의한 홍수 추적' 한국수자원학회 2000 학술발표회논문집, pp. 100-105
17 김선주, 지용근, 김필식 (2004). '유전자 알고리즘을 이 용한 장.단기 유출모형의 매개 변수 최적화', 한국수자원학회 2004 학술발표회초록집, pp. 163
18 김재한 (2005). 수문계의 수학적 모형, 선형계를 중심으로, 도서출판새론