• Journal of the Korean GEO-environmental Society
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• v.7 no.6
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• pp.89-100
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• 2006

Recently, lots of lives and properties have been lost because comparatively large magnitude earthquakes were occurred in relatively safe regions and nations. It has been reported that number of earthquakes was increased rapidly in Korea. Hence, recently civil constructions were ensured against risks about earthquake not only large-scale structures but also comparative small-scale structures such as reservoir dams and life line by systematic aseismic design. Therefore, in this study, the seismic stability was ensured to evaluate aseismic performance for major planned reservoir dams in Korea. The seismic response analyses were conducted using SHAKE program on new reservoir dams under short-period, long-period and artificial seismic wave. The liquefaction potential for reservoir dams was assessed by using results from seismic response analysis (simplified assessment method for liquefaction potential). Also, fully coupled analysis--interaction of pore-pressure and soil--was performed to investigate both the development of excess pore water pressure and the characteristic of dynamic shear strain.

• Journal of Korean Society on Water Environment
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• v.32 no.5
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• pp.433-441
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• 2016

Many large dams have been constructed for water supply, irrigation, flood control and hydropower in Korea for the last century. Meanwhile, recent studies indicated that the artificial reservoirs impounded by these dams are major sources of carbon dioxide (CO₂) to the atmosphere and relevant to global budget of green house gases. However, limited information is available on the seasonal variations of CO₂ evasion from the reservoirs located in the temperate monsoon regions including Korea. The objectives of this study were to estimate daily Net Atmospheric Flux (NAF) of CO₂ in Daecheong Reservoir located in Geum River basin of Korea, and analyze the influencing parameters that characterize the variation of NAF. Daily pH and alkalinity (Alk) data collected in wet year (2012) and dry year (2013) were used for estimating the NAFs in the reservoir. The dissolved inorganic carbon (DIC) was computed using the pH and Alk measurements supposing an equilibrium state among the carbonate species. The results showed seasonal variations of NAF; negative NAFs from May to October when the primary production of the reservoir increased with water temperature increase, while positive NAF for the rest of the period. Overall the reservoir acted as sources of CO₂ to the atmosphere. The estimated NAFs were 2,590 and 771 mg CO₂ m^-2d^-1 in 2012 and 2013, respectively, indicating that the NAFs vary a large extent for different hydrological years. Statistical analysis indicated that the NAFs are negatively correlated to pH, water temperature, and Chl-a concentration of the reservoir.

• Journal of the Korean Institute of Gas
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• v.18 no.2
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• pp.1-9
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• 2014

To develop a coalbed methane(CBM) reservoir, it is important to apply production methods such as drilling, completion, and stimulation which coincide with coal properties. However, the reliability of the selected resulted in most of CBM field is not enough to accept because the selection of production method has been done by empirical decision. As the result, the empirical decision show inaccurate results and need to prove using simulation whether it was true exactly. In this study, the intelligent system has been developed to assist the selection of CBM production method using artificial neural network(ANN). Before the development of the system, technical screening guideline was analyzed by literature survey and the system to select drilling and completion method, and hydraulic fracture fluid was developed by utilizing the guideline. The result as a validation of the developed system showed a high accuracy. In conclusion, it has been confirmed that the developed system can be utilized as a effective tool to select production method in CBM reservoir.

• Journal of Environmental Science International
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• v.21 no.7
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• pp.825-835
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• 2012

This study for the development of water purification Artificial floating island maximizing domestic Artificial floating island patent trends and product development, according to the timing of patent registration was analyzed for trends. In addition, domestic invention patent technology Artificial floating island typed according to the purpose and characteristics of domestic patents were Artificial Floating Island. In particular, domestic leisure space with a growing population and the need for securing emerging role as a reservoir of water only in the past, who do appeal as a tourist destination or as an ecological space utilized, and accordingly will transform and the need to secure a hydrophilic, degrade water quality problems using this aquatic environment (water acquisition and hydrophilic), the requirements are a big obstacle is the reality factor. This patented product differentiation strategy through the analysis of the development of technology progressiveness (Field Application) in terms of water quality improvement and maintenance side, and the hydrophilic side scenery, ecological restoration aspects, and applicability to the field and taking into account existing technology economic aspects of distinction were presented and advertised a lot in terms of cost compared to other techniques without the use of highly efficient methodology for building a water purification and also appears identity appeal, wetlands, rivers, etc. can be applied broadly technician widespread deployment and installation time to less simple and more are expected to spread.

• Journal of Korea Water Resources Association
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• v.46 no.7
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• pp.697-706
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• 2013

In recent, Korea has faced on water quality management problems in reservoir and river because of increasing water temperature and rainfall frequency caused by climate change. This study is effectively to manage water quality for establishment of algal bloom forecasting models with artificial neural network. Daecheong reservoir located in Geum river has suitable environment for algal bloom because it has lots of contaminants that are flowed by rainfall. By using back propagation algorithm of artificial neural networks (ANNs), a model has been built to forecast the algal bloom over short-term (1, 3, and 7 days). In the model, input factors considered the hydrologic and water quality factors in Daecheong reservoir were analyzed by cross correlation method. Through carrying out the analysis, input factors were selected for algal bloom forecasting model. As a result of this research, the short term algal bloom forecasting models showed minor errors in the prediction of the 1 day and the 3 days. Therefore, the models will be very useful and promising to control the water quality in various rivers.

• Journal of the Korean Society of Industry Convergence
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• v.16 no.3
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• pp.61-68
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• 2013

Long-term runoff model can be used to establish the effective plan of water reources allocation and the determination of the storage capacity of reservoir. So this study aims at the development of monthly runoff model using artificial neural network technique. For this, it was selected multi-layer neural network(MLN) and radial basis function neural network(RFN) model. In this study, it was applied model to analysis monthly runoff process at the Wi stream basin in Nakdong river which is representative experimental river basin of IHP. For this, multi-layer neural network model tried to construct input 3, hidden 7, and output 1 for each number of layer. As the result of analysis of monthly runoff process using models connected with artificial neural network technique, it showed that these models were effective in the simulation of monthly runoff.

• Journal of Environmental Impact Assessment
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• v.9 no.3
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• pp.163-176
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• 2000

The purpose of this study is to analyze the pollutant loads and its distribution, and to suggest the management of nonpoint sources in Daechong Reservoir. The loads from point and nonpoint sources such as population, industry, livestock and land use were calculated per stream or river with topography(1:25,000) of the watershed of Daechong Reservoir. The generating pollutant loads were obtained through multiplication of pollutant sources by generating pollutant quantity per unit pollutant source. The effluent point sources loads is defined as loads from wastewater treatment facilities such as domestic, industrial and livestock wastewater treatment facilities, which were calculated through multiplication of effluent flowrates by water quality constituents concentration. Untreated point sources loads were estimated to be 35 % of total point sources loads. The effluent nonpoint sources pollutant loads were obtained through the multiplication of generating nonpoint sources loads by effluent ratios based on previous studies. The effluent nonpoint sources loads have the ratio of 26.2% of total BOD effluent loadings, 20.1% of total T-N effluent loadings, and 10.5% of total T-P effluent loadings. For the reduction of nonpoint sources loads in Daechong Reservoir, silviculture, artificial wet land, and grassed waterways could be applied. And untreated livestock waste scattered can result in nonpoint loadings, so required the livestock wastes treatment facilities and purifying facilities together with the management of shed, pasture, livestock waste storage site and composting site. Finally, remote sensing and GIS should be applied to the identification of distribution of water quality, watershed, the location and scale of nonpoint sources, effluent process during rainfall, for more detailed analysis of nonpoint sources.

• Journal of Marine Life Science
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• v.4 no.2
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• pp.70-80
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• 2019

Ichthyofauna and community structure of fish were studied for two fisheries resource reserves, Chuncheon reservoir and Andong reservoir from 2017 to 2018. Fish were sampled 8 times at each reservoir. In Chuncheon reservoir, total number of fish sampled was 1,197 representing 34 species and 13 families. Dominant species and sub-dominant species were Lepomis macrochirus (23.2%) and Zacco platypus (17.4%), respectively. In Andong reservoir, total number of fish sampled was 1,393 representing 24 species and 9 families. Dominant species and sub-dominant species were L. macrochirus (15.7%) and Carassius carassius (15.2%), respectively. The diversity index of two sampling site increased compared to previous investigation. The evenness index was not changed much in Andong reservoir but increased in Chuncheon reservoir. Ichthyofauna and community structure of fish at sampling sites in both reservoirs maintained stable except high proportion of exotics species with needed to be reduced by consistent effort. For better fish population in these communities, however, various efforts such as seed stocking and installment of artificial spawning ground should be provided to these reservoirs.

• Korean Journal of Ecology and Environment
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• v.42 no.1
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• pp.19-25
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• 2009

The effects of artificial floating island on the changes in phytoplankton and zooplankton community structure were investigated monthly from September 2006 to May 2007 in Shingu reservoir. The total cell number of phytoplankton under the artificial floating island was three times less than those of control (without artificial floating island). The dominant species of phytoplankton were Lyngbya sp. on September, Cryptomonas sp. from October to January, Aulacoseira granulata on February and Oscillatoria sp. from March to May at lake water. Cyanophyta was dominated from February to March at lake water but it was dominated from March at artificial floating island area. The total individual number, species number of zooplankton and species diversity of phytoplankton and zooplankton under the artificial floating island were higher than those of lake water.

• Journal of Korean Society on Water Environment
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• v.27 no.4
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• pp.533-541
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• 2011

Algal blooms have caused problems for drinking water as well as eutrophication. However it is difficult to control algal blooms by current warning manual in rainy season because the algal blooms happen in a few days. The water quality data, which have high correlations with Chlorophyll-a on Daecheongho station, were analyzed and chosen as input data of Artificial Neural Networks (ANN) for training pattern changes. ANN was applied to early forecasting of algal blooms, and ANN was assessed by forecasting errors. Water temperature, pH and Dissolved oxygen were important factors in the cross correlation analysis. Some water quality items like Total phosphorus and Total nitrogen showed similar pattern to the Chlorophyll-a changes with time lag. ANN model (No. 3), which was calibrated by water temperature, pH and DO data, showed lowest error. The combination of 1 day, 3 days, 7 days forecasting makes outputs more stable. When automatic monitoring data were used for algal bloom forecasting in Daecheong reservoir, ANN model must be trained by just input data which have high correlation with Chlorophyll-a concentration. Modular type model, which is combined with the output of each model, can be effectively used for stable forecasting.