• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.6
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• pp.65-76
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• 2012

Agricultural reservoir water quality simulation model (ARSIM-rev) was developed in this study for water quality simulation of a small and shallow agricultural reservoir with limited observed water quality data. Developed ARSIM-rev is a zero-dimensional water quality model because of little spatial differences in water quality between stations in a small and shallow agricultural reservoir. ARSIM-rev used same water quality reaction equations with WASP except for several equations, and daily based input parameters such as settling rate, release rate from sediment, and light extinction coefficient changed yearly based input parameters in ARSIM-rev. A number of pre- and post-processors were developed such as auto calibration and scenario analysis for ARSIM-rev. CE-QUAL-W2, WASP, and developed ARSIM-rev were applied to Mansu agricultural reservoir to evaluate model performance, and ARSIM-rev demonstrated similar model performance with CE-QUAL-W2 and WASP when low number of observed data was used for agricultural reservoir water quality simulation. Overall, developed ARSIM-rev was feasible for water quality simulation in a small and shallow agricultural reservoir with limited observed water quality data, and it can simulate agricultural reservoir water quality precisely enough like common water quality model such as CE-QUAL-W2 and WASP within a limited time.

• Journal of Environmental Impact Assessment
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• v.15 no.1
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• pp.45-52
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• 2006

The purpose of this study is to assess spatiotemporal variation of coastal water quality according to time and location changes. For this we developed numerical marine trophic index base on four water quality components (chlorophyll, suspended solids, dissolved inorganic nitrogen and phosphorus) and applied this index to the water quality data measured in the korean coastal zone for the 7-years period from 1997 to 2003. Water quality data are obtained only at selected sites even though they are potentially available at any location. Therefore, in order to estimate spatial variation of coastal water quality, it is necessary to estimate the unknown values at unsampled locations based on observation data. In this study, we used IDW (Inverse Distance Weighted) method to predict water quality components at unmeasured locations and applied marine trophic index to predicted values obtained by IDW interpolation. The results of this study indicate that marine trophic index and spatial interpolation are useful for understanding spatiotemporal characteristics of coastal water quality.

• Journal of Korean Society on Water Environment
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• v.22 no.3
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• pp.427-430
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• 2006

Uncertainty is one of the key issues of the water quality management. Uncertainty occurs in the course of all water quality management stages including monitoring, modeling, and regulation enforcement. To reduce uncertainties of water quality monitoring, manualized monitoring methodology should be developed and implemented. In addition, long-term monitoring is essential for acquiring reliable water quality data which enables best water quality management. For the water quality management in the watershed scale, fate of pollutant including its generation, transport and impact should be considered while regarding each stage of water quality management as an unit process. Uncertainties of each stage of water quality management should be treated properly to prevent error propagation transferred to the next stage of management for successful achievement of water quality conservation.

• Water for future
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• v.14 no.3
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• pp.55-66
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• 1981

The theory and practice of water quality scoring and indexing are introduced. The monthly water analysis data are available for six stations long the down-stream Han River whthin the areal boundary of the Special City of Seoul. The data cover the period between 1975 and 1979 inclusive and contain the analytical findings on 37 water constituents including DO, BOD, temperature, total solids and etc. Sic parameters are selected form the 37 items, that, to the judgement of the writer, best reflect the water quality of the Han River. They are; dissolved oxggen saturation, pH, fecal coliform, total solids, BOD and nitrate+ammonia. For each of the six parameters, a subscore function is developed and graphically presented to facilitate the transform of a measurment of the arameter to a subscore on a common score(e.G. 0-100) The score of a sample is calculated as a fuction of the six subscores, using four different approaches; (1) the unweighted arithmetic water quality score, (2) the weighted arithmetic water quality score, (3)the unweighted multiplicative score and (4) the reduced (total) score. Independent of these calculated scores, the experts' score which is calculated by averaging the ratings of water quality experts is obtained and compared with each of the four calculated scores by means of the least square method. The experts' score compares most favorably with the "reduced" score with the correlation coefficient of 0.956 : therefore this method of water quality scoring is adopted to calculate the Han River water quality scores and indices. Water quality index data for Guiri, ukdo, Pokwangdong, Noryangjin, Yongdungpo and Kayang Stations, 1975-1979 are as follow: The overall water quality index data of the Han River between Guiri and Kayang Stations are found; 47.3 in 1976, 48.0 in 1977, 48.5 in 1978 and 54.7 in 1979, indicating the general trend towards water quality improvent in this part of the river, in terms of the increased water quality index by average 1.85 points per year during this period. Finally the optimum sampling frequencies distributed among the six stations, using an equation which takes into account the coefficients of variation of the water quality scores and indices arec calculated.alculated.

• Journal of Korean Society on Water Environment
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• v.21 no.6
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• pp.651-658
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• 2005

The Non-parametric Analysis is powerful in data test especially for the non- normality water quality data. The data at three monitoring stations of the Tam-Jin River were evaluated for their normality using Skewness, Q-Q plot and Shapiro-Willks tests. Various constituent of water quality data including temperature, pH, DO, SS, BOD, COD, TN and TP in the period of January 1994 to December 2004 were used as dataset. Shapiro-Willks normality test was carried out for a test 5% significance level. Most water quality data except DO at monitoring stations 1 and 2 showed that data does not normally distributed. It is indicating that non-parametric method must be used for a water quality data. Therefore, a homogeneity was conducted by Mann-Whitney U test (p<0.05). Two stations were paired in three pairs of such stations. Differences between stations 1, 2 and stations 1, 3 for pH, BOD, COD, TN and TP were meaningful, but Tam-Jin 2 and 3 stations did not meaningful. In addition, a narrow gap of the water quality ranges is not a difference. Categories in which all three pairs of stations (1 and 2, 2 and 3, 1 and 3) in the Tam-Jin River showed difference in water quality were analyzed on TN and TP. The results of in this research suggest a right analysis in the homogeneity test of water quality data and a reasonable management of pollutant sources.

• Magazine of the Korean Society of Agricultural Engineers
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• v.32 no.3
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• pp.116-129
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• 1990

A rational management of water resources in estuary reservoirs necessiates the prediction of water quality. In this study, a multiple box model for the water quality prediction was developed as a tool for the purpose of examining an adequate way to improve and maintain the water quality. Some submodels that are suitable for simulating the mixing behavior of pollutant materials in a lake were considered in this model. The model was appiled for predicting water qualities of Haenam Esturay Reservoir. The result from this study can be summarized as follows : 1.A water quality simulation model that can predict the 10-day mean value of water qualities was developed by adding some submodels that simulate the concentrations of chlorophyll-a, BOD, T-P and T-N to the existing Multiple Box Model representing the mixing and circulating of materials by the hydarulic action. 2.As input data for the model developed, the climatic data including precipitation, solar radiation, temperature, cloudness, wind speed and relative humidity, and the water buget records including the pumping discharge and the releasing discharge by drainage gate were ollected. The hydrologic data for the inflow discharge from the watershed was obtained by simulation with the aid of USDAUL-74/SNUA watershed model. Also the water quality data were measured at streams and the reservoir. 3.As a result of calibration and verification test by using four comonents of water quality such as Chlorophyll-a, BOD, T-P and T-N, it was found that the correlation coefficeints between the observed and the simulated water qualities showed greater than 0.6, therefore the capability of the model to simulate the water quality was proved. 4.The result based on the model application showed that the water quality of the Haenam Estuary Reservoir varies seasonally with the harmonic trend, however the water quality is good in winter and get worse in summer. Also it may be concluded that the current grarde of water quality in the Heanam Esutary Reservoir is ranked as grade 4 suitable only for the agricultutal use.

• Journal of Korea Water Resources Association
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• v.44 no.6
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• pp.439-447
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• 2011

This study aims to test the feasibility of combined use of EFDC (Environmental Fluid Dynamics Code) hydrodynamic model and WASP7.3 (Water Quality Analysis Program) model to improve accuracy of water quality predictions of the Yongdam Lake, Korea. The orthogonal curvilinear grid system was used for EFDC model to represent riverine shape of the study area. Relationship between volume, surface and elevation results were checked to verify if the grid system represents morphology of the lake properly. Monthly average boundary water quality conditions were estimated using the monthly monitored water quality data from Korean Ministry of Environment DB system. Monthly tributary flow rates were back-routed using dam discharge data and allocated in proportion to each basin area as direct measurements were not available. The optimum number of grid system was determined to be 372 horizontal cells and 10 vertical layers of the site for 1 year simulation of hydrodynamics and water quality out of iterative trials. Monthly observed BOD, TN, TP and Chl-a concentrations inside the lake were used for calibration of WASP7.3 model. This study shows that EFDC and WASP can be used in series successfully to improve accuracy in water quality modeling. However, it was observed that the amount of data to develop inflow water quality and flow rate boundary conditions and water quality data inside lake for calibration were not enough for accurate modeling. It is suggested that object-oriented data collection systems would be necessary to ensure accuracy of EFDC-WASP model application and thus for efficient lake water quality management strategy development.

• Korean Journal of Agricultural Science
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• v.49 no.2
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• pp.193-202
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• 2022

The recurrent neural network (RNN) algorithm has been widely used in water-related research areas, such as water level predictions and water quality predictions, due to its excellent time series learning capabilities. However, studies on water quality predictions using RNN algorithms are limited because of the scarcity of water quality data. Therefore, most previous studies related to water quality predictions were based on monthly predictions. In this study, the quality of the water in a reservoir in Nonsan, Chungcheongnam-do Republic of Korea was predicted using the RNN-LSTM algorithm. The study was conducted after constructing data that could then be, linearly interpolated as daily data. In this study, we attempt to predict the water quality on the 7th, 15th, 30th, 45th and 60th days instead of making daily predictions of water quality factors. For daily predictions, linear interpolated daily water quality data and daily weather data (rainfall, average temperature, and average wind speed) were used. The results of predicting water quality concentrations (chemical oxygen demand [COD], dissolved oxygen [DO], suspended solid [SS], total nitrogen [T-N], total phosphorus [TP]) through the LSTM algorithm indicated that the predictive value was high on the 7th and 15th days. In the 30th day predictions, the COD and DO items showed R² that exceeded 0.6 at all points, whereas the SS, T-N, and T-P items showed differences depending on the factor being assessed. In the 45th day predictions, it was found that the accuracy of all water quality predictions except for the DO item was sharply lowered.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.6
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• pp.89-100
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• 2021

The conservation of stream habitats has been gaining more public attention and fish habitat suitability index (HSI) is an important measure for ecological stream habitat assessment. The fish habitat preference is affected not only by physical stream conditions but also by water quality of which HSI was not available due to the lack of field data. The purpose of this study is to estimate the HSI of Zacco platypus for water quality parameters of water temperature, dissolved oxygen (DO), and biochemical oxygen demand (BOD) using the water environment monitoring data provided by the Ministry of Environment (ME). Fish population data merged with water quality were constructed by spatio-temporal matching of nationwide water quality monitoring data with bio-monitoring data of the ME. Two types of the HSI were calculated by the Instream Flow and Aquatic Systems Group (IFASG) method and probability distribution (Weibull) fitting for the four major river basins. Both the HSIs by the IFASG and Weibull fitting appeared to represent the overall distribution and magnitude of fish population and this can be used in stream fish habitat evaluation considering water quality.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.63-69
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• 1999

The purpose of this study is to develop Water Quality Management System(WQMS), which performs calculating pollutant discharge and forecasting water quality with water pollution model. Operational water quality management requires not only controlling pollutants but acquiring and managing exact information. A GIS software, ArcView was used to enter or edit geographic data and attribute data, and MapObject was used to customize the user interface. PCI, a remote sensing software, was used for deriving land cover classification from 20 m resolution SPOT data by image processing. WQMS has two subsystems, Database Subsystem and Modelling subsystem. Database subsystem consisted of watershed data from digital map, remote sensing data, government reports, census data and so on. Modelling subsystem consisted of NSPLM(NonStorm Pollutant Load Model)-SPLM(Storm Pollutant Load Model). It calculates the amount of pollutant and predicts water quality. This two subsystem was connected through graphic display module. This system has been calibrated and verified by applying to Mokhyun stream watershed.