• Journal of Korea Water Resources Association
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• v.30 no.4
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• pp.401-409
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• 1997

This study aims to predict the bed elevation change of river and reservoir by compound water model, two-dimensional jet model and one-dimensional density current model, assuming that the river has a single channel and the reservoir has multiple channels. In numerical model, discharge and water level changes is obtained by flow continuity equation and flow momentum equation through double-sweep method, and then applied to sediment continuity equation to predict the scour and deposit of channel bed. The span ranged from the Bosung Dam to Mundueok Bridge at the upstream of Juam Dam, which is approximately 31km long (13km of river and 18km of reservoir), is taken as survey area.

• Korean Journal of Ecology and Environment
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• v.36 no.4 s.105
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• pp.403-412
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• 2003

Temporal and spatial variations of size-structured phytoplankton (chlorophyll a) were investigated over an annual cycle (February-October, 2003) to elucidate phytoplankton dynamics in the Juam Reservoir, Chonnam. Physical properties were also measured to investigate the relationship between the properties and temporal and spatial variations of size structured phytoplankton using simple linear regression. Phytoplankton (chlorophyll a) were grouped into three size classes: micro-size(> 20 ${\mu}m$), nano-size (3-20 ${\mu}m$) and pico-size (< 3 ${\mu}m$) in this study. Physical properties included water temperature, light attenuation coefficients, PAR (photosynthetically active radiation) and turbidity. Maximum chlorophyll a was observed in April, 2003 in the lower region whereas a peak of chlorophyll a developed in October, 2003 in the upper region. Large cell-sized phytoplankton (micro-size class)were dominant in the events of the chlorophyll a peaks. Potential mechanisms in the physical properties affecting the size-structured phytoplankton dynamics in the Juam Reservoir were discussed.

• Journal of Environmental Science International
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• v.18 no.3
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• pp.309-314
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• 2009

A accurate reservoir inflow is very important as providing information for decision making about the water balance and the flood control, as well as for dam safety. The methods to calculate the inflow were divided by the directed method to measure streamflow from upstream reservoirs and the indirected method to estimate using the correlation of reservoir water level and release. Currently, the inflow of multi-purpose dam is being calculated by the indirect method and the reservoir water level to calculate the storage capacity is being used by centimeters(cm) units. Corresponding to the storage volume of 1cm according to scale and water level of multi-purpose dam comes up to from several 10 thousand tons to several million tons. If it converts to inflow during 1 hour, and it comes to several hundred $m^3/sec$(CMS). Therefore, the inflow calculated on the hourly is largely deviated along the water level changes and is occurred minus value as the case. In this research, the water level gage has been developed so that it can measure a accurate water level for the improvement for the error and derivation of inflow, even though there might be various hydrology and meteorologic considerations to analyse the water balance of reservoir. Also, it is confirmed that the error and the standard derivation of data observed by the new gage is decreased by 89,6% and 1/3 & 87% and 2/3 compared to that observed by the existing gage of Daecheong and Juam multi-purpose dam.

• Journal of Soil and Groundwater Environment
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• v.10 no.1
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• pp.43-57
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• 2005

Twelve bottom sediments and three cores were collected in Juam reservoir for a study on transportation, which was controlled by particle grain size (2mm-200{\mu}m,\;200-100{\mu}m,\;100-50{\mu}m,\;50-20{\mu}m,\;<20{\mu}m), and vertical distribution of heavy metals. Sediment cores were sliced into 2 to 5 cm intervals to measure heavy metal concentrations in interstitial water and sediments with depth. Pb isotopic compositions of core samples were determined to calculate sedimentation rate. Regardless of sampling sites, levels of heavy metals and trace elements in bottom sediments are nearly constant with mean values of $14.9\;{\mu}g/g\;for\;As,\;0.81{\mu}g/g\;for\;Cd,\;30.7{\mu}g/g\;for\;Cu,\;34.7{\mu}g/g\;for\;Ni,\;63.3{\mu}g/g\;for\;Pb\;and\;87.9{\mu}g/g\;for\;Zn$. In general, Cu, Pb, Zn, Wi, and Cr in fraction of $<20{\mu}m$ exhibit the highest concentration, but content of As is the highest in grain size of $2\;mm-200\;{\mu}m$ and $200-100\;{\mu}m$. Fe and Mn occur as the dissolved compositions of the highest concentrations in interstitial waters and increase in their concentrations toward lower part of cores. On the contrary, concentrations of Zn and Cu show the highest value in the uppermost part in cores, suggesting these elements are released from reductive dissolution of hydroxides and oxidation of organic matters under different redox conditions. The highest accumulations of Cu, Ni, Pb, and Zn contents in the sediment cores are observed at 0-4 cm layers, and concentrations of Cu and Pb are especially high, implying these heavy metals are originated from anthropogenic sources. The apparent sedimentation rate estimated using unsupported $^{210}Pb$ is 0.91 cm $year^{-1}$, corresponding about 10 cm sedimentation in total depth since construction of Juam dam. These results will provide available information for management of bottom sediment in Juam reservoir.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.3
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• pp.90-96
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• 2018

This paper proposed data driven techniques to forecast the time point of water management of the water reservoir without measuring manganese concentration with the empirical data as Juam Dam of years of 2015 and 2016. When the manganese concentration near the surface of water goes over the criteria of 0.3mg/l, the water management should be taken. But, it is economically inefficient to measure manganese concentration frequently and regularly. The water turnover by the difference of water temperature make manganese on the floor of water reservoir rise up to surface and increase the manganese concentration near the surface. Manganese concentration and water temperature from the surface to depth of 20m by 5m have been time plotted and exploratory analyzed to show that the water turnover could be used instead of measuring manganese concentration to know the time point of water management. Two models for forecasting the time point of water turnover were proposed and compared as follow: The regression model of CR20, the consistency ratio of water temperature, between the surface and the depth of 20m on the lagged variables of CR20 and the first lag variable of max temperature. And, the Box-Jenkins model of CR20 as ARIMA (2, 1, 2).

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2003.11a
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• pp.267-268
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• 2003

대기중으로 방출된 오염물질은 기상조건에 따라 다른 지역으로 이동하여 침적하는 메커니즘을 가지고 있는데, 이의 규명을 위하여 주암호 유역을 대상으로 건성침강하는 대기오염물질의 양과 이들에 의한 수질의 오염기여도 및 발생원에 대한 추적을 본 연구에서 시도하였다. 전라남도 송광면에 위치하고 있는 주암호는 홍수의 조절 및 억제와 수자원의 안정적인 공급을 위하여, 1984년도에 만들어졌으며, 현재 광주 및 전남의 식수 및 생활용수를 공급하는 중요 상수원일 뿐 만 아니라 광양제철 등의 여천산업단지의 공업용수를 공급하고 있는데 최근 수자원의 고갈이 심각하여 대두되고 있는 현시점에서 주암호에 대한 중요성 및 의존도는 더욱 증대되었다. (중략)

• Journal of Environmental Science International
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• v.19 no.1
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• pp.39-45
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• 2010

When the Juam multipurpose dam which is connected with existing large water supply facilities is finished, water environment is changed from stream to lake. The changed quality of water should be examined. In this study, the result of water quality forecasting is analysed and an effective management plan of water quality is presented. Tn this study, the WASPS model that is a dynamic water quality simulation model was selected to forecast the water quality. This model forecasts movement of change of pollutants. For an application of the model, the subject areas were divided into seventeen sub-areas by considering change temperature depending measuring points and on depth of water. Meteorological data collected by the meteorological observatory and data about quality measured by the Korea Water Resources Development Corporation were used for an operation of the model. As a result of quality examination through quality data and estimated pollutant loading, the water quality environment criterion was grade II and the nutritive condition was measured as meso-graphic grade. In this study, an effective management was planned to improve water quality by reducing pollution load. According to the result of examination, when more than 30% of BOD was reduced it was recorded that the environment standard of water quality was improved to the second grade.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.246-246
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• 2023

Multi-purpose dams are operated accounting for both physical and socioeconomic factors. This study aims to evaluate the utility of a deep learning algorithm-based model for three multi-purpose dam operation (Seomjin River dam, Juam dam, and Juam Control dam) in Seomjin River. In this study, the Gated Recurrent Unit (GRU) algorithm is applied to predict hourly water level of the dam reservoirs over 2002-2021. The hyper-parameters are optimized by the Bayesian optimization algorithm to enhance the prediction skill of the GRU model. The GRU models are set by the following cases: single dam input - single dam output (S-S), multi-dam input - single dam output (M-S), and multi-dam input - multi-dam output (M-M). Results show that the S-S cases with the local dam information have the highest accuracy above 0.8 of NSE. Results from the M-S and M-M model cases confirm that upstream dam information can bring important information for downstream dam operation prediction. The S-S models are simulated with altered outflows (-40% to +40%) to generate the simulated water level of the dam reservoir as alternative dam operational scenarios. The alternative S-S model simulations show physically inconsistent results, indicating that our deep learning algorithm-based model is not explainable for multi-purpose dam operation patterns. To better understand this limitation, we further analyze the relationship between observed water level and outflow of each dam. Results show that complexity in outflow-water level relationship causes the limited predictability of the GRU algorithm-based model. This study highlights the importance of socioeconomic factors from hidden multi-purpose dam operation processes on not only physical processes-based modeling but also aritificial intelligence modeling.

• Journal of Korean Society of Environmental Engineers
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• v.28 no.6
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• pp.667-676
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• 2006

The reduction of $Hg^{2+}$ in the aqueous phase results in the production of dissolved gaseous mercury(DGM), and the volatilization of DGM has been identified as an important mechanism for the loss of Hg from waterbodies to the atmosphere. Although mercury emission in the world is known to be mostly from Asia, there have been few studies of measuring DGM concentrations in lakes in Asia. In this study, DGM concentrations were measured at Juam reservoir($35^{\cir}00'N,\;127^{\circ}14'E$), Korea. The results showed that the average concentrations of DGM at the upper and down stream of the lake during summer time were $95{\pm}8\;and\;130{\pm}15$ pg/L, respectively and the concentration of total mercury(TM) at the upper and down stream was $2.1{\pm}0.7,\;1.7{\pm}0.3$ ng/L respectively. Average DGM concentration during summer time($101{\pm}14pg/L$) was approximately 5.5 times higher than that during fall($18{\pm}0.1pg/L$). The DGM concentrations ai the midstream decreased from 32 to 13.7 pg/L during rain event, while the TM concentrations increased from 2.2 ng/L to 2.7 ng/L indicating the deposition of mercury from the atmosphere. Also, the diurnal patterns between DGM concentrations and UV intensities were observed. Water temperatures and DOC concentrations were significantly related to DGM concentrations, while TM concentrations were negatively related to DGM concentrations(p<0.0001). Comparing with the study of Dill et al.,(2006) the average concentrations of DGM $(109{\pm}15pg/L)\;and\;TM(2.2{\pm} 0.4ng/L)$ at Juam reservoir were approximately 3 and 2.2 times higher than those measured in other lakes(DGM: $38{\pm}16pg/L$, TM: $1.0{\pm}1.2ng/L$).

• Korean Journal of Ecology and Environment
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• v.43 no.2
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• pp.319-337
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• 2010

Major objective of this study was to determine interannual and seasonal water quality along with characteristics of longitudinal gradients along the reservoir axis of the riverine zone (Rz)-to-lacustrine zone (Lz). Water quality dataset of five years during 2003~2007 used here were obtained from Ministry of Environment, Korea and ten physical, chemical and biological parameters were analyzed in the study. Similarity analysis, based on moropho-hydrological variables of reservoir surface area, watershed area, total inflow, and outflow, showed that the reservoirs were categorized as three groups of large-dam reservoirs (Chungju Reservoir, Daecheong Reservoir and Soyang Reservoir), mid-size reservoirs (Andong Reservoir, Yongdam Reservoir, Juam Reservoir and Hapcheon Reservoir), and small-size reservoirs (Hoengseong Reservoir and Buan Reservoir). According to the data comparison of high-flow year (2003) vs. lowflow year (2005), dissolved oxygen (DO), pH, biological oxygen demand (BOD), suspended solids (SS), total nitrogen (TN), total phosphorus (TP), chlorophyll-a (CHL) and electrical conductivity (EC) declined along the longitudinal axis of Rz to Lz and water transparency, based on Secchi depth (SD), increased along the axis. These results indicate that transparency was a function of Values of pH, DO, SS, SD, and EC at each site were greater in the low-flow year (2005) than the high-flow year (2003), whereas values of BOD, COD, TN, TP and CHL were greater in the high-flow year (2003). When values of TN, TP, CHL and SD in nine reservoirs were compared in the three zones of Rz, Tz, and Lz, values of TN, TP and CHL declined along longitudinal gradients and SD showed the opposite due to the sedimentation processes from the water column. Values of TN were not statistically correlated with TP values. The empirical linear models of TP-CHL and CHL-SD showed significant (p<0.05, $R^2$>0.04). In the mid-size reservoirs, the variation of CHL was explained ($R^2$=0.2401, p<0.0001, n=239) by the variation of TP. The affinities in the correlation analysis of mid-size reservoirs were greater in the CHL-SD model than any other empirical models, and the CHL-SD model had an inverse relations. In the meantime, water quality variations was evidently greater in Daecheong Reservoir than two reservoirs of Andong Reservoir and Hoengseong Reservoir as a result of large differences of water quality by long distance among Rz, Tz and Lz.