Water quality in the Daecheong reservoir has been deteriorated by algal bloom due to nutrient supply from the upstream of the Daecheong reservoir after heavy rainfall. Algal bloom is propagated from eutrophicated tributary into the main body of the reservoir according to the hydrological conditions. This study is aimed to estimate the water current and temperature effect by the simulation of dam spill flow control using water quality model, CE-QUAL-W2 in 2003. Water current was resulted in nutrient transport from upstream of main reservoir and nutrients were delivered up to downstream by fast water velocity. Algal blooms occurred in stagnate zone of reservoir downstream as the current of downstream was retarded according to dam outflow control. Consequently water balance in stagnate zone triggered a rise of water temperature in summer. It affected algal bloom in the embayment of the reservoir. The simulation result by outflow control scenarios showed that spill flow augmentation induced in water body instability of stagnate zone so that water temperature declined. It could be suggested that outflow control minimize algal bloom in the downstream in the flooding season as long as water elevation level is maintained properly.
Lee, Hyeon No;Jung, Kwan Sue;Cheon, Geun Ho;Hur, Young Teck
Journal of Korea Water Resources Association
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v.48
no.6
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pp.501-509
/
2015
Lately multipurpose dam is required to consider various interests such as quality, ecological environment as well as flood control, water supply, hydropower generation, etc. The objective of this study is to investigation and analysis of water temperature in the areas where there are social conflicts due to cold water outflow. In this study, we monitored water temperature of Juam regulation dam, downstream river, Suncheon bay in a long term period and performed comparative analysis on a change of water temperature in downstream river and Suncheon bay by using three-dimensional numerical mode (EFDC) considering various external factors such as water outflow amount. The result of monitoring and numerical modelling indicates that effects of cold water outflow takes place from april to september. Also effects of the low temperature discharge of dam was complicatedly altered by various factors such as outflow time and amount, weather and tide level conditions etc. The result of this study can be utilized as a basic data for establishing improvement of dam operation plan to minimize negative effects of dam's cold temperature water outflow to downstream river and coastal area.
The purpose of this study is to analyze the characteristics and correlations of the Yeongcheon Lake in order to reduce the occurrence of harmful cyanobacteria. In this study, we investigated the water quality and phytoplankton of the lake from May to November in 2017. Correlation and data mining analyses were performed to analyze the relationship between the two factors. The water temperature was lowest at the point where the Yeongcheon Lake inflow occurs at Imha Lake. It was highest at the point where the outflow occurs to Angye Lake. The pH was also highest at the outflow point, but in the case of DO, it was highest at the midpoint between the inflow and outflow. The main cyanobacteria that emerged during the study period were Oscillatorialimosa, Microcysti saeruginosa and Aphanizomenon flos-aquae. As a result of correlation analysis, the water temperature, inflow, COD loading, TOC loading at the inflow point of the Yeongcheon Lake were the items that were related to the harmful cyanobacteria. The data mining analysis indicated that the TP loading and harmful cyanobacteria in the inflow point of the Yeongcheon Lake were influential on the detrimental cyanobacteria in the Yeongcheon Lake outflow point. When the TP loading was less than 39.0 kg/day at the inflow site, it was expected that the amount of harmful cyanobacteria could be maintained below 10,000 cells/mL.
Korea's multi-purpose dams, which were constructed in the 1970s and 1980s, have a single outlet located near the bottom for hydropower generation. Problems such as freezing damage to crops due to cold water discharge and an increase the foggy days have been raised downstream of some dams. In this study, we analyzed the effect of water intake depth on the reservoir's water temperature stratification structure and outflow temperature targeting Hapcheon Reservoir, where hypolimnetic withdrawal is drawn via a fixed depth outlet. Using AEM3D, a three-dimensional hydrodynamic water quality model, the vertical water temperature distribution of Hapcheon Reservoir was reproduced and the seasonal water temperature stratification structure was analyzed. Simulation periods were wet and dry year to compare and analyze changes in water temperature stratification according to hydrological conditions. In addition, by applying the intake depth change scenario, the effect of water intake depth on the thermal structure was analyzed. As a result of the simulation, it was analyzed that if the hypolimnetic withdrawal is changed to epilimnetic withdrawal, the formation location of the thermocline will decrease by 6.5 m in the wet year and 6.8 m in the dry year, resulting in a shallower water depth. Additionally, the water stability indices, Schmidt Stability Index (SSI) and Buoyancy frequency (N2), were found to increase, resulting in an increase in thermal stratification strength. Changing higher withdrawal elevations, the annual average discharge water temperature increases by 3.5℃ in the wet year and by 5.0℃ in the dry year, which reduces the influence of the downstream river. However, the volume of the low-water temperature layer and the strength of the water temperature stratification within the lake increase, so the water intake depth is a major factor in dam operation for future water quality management.
Presently, aquatic plants are used for the water purification in inland water. This study was carried out to investigate the water purification effect of aquatic plants, Oenanthe javanica and Typha angustata, The experiment was conducted in outdoor flowing water was conducted for ten days, Water quality was measured in terms of water temperature, COD(chemical oxygen demand), SS(suspended solids), Total N, Total P. The results of field experimentation showed that hydraulic retention time was the earliest in July and August 2003, and there were not any particular changes of monthly water temperature in inflow water and outflow water. As we look at the changes taken place in inflow water and outflow water throughout the whole experiment period, the change of water quality in summer was salient, especially SS removal ratio showed distinguished change as $25\%$, when the pebble filter and aquatic were attached to it. The removal rate of COD, total N total P were $14,7\%,\;8\%\;and\;9\%$, respectively. In relating the length of water extension to the change in water quality, the water quality tended to get lower generally in proportion to hydraulic retention time.
As a basic study for developing a forecasting/estimating system that predicts water quality changes when Deep Sea Water (DSW) drains to the ocean after using it, this study was carried out as follows: 1) numerical simulation of the present state at DSW developing region in the East sea using SWEM, 2) numerical prediction of water quality changes by effluent DSW, 3) analysis of influence degree 'With defined DEI (DSW effect index) at F station. On the whole, when DSW drained to the ocean, Chl-a, COD and water-temperature were decreased and DIN, DIP and DO were increased by effluent DSW, and Salinity was steady. According to analysis of influence degree, the influence degree of DIN was the highest and it was high in order of Chl-a, COD, Water-temperature, DO, DIP and Salinity. The influence degree classified by DSW effluent position was predicted that suiface outflow was lower than bottom outflow. Ad When DSW discharge increased 10 times, the influence degree increased about $5{\sim}14$ times.
Park Seong-Sook;Yun Seong-Taek;Chae Gi-Tak;So Chil-Sup;Koh Yong-Kwon;Choi Hyeon-Su
Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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2006.04a
/
pp.303-306
/
2006
Using a variety of chemical geothermometers we estimate the temperature of a deep geothermal reservoir in relation to thermal groundwater in the Bugok area, southern Korea, in order to assess the potential use of geothermal energy in South Korea. Thermal water at Bugok has been exploited down to about 400 m below the land surface and shows the highest outflow temperatures (up to $78{\circ}C$) in South Korea. Based on the hydrochemical data and occurrence, groundwater in Bugok can be classified into three groups: $Na-SO_4$ type thermal groundwater (CTGW) occurring in the central part (about 0.24 $km^2$) $Ca-HCO_3$ type cold groundwater (SCGW) occurring in shallow peripheral parts of CTGW; and the intermediate type groundwater (STGW). CTGW waters are typical of thermal water in the area, because they have the highest outflow temperatures and contain very high concentrations of Na, K and $SiO_2$ due to the sufficient reaction with silicate minerals in deep reservoir. Their enriched $SO_4$ was likely formed by gypsum dissolution. The major ion composition of CTGW shows the general approach to a partial equilibrium state with rocks at depth. The application of various alkali ion geothermometers yields temperature estimates in the range of 88 to $198{\circ}C$ for the thermal reservoir. Multiple mineral equilibrium calculation indicates asimilar but narrower temperature range between about 100 and $155{\circ}C$. These temperature estimates are not significantly higher than the measured outflow temperatures for CTGW Considering the heat loss during the ascent- of thermal waters, this fact may suggest that a thermal reservoir in the study area is likely located at relatively shallow depths (possibly close to the depth of preexisting wells). Therefore, we suggest a high potential for geothermal energy development around the Bugok area in southern Korea.
For the efficient discovery of knowledge and information from the observed systems, data mining techniques can be an useful tool for the prediction of water quality at intake station in rivers. Deterioration of water quality can be caused at intake station in dry season due to insufficient flow. This demands additional outflow from dam since some extent of deterioration can be attenuated by dam reservoir operation to control outflow considering predicted water quality. A seasonal occurrence of high ammonia nitrogen ($NH_3$-N) concentrations has hampered chemical treatment processes of a water plant in Geum river. Monthly flow allocation from upstream dam is important for downstream $NH_3$-N control. In this study, prediction models of water quality based on multiple regression (MR), artificial neural network and data mining methods were developed to understand water quality variation and to support dam operations through providing predicted $NH_3$-N concentrations at intake station. The models were calibrated with eight years of monthly data and verified with another two years of independent data. In those models, the $NH_3$-N concentration for next time step is dependent on dam outflow, river water quality such as alkalinity, temperature, and $NH_3$-N of previous time step. The model performances are compared and evaluated by error analysis and statistical characteristics like correlation and determination coefficients between the observed and the predicted water quality. It is expected that these data mining techniques can present more efficient data-driven tools in modelling stage and it is found that those models can be applied well to predict water quality in stream river systems.
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.
Hyo-Sang Choo;Jin-Young Lee;Kyeung-Ho Han;Dong-Sun Kim
Journal of the Korean Society of Marine Environment & Safety
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v.29
no.3
/
pp.255-269
/
2023
Surface water temperature of a bay (from the south to the north) increases in spring and summer, but decreases in autumn and winter. Due to shallow water depth, freshwater outflow, and weak current, the water temperature in the central to northern part of the bay is greatly affected by the land coast and air temperature, with large fluctuations. Water temperature variations are large in the north-east coast of the bay, but small in the south-west coast. The difference between water temperature and air temperature is greater in winter and in the south-central part of the bay than that in the north to the eastern coast of the bay where sea dykes are located. As the bay goes from south to north, the range of water temperature fluctuation and the phase show increases. When fresh water is released from the sea dike, the surrounding water temperature decreases and then rises, or rises and then falls. The first mode of empirical orthogonal function (EOF) represents seasonal variation of water temperature. The second mode represents the variability of water temperature gradient in east-west and north-south directions of the bay. In the first mode, the maximum and the minimum are shown in autumn and summer, respectively, consistent with seasonal distribution of surface water temperature variance. In the second mode, phases of the coast of Seosan~Boryeong and the east coast of Anmyeon Island are opposite to each other, bordering the center of the deep bay. Periodic fluctuation of the first mode time coefficient dominates in the one-day and half-day cycle. Its daily fluctuation pattern is similar to air temperature variation. Sea conditions and topographical characteristics excluding air temperature are factors contributing to the variation of the second mode time coefficient.
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