• Title/Summary/Keyword: storage function model

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Fundamental researches on the storage function model and It's application (저유함수법과 그 응용에 관한 기초적 연구)

  • 남궁달
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.26 no.3
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    • pp.90-98
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    • 1984
  • In this paper, the anthor made a basic study of the storage function model and examined several constants in applying the storage function model to flood run-off analysis by dealing with the data in the Supyung and Hoyng Syung watershed, the applicabilities of the storage function model are examined by searching this optimum model parameters in two watersheds. The results are summarized as follows, 1) The optimum values of the exponential constants, P, in the storage function model showed to be 0.77 to 0.87 in two watersheds observed, therefore it was confirmed that the storage fumction model was approaching to the surface runoff model. 2) It was confirmed that the interval of variation of the storage constant, K, Showed to be larger than that of the exponential constant, p. 3) Relative erros in the discharge obtained by using the storage function model and the SDFP mothod showed to be 20 and 17 percent respectively to the observed discharge, therefore it was confirmed that the applicability of the storage function model using the SDFP method are excellent for runoff analysis. 4) A simple method is proposed for estimating the lag time in the storage function model.

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Flood Runoff Analysis by a Storage Function Model (저류함수법에 의한 홍수유출해석)

  • 남궁달;김규성
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.38 no.2
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    • pp.75-86
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    • 1996
  • The formulas for estimating the constants of storage function model including K and TL for runoff analysis and a distributed storage function model are discussed in this study. First, the relations between parameters of the storage function model and the kinematic runoff model are theoretically examined, and then optimum constants of storage function model are obtained by the Standardized Davidson-Fletcher-Powell (SDFP) method. Through this analysis, theoretical formulas were obtained as $K = 0.63 {\alpha} KsB{^0.6}$ and $T_{L}=0.11 {\alpha} KsB{^0.6} r{^0.4} {_e}$, which are difficult to use practically because of the unclarified definition of shape factors. From a practical point of view, empirical formula were derived as $K=15.6{^0.3} {_m}$ and $T_{L}=2.1B{^0.36} {_m} {_e}/r{^0.4} {_e}$ for applied watersheds. The proposed formulas are verified for several recoded floods at a few points of watersheds. It is also found that the distributed storage function. can be applied to flood runoff analysis using the new formulas aboved mentioned.

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Integrated Storage Function Model with Fuzzy Control for Flood Forecasting (I) - Theory and Proposal of Model - (홍수예보를 위한 통합저류함수모형의 퍼지제어 (I) - 이론 및 모형의 수립 -)

  • Lee, Jeong-Gyu;Kim, Han-Seop
    • Journal of Korea Water Resources Association
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    • v.33 no.6
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    • pp.689-699
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    • 2000
  • This paper presents the integrated storage function model (ISFM) to improve the accuracy of the storage function model (SFM) which is widely employed for flood runoff analysis and its forecasting in Korea. In order to achieve this objective, the optimization method is applied for estimation of parameters of the model which dominate the accuracy of the analysis, which is usually taken by empirical formulae, and they are treated as time dependent variables. The fuzzy control technique is used to detennine the time variant parameters. In addition, the ISFM can be applied to the combined routing of the watershed and the channel with a residual watershed.ershed.

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Evaluation of Parameter Characteristics of the Storage Function Model Using the Kinematic Wave Model (운동파모형을 이용한 저류함수법 매개변수의 특성 평가)

  • Choi, Jong-Nam;Ahn, Won-Shik;Kim, Hung-Soo;Park, Min-Kyu
    • Journal of the Korean Society of Hazard Mitigation
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    • v.10 no.4
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    • pp.95-104
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    • 2010
  • The storage function model is one of the most commonly used models for flood forecasting and warning system in Korea. This paper studies the physical significance of the storage function model by comparing it with kinematic wave model. The results showed universal applicability of the storage function model to Korean basins. Through a comparison of the basic equations for the models, the storage function model parameters, K, P and $T_l$, are shown to be related with the kinematic wave model parameters, k and p. The analysis showed that P and p are identical and K and $T_l$ can be related to k, basin area, and coefficients of Hack's law. To apply the storage function model throughout the southern part of Korean peninsular, regional parameter relationships for K and $T_l$ were developed for watershed area using data from 17 watersheds and 101 flood events. These relationships combine the kinematic wave parameters with topographic information using Hack's Law.

Parameter Determination of Rainfall Runoff Model by Storage Function Model (저유함수법에 의한 강우-유출모형의 변수추정)

  • 남궁달
    • Water for future
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    • v.18 no.2
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    • pp.175-185
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    • 1985
  • This paper discusses the posibility of synthesizing flood hudrographs by the stroage function model. Eight small watersheds from Han, Gum, Nakdong, Youngsan river system were selected for this purpose. The optimum constants are computed from the chi square criterion by the SDFP methods Based on these constants, equations for the storage constant and Lag time are derived from the kinematic wave theory and storage function theory. These relations are examined by using optimum constants of the storage function model and assumptive constant of the kinematic wave model. Main results are sumarized as follows. 1. Constants of the storage function model are closely related to those of the kinematic wave model. The formula obtained theoretically is difficult to use practically because of the unclaified definition of factors. 2. In order to estimate constants of the storage function model for the practical purpose, new equations are also proposed for mountaneous area. 3. The verification of proposed equation is made for several recorded floods for mountaeous areas.

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Parameter Optimization of Long and Short Term Runoff Models Using Genetic Algorithm (유전자 알고리즘을 이용한 장·단기 유출모형의 매개변수 최적화)

  • Kim, Sun-Joo;Jee, Yong-Geun;Kim, Phil-Shik
    • Journal of The Korean Society of Agricultural Engineers
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    • v.46 no.5
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    • pp.41-52
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    • 2004
  • In this study, parameters of long and short term runoff model were optimized using genetic algorithm as a basic research for integrated water management in a watershed. In case of Korea where drought and flood occurr frequently, the integrated water management is necessary to minimize possible damage of drought and flood. Modified TANK model was optimized as a long term runoff model and storage-function model was optimized as a short term runoff model. Besides distinguished parameters were applied to modified TANK model for supplementing defect that the model estimates less runoff in the storm period. As a result of application, simulated long and short term runoff results showed 7% and 5% improvement compared with before optimized on the average. In case of modified TANK model using distinguished parameters, the simulated runoff after optimized showed more interrelationship than before optimized. Therefore, modified TANK model can be applied for the long term water balance as an integrated water management in a watershed. In case of storage-function model, simulated runoff in the storm period showed high interrelationship with observed one. These optimized models can be applied for the runoff analysis of watershed.

Parameter Estimation of the Storage Function Model: 1. Development of the Universal Model for the Parameter Estimation (저류함수법의 매개변수 추정: 1. 범용모형 개발)

  • Choi, Jong-Nam;Ahn, Won-Shik; Kim, Hung-Soo;Park, Min-Kyu
    • Journal of the Korean Society of Hazard Mitigation
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    • v.10 no.6
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    • pp.119-130
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    • 2010
  • The universal model for the parameter estimation of the Storage Function Model(SFM) was developed through the applications of the distributed model for various hypothetical watersheds and runoff conditions. The existing parameter estimation equations are based on observations and these equations which are derived from the restricted conditions are not sensitive to the variation of physical characteristics of a watershed. This study developed the universal model for the parameter estimation through the runoff simulations of 35,000 times. As the simulation results, we have known that the lag time is related to the longest stream channel characteristics and the storage coefficient is related to the watershed characteristics.

Parameter Calibration of Storage Function Model and Flood Forecasting (2) Comparative Study on the Flood Forecasting Methods (저류함수모형의 매개변수 보정과 홍수예측 (2) 홍수예측방법의 비교 연구)

  • Kim, Bum Jun;Song, Jae Hyun;Kim, Hung Soo;Hong, Il Pyo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.1B
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    • pp.39-50
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    • 2006
  • The flood control offices of main rivers have used a storage function model to forecast flood stage in Korea and studies of flood forecasting actively have been done even now. On this account, the storage function model, which is used in flood control office, regression models and artificial neural network model are applied into flood forecasting of study watershed in this paper. The result obtained by each method are analyzed for the comparative study. In case of storage function model, this paper uses the representative parameters of the flood control offices and the optimized parameters. Regression coefficients are obtained by regression analysis and neural network is trained by backpropagation algorithm after selecting four events between 1995 to 2001. As a result of this study, it is shown that the optimized parameters are superior to the representative parameters for flood forecasting. The results obtained by multiple, robust, stepwise regression analysis, one of the regression methods, show very good forecasts. Although the artificial neural network model shows less exact results than the regression model, it can be efficient way to produce a good forecasts.

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Comparative Analysis of Parameter Estimation Methods for the Storage Function Model (저류함수모형의 매개변수 산정방법들에 대한 비교 분석)

  • Song JaeHyun;Kim HungSoo;Hong IlPyo;Kim SangUg
    • Proceedings of the Korea Water Resources Association Conference
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    • pp.731-736
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    • 2005
  • 현재 국내 주요 하천의 홍수예경보시스템 운영과 다목적댐의 홍수조절관리를 위하여 수문학적 모형의 하나인 저류함수모형(Storage Function Model)을 사용하고 있다. 저류함수모형은 산지가 많은 유역에 적합하도록 개발된 모형으로, 계산절차가 간편하고 홍수유출의 비선형성을 고려할 수 있는 방법이므로 선형모형보다 합리적이라고 알려져 있다. 그러나 저류함수모형을 실제 홍수유출현상에 적용하는데 있어 매개변수를 결정하는 것이 매우 어렵다. 현재 매개변수들을 결정할 수 있는 객관적이고 합리적인 방법이 제시되어 있지 않기 때문에 모형의 매개변수를 결정할 때 경험식을 이용하거나 수문기술자의 판단에 의한 보정에 의존하고 있다. 따라서, 본 논문에서는 홍수통제소에서 사용하고 있는 저류함수 모형의 대표(평균) 매개변수와 경험식, 시행착오법(trial & error method) 및 최적화기법(optimization technique) 중에 Rosenbrock 방법을 이용하여 매개변수를 산정하고 이들을 비교 분석하고자 한다.

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A Study on the Introduction of Fuzzy Theory to the Adjustment of Time Variant parameter

  • Lee, Jong-Kyu;Lee, Chang-Hae
    • Korean Journal of Hydrosciences
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    • v.8
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    • pp.69-83
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    • 1997
  • The Parameters of the storage function model (SFM) are taken as constants, while they have different values during every rainfall period and the duration of the runoff. Therefore, the results of the SFM generally show remarkably large errors. In this study, the modified storage function model (MSFM), in which the time variant parameters are introduced, is proposed to improve the SFM which is a conceptual rainfall-runoff model. The fuzzy reasoning method is applied as a real-time control one of the time variant parameters of the proposed model. The applicability of the MSFM was examined in the Bochung river, at a tributary of the Geum River, Korea. The pattern of the predicted runoff hydrograph and the peak discharge by the MSFM with fuzzy control are very similar to the measured values, compared with the results produced by the SFM.

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