• 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.

• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.1057-1066
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• 2019

The storage function method is used as a flood prediction model for four flood control offices in Korea as a method to analyze the actual rainfall-runoff relationship with non-linearity. It is essential to accurately estimate the parameters of the storage function method for accurate runoff analysis. However, the parameters of the storage function method currently in use are estimated by the empirical formula developed by the limited hydrological analysis in 2012; therefore, they are somewhat inaccurate. The kinematic wave method is a method based on physical variables of watershed and channel and is widely used for rainfall-runoff analysis. By adopting the two-term storage function method by the conversion of the kinematic wave method, parameters can be estimated based on physical variables, which can increase the accuracy of runoff calculation. In this research, the reproducibility of the kinematic wave method by the two-term storage function method was investigated. It is very easy to estimate the parameters because equivalent roughness, which is an important physical variable in watershed runoff, can be easily obtained by using land use and land cover, and the physical variable of channel runoff can be easily obtained from the basic river planning report or topographic map. In addition, this research examined the applicability of the two-term storage function method to runoff simulation of Naechon Stream, a tributary of the Hongcheon River in the Han River basin. As a result, it is considered that more accurate runoff calculation results could be obtained than the existing one-term storage function method. It is expected that the utilization of the storage function method can be increased because the parameters can be easily estimated using physical variables even in unmeasured watersheds and channels.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.20 no.10
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• pp.702-709
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• 2008

In this paper, the optimal thermal storage time of an air-conditioning system with slab thermal storage in office building was analyzed on the basis of the gradient method algorithm. The sum of room temperature deviation and heat extraction rate was set to the criterion function. It was calculated that four hours is the optimal thermal storage time under the standard evaluation criterion. Furthermore, some case studies were executed by controlling ratio of weight functions of room temperature deviation and heat extraction rate in criterion function. It is possible to design many kinds of optimal operation of an air-conditioning system with slab thermal storage by controlling ratio of the weight functions in criterion function.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.6
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• pp.81-87
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• 2010

In order to calculate the accurate runoff from a basin, nonlinearity in the relationship between rainfall and runoff has to be considered. Many runoff calculation models assume the linearity in the relationship or are too complicated to be analyzed. Therefore, the storage function method has been used in the prediction of flood because of the simplicity of the model. The storage function method has five parameters with related to the basin and rainfall characteristics which can be estimated by the empirical trial and error method. To optimize these parameters, regression method or optimization techniques such as genetic algorithm have been used, however, it is not easy to optimize them because of the complexity of the method. In this study, the metamodel is proposed to estimate those model parameters. The metamodel is the combination of artificial neural network and genetic algorithm. The model is consisted of two stages. In the first stage, an artificial neural network is constructed using the given rainfall-runoff relationship. In the second stage, the parameters of the storage function method are estimated using genetic algorithm and the trained artificial neural network. The proposed metamodel is applied in the Peong Chang River basin and the results are presented.

• Journal of Korean Society of Forest Science
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• v.98 no.3
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• pp.272-278
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• 2009

This study was conducted to develope calculation method of standard rainfall, which was used for predicting the outbreaking time of disaster by using Tank model, on warning and evacuation for soil sediment disaster. We investigate adeption possibility of developed method through comparing storage function method with Tank model. We calculated storage amount rainfall by storage function method and Tank model with 36 hillslope failures which have record on outbreaking time of disaster. The result in case of Sedimentary (quarternary period) showed that the difference of outbreaking time was 1.6 hour in case of tank model, but 3.2 hour in case of storage function method. In addition, the deviation of the peak storage were 7% in case of tank model, but 63% in case of storage function method. Total evacuation period was analyzed by using observed 5 years (1993-1997) rainfall data as well as each standard rainfalls which were determinated by two methods. The result showed that evacuation time by storage function method was about twice as many as that by tank model. Therefore, we concluded that calculation by tank model for predicting the outbreaking time of disaster was more useful and accurate than storage function method.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.24-27
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• 1996

The storage function method(SFM) is one of hydrologic flood routings which has been used most widely in Korea and Japan. This paper presents a storage function method using multiple model adaptive estimation(MMAE), in which a model set is generated by partitioning storage parameters over feasible range, and each storage function model is estimated, and then the weighted average of them is calculated. Finally, the future runoff is predicted in real time by means of observed data of water level at dam and rainfall. Simulation results applied to actual data show that the proposed method has much better performance than that of conventional SFM.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.449-453
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• 2007

Has been being operated since 1974, recently, the flood forecasting and warning system is applied in almost all the rivers in Korea, and the Storage Function Method(SFM) is used for flood routing. The SFM which was presented by Toshimitsu Kimura(1961) routes floods in channels and basins with the storage function as the basic equation. A watershed is devided into two zone, runoff and percolation area and Runoff is occured when cumulated rainfall is not exceed saturation rainfall, but exceed, runoff is occured from percolation area, too. Runoff area is given and not changed, runoff ratio is constant. In routing process, runoff from runoff and percolation area is routed seperately with nonlinear cenceptual reservior having same characteristics and it is unreasonable assumption. Modified SFM is proposed with storage function and continuity Equation which has no assumption for routing process and effective rainfall is calculated by SCS Method. For Wi Stream, comparision of Kimura and Modified SFM is conducted and It could be seen that Modified SFM is more improvemental and easily applicable method.

• Journal of Korea Water Resources Association
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• v.40 no.7
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• pp.523-532
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• 2007

It has been operated since 1974, recently, the flood forecasting and warning system is applied in almost all the rivers in Korea, and the Storage Function Method (SFM) is used for flood routing. The SFM which was presented by Toshimitsu Kimura (1961) routes floods in channels and basins with the storage function as the basic equation. A watershed is divided into two zone, runoff and percolation area and runoff from runoff area is occurred when cumulated rainfall is not exceed saturation point, but exceed runoff is occurred from percolation area, too. Runoff area is given and not changed, runoff ratio is constant. In routing Process, runoff from runoff and percolation area is routed seperately with nonlinear conceptual reservoir having the same characteristics and it is unreasonable assumption. A modified SFM is proposed with storage function and continuity equation which has no assumption for routing process and effective rainfall is calculated by SCS Method. For Wi-stream, comparison of Kimura and the modified SFM is conducted, and it could be seen that the modified SFM is more improvable and applicable method easily by reducing the parameters.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.5
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• pp.125-130
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• 2009

Storage function method which considers the non-linearity of the relationship between rainfall and runoff has been frequently used to predict runoff in a basin and a flood pattern. However, it is time-consuming to estimate appropriate parameters of every basin and rainfall event, which requires the empirical parameter equation applicable in Korea. In this study, multiple regression analysis is used to develop empirical equations to estimate parameters of Storage Function method using basin characteristics. The basin area, maximum stream length, and stream slope are considered as the basin characteristics as the result of the regression analysis. Collinearity is removed and trial-and-error method is used to choose the most descriptive parameters to the dependent variables in Han River basin which is divided into 30 subbasins. The developed equations are validated using the rainfall events in MunMak gauging station and named as 'Han River equation'. The equation could provide the useful information about Storage Function method parameter to calculate runoff from a basin and predict river stage.

• Journal of Korea Water Resources Association
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• v.46 no.1
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• pp.73-85
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• 2013

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.