• Journal of Korean Society on Water Environment
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• v.38 no.6
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• pp.292-305
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• 2022

The Yeongsan River, one of the four largest rivers in South Korea, has been facing difficulties with water quality management with respect to algal bloom. The algal bloom menace has become bigger, especially after the construction of two weirs in the mainstream of the Yeongsan River. Therefore, the prediction and factor analysis of Chlorophyll-a (Chl-a) concentration is needed for effective water quality management. In this study, Chl-a prediction model was developed, and the performance evaluated using machine and deep learning methods, such as Deep Neural Network (DNN), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost). Moreover, the correlation analysis and the feature importance results were compared to identify the major factors affecting the concentration of Chl-a. All models showed high prediction performance with an R² value of 0.9 or higher. In particular, XGBoost showed the highest prediction accuracy of 0.95 in the test data.The results of feature importance suggested that Ammonia (NH₃-N) and Phosphate (PO₄-P) were common major factors for the three models to manage Chl-a concentration. From the results, it was confirmed that three machine learning methods, DNN, RF, and XGBoost are powerful methods for predicting water quality parameters. Also, the comparison between feature importance and correlation analysis would present a more accurate assessment of the important major factors.

• Journal of Korean Society on Water Environment
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• v.39 no.6
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• pp.475-490
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• 2023

Chemical water quality suitability for species (Ephemera strigata, Ephemera separigata, and Ephemera orientalis-sachalinensis group) of the mayfly genus Ephemera (Order Ephemeroptera) was analyzed with probability distribution models (Exponential, Normal, Lognormal, Logistic, Weibull, Gamma, Beta, Gumbel). Data was collected from 23,957 sampling units of 6,664 sites in Korea from 2010 to 2021. E. orientalis-sachalinensis occurred at the range of BOD₅ 0.3~11.1 mg/L (the best-fit Lognormal model); T-P 0.007~0.769 mg/L (the Gumbel model); TSS 0.4~142.2 mg/L (the Lognormal model). E. strigata occurred at the range of BOD₅ 0.4~7.4 mg/L (the Gumbel model); T-P 0.007~0.254 mg/L (the Lognormal model); TSS 0.4~17.1 mg/L (the Lognormal model). E. separigata occurred at the range of BOD₅ 0.4~2.6 mg/L (the R-Weibull model); T-P 0.007~0.134 mg/L (the Lognormal model); TSS 0.7~10.0 mg/L (the Lognormal model). Habitat suitability range of E. orientalis-sachalinensis was estimated to be 0.4~1.9 mg/L (BOD₅), 0.024~0.086 mg/L (T-P), 2.5~22.4 mg/L (TSS); that of E. strigata was 0.4~0.7 mg/L (BOD₅), 0.007~0.018 mg/L (T-P), 0.0~1.7 mg/L (TSS); that of E. separigata was 0.0~0.4 mg/L (BOD₅), 0.000~0.015 mg/L (T-P), 0.5~3.1 mg/L (TSS). In a relative comparision, E. orientalis-sachalinensis was estimated to be eurysaprobic, and narrowly adapted in high levels of T-P and TSS, E. strigata was estimated to be oligosaprobic and adapted in low levels of T-P and TSS, and E. separigata was estimated to be stenooligosaprobic and widely adapted in low level of T-P and TSS.

• Journal of Environmental Science International
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• v.18 no.9
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• pp.1035-1043
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• 2009

High turbid water in the River has been one of the major concerns to the downstream residence. Especially in the Nakdong River basin severe turbid water problem occurred in year 2002 and 2003 due to the typhoon Rusa and Maemi consecutively. The main objective of this study is to develop turbid water management system in reservoir downstream of the Nakdong River combining physically based semi-distributed hydrologic simulation model SWAT with 1-dimensional dynamic water quality simulation model. SWAT model covers the area from the upstream of the Imha and Andong reservoir to the Gumi gage station for the purpose of estimating flow rates and suspended sediment of the tributaries. From year 1999 to 2007 runoff simulation for 8 years $R_{eff}$ and $R^2$ ranges $0.46{\sim}0.9$, $0.54{\sim}0.99$ respectively. Through the linkage of models, outputs of SWAT model such as suspended sediment and flow rates of the tributaries can be incorporated into the 1-dimensional dynamic water quality simulation model, KoRiv1 to support joint reservoir operation considering the turbidity released from Imha and Andong reservoir. The applicability of model simulation has been tested for year 2006 and compared with measured data.

• Journal of Korean Society on Water Environment
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• v.36 no.6
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• pp.636-650
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• 2020

A modeling system that can consider the overall water environment and be used to integrate hydrology, water quality, and aquatic ecosystem on a watershed scale is essential to support decision-making in integrated water resources management (IWRM). In adapting imported models for evaluating the unique water environment in Korea, a platform perspective is becoming increasingly important. In this study, a modeling platform is defined as an ecosystem that continuously grows and provides sustainable values through voluntary participation- and interaction-of all stakeholders- not only experts related to model development, but also model users and decision-makers. We assessed the conceptual values provided by the IWRM modeling platform in terms of openness, transparency, scalability, and sustainability. I We also reviewed the technical aspects of functional and spatial integrations in terms of socio-economic factors and user-centered multi-scale climate-forecast information. Based on those conceptual and technical aspects, we evaluated potential modeling platforms such as Source, FREEWAT, Object Modeling System (OMS), OpenMI, Community Surface-Dynamics Modeling System (CSDMS), and HydroShare. Among them, CSDMS most closely approached the values suggested in model development and offered a basic standard for easy integration of existing models using different program languages. HydroShare showed potential for sharing modeling results with the transparency expected by model user-s. Therefore, we believe that can be used as a reference in development of a modeling platform appropriate for managing the unique integrated water environment in Korea.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.1
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• pp.107-120
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• 2019

Reservoir water level data identify the current water storage of the reservoir, and they are utilized as primary data for management and research of agricultural water. For the reservoir storage management, Korea Rural Community Corporation (KRC) installed water level stations at around 1,600 agricultural reservoirs and has been collecting the water level data every 10 minutes. However, various kinds of outliers due to noise and erroneous problems are frequently appearing because of environmental and physical causes. Therefore, it is necessary to detect outlier and improve the quality of reservoir water level data to utilize the water level data in purpose. This study was conducted to detect and classify outlier and normal data using two different models including the threshold model and the artificial neural network (ANN) model. The results were compared to evaluate the performance of the models. The threshold model identifies the outlier by setting the upper/lower bound of water level data and variation data and by setting bandwidth of water level data as a threshold of regarding erroneous water level. The ANN model was trained with prepared training dataset as normal data (T) and outlier (F), and the ANN model operated for identifying the outlier. The models are evaluated with reference data which were collected reservoir water level data in daily by KRC. The outlier detection performance of the threshold model was better than the ANN model, but ANN model showed better detection performance for not classifying normal data as outlier.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.5
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• pp.35-42
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• 2011

This study is to check the applicability of SWAT-APEX (Soil and Water Assessment Tool-Agricultural Policy / Environmental eXtender) model as combined watershed and field models by applying the APEX to paddies in a watershed (465.1 $km^2$) including Yedang reservoir. Firstly, the SWAT were calibrated with 3 years (2000~2002) daily streamflow and monthly water quality (T-N and T-P) data, and validated for another 3 years (2003~2005) data. The average Nash-Sutcliffe model efficiency (ME) of streamflow during validation was 0.73, and the coefficient of determination ($R^2$) of T-N and T-P were 0.77 and 0.73 respectively. Next, running the SWAT-APEX model with the SWAT calibrated parameters for paddies, the $R^2$ of T-N and T-P were 0.80 and 0.76 respectively. The results showed that SWAT-APEX model was more correctly predicted for T-N and T-P loads than SWAT model. The difference results between watershed and field models was predicted to have substantial impact on NPS loads, especially on T-N and T-P loads. Therefore, to improve negative NPS load simulations should be considered the model characteristics as simulating mechanism to properly select the NPS model for agricultural watershed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.1
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• pp.130-135
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• 2007

In order to examine the corrosiveness of tap water, we studied methods calculating various indices including calcium carbonate saturation indices, using RTW model and LPLWIN model. Indices such as LI, RI and AI could be computed using the RTW model, whereas the LPLWIN model could find indices as LI, LR and CCPP. With water quality data obtained from tap water of Han River and Nak-Dong River watersheds, based on the indices found from the models, the water quality of the Nak-Dong River is better than that of Han River in the point of resisting corrosiveness. Further, the water quality of winter is highly corrosive than that of summer, as long as the temperature rises up, the corrosiveness is reduced.

• Journal of Korean Society of Water and Wastewater
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• v.29 no.4
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• pp.511-517
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• 2015

Korea's modern waterworks began with construction of DDukdo water treatment plant in 1908 and has been growing rapidly along with the country's economic development. As a result, water supply rates have reached 98.5% based on 2013. Despite multilateral efforts for high-quality water supply, such as introduction of advanced water treatment process, expansion of waterworks infrastructure and so on, distrust for drinking tap water has been continuing and domestic consumption rate of tap water is in around 5% level and extremely poor comparing to advanced countries such as the United States(56%), Japan(52%), etc. Recently, the water management has been facing the new phase due to water environmental degradation caused by climate change, aging facilities, etc. Therefore, K-water has converted water management paradigm from the "clean and safe water" to the "healthy water" and been pushing the Smart Water City(SWC) Pilot Project in order to develop and spread new water supply models for consumers to believe and drink tap water through systematic water quality and quantity management combining ICT in the whole water supply process. The SWC pilot projects in Pa-ju city and Go-ryeong county were an opportunity to check the likelihood of the "smart water management" as the answer to future water management. It is needed to examine the necessity of smart water management introduction and nationwide SWC expansion in order to improve water welfare for people and resolve domestic & foreign water problems.

• Journal of Korea Water Resources Association
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• v.33 no.2
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• pp.145-157
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• 2000

The Water Quality Analysis Simulation Program 5 (WASP5) and HEC-2 models have been coupled and applied to find the possibility of simulation of long-term river water quality variation. The EUTR05 as a simulator of water quality simulation in WASPS model was used to simulate the water quality variables in the downstream of Geum-River from Daechung multi-purpose dam during the dry period. The water quality and flow rate conditions have been measured at the stage measurement stations located in the downstream of Geum-River from Daechung dam in December, 1998 and January and March, 1999. The water quality simulation model was calibrated with January data of 1999, and verified with December data of 1998 and March data of 1999. The trend of longitudinal variation of water quality variables simulated by model is consistent with that of measured water quality constituents except chlorophyll-a, $BOD_5,\;NH_3-N\;and\;PO_4-P$ simulated with March data of 1999. Furthennore, the chlorophyll a concentration in the mainstream of Geum-River was simulated by changing the concentrations of $PO_4-P$ and/or $NH_4-N$ flowing into the mainstream of Geum-River from Gabcheon and Mihocheon. The variation of chlorophyll a concentration in the mainstream was almost ignorable except only when $NH_3-N\;and\;PO_4-P$ concentrations decreased by 70% flow into the mainstream from Gabcheon and Mihocheon.

• Journal of Wetlands Research
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• v.6 no.3
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• pp.47-54
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• 2004

A hydraulically and hydrologically based estimation method of pollutant delivery load for water quality modeling is proposed. The proposed method works on grid basis and routes overland flows from one cell to the next following the maximum downslope directions. The method is able to consider spatially-varied data of source pollutant, topography, land slopes, soil characteristics, land use and aspects, which can be extracted from geographic information systems (GIS) and from digital elevation models (DEMs). Because of this feature, the proposed method can be expected to be used for evaluating the impacts of various practices on watershed management for water quality.