• Journal of Korea Water Resources Association
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• v.37 no.1
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• pp.67-75
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• 2004

In this study, real-time forecasting model(Neural Dam Inflow Forecasting Model; NDIFM) based on neural network to predict the dam inflow which is occurred by flood runoff is developed and applied to check its availability for the operation of multi-purpose reservoir Developed model Is applied to predict the flood Inflow on dam Nam-Gang in Nak-dong river basin where the rate of flood control dependent on reservoir operation is high. The input data for this model are average rainfall data composed of mean areal rainfall of upstream basin from dam location, observed inflow data, and predicted inflow data. As a result of the simulation for flood inflow forecasting, it is found that NDIFM-I is the best predictive model for real-time operation. In addition, the results of forecasting used on NDIFM-II and NDIFM-III are not bad and these models showed wide range of applicability for real-time forecasting. Consequently, if the quality of observed hydrological data is improved, it is expected that the neural network model which is black-box model can be utilized for real-time flood forecasting rather than conceptual models of which physical parameter is complex.

• Korean Journal of Remote Sensing
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• v.30 no.1
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• pp.61-73
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• 2014

This study reviewed an application of water quality estimation using an Airborne Hyperspectral Imagery (A-HSI) and tested a part of Han River water quality (especially suspended solid) estimation with available in-situ data. The estimation of water quality was processed two methods. One is using observation data as downwelling radiance to water surface and as scattering and reflectance into water body. Other is linear regression analysis with water quality in-situ measurement and upwelling data as at-sensor radiance (or reflectance). Both methods drive meaningful results of RS estimation. However it has more effects on the auxiliary dataset as water quality in-situ measurement and water body scattering measurement. The test processed a part of Han River located Paldang-dam downstream. We applied linear regression analysis with AISA eagle hyperspectral sensor data and water quality measurement in-situ data. The result of linear regression for a meaningful band combination shows $-24.847+0.013L_{560}$ as 560 nm in radiance (L) with 0.985 R-square. To comparison with Multispectral Imagery (MSI) case, we make simulated Landsat TM by spectral resampling. The regression using MSI shows -55.932 + 33.881 (TM1/TM3) as radiance with 0.968 R-square. Suspended Solid (SS) concentration was about 3.75 mg/l at in-situ data and estimated SS concentration by A-HIS was about 3.65 mg/l, and about 5.85mg/l with MSI with same location. It shows overestimation trends case of estimating using MSI. In order to upgrade value for practical use and to estimate more precisely, it needs that minimizing sun glint effect into whole image, constructing elaborate flight plan considering solar altitude angle, and making good pre-processing and calibration system. We found some limitations and restrictions such as precise atmospheric correction, sample count of water quality measurement, retrieve spectral bands into A-HSI, adequate linear regression model selection, and quantitative calibration/validation method through the literature review and test adopted general methods.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.4
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• pp.1-8
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• 2012

This study is to assess the reduction of non-point source pollution loads for rice straw surface covering of upland crop cultivation at a watershed scale. For Byulmi-cheon watershed ($1.21km^2$) located in the upstream of Gyeongancheon, the HSPF (Hydrological Simulation Program-Fortran), a physically based distributed hydrological model was applied. Before evaluation, the model was calibrated and validated using 9 rainfall events. The Nash-Sutcliffe model efficiency (NSE) for streamflow was 0.62~0.78 and the NSE for water quality (Sediment, T-N, and T-P) were 0.68, 0.60, and 0.58 respectively. From the field experiment of 16 rainfall events, the rice straw covering reduced surface runoff average 10 % compared to normal surface condition. By handling infiltration parameter (INFILT) in the model, the value of 16.0 mm/hr was found to reduce about 10 % reduction of surface runoff. For this condition, the reduction effect of Sediment, T-N, and T-P loads were 87.2, 28.5, and 85.1 % respectively. The rice straw surface covering was effective for removing surface runoff dependent loads such as Sediment and T-P.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.469-473
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• 2005

수질모형의 지배방정식에서 정의되는 대표적인 수질매개변수는 유역 및 대기로부터의 오염부하량 퇴적물로부터의 오염물질 용출부하량, 확산계수. 반응계수 등으로 직접적인 관측이 곤란할 뿐만 아니라 많은 관측비용을 필요로 한다. 본 연구에서는 매개변수를 포함한 오염물질 수지방정식을 구성하고, 구성된 선형 연립방정식을 이용함으로써 계산된 농도분포자료와 관측된 시계열 농도분포자료를 이용하여 계산한 질량변화량의 차이를 최소화하는 역산문제를 구성하여 모형의 매개변수를 추정하는 방법을 제시하였다. 이 방법을 이용하여 천수만, 울산만(울산항) 해역에서 관측된 연직방향 농도분포 자료를 이용하여 확산계수 및 대기로부터의 오염부하량, 퇴적물로부터의 오염물질 용출율, 확산$\cdot$반응에 의한 오염물질 변화량 등을 추정하였으며, 추정 매개변수는 시기적으로 변동이 크게 나타났다. 반면, 추정매개변수를 이용한 관측자료와 계산결과를 비교한 결과, RMS 오차는 관측자료 범위의 $5.0\% 이하, 일치지수는 0.95 이상으로 본 방법을 이용한 매개변수 추정결과의 신뢰성은 우수한 것으로 파악되었다.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.17 no.3
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• pp.149-157
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• 2005

Typical water quality (WQ) parameters defined in the governing equation of the WQ model are the pollutant loads from atmosphere and watersheds, pollutant release rates from sediment, diffusion coefficient and reaction coefficient etc. The direct measurement of these parameters is very difficult as well as requires high cost. In this study, the pollutant budget equation including these parameters was used to construct the linear simultaneous equations. Based on these equations, the inverse problems were constructed and WQ parameter estimation method minimizing the sum of squared errors between the computed and observed amounts of the mass changes was suggested. WQ parameters, i.e., the atmospheric pollutant loads, sediment release rates, diffusion coefficients and reaction coefficient, were estimated using .this method by utilizing the vertical concentration profile data which has been observed in Cheonsu Bay and Ulsan Port. Values of the estimated parameters show a large temporal variation. However, this technique is persuasive in that the RHS (root mean square) error was less than $5.0\%$ of the observed value ranges and the agreement index was greater than 0.95.

• Advances in environmental research
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• v.5 no.3
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• pp.153-167
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• 2016

We applied multilayer perceptron (MLP) and radial basis function (RBF) neural network in upstream and downstream water quality stations of the Karaj Reservoir in Iran. For both neural networks, inputs were pH, turbidity, temperature, chlorophyll-a, biochemical oxygen demand (BOD) and nitrate, and the output was dissolved oxygen (DO). We used an MLP neural network with two hidden layers, for upstream station 15 and 33 neurons in the first and second layers respectively, and for the downstream station, 16 and 21 neurons in the first and second hidden layer were used which had minimum amount of errors. For learning process 6-fold cross validation were applied to avoid over fitting. The best results acquired from RBF model, in which the mean bias error (MBE) and root mean squared error (RMSE) were 0.063 and 0.10 for the upstream station. The MBE and RSME were 0.0126 and 0.099 for the downstream station. The coefficient of determination ($R^2$) between the observed data and the predicted data for upstream and downstream stations in the MLP was 0.801 and 0.904, respectively, and in the RBF network were 0.962 and 0.97, respectively. The MLP neural network had acceptable results; however, the results of RBF network were more accurate. A sensitivity analysis for the MLP neural network indicated that temperature was the first parameter, pH the second and nitrate was the last factor affecting the prediction of DO concentrations. The results proved the workability and accuracy of the RBF model in the prediction of the DO.

• Journal of Korea Water Resources Association
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• v.46 no.12
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• pp.1181-1191
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• 2013

This study have implemented finding the optimal water temperature parameter set for Hapcheon dam reservoir using CE-QUAL-W2 model. In particular the sensitivity analysis was carried out for four water temperature parameters of wind sheltering coefficient (WSC), radiation heat coefficient (BETA), light extinction coefficient (EXH2O), heat exchange coefficient at the channel bed (CBHE). Firstly, WSC, BETA, EXH2O shows relatively high sensitivity in common during April to September, and CBHE does during August to November. Secondly, as a result of identifying depth range of parameter influence, BETA and EXH2O show 0~9 m and 8~14 m which is thermocline layer close to water surface, CBHE is deep layer 12 m away from bottom. Finally, applying annual or monthly optimal parameter sets indicates that the bias between two sets does not show much differences for WSC and CBHE parameters, but BETA and EXH2O parameters show $0.20^{\circ}C$ and $0.51^{\circ}C$ of monthly average biases for two parameter sets. In particular the bias reveals to be $0.4^{\circ}C$ and $1.09^{\circ}C$ during May and August that confirms the necessity of use of monthly parameters during that season. It is claimed that the current operational custom use of annual parameters in calibration of reservoir water quality model requires the improvement of using monthly parameters.

• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09b
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• pp.975-976
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• 2006

The present paper is a parameter study of zinc flake production using a Simoloyer CM01 horizontal high energy rotary ball mill. The manufactured flakes have a dimension in thickness (t) < $1{\mu}m$ and diameters (d) 5-100 ${\mu}m$, consequently a ratio d/t up to 200. The flake geometry is mainly controlled by the variation of process parameters such as rotary speed of the rotor, ratio of powder/ball charge, load ratio of the system, process temperature, operating model and the quantity of process control agent (PCA). The Zn flakes were characterized by SEM, tap densitometry, laser diffraction and water coverage measurement.

• Journal of Korea Water Resources Association
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• v.30 no.1
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• pp.83-93
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• 1997

The purpose of the study is to analyze the sensitivity of the parameters that affect the runoff and water quality in the studied drainage basins. SWMM model is applied to the four drainage basins located at Namgazwa and Sanbon in Seoul and Gray Haven and Kings Creek in the USA. first of all, the optimum values of the parameters which have least simulation error to the observed data, are detected by iteration procedure. These are used as the standard values which are compared against the procedure. These are used as the standard values which are compared against the varied parameter values. In order to catch the effectiveness of the parameters to the computing result, the parameters are changed step by setp, and the results are compared to the standard results in flowerate and quality of the sewer. The study indicates that the discharge is greatly affected by the types of runoff surface, i.e., impervious area remarkably affects the peak flow and runoff volume while the surface storage affects the runoff volume at mild sloped basins. In addition, the major parameters affecting the pollution concentrations and loadings are the contaminant accumulation coefficient per unit area per time and the continuous dry weather days. Furthermore, the factors that affect the water quality during the initial rainfall period are the rainfall intensity, transport capacity coefficient and its power coefficient. Consequently, in order to simulate the runoff-water quality, it is needed to evaluate previous data in the research performed for the studied basins. To accurately estimated from the tributary areas and the rational computation methods of the pollutants calculation should be introduced.

• Journal of the Korean Society of Radiology
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• v.14 no.1
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• pp.53-60
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• 2020

The purpose of this study is to identify factors affecting picture quality in Roadmap images, which were studied by varying the dilution rate, collimation field and flow rate of contrast medium. For a quantitative evaluation of the quality of the picture, a 3mm vessel model Water Phantom was self-produced using acrylic, a roadmap image was acquired with a self-produced vascular model Water Phantom, and the SNR(Signal to Noise Ratio) and CNR (Contrast to Noise Ratio) were analyzed. CM:N/S In the study on the change of dilution rate, CM:N/S dilution rate changed to (100%~10%:100%), and the measurement of the roadmap image taken using the vascular model Water Phantom showed that the measurement value of SNR gradually decreased as the N/S dilution rate was increased, and the measurement of CNR was gradually reduced. It was confirmed that the higher the dilution rate of CM:N/S, the lower the SNR and CNR, and also significant image can be obtained at the dilution rate of CM:N/S (100%~70:30%). The study showed the value of SNR and CNR in Roadmap image was increased as the Collimation Field was narrowed to the center of the vascular phantom; the Collimation Field was narrowed to the center of the vessel model by 2cm intervals to 0cm through 12cm. To verify the relationship with Roadmap image and Flow Rate, volume of the autoinjector was kept constant at 15 and the flow rate was gradually increased 1, 2, 3, 4, 5, 6, 7, 8, 9, 10. The value of SNR and CNR of images taken by using water Phantom gradually decreased as the Flow Rate increased, but at Flow Rate 9 and 10, the SNR and CNR value was increase. It was not possible to confirm the relationship with SNR and CNR by ROI mean value and Background mean value. It is considered that further study is needed to evaluate the correlation about Roadmap image and Flow Rate. In conclusion, as the dilution rate of N/S in contrast medium was increased, the value of SNR and CNR was decreased. The narrower the Collimation Field, the higher image quality by increasing value of SNR and CNR. However, it is not confirmed the relationship Roadmap image and Flow Rate. It is considered that appropriate contrast medium concentration to minimize the effects of kidney and proper Collimation Field to improve contrast of image and reduce exposure X-ray during procedure is needed.