• Journal of Environmental Health Sciences
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• v.45 no.6
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• pp.622-629
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• 2019

Objectives: The occurrence of norovirus food poisoning in South Korea has been reported since 2003. This study was performed to investigate the characteristics of norovirus food poisoning outbreaks in Korea from 2006 to 2015 and to analyze the relationship between these outbreaks and climate factors. Methods: Data on norovirus food poisoning outbreaks were obtained from the Korea Ministry of Food and Drug Safety. Data on climate factors were obtained from the Korea Meteorological Administration. Frequency analysis and Pearson's correlation analysis were adopted for this study. Results: During the study period, norovirus was the greatest contributing factor of food poisoning outbreaks. Approximately half of the outbreaks of norovirus food poisoning occurred in winter. Average temperature, highest and lowest temperatures, precipitation, number of days with rainfall, and humidity all had a significant negative correlation with monthly number of outbreaks of norovirus food poisoning (p<0.05). Among these, the lowest and average temperature showed higher correlation coefficients. However, the sum of the outbreaks in spring and autumn was similar to that of winter, and more than one-third occurred in group meal-service settings, including school lunches. This was strongly assumed as the use of norovirus-contaminated groundwater for preparation of meals in some settings. Conclusion: The cold and dry of the winter season in Korea may assist the transmission of norovirus. Also, the use of groundwater in group meal service is suspected of inducing a larger scale of norovirus food poisoning. Both health authorities and community-based prevention and control measures are required to respond to these complex etiological outbreaks.

• Journal of Environmental Science International
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• v.23 no.4
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• pp.637-647
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• 2014

Quantitative assessment of groundwater level change under extreme event is important since groundwater system is directly affected by drought. Substantially, groundwater level fluctuation reveals to be delayed from several hours to few months after raining according to the aquifer characteristics. Groundwater system in Jeju Island would be also affected by drought and almost all regions were suffered from a severe drought during summer season (July to September) in 2013. To estimate the effect of precipitation to groundwater system, monthly mean groundwater levels in 2013 compared to those in the past from 48 monitoring wells belong to be largely affected by rainfall(Dr) over Jeju Island were analyzed. Mean groundwater levels during summer season recorded 100 mm lowered of precipitation compared to the past 30 years became decreased to range from 2.63 m to 5.42 m in southern region compared to the past and continued to December. These decreasing trends are also found in western(from -1.21 m to -4.06 m), eastern(-0.91 m to -3.24 m), and northern region(from 0.58 m to -4.02 m), respectively. Moreover, the response of groundwater level from drought turned out to be -3.80 m in August after delaying about one month. Therefore, severe drought in 2013 played an important role on groundwater system in Jeju Island and the effect of drought for groundwater level fluctuation was higher in southern region than other ones according to the regional difference of precipitation decrease.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.13 no.5
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• pp.81-89
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• 2010

This study was conducted to evaluate the effects of early revegetation by analyzing the characteristics of germination and growth of Chrysanthemum zawadskii using vegetation-plant in rock slopes. After making up a growing basis of approximately 20-cm depth and 10-cm diameter by using a boring machine, the surface of rock slopes was planted with vegetation-plant. The number of germinating populations by soil media was 41 in H.s, 4 in T.s, 3 in M.s, and 0 in M.g.s. The germination rate (%) by soil media was 20.0% in H.s, 3.3% in T.s, 2.5% in M.s and 0% in M.g.s. In monthly changes of growth rate, the aspect was northwest direction, the soil media was H.s, and the treatment was microorganism plot. The main factors affecting survivorship and growth of population were soil media and treatment plot. The interaction between each factor had a good effects in bearing x treatment plot, soil media x treatment plot. but, it is recommended that the mulching of vegetation plant is highly needed to help the germination of seed and growth of vegetation because of loss of seed and soil media occurred due to rainfall. Therefore, The result suggests that the revegetation technique using boring in rock slope was very efficient in respect of the early revegetation and the landscape.

• Journal of Korea Water Resources Association
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• v.37 no.10
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• pp.813-822
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• 2004

This study quantifies and compares the drought return and duration characteristics by applying the Poisson process as well as based on by analyzing the observed data directly. The drought spatial distributions derived for the Gyunggi province are also compared. The monthly rainfall data are used to construct the SPI as a drought index. Especially, this study focuses on the evaluation of the Poisson process model when applying it to various data lengths such as in the spatial analysis 'of drought. Summarizing the results are as follows. (1) The Poisson process is found to be effective for the quantification of drought, especially when the data length is short. When applying the Poisson process, two neighboring sites are found insensitive to the data length to show similar drought characteristics, so the overall drought pattern becomes smoother than that derived directly from the observed data. (2) When the data length is very different site by site, the spatial analysis of drought based on a model application seems better than that based on the direct data analysis. This study also found more obvious spatial pattern of drought occurrence and duration when applying the Poisson process.

• Korean Journal of Ecology and Environment
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• v.37 no.3 s.108
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• pp.263-271
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• 2004

To collect the basic ecological information about the microbial food webs in eutrophic water system with different residence time, the monthly variation of bacterioplankon (bacteria and small-sized cyanobacteria) and nanoplankton (phytoplankton and protists) were examined from December 2000 to September 2001. Kyungan stream is shorter in resident time (ca.5.4 d) than Seokchon reservoir (ca.72 d), even though they showed the same pattern in precipitation. With the basic environments, we examined the biomass (standing crops and its carbon content) of each plankton collected from the surface water. Large-sized planktons flourished in the time of low temperature, while small planktons were in the time of the high temperature period. Especially, in the Kyungan stream with much disturbance by rainfall and outflow, high diversity showed in term of species and cell morphology, compared to that of Seokchon lake. The time-lag relationship remarkably showed between phytoplankton and bacteria in Seokchon reservoir, and between protists and bacteria in Kyungan stream, respectively.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.415-415
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• 2018

갈수관리를 효과적으로 수행하기 위해서는 하천유량을 예측할 수 있는 방안을 마련하는 것이 중요하다. 하천유량 예측을 위해서는 강수량에 대한 예측 값을 활용하는 방안이 가장 적합하다고 할 수 있으나 강수량 예측에 대한 불확실성은 하천유량 예측의 정확도 확보에 있어 한계로 작용하고 있다. 강수량 예측에 대한 불확실성 극복을 위해서는 다양한 강수 시나리오를 설정하여 활용하는 방안을 검토할 수 있으며, 유량 예측을 하고자 하는 유역에 대해 과거 발생했던 강수량이 반복된다는 가정 하에 유량 예측을 제한적으로 수행하고 있는 상황이다. 이와 함께 강수 시나리오의 다양성 확보 차원에서 하천유량을 예측하고자 하는 유역에 대해 가뭄빈도 강수량을 사전에 산정한 후 유량 예측 과정에 활용하는 방안도 고려해볼 수 있는 방안이다. 이에 본 연구에서는 2016년 수립된 수자원장기종합계획(국토교통부, 2016)에서 제시된 중 권역별 일 강수량 자료를 이용하여 중권역별로 월 강수량을 산정한 후 월별 가뭄빈도분석을 수행하였다. 1966~2015년까지의 기간에 대한 월 강수량 자료를 이용하여 월별로 가뭄빈도분석을 수행하였으며, 빈도분석 방법으로는 확률가중모멘트법을 이용하여 적정 분포형 결정 및 갈수빈도별 강수량을 산정하여 제시하였다. 이때 빈도 강수량의 재현기간은 총 7가지 빈도(2년, 5년, 10년, 20년, 50년, 80년, 100년)를 고려하였다. 산정된 빈도 강수량을 이용하여 월 유출모형에 적용함으로써 월 유출 전망 자료 생산이 가능하며, 금강수계의 용담댐유역에 시범 적용하여 그 결과를 검토하였다. 검토 결과, 중권역별로 산정된 월별 가뭄빈도 강수량을 활용한 하천유량 예측 방법은 갈수예보에 있어 유용한 정보를 제공할 수 있을 것으로 판단된다.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.1029-1037
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• 2020

The machine learning algorithm has been widely used in water-related fields such as water resources, water management, hydrology, atmospheric science, water quality, water level prediction, weather forecasting, water discharge prediction, water quality forecasting, etc. However, water quality prediction studies based on the machine learning algorithm are limited compared to other water-related applications because of the limited water quality data. Most of the previous water quality prediction studies have predicted monthly water quality, which is useful information but not enough from a practical aspect. In this study, we predicted the dissolved oxygen (DO) using recurrent neural network with long short-term memory model recurrent neural network long-short term memory (RNN-LSTM) algorithms with hourly- and daily-datasets. Bugok Bridge in Oncheoncheon, located in Busan, where the data was collected in real time, was selected as the target for the DO prediction. The 10-month (temperature, wind speed, and relative humidity) data were used as time prediction inputs, and the 5-year (temperature, wind speed, relative humidity, and rainfall) data were used as the daily forecast inputs. Missing data were filled by linear interpolation. The prediction model was coded based on TensorFlow, an open-source library developed by Google. The performance of the RNN-LSTM algorithm for the hourly- or daily-based water quality prediction was tested and analyzed. Research results showed that the hourly data for the water quality is useful for machine learning, and the RNN-LSTM algorithm has potential to be used for hourly- or daily-based water quality forecasting.

• Journal of Korean Society on Water Environment
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• v.27 no.6
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• pp.794-803
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• 2011

Self Organizing Map (SOM) was applied for pattern classification of hydrological and water quality data measured at Jangseong Reservoir on a monthly basis. The primary objective of the present study is to understand better data characteristics and relationship between the data. For the purpose, two SOMs were configured by a methodologically systematic approach with appropriate methods for data transformation, determination of map size and side lengths of the map. The SOMs constructed at the respective measurement stations for water quality data (JSD1 and JSD2) commonly classified the respective datasets into five clusters by Davies-Bouldin Index (DBI). The trained SOMs were fine-tuned by Ward's method of a hierarchical cluster analysis. On the one hand, the patterns with high values of standardized reference vectors for hydrological variables revealed the high possibility of eutrophication by TN or TP in the reservoir, in general. On the other hand, the clusters with low values of standardized reference vectors for hydrological variables showed the patterns with high COD concentration. In particular, Clsuter1 at JSD1 and Cluster5 at JSD2 represented the worst condition of water quality with high reference vectors for rainfall and storage in the reservoir. Consequently, SOM is applicable to identify the patterns of potential eutrophication in reservoirs according to the better understanding of data characteristics and their relationship.

• Journal of Korean Society on Water Environment
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• v.27 no.3
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• pp.264-272
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• 2011

The objective of this study was to develop a model for predicting long-term runoff in a basin using the ensemble streamflow prediction (ESP) technique and review its reliability. To achieve the objective, this study improved not only the ESP technique based on the ensemble scenario analysis of historical rainfall data but also conventional ESP techniques used in conjunction with qualitative climate forecasting information, and analyzed and assessed their improvement effects. The model was applied to the Geum River basin. To undertake runoff forecasting, this study tried three cases (case 1: Climate Outlook + ESP, case 2: ESP probability through monthly measured discharge, case 3: Season ESP probability of case 2) according to techniques used to calculate ESP probabilities. As a result, the mean absolute error of runoff forecasts for case 1 proposed by this study was calculated as 295.8 MCM. This suggests that case 1 showed higher reliability in runoff forecasting than case 2 (324 MCM) and case 3 (473.1 MCM). In a discrepancy-ratio accuracy analysis, the Climate Outlook + ESP technique displayed 50.0%. This suggests that runoff forecasting using the Climate Outlook +ESP technique with the lowest absolute error was more reliable than other two cases.

• Korean Journal of Environmental Agriculture
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• v.41 no.3
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• pp.177-184
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• 2022

BACKGROUND: Recently, the inflow of nonpoint pollutants into rivers caused by rapid urban and industrialization promotes the proliferation of algae, which causes eutrophication of rivers. This study was conducted to evaluate the seasonal variation of water quality characteristics and cryptomonads growth in the Oncheon River. METHODS AND RESULTS: The water quality and distribution characteristics of cryptomonads in the Oncheon River were investigated monthly for 12 months from January 2021. The cell number of cryptomonads was intensively developed in January-April, and it decreased sharply in the summer with heavy rainfall. In particular, cryptomonads moved to the downstream side of the river depending on the time, and as a result, significant differences were shown for each investigation point. The Korean trophic state index (Tsi_KO) in Oncheon River was classified as eutrophy all year round, indicating that cryptomonads can grow year-round. Distribution characteristics of cryptomonads in Oncheon River showed high correlations with DO (r=0.678), BOD (r=0.826) and chlorophyll-a (r=0.613) in water. CONCLUSION(S): In order to reduce cryptomonads in the Oncheon River, it is judged that a complex countermeasure considering the residence time, insolation and precipitation along with water quality factors is required.