• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2000.10a
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• pp.590-598
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• 2000

A multiplicative ARIMA model was tested and applied to analyze the periodicity and trends of 168 monthly oxygen demand data from the Noryanggin water quality gauging station in the downstream Han River. ARIMA model was identified to fit to the data using ACF and PACF tests, and the parameters estimated using an unconditional least square method. The residuals between the observed and forecasted data were acceptable with the Porte-Manteau test. A forecast of DO changes was made for its applications.

• Journal of Environmental Impact Assessment
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• v.25 no.3
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• pp.222-232
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• 2016

Water Footprint is utilized to analyze direct and indirect water consumption for sustainable water resource management. This study aims to understand potential applicability of water footprint concept by analyzing the status of water consumption and related water policies in Seoul. We analyzed a direct gray water footprint and the blue water footprint in Seoul affected by the social and economic characteristics of the consumers in the city. In particular, in order to analyze the blue water footprint represented by both surface and underground water for the provision and consumption of products, we calculated the actual water consumptions of surface and underground water for 25 districts in Seoul. Our analysis in consideration of population and households indicates that Jung-gu has the highest blue water footprint followed by Jongro-gu, Gangnam-gu, Yongsan-gu, and Seocho-gu. Gray water footprint was calculated by estimating the amount of water for purifying wastewater to meet the water quality standard (above BOD 3.5ppm) for each district. As a result, Jung-gu has the highest gray water footprint, followed by Jongro-gu, Gangnam-gu, Yongsan-gu, Seocho-gu, and Youngdeungpo-gu. Our study suggests the potential value of using water footprint concept to complement the current limitations of water use management focusing on water supply control. We expect that our analysis will provide an important basis for considering water use management which is economically and socially more resilient and sustainable.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.6
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• pp.137-149
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• 2020

This study was carried out to analyze the monthly runoff concentration on non rainfall days in order to prepare basic data to compare the runoff concentration on rainfall days in 7 forest watersheds in the Republic of Korea. Forest stream water has been collected through 15 times of sampling in each watershed and analyzed based on the changes in concentration of Biochemical Oxygen Demand(BOD), Chemical Oxygen Demand(COD), Total Organic Carbon(TOC), Total Nitrogen(TN), and Total Phosphorus(TP). The average concentration was 0.8 mg/L for BOD, 1.4 mg/L for COD, 0.8 mg/L for TOC, 1.85 mg/L for TN and 0.002 mg/L for TP during non rainfall days. Coniferous forested watersheds showed higher value of TN and TP concentration. Concentrations of BOD and TP in early March (p<0.01) were affected by melt water flow input in spring season. Significant differences (p<0.01) in concentrations were observed in BOD and TOC, indicating seasonal rainfall and vegetation growth impacts on forest stream quality. Concentration of TN and TP showed significant positive correlation, and weak negative correlation was found in the concentration of BOD and TOC. It is expected that result of forest stream water on non rainfall days could be basic information in managing non-point source from forest watersheds.

• Journal of Soil and Groundwater Environment
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• v.16 no.3
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• pp.38-47
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• 2011

Groundwater monitoring data from the National Groundwater Monitoring Stations, a total of 320 stations, were analyzed to identify the response of water level and quality to the Odaesan earthquake (M4.9) occurred in January 2007. Among the total of eight stations responded to the earthquake, five wells showed water-level decline, and in three wells, water level rose. In terms of recovery, water levels in four stations had recovered to the original level in five days, but not in the rest four wells. The magnitude of water-level change shows weak relations to the distance between the earthquake epicenter and the groundwater monitoring station. However, the relations to the transmissivities of monitored aquifer in the station with the groundwater change were not significant. To implement the earthquake monitoring system through the groundwater monitoring network, we still need to accumulate the long-term monitoring data and geostatistically analyze those with hydrogeological and tectonic factors.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.6
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• pp.551-556
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• 2004

Coagulation process is one of the most important processes in water treatment procedures for stable and economical operation, and coagulant dosing of this process for most plants is generally determined by the jar test. However, this method does not only take a long time to analyze and get the result but also has difficulties in applying to automatic control. This paper shows the feasibility of applying neural network to control the coagulant dosing automatically in water treatment plant. To be specific, the predicted results of the neural network model is shown to be similar to that of jar test. The input variables for learning the neural network are turbidity, water temperature, pH, and alkalinity. Combining the neural network and SCD(Streaming Current Detector) for feedforward and feedback control of injecting coagulant, a rapid change of the raw water quality can be accommodated.

• Journal of Korean Society of Water and Wastewater
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• v.25 no.3
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• pp.407-417
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• 2011

Nowadays, the high land use, mainly used for urbanization, is affecting runoff loads of non-point pollutants to increase. According to this fact, increasing runoff loads seems like to appear that it contributes to high ratio of pollution loads in the whole the pollution loads and that this non-point source is the main cause of water becoming worse quality. Especially, concentrated pollutants on the impermeable roads run off to the public water bodies. Also the coefficient of runoff from roads is high with a fast velocity of runoff, which ends up with consequence that a lot of pollutants runoff happens when it is raining. Therefore it is very important project to evaluate the quantity of pollutant loads. In this study, I computed the pollutant loadings depending on time and rainfall to analyze characteristics of runoff while first flush storm water and evaluated the runoff time while first flush storm water and rainfall based on the change in curves on the graph. I also computed contribution ratio to identify its impact on water quality of stream. I realized that the management and treatment of first flush storm water effluents is very important for the management of road's non-point source pollutants because runoff loads of non-point source pollution are over the 80% of whole loads of stream. Also according to the evaluation of runoff loads of first flush storm water for SS, run off time was shown under the 30 minute and rainfall was shown under the 5mm which is less than 20% of whole rainfall. These are under 5mm which is regarded amount of first flush storm water by the Ministry of Environment and it is judged to be because run off by rainfall is very fast on impermeable roads. Also, run off time and rainfall of BOD is higher than SS. Therefore I realized that the management of non-point source should be managed and done differently depending on each material. Finally, the contribution ratio of pollutants loads by rainfall-runoff was shown SS 12.7%, BOD 12.7%, COD 15.9%, T-N 4.9%, T-P 8.9%, however, the pollutants loads flowing into the steam was shown 4.4%. This represents that the concentration of non-point pollutants is relatively higher and we should find the methodical management and should be concerned about non-point source for improvement on water quality of streams.

• Korean Journal of Ecology and Environment
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• v.39 no.3 s.117
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• pp.296-309
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• 2006

This study aimed to analyze water quality (temperature, secchi depth, DO, $NH_4$, $NO_3$, $PO_4$, TN, TP, chlorophyll a) and trophic state index during the period of year 2000 ${\sim}$ 2004 in Lake Juam, Lake Dongbok and Lake Youngsan. Lakes Juam and Dongbok except Lake Youngsan were stratified during warm seasons. Water turbidity estimated by secchi disk depth was the highest in Lake Youngsan compared with other lakes. DO concentrations were low in the bottom water when chlorophyll a was high in Lake Juam and Dongbok. Nutrient concentrations were higher in Lake Youngsan than other lakes whereas chlorophyll a was highest in Lake Dongbok. Lake Youngsan was the most eutrophic compared to other two lakes based on the Trophic State Idex (TP) and TSI (SD), The TSI (CHL) was high but the TSI (TP) were low in Lake Juam and Dongbok. These results suggest phytoplankton may be limited by phosphates (P) in Lake Juam and Dongbok whereas light availability in the water column may affect growth of phytoplankton in Lake Youngsan.

• Journal of Wetlands Research
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• v.24 no.1
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• pp.25-37
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• 2022

Climate change is becoming increasingly unpredictable. This has led to changes in various systems such as ecosystems, human life and hydrological cycles. In particular, the recent unpredictable climate change frequently causes extreme droughts and torrential rains, resulting in complex water resources disasters that cause water pollution due to inundation and retirement rather than primary disasters. SWAT was used as a watershed model to analyze future runoff and pollutant loads. The climate scenario analyzed the RCP4.5 climate scenario of the Meteorological Agency standard scenario (HadGEM3-RA) using the normal quantitative mapping method. Runoff and pollutant load analysis were performed by linkage simulation of climate scenario and watershed model. Finally, the results of application and verification of linkage model and analysis of future water quality change due to climate change were presented. In this study, we simulated climate change scenarios using artificial neural networks, analyzed changes in water temperature and turbidity, and compared the results of dams with artificial neural network results through W2 model, a reservoir water quality model. The results of this study suggest the possibility of applying the nonlinearity and simplicity of neural network model to Hapcheon dam water quality prediction using climate change.

• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.473-487
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• 2023

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.

• Tribology and Lubricants
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• v.33 no.6
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• pp.263-268
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• 2017

The significance of maintaining the soil environment is gradually increasing owing to soil and underground water contamination by petroleum leak accidents. However, the purification of soil is an expensive and more time-consuming process than the purification of contaminated water and air. Moreover, determining the source and people responsible for soil pollution gets often embroiled in legal conflicts, further delaying the cleanup process of the contaminate site. Generally, TPH (total petroleum hydrocarbon) pattern analysis is used to determine the petroleum species and polluter responsible for soil contamination. However, this process has limited application for petroleum products with a similar TPH pattern. In this study, we analyze the TPH pattern and specific sectional ratio (${\sim}C_{10}$, $C_{10}-C_{12}$, $C_{12}-C_{36}$, and $C_{36}{\sim}$) of various domestic petroleum products to identify the petroleum product responsible for soil contamination. Also, we perform BTEX (benzene, toluene, ethyl benzene, xylene) quantitative analysis and determine B:T:E:X ratio using GC-MS. The results show that gasoline grade 1 and 2 have a similar TPH pattern but different BTEX values and ratios. This means that BTEX analysis can be used as a new method to purify soil pollution. This complementary TPH and BTEX method proposed in this study can be used to identify the petroleum species and polluters present in the contaminated soil.