• Magazine of the Korean Society of Agricultural Engineers
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• v.32 no.E
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• pp.1-19
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• 1990

Abstract Over the last several decades, crop production in the United States increased largely due to the extensive use of animal waste and fertilizers as plant nutrient supplements, and pesticides for crops pests and weed control. Without the application of animal waste best management, the use of animal waste can result in nonpoint source pollution from agricultural land area. In order to increase nutrient levels and decrease contamination from agricultural lands, nonpoint source pollution is responsible for water quality degradation. Nonpoint source pollutants such as animal waste, ferilizers, and pesticides are transported primarily through runoff from agricultural areas. Nutrients, primarily nitrogen and phosphorus, can be a major water quality problem because they cause eutrophic algae growth. In 1985, it was presented that Watershed/Water Quality Monitoring for Evaluation BMP Effectiveness was implemented for Nomini Creek Watershed, located in Westmoreland County, Virginia. The watershed is predominantly agricultural and has an aerial extent of 1505 ha of land, with 43% under cropland, 54% under woodland, and 3% as homestead and roads. Rainfall data was collected at the watershed from raingages located at sites PNI through PN 7. Streams at stations QN I and QN2 were being measured with V-notch weirs. Water levels at the stream was measured using an FW-l Belfort (Friez FWl). The water quality monitoring system was designed to provide comprehensive assessment of the quality of storm runoff and baseflow as influenced by changes in landuse, agronomic, and cultural practices ill the watershed. As this study was concerned with the Nomini Creek Watershed, the separation of storm runoff and baseflow measured at QNI and QN2 was given by the master depletion curve method, and the loadings of baseflow and storm runoff for TN (Total Nitrogen) and TP (Total Phosphorus) were analyzed from 1987 through 1989. The results were studied for the best management practices to reduce contamination and loss of nutrients, (e.g., total nitrogen and total phosphorus) by nonpoint source pollution from agricultural lands.

• Journal of Soil and Groundwater Environment
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• v.12 no.5
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• pp.64-72
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• 2007

Nationwide occurrence of arsenic in groundwater of Korea was investigated with the data from the groundwater quality monitoring stations. During 2001-2006, As has been quantitatively detected in 3.0 % of the total wells $(5.0{\sim}188{\mu}g/L)$, and its geographical distribution suggests 3 groups: an urbanized and industrialized area (Seoul and its neighbouring province), and two naturally occurring areas (Chungbuk and Gyeongnam provinces). Natural occurrence of As appears to be geologically related with Ogcheon metasedimentary rocks and Cretaceous volcanic rocks. Based on the results of the previous studies in the high As sites, the oxidation of sulfides can be a major control on As concentrations in groundwater in the mineralized and altered zone within the area of Cretaceous volcanic rocks. Desorption process under slightly high pH conditions may also be responsible for high As in groundwater in areas of Ogcheon metasedimentary rocks.

• Journal of Environmental Science International
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• v.27 no.11
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• pp.1029-1048
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• 2018

In this study, seasonal Mann - Kendall test method was applied to 12 stations of the water quality measurement network of Nam-River based on data of BOD, COD, TN and TP for 11 years from January 2005 to December 2015 The changes of water quality at each station were examined through linear trends and the tendency of water quality change during the study period was analyzed by applying the locally weighted scatter plot smoother (LOWESS) method. In addition, spatial trends of the whole Nam-River were examined by items. The flow-adjusted seasonal Kendall test was performed to remove the flow at the water quality measurement station. As a result, BOD, COD concentration showed "no trand" and TN and TP concentration showed "down trand" in regional Kendall test throughout the study period. BOD and TP concentration in "no trand", COD, and TN concentration showed an "up trand" tendency in Nam-River dam. LOWESS analysis showed no significant water quality change in most of the analysis items and stations, but water quality fluctuation characteristics were shown at some stations such as NR1 (Kyungho-River 1), NR2 (Kyungho-River 2), NR3 (Nam-River), NR6 (Nam-River 2A). In addition, the flow-adjusted seasonal Kendall results showed that the BOD concentration was "up trand" due to the flow at the NR3 (Nam-River) station. The COD concentration was "up trand" due to the flow at NR1 (Kyungho-River 1) and NR2 (Kyungho-River 2) located upstream of the Nam-River. The effect of influent flow on water quality varies according to each site and analysis item. Therefore, for the effective water quality management in the Nam-River, it is necessary to take measures to improve the water quality at the point where the water quality is continuously "up trand" during the study period.

• Journal of Environmental Science International
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• v.3 no.4
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• pp.357-365
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• 1994

Air pollution characteristics and the influence of sea breeze on air pollution concentration were studied using the data measured at 7 air quality continuous monitoring stations in Pusan, 1993. Maximum air pollution concentration in Pusan was Gamjeondong for $SO_2$, Sinpyeongdong for TSP, Daeyeondong for $O_3, Kwangbokdong for $NO_2$, Beomcheondong for CO and all substances were under annual ambient air quality standards. Increased rate of concentration for sea breeze was 24.4% for 502, 31.5% for TSP, 8.0% fort $O_3, 26.7% for $NO_2$, 15.7% for CO. Frequencies distribution of $SO_2$, TSP, $O_3$, $NO_2$, and CO concentration for sea breeze moved toward high concentration class.

• Journal of Korean Society for Atmospheric Environment
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• v.11 no.2
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• pp.199-209
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• 1995

The variations of TSP concentrations observed at Air Quality Monitoring Stations(AQMSs) in Seoul were analysed from 1986 to 1993. And those of Yellow Sand period were investigated to find out the characteristics between normal and Yellow Sand period. The TSP concentrations have begun lower than 150.mu.g/m$^{3}$ annual mean concentration at Gwanghwamun, Hannam-dong, and south river region since 1989, and air quality in Seoul was improved in 1991, but polluted again in Hannam-dong, and Seongsu-dong in 1992. Yellow sand phenomena of 1990 and 1993 were selected for case study. During the whole period in 1990, the TSP concentrations were exceeded over 300.mu.g/m$^{3}$, which is the upper limit of 24 hour concentration, at the center of city such as Mapo, Gileum-dong, sinseol-dong. But in 1993, the TSP concentrations got lower than 24 hour concentration, and air quality was highly improved.

• Journal of Environmental Science International
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• v.30 no.11
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• pp.967-977
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• 2021

From January 1, 2020, the International Maritime Organization has implemented a global regulation, known as IMO 2020, to reduce the sulfur content in fuel oil of ships from 3.5% to 0.5%. In this study, we used data from air monitoring stations to evaluate the change in air quality at New Port and North Port in Korea areas after the regulation was implemented. The concentration of SO₂ and NO₂ was higher in the port areas than in the surrounding areas due to exhaust gas from ships and vehicles. However, the SO₂ concentration decreased by more than 50% in the port area, demonstrating the efficiency and positive effect of the IMO 2020 sulfur limit.

• Journal of Korean Society on Water Environment
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• v.33 no.6
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• pp.640-649
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• 2017

The purpose of this study is the analysis of the water quality spatial characteristics for the main stream of Nakdong River in consideration of the tributary inflow. The flow and water quality (BOD, TOC, TP) data for 32 monitoring stations located in the main stream and the tributaries of Nakdong River were collected from 2003 to 2016. From the results of the flow and water quality analyses for each site, a status map of the flow and the water quality for Nakdong River was produced. The water quality of each river section was classified according to seven river-environment standards. The water quality changes in the main stream before and after the confluence were analyzed spatially. As a result, the water quality of Kumho River, in particular the Kumho B to Kumho C section, is the worst among the tributaries. In addition, the water quality grades of the lower streams such as Nam River and Miryang are worse than that of the upper streams of the Nakdong River. In the case of the main stream, the water quality grades of the sections between the Wicheon and Nam River confluences and the section from Nakbon L to Nakbon N are relatively poor.

• Journal of Korea Water Resources Association
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• v.38 no.7 s.156
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• pp.565-574
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• 2005

It is used water quality data that was measured at Pyeongchanggang real time monitoring stations in Namhan river. These characteristics were analyzed with the water qualify of rainy and nonrainy periods. TOC (Total Organic Carbon) data of rainy periods has correlation with discharge and shows high values of mean, maximum, and standard deviation. DO (Dissolved Oxygen) value of rainy periods is lower than those of nonrainy periods. Input data of the water quality forecasting models that they were constructed by neural network and neuro-fuzzy was chosen as the reasonable data, and water qualify forecasting models were applied. LMNN, MDNN, and ANFIS models have achieved the highest overall accuracy of TOC data. LMNN (Levenberg-Marquardt Neural Network) and MDNN (MoDular Neural Network) model which are applied for DO forecasting shows better results than ANFIS (Adaptive Neuro-Fuzzy Inference System). MDNN model shows the lowest estimation error when using daily time, which is qualitative data trained with quantitative data. The observation of discharge and water quality are effective at same point as well as same time for real time management. But there are some of real time water quality monitoring stations far from the T/M water stage. Pyeongchanggang station is one of them. So discharge on Pyeongchanggang station was calculated by developed runoff neural network model, and the water quality forecasting model is linked to the runoff forecasting model. That linked model shows the improvement of waterquality forecasting.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.2
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• pp.53-63
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• 2016

Monitoring of cyanobacteria bloom in reservoir systems is important for water managers responsible of water supply system. Cyanobacteria affect the taste and smell of water and pose considerable filtration problems at water use places. Harmful cyanobacteria bloom in reservoir have significant economic impacts. We develop a new method for estimating the cyanobacteria bloom using Landsat TM and ETM+ data. Developed model was calibrated and cross-validated with existing in situ measurements from Daecheong Reservoir's Water Quality Monitoring Program and Algae Alarm System. Measurements data of three stations taken from 2004 to 2012 were matched with radiometrically converted reflectance data from the Landsat TM and ETM+ sensor. Stepwise multiple linear regression was used to select wavelengths in the Landsat TM and ETM+ bands 1, 2 and 4 that were most significant for predicting cyanobacteria cell number and bio-volume. Based on statistical analysis, the linear models were that included visible band ratios slightly outperformed single band models. The final monitoring models captured the extents of cyanobacteria blooms throughout the 2004-2012 study period. The results serve as an added broad area monitoring tool for water resource managers and present new insight into the initiation and propagation of cyanobacteria blooms in Daecheong reservoir.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.6
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• pp.1311-1322
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• 1997

Performance management of ATM network is urgently required because a different quality of service should be guaranteed on each connection. A lot of performance measurement data increase the burden on agent systems and on managment stations. In this paper, an effective OAM-based performance monitoring and faulty node identification technique is proposed. A proposed VP Selection Algorithm reduces management-related traffic and when the indication of hard or soft failure state is detected, failed node is identified by Fault Identification Rule.