• Journal of Korea Water Resources Association
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• v.45 no.5
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• pp.481-493
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• 2012

The Uncertainty of drought events can be regarded as supernatural phenomena so that the uncertainty of water supply system will be also uncontrollable. Decision making for water supply system operation must be dealt with in consideration of hydrologic uncertainty conditions. When ultimate small quantity of precipitation or streamflow lasts, water supply system might be impacted as well as stream pollution, aqua- ecosystem degradation, reservoir dry-up and river aesthetic waste etc. In case of being incapable of supplying water owing to continuation of severe drought, it can make the damage very serious beyond our prediction. This study analyzes comprehensively sustained drought impacts on the Han River Basin Water Supply System. Drought scenarios consisted of several sustained times and return periods for 5 sub-watersheds are generated using a stochastic hydrologic time series model. The developed drought scenarios are applied to assess water supply performance at the Paldang Dam. The results show that multi-year drought events reflecting spatial hydrologic diversity need to be examined in order to recognize variation of the unexpected drought impacts.

• Korean Journal of Environmental Agriculture
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• v.10 no.1
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• pp.67-75
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• 1991

The QUAL-II E Model was applied to predict the water quality of the Mankyong drainage System, and lead to following conclusion. 1. The difference between computed and measured BOD at the M-3 (Bakgugeong) station was within 10%, indicating that the application of the QUAL-IIE Model for the prediction of water quality was satisfactory thus far. 2. The application of the model states that the discharge of concentrated pollutants at the M-1 station on the Jeonju stream, located 41Km upstream from the estuary, causes the worst problems. The sluice which extends residence time and enlarges watery surface improves water quality by a Self-purification process at the M-3 station, 28km upstream from the estuary. 3. The accuracy of the model diminished when this model was applied on the estuary downstream of the sluice. Hence, the application of the model on the estuary needs to be used with caution. 4. Among the conputed water quality parameters, BOD is the worst problem. At the M-3 station, BOD is computed to be 26.6 mg/1 in 1996, 30.7 mg/1 in 2,001, 33.0 mg/l in 2006, and 37.5 mg/1 in 2011. When preventive measures against water pollution are not properly exercised, severe problems in irrigation and water resources are expected. This study will be of used in the selection of irrigation water intake points, the criteria of effluent treatment, the management of water resources, and the establishment of water quality managemont policy.

• Magazine of the Korean Society of Agricultural Engineers
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• v.22 no.4
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• pp.108-114
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• 1980

A deterministic conceptual erosion model which simulates detachment, entrainment, transport and deposition of eroded soil particles by rainfall impact and flowing water is presented. Both upland and channel phases of sediment yield are incorporated into the erosion model. The algorithms for the soil erosion and sedimentation processes including land and crop management effects are taken from the literature and then solved using a digital computer. The erosion model is used in conjunction with the modified Kentucky Watershed Model which simulates the hydrologic characteristics from watershed data. The two models are linked together by using the appropriate computer code. Calibrations for both the watershed and erosion model parameters are made by comparing the simulated results with actual field measurements in the Four Mile Creek watershed near Traer, Iowa using 1976 and 1977 water year data. Two water years, 1970 and 1978 are used as test years for model verification. There is good agreement between the mean daily simulated and recorded streamflow and between the simulated and recorded suspended sediment load except few partial differences. The following conclusions were drawn from the results after testing the watershed and erosion model. 1. The watershed and erosion model is a deterministic lumped parameter model, and is capable of simulating the daily mean streamflow and suspended sediment load within a 20 percent error, when the correct watershed and erosion parameters are supplied. 2. It is found that soil erosion is sensitive to errors in simulation of occurrence and intensity of precipitation and of overland flow. Therefore, representative precipitation data and a watershed model which provides an accurate simulation of soil moisture and resulting overland flow are essential for the accurate simulation of soil erosion and subsequent sediment transport prediction. 3. Erroneous prediction of snowmelt in terms of time and magnitute in conjunction with The frozen ground could be the reason for the poor simulation of streamflow as well as sediment yield in the snowmelt period. More elaborate and accurate snowmelt submodels will greatly improve accuracy. 4. Poor simulation results can be attributed to deficiencies in erosion model and to errors in the observed data such as the recorded daily streamflow and the sediment concentration. 5. Crop management and tillage operations are two major factors that have a great effect on soil erosion simulation. The erosion model attempts to evaluate the impact of crop management and tillage effects on sediment production. These effects on sediment yield appear to be somewhat equivalent to the effect of overland flow. 6. Application and testing of the watershed and erosion model on watersheds in a variety of regions with different soils and meteorological characteristics may be recommended to verify its general applicability and to detact the deficiencies of the model. Futhermore, by further modification and expansion with additional data, the watershed and erosion model developed through this study can be used as a planning tool for watershed management and for solving agricultural non-point pollution problems.

• Journal of Environmental Impact Assessment
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• v.32 no.1
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• pp.29-40
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• 2023

The need for improvement is raised due to limitations with environmental impact assessment, and the importance for data-based environmental impact assessment is increasing. In this study, data demand was derived by analyzing Agreed Terms and Conditions in the Water Environment field (Water Quality, Hydraulic & Hydrologic Conditions, and Marine Environment) of environmental impact assessment. Agreed Terms and Conditions on environmental impact assessment in the water environment field were classified and categorized by environmental impact assessment stage (addition to status survey, impact prediction and evaluation, establishment of reduction measures, post-environmental impact survey), and data demand for each type of consultation opinion was linked. As a result of the categorization of Agreed Terms and Conditions, it was classified into 18 types in the water quality, 15 types in the hydraulic & hydrologic conditions, and 17 types in the marine environment. As a result of linking data demand, the total number of data demand was 236 in the water quality, 98 in the hydraulic & hydrologic conditions, and 73 in the marine environment. The highest number of Agreed Terms and Conditions and data demands were found in the water quality for the evaluation item and establishment of reduction measures, specifically establishment of non-point source pollution reduction measures, for the stage. The numbers were judged to be linked to the relative importance of the items and the primary purpose of environmental impact assessment. The derivation of data demand through the analysis of Agreed Terms and Conditions in the environmental impact assessment can contribute to the advancement of the preparation of environmental impact assessment reports and is expected to increase data utilization by various decision-makers by establishing a systematic database.

• Journal of Korean Society on Water Environment
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• v.16 no.4
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• pp.491-499
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• 2000

Effluent concentration estimation equations for treatment wetland were reviewed with 3 -year experimental data. Four equations from USEPA, WPCF, Kadlec and Knight, and this study were applied to the over 100 data points of 1996 to 1999 study at the pilot plant in Konkuk University. The system was a subsurface flow type and consisted of 60cm depth of sand and reeds, and it worked continuously including winter with domestic sewage from school building. Generally, all the equations demonstrated reasonable agreement with experimental data and they could be used for design process if selected carefully. Among them, the equation from this study showed the best fit for the data. The reason might be not only the equation was derived from the experimental data, but also it included plant coverage parameter in the equation while others did not Plant coverage was proved to be an important parameter in the prediction of the treatment wetland system, and its inclusion in the estimation equation could improve the accuracy. Although existing equations could be used in the wetland design, pilot plant experiment for the anticipated condition and subsequent equation development can provide more reliable equation. It takes time to obtain meaningful data from wetland system. Therefore, timely onset of well organized study is recommended before large scale application of treatment wetland system to either point or nonpoint source pollution abatement.

• Journal of Wetlands Research
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• v.24 no.1
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• pp.25-37
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• 2022

Climate change is becoming increasingly unpredictable. This has led to changes in various systems such as ecosystems, human life and hydrological cycles. In particular, the recent unpredictable climate change frequently causes extreme droughts and torrential rains, resulting in complex water resources disasters that cause water pollution due to inundation and retirement rather than primary disasters. SWAT was used as a watershed model to analyze future runoff and pollutant loads. The climate scenario analyzed the RCP4.5 climate scenario of the Meteorological Agency standard scenario (HadGEM3-RA) using the normal quantitative mapping method. Runoff and pollutant load analysis were performed by linkage simulation of climate scenario and watershed model. Finally, the results of application and verification of linkage model and analysis of future water quality change due to climate change were presented. In this study, we simulated climate change scenarios using artificial neural networks, analyzed changes in water temperature and turbidity, and compared the results of dams with artificial neural network results through W2 model, a reservoir water quality model. The results of this study suggest the possibility of applying the nonlinearity and simplicity of neural network model to Hapcheon dam water quality prediction using climate change.

• Journal of Navigation and Port Research
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• v.26 no.1
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• pp.137-145
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• 2002

Water flow simulations for environmental problems often require local detailed analyses for better understanding and accurate prediction of the fate of pollutant in water bodies. This study deals with the development and application of a two-dimensional flow an dispersion model to the coastal water area to find out possible changes due to the wide port development plan. As far as the spatial discretization is concerned, the finite element method is attractive because of its flexibility and ability to naturally treat complex coastal geometries. The model uses finite element theory and the Galerkin weighted-residual approach as its basis. Developed model is applied to the Busan New harbor Construction site. Results from the model were compared with the measured water level and flows in four stations. The flow pattern by the model shows to be similar to the observed data away from the construction site where the flow is not affected. From the simulation results, it is concluded that the model may be useful for numerous other studies for planning and management purposes, especially flow and pollution dispersion in the coastal water bodies where the flow is so complicated.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1273-1273
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• 2001

The efficiency of the luminal fermentation process influences overall efficiency of luminal production, animal health and reproduction. Ruminant production systems have a significant impact on the global environment, as well. Animal wastes contribute to pollution of the environment as ammonia volatilized to the air and nitrate leached to ground water. Microbial protein synthesis in the rumen satisfies a large proportion of the protein requirements of animals. Quantifying the microbial synthesis is possible by using markers for lumen bacteria and protozoa such as nucleic acids, purine bases, some specific amino acids, or by isotopic $^{15}N,^{32}P,\;and\;^{35}S$ labelled feeds. All those methods require cannulated animals, they are time-consuming and some methods are very expensive as well. Many attempts have been made to find an alternative method for indirect measurement of microbial synthesis in intact animals. The present investigations aimed to assess possibilities of NIRS for prediction of purine nitrogen excretion and ruminal microbial nitrogen synthesis by NIR spectra of urine. Urine samples were collected from 12 growing sheep,6 of them male, and 6- female. The sheep were included in feeding experiment. The ration consisted of sorghum silage and protein supplements -70:30 on dry matter basis. The protein supplements were chosen to differ in protein degradability. The urine samples were collected daily in a vessel containing $60m{\ell}$ 10% sulphuric acid to reduce pH below 3 and diluted with tap water to 4 liters. Samples were stored in plastic bottles and frozen at $-20^{\circ}C$ until chemical and NIRS analysis. The urine samples were analyzed for purine derivates - allantoin, uric acid, xantine and hypoxantine content. Microbial nitrogen synthesis in the lumen was calculated according to Chen and Gomes, 1995. Transmittance urine spectra with sample thickness 1mm were obtained by NIR System 6500 spectrophotometer in the spectral range 1100-2500nm. The calibration was performed using ISI software and PLS regression, respectively. The following statistical results of NIRS calibration for prediction of purine derivatives and microbial protein synthesis were obtained.(Table Omitted). The result of estimation of purine nitrogen excretion and microbial protein synthesis by NIR spectra of urine showed accuracy, adequate for rapid evaluation of microbial protein synthesis for a large number of animals and different diets. The results indicate that the advantages of the NIRS technology can be extended into animal physiological studies. The fast and low cost NIRS analyses could be used with no significant loss of accuracy when microbial protein synthesis in the lumen and the microbial protein flow in the duodenum are to be assessed by NIRS.

• Journal of Korea Water Resources Association
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• v.54 no.2
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• pp.121-133
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• 2021

Suspended Solids (SS) generated in rivers are mainly introduced from non-point pollutants or appear naturally in the water body, and are an important water quality factor that may cause long-term water pollution by being deposited. However, the conventional method of measuring the concentration of suspended solids is labor-intensive, and it is difficult to obtain a vast amount of data via point measurement. Therefore, in this study, a model for measuring the concentration of suspended solids based on remote sensing in the Nakdong River was developed using Sentinel-2 data that provides high-resolution multi-spectral satellite images. The proposed model considers the spectral bands and band ratios of various wavelength bands using a machine learning model, Support Vector Regression (SVR), to overcome the limitation of the existing remote sensing-based regression equations. The optimal combination of variables was derived using the Recursive Feature Elimination (RFE) and weight coefficients for each variable of SVR. The results show that the 705nm band belonging to the red-edge wavelength band was estimated as the most important spectral band, and the proposed SVR model produced the most accurate measurement compared with the previous regression equations. By using the RFE, the SVR model developed in this study reduces the variable dependence compared to the existing regression equations based on the single spectral band or band ratio and provides more accurate prediction of spatial distribution of suspended solids concentration.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2B
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• pp.187-197
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• 2008

This study is to assess the impact of future land use change on hydrology and water quality in Gyungan-cheon watershed ($255.44km^2$) using SWAT (Soil and Water Assessment Tool) model. Using the 5 past Landsat TM (1987, 1991, 1996, 2004) and $ETM^+$ (2001) satellite images, time series of land use map were prepared, and the future land uses (2030, 2060, 2090) were predicted using CA-Markov technique. The 4 years streamflow and water quality data (SS, T-N, T-P) and DEM (Digital Elevation Model), stream network, and soil information (1:25,000) were prepared. The model was calibrated for 2 years (1999 and 2000), and verified for 2 years (2001 and 2002) with averaged Nash and Sutcliffe model efficiency of 0.59 for streamflow and determination coefficient of 0.88, 0.72, 0.68 for Sediment, T-N (Total Nitrogen), T-P (Total Phosphorous) respectively. The 2030, 2060 and 2090 future prediction based on 2004 values showed that the total runoff increased 1.4%, 2.0% and 2.7% for 0.6, 0.8 and 1.1 increase of watershed averaged CN value. For the future Sediment, T-N and T-P based on 2004 values, 51.4%, 5.0% and 11.7% increase in 2030, 70.5%, 8.5% and 16.7% increase in 2060, and 74.9%, 10.9% and 19.9% increase in 2090.