• Journal of Korean Society on Water Environment
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• v.23 no.6
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• pp.934-944
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• 2007

Fine suspended solids (SS) induced into a reservoir after flood events play important ecological and water quality roles by presenting persistent turbidity and attenuating light. Thus the origin and physical features must be characterized to understand their transport processes and associated impacts, and for the establishment of watershed based prevention strategies. This study was aimed to characterize the physical properties of the SS sampled from Daecheong Reservoir and its upstream rivers during flood events. Extensive field and laboratory experiments were carried out to identify the turbidity-SS relationships, particle size distributions, settling velocity, and mineral compositions of the SS. Results showed that the turbidity-SS relationships are site-specific depending on the locations and flood events in the system. The turbidity measured within the reservoir was much greater than that measured in the upstream rivers for the same SS value. The effective diameters ($D_{50}$) in the rivers were in the range of $13.3{\sim}54.3{\mu}m$, while those in the reservoir were reduced to $2.5{\sim}14.0{\mu}m$ due to a fast settling of large particles in the rivers. The major minerals consisting of the SS were found to be Illite, Muscovite, Albite, and Quartz both in the rivers and reservoir. Their apparent settling velocities at various locations in the reservoir were in the range of 0.06~0.13 m/day. The research outcome provides a fundamental information for the fine suspended particles that cause persistent turbidity in the reservoir, and can be used as basic parameters for modeling study to search watershed based optimal control measures.

• Korean Journal of Ecology and Environment
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• v.42 no.4
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• pp.441-451
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• 2009

The major objectives of this study were to evaluate trophic state of reservoirs using major water quality variables and its relations in terms of trophic guilds and tolerance guilds with dominant lentic fishes. For this study, we selected 6 artificial reservoirs such as Namyang Reservoir ($N_yR$), Youngsan Reservoir ($Y_sR$), Daechung Reservoir ($D_cR$), Chungju Reservoir ($Cj_R$), Chungpyung Reservoir ($C_pR$), and Paldang Reservoir ($P_dR$), and collected fish during 2000~2007 along with data analysis of water quality monitored by the ministry of environment, Korea. Biological oxygen demand (BOD) and chemical oxygen demand (COD), indicators of organic matter pollution, varied depending on types of the reservoirs and the spatial patterns in terms of trophic gradients were similar to patterns of nutrients, Secchi depth and chlorophyll-a. Analysis of trophic state index (TSI) showed that reservoirs of $D_cR$ and $C_jR$ were mesotrophy and other 4 reservoirs were eutrophic state. The relations of trophic relations showedthat TSI (Chl-a) had a positive linear function [TSI (CHL)=0.407 TSI (TP)+28.2, n=138, p<0.05] with TSI (TP) but had a weak relation with TSI (TN). Also, TSI (TP) were negatively correlated ($R^2=0.703$, p<0.05) with TSI (SD), whereas TSI (TN) was not significant (p>0.05) relations with TSI (SD). Tolerance guilds of lentic fishes, based on three types of the reservoirs, reflected the exactly water quality in the TN, TP, BOD, and COD, and similar trends were shown in the fish feeding/trophic guilds.

• Water for future
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• v.28 no.6
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• pp.217-228
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• 1995

For optimal reservoir operation during flood period, a general and systematic policy is suggested to make balance of the conflicting purposes between water conservation and flood control. The purpose of this study is to decide the restricted water level of the reservoir during flood period specially to meet water demand in non-flood period. The optimal policy is derived by reallocation of storage capacity through the application of variable restricted water level(VRWL) and minimum required water level(MRWL) for shorter intervals. This study also suggests water level dconditions to secure conservation storage capacity at the end of the flood period estimated by reservoir operation study. This paper illustrates an application of the Daecheong Dam and Chungju Dam respectively during flood and the results are reviewed.

• Water for future
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• v.25 no.1
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• pp.75-82
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• 1992

This paper presents a methodology of developing reservoir operating rules which can consider the reliability levels incorporated with the discharge policy. The operating rules were derived based on the regression and risk analysis of the optimally operated results by using the long term historical and generated reservoir inflows. The methodology was applied to the operation of the Chungju reservoir system which is consisted of two reservoirs and powerplants, and monthly operation rules were developed. Simulations were performed by using the developed operating rules can not only significantly improve the output from the existing system but also improve the reliability incorporated with the output.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.3
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• pp.97-110
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• 2017

This study investigates the efficiencies of machine learning models, including artificial neural network (ANN), generalized regression neural network (GRNN), adaptive neuro-fuzzy inference system (ANFIS) and random forest (RF), for reservoir water level forecasting in the Chungju Dam, South Korea. The models' efficiencies are assessed based on model efficiency indices and graphical comparison. The forecasting results of the models are dependent on lead times and the combination of input variables. For lead time t = 1 day, ANFIS1 and ANN6 models yield superior forecasting results to RF6 and GRNN6 models. For lead time t = 5 days, ANN1 and RF6 models produce better forecasting results than ANFIS1 and GRNN3 models. For lead time t = 10 days, ANN3 and RF1 models perform better than ANFIS3 and GRNN3 models. It is found that ANN model yields the best performance for all lead times, in terms of model efficiency and graphical comparison. These results indicate that the optimal combination of input variables and forecasting models depending on lead times should be applied in reservoir water level forecasting, instead of the single combination of input variables and forecasting models for all lead times.

• Journal of Korea Water Resources Association
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• v.44 no.5
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• pp.407-416
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• 2011

This study expressed the reservoir's storage-discharge relation as a non-linear reservoir model and theoretically quantified the reservoir storage effect. Among those non-linear functions like exponential function, logarithmic function and power function considered, the exponential function of the storage-discharge relation was found to be the most valid. The non-linear reservoir model proposed was applied to the Chungju Dam and the Soyang River Dam, whose storage effects during flood were estimated to be about 23 hours and 43 hours, respectively. This result indicates that the Choongju Dam, even though its size and total storage volume are similar to those of the Soyang River Dam, does not achieve enough storage effect as its basin size and the inflow amount are much larger.

• Journal of the Korean Chemical Society
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• v.49 no.1
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• pp.78-82
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• 2005

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.857-871
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• 2013

The interest in rainfall observation and forecasting using remote sensing method like RADAR (Radio Detection and Ranging) and satellite image is increased according to increased damage by rapid weather change like regional torrential rain and flash flood. In this study, the basin runoff was calculated using adaptive neuro-fuzzy technique, one of the data driven model and MAPLE (McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation) forecasted precipitation data as one of the input variables. The flood estimation method using neuro-fuzzy technique and RADAR forecasted precipitation data was evaluated. Six rainfall events occurred at flood season in 2010 and 2011 in Chungju Reservoir basin were used for the input data. The flood estimation results according to the rainfall data used as training, checking and testing data in the model setup process were compared. The 15 models were composed of combination of the input variables and the results according to change of clustering methods were compared and analysed. From this study was that using the relatively larger clustering radius and the biggest flood ever happened for training data showed the better flood estimation. The model using MAPLE forecasted precipitation data showed relatively better result at inflow estimation Chungju Reservoir.

• Journal of Korea Water Resources Association
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• v.30 no.3
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• pp.269-278
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• 1997

Operating rules, the basic principle of reservoir operation, are mostly developed from maximum or minimum, mean inflow series so that those rules cannot be used in practical operating situations to estimate the expected benefits or provide the operating policies for uncertainty conditions. Many operating rules based on the deterministic method that considers all operation variables including inflows as known variables can not reflect to uncertainties of inflow variations. Explicit operating rules can be developed for improving the weakness. In this method, stochastic trend of inflow series, one of the reservoir operation variables, can be directly method, the stochastic technique was applied to develop reservoir operating rule. In this study, stochastic dynamic programming using the concepts was applied to develop optimal operating rule for the Chungju reservoir system. The developed operating rules are regarded as a practical usage because the operating policy is following up the basic concept of Lag-1 Markov except for flood season. This method can provide reservoir operating rule using the previous stage's inflow and the current stage's beginning storage when the current stage's inflow cannot be predicted properly.

• Korean Journal of Hydrosciences
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• v.10
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• pp.35-46
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• 1999

An integrated system of GIS and water quality model was suggested including the pollutant loads from the watershed. The developed system consits of two parts. First part is the information on landuse and several surface factors concerning the overland flow processes of water and pollutants. Second part is the modeling modules which include storm event pollutant load model(SEPLM), non-storm event pollutant load model(NSPLM), and river water quality simulation model(RWQSM). Models can calculate the pollutant load from the study area. The databases and models are linked through the interface modules resided in the overall system, which incorporate the graphical display modules and the operating scheme for the optimal use of the system. The developed system was applied to the Chungju multi-purpose reservoir to estimate the pollutant load during the four selected rainfall events between 1991 and 1993, based upon monthly basis and seasonal basis in drought flow, low flow, normal flow and wet flow.