• Journal of Korean Society of Water and Wastewater
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• v.34 no.6
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• pp.481-493
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• 2020

Deep learning models, which imitate the function of human brain, have drawn attention from many engineering fields (mechanical, agricultural, and computer engineering etc). The major advantages of deep learning in engineering fields can be summarized by objects detection, classification, and time-series prediction. As well, it has been applied into environmental science and engineering fields. Here, we compiled our previous attempts to apply deep learning models in water-environment field and presented the future opportunities.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09b
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• pp.1170-1171
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• 2005

• Proceedings of the Korea Society of Environmental Biology Conference
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• 2002.05a
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• pp.77-77
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• 2002

• Proceedings of the Korea Environmental Mutagen Society Conference
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• 2004.11a
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• pp.143-143
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• 2004

• Environmental Engineering Research
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• v.7 no.2
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• pp.75-84
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• 2002

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.40-45
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• 2007

Water regulators in New Zealand have recognised the need to adapt water allocation regimes and water permit conditions to reflect the likelihood of lower catchment yield on the east coast from 2030 due to climate change. Water management mechanisms to protect the environment and maintain the reliability of other water users are currently being applied or assessed in Marlborough province. These include seasonal water quota based on spring aquifer status, linking water use to environmental triggers to avoid seawater intrusion or spring depletion; and redefining water permit entitlements to account for recharge variability.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.4
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• pp.67-74
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• 2016

Load Duration Curve (LDC) can be used as a method for load management of point and non-point pollution source because the LDC easily assesses the water quality corresponding to hydrological changes in a watershed. Recently, the application of LDC to total pollution load management is a growing interest in Korea. In this regard, A desktop-based LDC assessment system was developed in this study to provide convenience to users in water quality evaluation. The developed system can simply produce the LDC by using streamflow and water quality data involved in its database. Also, The system can quantitatively inform the success or failure of the achievement for a target water quality at monthly scale. Furthermore, seasonal water quality and point/non-point pollution load in a watershed can be estimated by this system. We expect that the developed system will contribute to establish local and national policies regarding water management and total pollution load management because of its advantages such as the pollution tracking investigation and the analysis of water quality and pollution loading amount in an ungauged watershed.

• Journal of Korean Society of Water and Wastewater
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• v.32 no.5
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• pp.421-434
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• 2018

Water supply/intake pumps operation use 70~80% of power costs in water treatment plants. In the water treatment plant, seasonal and hourly differential electricity rates are applied, so proper pump scheduling can yield power cost savings. Accordingly, the purpose of this study was to develop an optimal water supply pump scheduling scheme. An optimal operation method of water supply pumps by using genetic algorithm was developed. Also, a method to minimize power cost for water supply pump operation based on pump performance derived from the thermodynamic pump efficiency measurement method was proposed. Water level constraints to provide sufficient disinfection performance in a clearwell and reservoirs were calibrated. In addition, continuous operation time constraints were calibrated to prevent frequent pump switching. As a result of optimization, savings ratios during 7 days in winter and summer were 4.5% and 5.1%, respectively. In this study, the method for optimal water pump operation was developed to secure disinfection performance in the clearwell and to save power cost. It is expected that it will be used as a more advanced optimal water pump operation method through further studies such as water demand forecasting and efficiency according to pump combination.

• Journal of Environmental Health Sciences
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• v.35 no.6
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• pp.517-525
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• 2009

The water quality of Lake Shihwa had been rapidly deteriorating since 1994 due to wastewater input from the watersheds, limited water circulation and the lack of a wastewater treatment policy. In 2000, the government decided to open the tidal embankment and make a comprehensive management plan to improve the water quality, especially inflowing stream water around Shihwa and Banwol industrial complex. However, the water quality and microbial community have not as yet been fully evaluated. The purpose of this study is to investigate the influent water quality around the industrial area based on chemical and biological analysis, and collected surface water sample from the Siheung Stream, up-stream to down-stream through the industrial complex, Samples were collected in July 2009. The results show that the downstream site near the industrial complex had higher concentrations of heavy metals (Cu, Mn, Fe, Mg, and Zn) and organic matter than upstream sites. A combination of DGGE (Denaturing Gradient Gel Electrophoresis) gels, lists of K-WQI (Korean Water Quality Index), cluster analysis, MDS (Multi-Dimensional Scaling) and PCA (Principal Component Analysis) has demonstrated clear clustering between Siheung stream 3 and 4 and with a high similarity and detected metal reducing bacteria (Shewanella spp.) and biodegrading bacteria (Acinetobacter spp.). These results suggest that use of both chemical and microbiological marker would be useful to fully evaluate the water quality.

• 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.