• Journal of Korean Society on Water Environment
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• v.29 no.6
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• pp.762-776
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• 2013

Load duration curve was applied to determine important water quality parameter control term for improvement of Paldang lake water quality. Load duration curve was analyzed with long term data from 1985 to 2012 including water quality, flow rate and climate state of Paldang water environment. From the result of flow rate patterns of paldang lake, differences between high and low flow rate of each year showed tendency of increase because rainfall characteristics of paldang lake watershed were changed by climate exchange. Both of land use state of upper Paldang lake watershed and number of limit excess from load duration curve indicated that seasonal action related with land use such as agricultural fertilizer distribution in upper watershed affected Paldang lake water quality. So focused BOD (biological oxygen demand) management during spring season from march to June is required to control organic materials in Paldand lake. The main affecting factor of TOC (total organic carbon) increase in Paldang lake was initial rainfall after march. T-N (total nitrogen) kept increasing during research period, so enhancement of T-N standard is needed to T-N control. Initial rainfall and increase of temperature during spring season from March to June showed a positive correlation with TP (total phosphorus) and Chl-a, respectively.

• Journal of Wetlands Research
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• v.16 no.1
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• pp.33-39
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• 2014

The purpose of this study is to monitor the rainwater flowing from the roof of buildings and to maximize the effectiveness of the rainwater storage. This study also analyses the changes in rainwater characteristics before and after subsequent chlorination disinfection. The stored rainwater was disinfected by chlorine and then analyzed for COD, TN, TP, enteric bacteria, and general microbial population changes over time. There was an observed 99% reduction of enteric bacteria and common microbes within two weeks after chlorine injection. Thus, chlorine disinfection of rainwater improves water quality for long-term storage and future use.

• Journal of Wetlands Research
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• v.18 no.1
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• pp.58-67
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• 2016

This study was performed to investigate the long-term changes in water quality and benthic ecology around the Nakdong River Estuary. The effect of the estuarine barrage on the ecosystem was also evaluated. The water quality was interpreted using the field survey (2013 and 2014) and monitoring data (MOE, 1989~2013) and the macrobenthic-fauna was investigated through analysis of the field survey data (2014) and literatures review (1985~2013). The long-term variation of water quality of Nakdong River generally showed increased nutrient concentration with decreased discharge, while abrupt influence of the barrage construction was not observed. However, the nutrient and organic matter concentration inside the barrage distinctly was higher than the concentration outside the barrage because the mixing of fresh and seawater was limited by the barrage. Especially, in the period of low discharge during winter, the Chlorophyll-a concentration clearly increased more in the downstream inside the barrage, showing the barrage effect. In other words, stagnant effect caused by barrage construction had an effect on the water quality degradation in dry seasons. As for the benthic ecology inside barrage after barrage construction, molluscans and brackish-water crustaceans disappeared. Outside the barrage, benthic ecosystem has deteriorated and the small-sized organic indicative species like Prionospio membranacea, Pseudopolydora kempi, Sinocorophium sinensis became dominant due to several construction such as Myeong-Gi Bridge, Airport construction, industrial complex after the Nakdong barrage construction.

• Journal of Korean Society on Water Environment
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• v.39 no.1
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• pp.46-60
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• 2023

Climate change causes fluctuations in water quality in the aquatic environment, which can cause changes in water circulation patterns and severe adverse effects on aquatic ecosystems in the future. Therefore, research is needed to predict and respond to water quality changes caused by climate change in advance. In this study, we tried to predict the dissolved oxygen (DO), chlorophyll-a, and turbidity of the Paldang reservoir for about two weeks using long short-term memory (LSTM) and gated recurrent units (GRU), which are deep learning algorithms based on recurrent neural networks. The model was built based on real-time water quality data and meteorological data. The observation period was set from July to September in the summer of 2021 (Period 1) and from March to May in the spring of 2022 (Period 2). We tried to select an algorithm with optimal predictive power for each water quality parameter. In addition, to improve the predictive power of the model, an important variable extraction technique using random forest was used to select only the important variables as input variables. In both Periods 1 and 2, the predictive power after extracting important variables was further improved. Except for DO in Period 2, GRU was selected as the best model in all water quality parameters. This methodology can be useful for preventive water quality management by identifying the variability of water quality in advance and predicting water quality in a short period.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.365-368
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• 2002

In spite of considerable advances in water quality control measures within lake, many basic questions concerning an eutrophication still remains unanswered and it becomes obvious that an extensive limnological database is needed for the inter-comparison between bodies of water and for the assessment of the status of lake water quality. In order to diagnose the water environment and assess the changes of the water quality, Wangkung irrigation reservoir was investigated by a long-term monitoring program for the physical, chemical and biological water quality parameters. In addition, these data was used to determine the design elements of natural purification facilities.

• Membrane and Water Treatment
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• v.10 no.5
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• pp.339-352
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• 2019

Long term water quality change was analyzed to evaluate the effect of the Total Maximum Daily Load (TMDL) policy. A trend analysis was performed for biochemical oxygen demand (BOD) and total phosphorus (TP) concentrations data monitored at the outlets of the total 41 TMDL unit watersheds of the Nakdong River in the Republic of Korea. Because water quality data do not usually follow a normal distribution, a nonparametric statistical trend analysis method was used. The monthly mean values of BOD and TP for the period between 2004 and 2015 were analyzed by the seasonal Mann-Kendall test and the locally weighted scatterplot smoother (LOWESS). The TMDL policy effect on the water quality change of each unit watershed was analyzed together with the results of the trend analysis. From the seasonal Mann-Kendall test results, it was found that for BOD, 7.8 % of the 41 points showed downward trends, 26.8 % and the rest 65.9% showed upward and no trends. For TP, 51.2% showed no trends and the rest 48.8% showed downward trends. From the LOWESS analysis results, TP began to decrease in most of the unit watersheds from mid-2010s when intensive chemical treatment processes were introduced to existing wastewater treatment plants. Overall, for BOD, relatively more points were improved in the main stream compared to the points of the tributaries although overall trends were mostly no trend or upward. For TP, about half of the points were improved and the rest showed no trends.

• Journal of the Korean Society of Marine Environment & Safety
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• v.15 no.4
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• pp.315-328
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• 2009

Long-term trends and distribution patterns of water quality were investigated in the Garolim coastal areas of Yellow Sea, Korea from 1998 to 2007. Water samples were collected at 3 stations and physicochemical parameters were analyzed including water temperature, salinity, suspended solids(SS), chemical oxygen demand(COD), dissolved oxygen(DO) and nutrients. Spatial distribution patterns were not clear among stations but the seasonal variations were distinct except pH and ammonia. The trend analysis by principal component analysis(PCA) during twenty years revealed the significant variations in water quality in the study area. Annual water qualities were clearly classified into 4 clusters by PCA; year cluster 1997, 1998 and 2000-2002, 1999 and 2003-2006/2008. By this multi-variate analysis the annual trends were summarized as follows; In recent years, salinity increased, whereas dissolved inorganic nitrogen, nitrate nitrogen and COD decreased and water quality generally continued to be in good condition in Gsrolim coastal areas without inflow of freshwater from land. Garolim coastal areas are required to be conserved continuously as important coastal areas for fisheries.

• Wind and Structures
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• v.26 no.2
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• pp.69-74
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• 2018

Nowadays, using math logic in great civil projects is considered by the clients to achieve the goals of project including quality optimization, costs, avoiding individual, emotional and political decision making, long-term and short-term goals and they are the main requirements of each project and should be considered by the decision makers to avoid the illogical decision making applied on the majority of civil projects and this imposes great financial and spiritual costs on our country. The present study attempts to present one of the civil projects (Ghasre Shirin storage dam) whose client was not ministry of energy for the first time and the short-term and long-term goals of the private sector were applied based on the triangle of quality, cost and time. Also, the math logic and model (multi-criteria decision making method and decision making matrix) is used in one of the most important sections of project, sealing element, policies and new materials (Geosynthetics) are considered and this leads to suitable decision making in this regard. It is worth to mention that this method is used for other sections of a dam including body, water diversion system, diaphragm and other sectors or in other civil projects of building, road construction, etc.

• Journal of the Korean Society of Marine Environment & Safety
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• v.15 no.4
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• pp.297-313
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• 2009

Long-term trends and distribution patterns of water quality were investigated in the Gunsan coastal areas of Yellow Sea, Korea from 1972 to 2006. Water samples were collected at 6 stations and physicochemical parameters were analyzed including water temperature, salinity, suspended solids(SS), chemical oxygen demand(COD), dissolved oxygen(DO) and nutrients. Spatial distribution patterns of temperature, DO and SS were not clear among stations but the seasonal variations were distinct except COD and SS. The trend analysis by principal component analysis(PCA) during 24 years revealed the significant variations in water quality in the study area. Spatial water qualities were clearly classified into 3 clusters by PCA; station cluster 1, 2~4, and 5~6. Annual water qualities were clearly classified into 4 surface water clusters and 5 bottom water clusters by PCA. By this multi-variate analysis. The annual trends were summarized as follows; Salinity, pH and DO tended to increase since late 1970's, COD to increase since 1987, and SS to decrease and nutrients to increase in Gunsan coastal waters due to the input of fresh water from land same as in Kyoungin coastal area, Asan coastal area and Choensoo bay.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1283-1293
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• 2022

The purpose of this study is to predict residual chlorine in order to maintain stable residual chlorine concentration in sedimentation basin by using artificial intelligence algorithms in water treatment process employing pre-chlorination. Available water quantity and quality data are collected and analyzed statistically to apply into mathematical multiple regression and artificial intelligence models including multi-layer perceptron neural network, random forest, long short term memory (LSTM) algorithms. Water temperature, turbidity, pH, conductivity, flow rate, alkalinity and pre-chlorination dosage data are used as the input parameters to develop prediction models. As results, it is presented that the random forest algorithm shows the most moderate prediction result among four cases, which are long short term memory, multi-layer perceptron, multiple regression including random forest. Especially, it is result that the multiple regression model can not represent the residual chlorine with the input parameters which varies independently with seasonal change, numerical scale and dimension difference between quantity and quality. For this reason, random forest model is more appropriate for predict water qualities than other algorithms, which is classified into decision tree type algorithm. Also, it is expected that real time prediction by artificial intelligence models can play role of the stable operation of residual chlorine in water treatment plant including pre-chlorination process.