• Journal of Korean Society for Geospatial Information Science
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• v.9 no.1 s.17
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• pp.19-25
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• 2001

Satellite remote sensing, with its synoptic coverage, is used to evaluate the trophic state of large reservoir for agriculture in Kum River basin. The prediction model for chlorophyll-${\alpha}$ which was derived from Daecheong reservoir was applied to four LANDSAT TM imageries to generate a distribution map of trophic state. The chlorophyll-${\alpha}$ model was found to be reasonably reliable predictors for average trophic state value of reservoir. LANDSAT TM imagery data appears to have great utility in assessing trophic state of reservoir.

• Journal of Environmental Impact Assessment
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• v.25 no.4
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• pp.248-260
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• 2016

This study was aimed to assess the effect of diverse pollutants control measures suggested in the Chuso basin and its upstream of So-oak stream watershed where are the most concerned areas on the control of algal bloom occurring in Daecheong Reservoir. The control measures were classified as watershed measures and in-reservoir measures, and their effects were simulated using a two-dimensional hydrodynamic and water quality model. The watershed measures were made up of 1) point sources control, non-point sources control, and their combinations. The in-reservoir measures were supposed to treat sediment at Chuso basin and to install a phosphorus elimination plant (PEP) at the end of So-oak stream. The results showed that the effect of each measure was influenced by the hydrological condition of the year. In wet year, as the contribution of non-point sources increased, the non-point source control measures (NPS1~NPS4) showed more effective compared to other measures, while, the PEP system to eliminate phosphorus from So-oak stream showed better performance in dry year. In particular, the scenario of NPS1, in which all livestock manures were collected and treated but only chemical fertilizers (NPS1) were used for agriculture fields, showed the best performance for the control of algal bloom in Chuso basin among the watershed measures.

• Journal of Korea Water Resources Association
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• v.41 no.12
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• pp.1187-1198
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• 2008

Many reservoirs in Korea and their downstream environments are under increased pressure for water utilization and ecosystem management from longer discharge of turbid flood runoff compared to a natural river system. Turbidity($C_T$) is an indirect measurement of water 'cloudiness' and has been widely used as an important indicator of water quality and environmental "health". However, $C_T$ modeling studies have been rare due to lack of experimental data that are necessary for model validation. The objective of this study is to validate a coupled three-dimensional(3D) hydrodynamic and particle dynamics model (ELCOM-CAEDYM) for the simulation of turbid density flows in stratified Daecheong Reservoir using extensive field data. Three different groups of suspended solids (SS) classified by the particle size were used as model state variables, and their site-specific SS-$C_T$ relationships were used for the conversion between field measurements ($C_T$) and state variables (SS). The simulation results were validated by comparing vertical profiles of temperature and turbidity measured at monitoring stations of Haenam(R3) and Dam(R4) in 2004. The model showed good performance in reproducing the reservoir thermal structure and propagation of stream density flow, and the magnitude and distribution of turbidity in the reservoir were consistent with the field data. The 3D model and turbidity modeling framework suggested in this study can be used as a supportive tool for the best management of turbidity flow in other reservoirs that have similar turbidity problems.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.785-799
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• 2022

The aim of this study was to characterize the emission pathways and the footprint of greenhouse gases (GHG) in Daecheong Reservoir using the G-res Tool, and to evaluate the GHG emission intensity (EI) compared to other energy sources. In addition, the change in GHG emissions was assessed in response to the total phosphorus (TP) concentration. The GHG flux in post-impoundment was found to be 262 gCO₂eq/m²/yr, of which CO₂ and CH₄ were 45.7% and 54.2%, respectively. Diffusion of CO₂ contributed the most, followed by diffusion, degassing, and bubbling of CH₄. The net GHG flux increased to 510 gCO₂eq/m²/yr because the forest (as CO₂ sink) was lost after dam construction. The EI of Daecheong Reservoir was 86.8 gCO₂eq/kWh, which is 3.7 times higher than the global EI of hydroelectric power, due to its low power density. However, it was remarkable to highlight the value to be 9.5 times less than that of coal, a fossil fuel. We also found that a decrease in TP concentration in the reservoir leads to a decrease in GHG emissions. The results can be used to improve understanding of the GHG emission characteristics and to reduce uncertainty of the national GHG inventory of dam reservoirs.

• Journal of Korean Society on Water Environment
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• v.33 no.3
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• pp.326-333
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• 2017

The lakes and reservoirs have been reported as important sources of carbon emissions to the atmosphere in many countries. Although field experiments and theoretical investigations based on the fundamental gas exchange theory have proposed the quantitative amounts of Net Atmospheric Flux (NAF) in various climate regions, there are still large uncertainties at the global scale estimation. Mechanistic models can be used for understanding and estimating the temporal and spatial variations of the NAFs considering complicated hydrodynamic and biogeochemical processes in a reservoir, but these models require extensive and expensive datasets and model parameters. On the other hand, data driven machine learning (ML) algorithms are likely to be alternative tools to estimate the NAFs in responding to independent environmental variables. The objective of this study was to develop random forest (RF) and multi-layer artificial neural network (ANN) models for the estimation of the daily $CO_2$ NAFs in Daecheong Reservoir located in Geum River of Korea, and compare the models performance against the multiple linear regression (MLR) model that proposed in the previous study (Chung et al., 2016). As a result, the RF and ANN models showed much enhanced performance in the estimation of the high NAF values, while MLR model significantly under estimated them. Across validation with 10-fold random samplings was applied to evaluate the performance of three models, and indicated that the ANN model is best, and followed by RF and MLR models.

• Journal of Korean Society on Water Environment
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• v.26 no.5
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• pp.796-801
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• 2010

Water quality index (WQI) can be a great tool that allows experts to translate large amount of complex water quality data into a format more easily understood by the public and policy makers. Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) can be calculated with the three factors (Scope: $F_1$, Frequency: $F_2$, Amplitude: $F_3$). After all, the WQI for a specific site is produced as a number between 0 to 100; the scale is also divided into five categories, i.e., Excellent, Good, Fair, Marginal and Poor. The WQI was found to be highly related to Chl-a, pH, temperature among the collected items. When the more input parameters were used, the range of variation generally became smaller. $F_3$ among the factors of WQI was influenced by algae. It showed a similar variation tendency between WQI and algal bloom in 2008.

• Korean Journal of Ecology and Environment
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• v.49 no.4
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• pp.258-270
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• 2016

This study was conducted to test the green-tide mitigation technique in the lower part of the Sook Stream (Chusori) of Daecheong Reservoir from June 27 to August 24, 2014. And the effects were compared with weekly monitoring result of the watching station of the algae alert system (AAS) as well as test beds reach. The green-tide in a test bed was begun from the upstream, and it was gradually transferred and spread toward the downstream by the hydrological factors. The total amount of algae removed by algae removal device during the test period was 33,920 kg, and solids dewatered by natural gravity was 8,480 kg. Also chlorophyll-a content was 2.83 kg, the number of blue-green algae cells was equivalent to $78.6{\times}10^{14}$ cells. Compared with the results of the watching station of AAS, the pre-concentrate removal work in the outbreak waters was able to suggest the possibility of green-tide mitigation. In addition, an effective management of the green-tide was required spatial and temporal occurrence information and practical device technology. Particularly, the optimal timing of algae removal in the river-reservoir hybrid system was recommended at times before the monsoon rainy season and reached the lowest water level.

• Korean Journal of Agricultural Science
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• v.38 no.3
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• pp.513-524
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• 2011

To evaluate the applicability of inflow runoff model to reservoir operation in Korea, DAWAST model and TPHM model which are conceptual lumped daily runoff model and were developed in Korea, were selected and applied to simulate inflows to Daecheong multipurpose dam with watershed area of 4,134 $km^2$, and water storages in Geryong reservoir with watershed area of 15.1 $km^2$ and total water storage of 3.4 M $m^3$. Evaluating inflows on an yearly, monthly, ten-day, and daily basis, inflows by DAWAST model showed balanced scatters around equal value line. But inflow by TPHM model showed high in high flows. Annual mean water balance by DAWAST model was rainfall of 1,159.9 mm, evapotranspiration of 622.1 mm, and inflow of 644.6 mm, from which rainfall was 104.8 mm less than sum of evapotranspiration and inflow, and showed unbalanced result. Water balance by TPHM model showed satisfactory result. Reservoir water storages were shown to simulate on a considerable level from applying DAWAST and TPHM models to simulate inflows to Geryong reservoir. But it was concluded to be needed to improve DAWAST and TPHM model together from imbalance of water balance and low estimation in high flow.

• Journal of Korea Water Resources Association
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• v.41 no.3
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• pp.293-303
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• 2008

Reservoir turbidity flows degrade the efficiency and sustainability of water supply system in many countries located in monsoon climate region. A decision support system called RTMMS aimed to assist reservoir operations was developed for the real time monitoring, modeling, and management of turbidity flows induced by flood runoffs in Daecheong reservoir. RTMMS consists of a real time data acquisition module that collects and stores field monitoring data, a data assimilation module that assists pre-processing of model input data, a two dimensional numerical model for the simulation of reservoir hydrodynamics and turbidity, and a post-processor that aids the analysis of simulation results and alternative management scenarios. RTMMS was calibrated using field data obtained during the flood season of 2004, and applied to real-time simulations of flood events occurred on July of 2006 for assessing its predictive capability. The system showed fairly satisfactory performance in reproducing the density flow regimes and fate of turbidity plumes in the reservoir with efficient computation time that is a vital requirement for a real time application. The configurations of RTMMS suggested in this study can be adopted in many reservoirs that have similar turbidity issues for better management of water supply utilities and downstream aquatic ecosystem.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.19 no.6
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• pp.111-121
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• 2016

This study was carried out to assess the riparian vegetation health in the fluctuation area and vicinity of reservoirs. The results of this study could be a basic data to improve the ecological function and establish green-network of waterside ecosystem. The study site is Daecheong lake reservoirs which the representative landscape of Geum river and with great number of visitors near metropolitan city. The 6 survey plots of 2 survey area were selected, survey area 1 had 4 survey plots and survey area 2 had 2 survey plots, and to compare the study results 4 control plots were selected in Gyeongcheon reservoir. The main dominant specie of survey sites was Salix koreensis in tree and subtree layer, were Salix koreensis and Salix glandulosa. in shrub layer. 2 survey plots of Samjeongdong and Kyeongcheon reservoir were assessed as 'Good', 2 survey plots of chudong were assessed as 'Fair' in vegetation health assessment. In the fluctuation area from flood water level to low water level, 58 populations of Salix koreensis were found in survey sites and Salix koreensis, Salix glandulosa and Acer tataricum subsp. ginale were found in control sites. The most adequate species at the condition affected by inundation impacts would be Salix koreensis and Salix glandulosa was more healthy at the area less affected by inundation. This study was carried out the vegetation health assessment on Daecheong reservoir which has been advanced natural succession for more than 30 years after the construction. Further, it should carry continuously out the research on the planting model of the waterside ecosystem for ecological restoration.