• Water for future
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• v.23 no.4
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• pp.499-507
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• 1990

Real-time reservoir operation models during flood period require optimization of hourly releases from the input data through on-line system. And predicted values. An algorithm of the simulation model to resolve the problem has already been reported with formulation of objectives to minimize the flood damage in downstream reaches and to conserve water at the end of operation for the later use. This paper presents an application of the model to a single reservoir system at the Daecheong Dam during flood and the results are reviewed. This paper also reviews measured inflows and releases in the past. The model is applied to the flood hydrographs of several return periods assuming different reservoir levels at the beginning of the operation. Also it demonstrates the simulation of test run with inflow forecasts obtained by rainfall-runoff model and compares the results. As a result, the model can use efficiently the flood control capacity with consideration of risk factor for the uncertainties associated with inflow forecasts.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.5
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• pp.1039-1049
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• 2015

The inflow estimation at large multipurpose dam reservoir is carried out by considering the water balance among the discharge, the storage change during unit time interval obtained from the observed water level near dam structure and area-volume curve. This method can be ideal for level pool reservoir but include potential errors when the inflow is influenced by the water level slope due to backwater effects from upstream flood inflows and strong wind induced by typhoon. In addition, the other uncertainties arisen from the storage reduction due to sedimentation after the dam construction and water level noise due to mechanical vibration transmitted from the electric power generator. These uncertainties impedes the accurate hydraulic inflow measurement requiring exquisite hydrometric data arrangement for reservoir waterbody. In this study, the distributed hydrologic model using UBC-3P boundary setting was applied and its feasibility was evaluated. Finally, the modeling performance has been verified since the calculated determination coefficient has been in between 0.96 to 0.99 after comparing with observed peak inflow and total inflow at Namgang dam reservoir.

• Water for future
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• v.26 no.2
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• pp.89-97
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• 1993

For the system benefit optimization by considering risk or reliability from a multiple reservoir system using the Monte Carlo technique, many stochastically generated inflow series have to be used for the system analysis. In this study, the stochastically generated inflow series for the multiple reservoir system operation are preprocessed according to the considered system objectives and operating time periods. Through this procedure, several representative inflow series which have discrete probability levels and operation horizons are selected among the thousands of generated inflows. Then a deterministic optimization technique is applied to the power energy estimation from the Han River Reservoirs System which considers five reservoirs in the study. It took much lower computational requirements then using the original Monte Carlo Technique, even though estimated result was almost similar.

• Proceedings of the Korea Water Resources Association Conference
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• 1992.07a
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• pp.411-418
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• 1992

The purpose of this study is to develop dynamic-stochastic models that can forecast the inflow into reservoir during low/drought periods and flood periods. For the formulation of the models, the discrete transfer function is utilized to construct the deterministic characteristics, and the ARIMA model is utilized to construct the stochastic characteristics of residuals. The stochastic variations and structures of time series on hydrological data are examined by employing the auto/cross covariance function and auto/cross correlation function. Also, general modeling processes and forecasting method are used the model building methods of Box and Jenkins. For the verifications and applications of the developed models, the Chungju multi-purpose reservoir which is located in the South Han river systems is selected. Input data required are the current and past reservoir inflow and Yungchun water levels. In order to transform the water level at Yungchon into streamflows, the water level-streamflows rating curves at low/drought periods and flood periods are estimated. The models are calibrated with the flood periods of 1988 and 1989 and hourly data for 1990 flood are analyzed. Also, for the low/drought periods, daily data of 1988 and 1989 are calibrated, and daily data for 1989 are analyzed.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.167-167
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• 2020

Annual sediment deposition in reservoirs behind weirs poses flood risk, while its accurate prediction remains a challenge. Sediment management by hydraulic flushing is an effective method to maintain reservoir storage. In this study, an integrated approach to predict sediment inflow and sediment flushing simulation in reservoirs is presented. The annual sediment inflow prediction was carried out with Artificial Neural Networks (ANN) modelling. RESCON model was applied for quantification of sediment flushing feasibility criteria. The integrated approach was applied on Sangju Weir and also on estuary of Nakdong River (NREB). The mean annual sediment inflow predicted at Sangju Weir and NREB was 400,000 ㎥ and 170,000 ㎥, respectively. The sediment characteristics gathered were used to setup RESCON model and sediment balance ratio (SBR) and long term capacity ratio (LTCR) were used as flushing efficiency indicators. For Sangju Weir, the flushing discharge, Q_f = 140 ㎥/s with a drawdown of 5 m, and flushing duration, T_f = 10 days was necessary for efficient flushing. At NREB site, the parameters for efficient flushing were Q_f = 80 ㎥/s, T_f = 5 days, N = 1, El_f = 2.24 m. The hydraulic flushing was concluded feasible for sediment management at both Sangju Weir and NREB.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.512-518
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• 1999

Recently rainfall and water evel are monitored via on -line system in real-time bases. We applied the on-line system to get the rainfall and waterlevel data for the development of the real-time flood forecasting model based on SCS method in hourly bases. Main parameters for the model calibration are concentration time of flood and soil moisture condition in the watershed. Other parameters of the model are based on SCS TR-%% and DAWAST model. Simplex method is used for promoting the accuracy of parameter estimation. The basic concept of the model is minimizing the error range between forcasted flood inflow and actual flood inflow, and accurately forecasting the flood discharge some hours in advance depending on the concentration time. The flood forecasting model developed was applied to the Yedang and Topjung reservoir.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.2
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• pp.141-149
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• 1993

Production of hydro-energy is random in its output amount due to the characteristics of the reservoir inflows. Therefore, it is necessary to provide the rationality in determining the amount of energy for a supply contract. This study presents a methodology for determining reasonably reliable amount of the energy supply considering the energy sale-incomes associated with the penalties which are subject to inflow-reliabilities. The objective function consists of the returns of energy sales and the risk-loss function to reflect statistically relevant risks. A range of the coefficient of the risk-loss function was figured out by its sensitivity analysis. The risk-loss herein means the penalty which should be paid by the energy supplier in case that the level of the energy supply is behind the contracted amount. And the reliability of reservoir inflow is defined by the exceedance probability of the inflow. The log-normal distribution was accepted as the probability density function of monthly inflows on the level of significance at 5%. Golden-ratio searching was applied to identify the optimal reliability and Incremental Dynamic Programming was used to maximize generation of the hydro-power energy in reservoir operation. The algorithm was the applied to the Daechung multi-purpose reservoir and hydro-power plant system in order to verify its usefulness.

• Journal of Korea Water Resources Association
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• v.31 no.1
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• pp.45-57
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• 1998

The purpose of this paper is to develop a neural network model in order to forecast flood inflow into the reservoir that has the nature of uncertainty and nonlinearity. The model has the features of multi-layered structure and parallel multi-connections. To develop the model. backpropagation learning algorithm was used with the Momentum and Levenberg-Marquardt techniques. The former technique uses gradient descent method and the later uses gradient descent and Gauss-Newton method respectively to solve the problems of local minima and for the speed of convergency. Used data for learning are continuous fixed real values of input as well as output to emulate the real physical aspects. after learning process. a reservoir inflows forecasting model at flood period was constructed. The data for learning were used to calibrate the developed model and the results were very satisfactory. applicability of the model to the Chungju Mlultipurpose Reservoir proved the availability of the developed model.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.495-498
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• 2003

In order to analyze water supply capacity in estuary barrage dam, a system was developed in which base model was consisted of daily water balance model and daily inflow model. Agricultural water demand to paddy fields and domestic and industrial water demand were considered in this daily water balance model. Also outflow volume through sluice gate and inside water level at time to start outflow was conditioned initially to simulate reservoir storage. The DAWAST model was selected to simulate daily reservoir inflow in which return flows from agricultural, domestic and industrial water were included to simulate runoff. Using this developed system, water supply capacity in the Keum river estuary reservoir was analyzed.

• Korean Journal of Veterinary Service
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• v.15 no.2
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• pp.203-214
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• 1992

Livestock waste causes ground and surface water pollution, eutrophication of reservoir as well as adverse affects living environment of those who dwell nearby. In order to investigate the pollution load from livestock waste, physical and chemical characteristics of the waste were determinded in the survey of livestock farms. Once pollution load is obtained as a function of the origin units of livestock, the influence of livestock waste on the Daecheong reservoir was studied. 1. For Daecheong reservoir inflow area, the liverstock manure productions of beef cattle swine, dairy cattle and chicken were 1,135.6t/day, 480t/day, 241.3t/day, 48t/day respectively； Beef cattle was the mai or source of the pollution. Pollution loading productions due to the livestock waste around the were found to be 53.31t/day for BOD, 222.49t /day for COD, 261.99t/day for T-S, 9.64t/day for T-N, 6.54t/day for T-P 2. Bocheong stream turnd out to be the major contribution for pollution loading production to Daecheong reservoir with 10,748kg /day of BOD, 47,157kg /day of COD, 1,946kg /day of T-N, 1,271kg /day of T-p. 3. Actual pollution loadings from livestock wastes for the area of Daecheong reservoir were estimated as 1,997kg /day(BOD), 8,546kg /day(COD), 364kg /day(T-N), 243kg /day (T-P), respectively Therefore, advanced treatment for livestock waste is recommended for Daectleong reservoir inflow area to eliminate the nutrients which are major sources of eutrophication of the reservoir.