• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.3
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• pp.165-174
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• 2011

The purpose of this research is to develop the model for analyzing the hydraulic behavior of off-stream reservoir whose purpose is to reduce a peak flood. When a flood occurs in river, off-stream reservoir has a capability of sharing a part of peak flood. It is accomplished by flowing over a off-line weir that is built by lowering a portion of bank and connecting river with off-line reservoir. Since flood control depends on river elevation, characteristics of off-line weir (elevation, length, position et al.) and reservoir capacities, an integrated model linking the one dimensional unsteady river flow model, off-line weir model and two dimensional unsteady flood model is developed to analyze the behavior of off-stream reservoir and off-line weir. The results show that a flood control capability of off-stream reservoir strongly depends on facilities of off-line weir and storage capacity of offstream reservoir.

• Journal of Korean Society on Water Environment
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• v.24 no.5
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• pp.581-591
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• 2008

Most of our rivers are fragmented by the presence of at least one large dam. Dams are often the most substantial controller of the flow regimes and aquatic environments of natural river system. The quality of downstream water released from a stratified reservoir is highly dependent on upstream reservoir water quality. Thus, an integrated modeling approach is more efficient, compared to fragmented modeling approach, and necessary to better interpret the impact of dam operation on the down stream water quality. The objectives of this study were to develop an integrated reservoir-river modeling system for Daecheong Reservoir and its downstream using a two-dimensional laterally averaged hydrodynamic and water quality model, and evaluate the model's performance against field measurement data. The integrated model was calibrated and verified using filed data obtained in 2004 and 2006. The model showed satisfactory performance in predicting temporal variations of water stage, temperature, and suspended solid concentration. In addition, the reservoir-river model showed efficient computation time as it took only 3 hours for one year simulation using personal computer (1.88 Ghz, 1.00 GB RAM). The suggested modeling system can be effectively used for assisting integrated management of reservoir and river water quality.

• Journal of Korean Society on Water Environment
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• v.27 no.5
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• pp.710-718
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• 2011

An integrated water quality management of reservoir and river would be required when the quality of downstream river water is affected by the discharge of upstream dam. In particular, for the control of downstream turbidity during flood events, the integrated modeling of reservoir and river is effective approach. This work was aimed to develop a laterally-averaged two-dimensional hydrodynamic and water quality model (CE-QUAL-W2), by which water quality can be predicted in the downstream of Yongdam dam in conjunction with the reservoir model, and to validate the model under two different hydrological conditions; wet year (2005) and drought year (2010). The model results clearly showed that the simulated data regarding water elevation and suspended solid (SS) concentration are well corresponded with the measured data. In addition, the variation of SS concentration as a function of time was effectively simulated along the river stations with the developed model. Consequently, the developed model can be effectively applied for the integrated water quality management of Yongdam dam and downstream river.

• Magazine of the Korean Society of Agricultural Engineers
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• v.39 no.2
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• pp.1-8
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• 1997

Abstract The need for integrated reservoir system operation become more intense as the demands from the system increase. A deterministic, three-dimensional discrete incremental dynamic programming approach is presented to derive reservoirs system operational planning strategies. The developed H3DP model optimizes the monthly operation of the Hwachon and Soyang Projects on the North Han river and Chungju Main Project on the South Han river. By using the H3DP model, Hwachon project was reevaluated as a component of the upstream multipurpose storage reservoirs in the basin based on 1993 hydrology. This case study demonstrates the practical use of the developed model for the basin multi-reservoir system operation in an integrated, multipurpose fashion.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.975-985
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• 2013

In this research, the integrated modeling system by coupling of a watershed model, a reservoir model, and a river model has been constructed in Doam reservoir watershed. Because of domestic climate characteristics, it is inevitable to construct the dam for control of flood, water use, and power production due to the heavy rain in the summer. Especially, when the dam is constructed on the stream for these kinds of purpose, it is necessary to consider this region as one watershed and also to make the integrated system for simulation and management. In this study, SWAT model was constructed for watershed modeling and EFDC-WASP model was constructed for simulating the hydrodynamic and water quality of the reservoir and the downstream in Doam dam watershed. Also, the water quality improvement equipment for demonstration was applied in the upstream part of Doam reservoir, which shows the applicability of the developed integrated modeling system.

• Water Engineering Research
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• v.3 no.2
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• pp.143-153
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• 2002

As the natural flows in rivers dramatically decrease during drought season in Korea, a deterioration of river water quality is accelerated. Thus, consideration of downstream water quality responding to changes in reservoir release is essential for an integrated watershed management with regards to water quantity and quality. In this study, water quality models based on artificial neural networks (ANNs) method were developed using historical downstream water quality (rm $\NH_3$-N) data obtained from a water treatment plant in Geum river and reservoir release data from Daechung dam. A nonlinear multiple regression model was developed and compared with the ANN models. In the models, the rm NH$_3$-N concentration for next time step is dependent on dam outflow, river water quality data such as pH, alkalinity, temperature, and rm $\NH_3$-N of previous time step. The model parameters were estimated using monthly data from Jan. 1993 to Dec. 1998, then another set of monthly data between Jan. 1999 and Dec. 2000 were used for verification. The predictive performance of the models was evaluated by comparing the statistical characteristics of predicted data with those of observed data. According to the results, the ANN models showed a better performance than the regression model in the applied cases.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.1184-1188
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• 2005

The impacts of turbidity flow induced by summer rainfall events on water supply, aquatic ecosystems, and socioeconomics are significant and major concerns in most of reservoirs operations. As a decision support tool, the real-time turbidity flow monitoring and modeling system RTMMS is under development using a laterally integrated two-dimensional (2D) hydrodynamic and water quality model. The objectives of this paper is to present the preliminary field observation results on the characteristics of rainfall-induced turbidity flows and their density flow regimes, and the model performance in replicating the fate and transport of turbidity plume in a reservoir. The rainfall-induced turbidity flows caused significant drop of river water temperature by 5 to $10^{\circ}C$ and resulted in density differences of 1.2 to $2.6kg/m^3$ between inflow water and ambient reservoir water, which consequently led development of density flows such as plunge flow and interflow in the reservoir. The 2D model was set up for the reservoir. and applied to simulate the temperature stratification, density flow regimes, and temporal and spatial turbidity distributions during flood season of 2004 After intensive refinements on grid resolutions , the model showed efficient and satisfactory performance in simulating the observed reservoir thermal stratification and turbidity profiles that all are essentially required to enhance the performance of RTMMS.

• 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.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.3_4
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• pp.48-60
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• 1995

A flood - flow forecasting system model of river basins has been developed in this study. The system model consists of the data management system(the observation and telemetering system, the rainfall forecasting and data-bank system), the flood runoff simulation system, the reservoir operation simulation system, the flood forecasting simulation system, the flood warning system and the user's menu system. The Multivariate Rainfall Forecasting model, Meteorological factor regression model and Zone expected rainfall model for rainfall forecasting and the Streamflow synthesis and reservoir regulation(SSARR) model for flood runoff simulation have been adopted for the development of a new system model for flood - flow forecasting. These models are calibrated to determine the optimal parameters on the basis of observed rainfall, 7 streamfiow and other hydrological data during the past flood periods.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.354-359
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• 2006

The analysis of large-scale water resources systems is often complicated by the presence of multiple reservoirs and diversions, the uncertainty of unregulated inflows and demands, and conflicting objectives. Reinforcement learning is presented herein as a new approach to solving the challenging problem of stochastic optimization of multi-reservoir systems. The Q-Learning method, one of the reinforcement learning algorithms, is used for generating integrated monthly operation rules for the Keum River basin in Korea. The Q-Learning model is evaluated by comparing with implicit stochastic dynamic programming and sampling stochastic dynamic programming approaches. Evaluation of the stochastic basin-wide operational models considered several options relating to the choice of hydrologic state and discount factors as well as various stochastic dynamic programming models. The performance of Q-Learning model outperforms the other models in handling of uncertainty of inflows.