• Journal of Wetlands Research
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• v.7 no.3
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• pp.57-66
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• 2005

This paper is to present the determination of the optimal loss rate parameters and unit hydrographs from the observed single rainfall-runoff event using optimization model. The linear program models has been formulated to derive the optimal unit hydrographs and loss rate parameters for the site of the Su-Jik Bridge in the HwangGuJichen River; one minimizes the summation of the absolute residual between predicted and observed runoff ordinates. In the perturbation stage of parameters the trial and error method has been adopted to determine the loss rate parameters for Kostiakov's, Philip's, Horton's, and Green-Ampt's equation. The unique unit hydrograph ordinates for a given rainfall-runoff event is exclusively obtained with ${\Phi}$ index, but unit hydrograph ordinates depend upon the parameters for each loss rate equations. In this paper the single rainfall-runoff event observed from the sample watershed is considered to test the proposed method. The optimal unit hydrograph obtained by the optimization model has smaller deviations than the ones by the conventional method.

• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.53-59
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• 2020

Initial response is important in marine oil spills, such as the Hebei Spirit oil spill, but it is very difficult to predict the movement of oil out of the ocean, where there are many variables. In order to solve this problem, the forecasting of oil spill has been carried out by expanding the particle prediction, which is an existing study that studies the movement of floats on the sea using the data of the float. In the ocean data format HDF5, the current and wind velocity data at a specific location were extracted using bilinear interpolation, and then the movement of numerous points was predicted by particles and the results were visualized using polygons and heat maps. In addition, we propose a spill oil particle matching algorithm to compensate for the lack of data and the difference between the spilled oil and movement. The spilled oil particle matching algorithm is an algorithm that tracks the movement of particles by granulating the appearance of surface oil spilled oil. The problem was segmented using principal component analysis and matched using genetic algorithm to the point where the variance of travel distance of effluent oil is minimized. As a result of verifying the effluent oil visualization data, it was confirmed that the particle matching algorithm using principal component analysis and genetic algorithm showed the best performance, and the mean data error was 3.2%.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.421-421
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• 2019

본 연구의 목적은 HSPF 모델을 이용하여 비점오염물질이 수질에 미치는 영향을 평가하는 것이다. 합천댐 유역을 연구대상지역으로 선정하였으며, 입력자료는 유역도, 하천도, 토지이용도, 수치표고모델 및 기상자료 등을 이용하였다. HSPF 모형은 2000년부터 2016년까지의 실측값을 이용하여 보정 및 검증이 이루어졌다. 수문 보정을 위한 매개변수는 사용자 설명서와 참고문헌에 근거하여 선정하였으며, 시행착오법에 의해 수행되었다. 모델의 적용성 평가는 $R^2$, RMSE, RMAE, NSE를 사용하였고 $R^2$가 0.78에서 0.83, RMSE는 2.55에서 2.76mm/day, RMAE는 0.46에서 0.48mm/day, NSE는 0.81에서 0.82까지의 범위로 나타났으며, 연간 유출량이 ${\pm}4%$ 오차 이내로 산정되었다. 수질 모형을 구동하기 위한 수질 자료는 환경부에서 제시한 지침에 따라 생활계, 축산계, 산업계, 토지이용량에 따른 발생 부하량과 배출부하량을 산정하였다. 수질 모형 또한 수문과 같은 기간의 자료를 이용하여 보정 및 검정이 이루어졌다. 보정 결과 연평균 BOD의 차이가 0.22mg/L이고 오차범위는 13%였으며, T-N과 T-P는 0.66mg/L, 0.027mg/L의 차이를 가지며 오차범위는 각각 16%, 13%로 나타났다. 수질항목 중에서도 비점오염 관리의 효과를 평가하기 위해 비점오염물질 중 가장 큰 비중을 차지하는 축산계에 감소 시나리오를 적용하였다. 축산계의 배출부하량 감소율이 20%일때의 BOD, T-N, T-P는 각각 3%, 1%, 3% 감소하였으며 40% 감소율을 적용하였을때는 5%, 3%, 4% 감소하였다. 이러한 수질 해석을 결과를 토대로 효과적인 오염물질 방법을 적용하여 수질 개선과 합천댐 유역의 목표수질을 달성 할 수 있을 것으로 판단된다.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.2
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• pp.125-135
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• 2005

Generation and transport of nonpoint source pollution, especially sediment-associated pollutants, are profoundly influenced by hydrologic features of runoff. In order to identify pollutant export rates, hence, clear knowledge of rainfall-runoff relationship is a pre-requisition. In this study, performance of AnnAGNPS model was assessed based on the ability of the model to predict rainfall-runoff relationship. Three catchments, each under different nearly single land use, were simulated. From the results, it was found that the model was likely to produce better predictions for larger catchments than smaller catchments. Because of using the daily time scale, the model could not account for short durations less than 24 hours, especially high intensity events with multiple peak flow that significantly contribute to the generation and transport of pollutants. Since CN information for regional areas has not been built up, a careful selection of CN is needed to achieve accurate prediction of runoff volume. Storm distribution also found to be considered as an important calibration parameter for the hydrologic simulation.

• Journal of Korea Water Resources Association
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• v.33 no.4
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• pp.505-515
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• 2000

THe purpose of this study is to forecast of runoff hydrographs according to rainfall event in a stream. The neural network theory as a hydrologic blackbox model is used to solve hydrological problems. The Back-Propagation(BP) algorithm by the Levenberg-Marquardt(LM) techniques and Radial Basis Function(RBF) network in Neural Network(NN) models are used. Runoff hydrograph is forecasted in Bocheongstream basin which is a IHP the representative basin. The possibility of a simulation for runoff hydrographs about unlearned stations is considered. The results show that NN models are performed to effective learning for rainfall-runoff process of hydrologic system which involves a complexity and nonliner relationships. The RBF networks consist of 2 learning steps. The first step is an unsupervised learning in hidden layer and the next step is a supervised learning in output layer. Therefore, the RBF networks could provide rather time saved in the learning step than the BP algorithm. The peak discharge both BP algorithm and RBF network model in the estimation of an unlearned are a is trended to observed values.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.155-155
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• 2012

최근 집중호우에 따른 자연재해가 크게 증가하여 수문 및 기상분야에서 강우를 관측 및 예측하기 위한 레이더 활용성이 증대되고 있으며, 이에 따라 정부 각 관련부처에서는 레이더의 도입 및 확충을 위한 방안을 계획 제시하고 있다. 특히, 레이더강우 자료는 수문해석분야에서의 GIS 등 디지털정보를 이용하여 유역매개변수를 추정함에 따라 더 정확하고 상세한 수문자료 확보가 가능하게 되어, 격자기반의 분포형 강우-유출모형 등을 이용하여 수문해석을 하는데 있어 그 활용성이 크게 증가하고 있다. 그러나 레이더강우 자료의 정확성은 아직까지 만족할 만한 수준에 이르지 못하고 있기 때문에, 그 불확실성으로 인하여 레이더강우 자료의 활용 및 적용에 한계를 가지고 있는 실정이다. 본 연구에서는 지상강우를 이용한 레이더강우 보정을 위하여 SOA(Statistical Objective Analysis)보정방법을 이용하였으며, 기존 SOA방법에서의 거리에 따른 가중치($_{kd}$)와 함께 지형(고도)에 따른 가중치($W_{ike}$), 바람의 영향에 따른 가중치($W_{ikw}$)를 추가로 산정하여 적용하였으며, 이를 통하여 보정된 강우장을 생성하였다. SOA방법을 통해 생성된 강우장이 어느 정도의 강우정확도를 가지고 강우분포를 재현하는지 검증하기 위하여 2011년 7~9월의 수문학적 분석에 활용 가능한 강우사상과 낙동강유역을 대상으로, 분포형모형인 $Vflo^{TM}$ 모형을 이용하여 산정된 유출량과 관측 유출량과의 비교를 실시하였다. 또한, 유출량에 대한 오차 및 ME(Model Efficiency)를 통해 레이더강우 자료의 유출모형에서의 효율성을 검토하고자 하였다. 본 연구에서 수행된 보정 강우장에 따른 유출량 비교를 통해 레이더 강우의 정확도에 대한 정량적 평가 방법 도출이 가능할 것으로 판단된다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.6
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• pp.989-999
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• 2017

In this study, hydraulic experimental studies were conducted to estimate the empirical formulas of loss coefficient, which is necessary to calculate the energy loss occurred in the dividing channel junction of sewer system. The experimental apparatus was consisted of two outflow conduit with a $90^{\circ}$ angle to the inlet conduit, and the pressure and velocity heads are measured to analyze the energy losses in the branch. The measurements of the hydraulic grade line show that the hydraulic grade line was steeply descended at the dividing point due to the head loss, and the decreasing amount of velocity head increased with the increase of flowrate ratio. The head loss exponentially increased in the outlet with larger runoff as the increase of flowrate ratio and Froude number, and the head loss coefficient also increased. On the other hands, the head loss coefficients decreased in the outlet with smaller runoff as the increase of the flowrate ratio and Froude number. Using the experimental results, the empirical formulas of loss coefficient was suggested for each outlet, and the error of empirical formula was 3.91 and 5.19%, respectively. Furthermore, the total head loss coefficient calculated by the two empirical formulas was compared with the experimental results, and the error was 3.62%.

• Journal of Wetlands Research
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• v.19 no.4
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• pp.515-522
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• 2017

This study investigated the runoff characteristics containing NPS pollutants in urban areas and estimated the optimal number of storm events to be monitored. 13 residential areas, 8 commercial areas, 9 transportation areas and 11 industrial areas were selected to be monitored located in urban areas. Monitoring was performed from 2008 to 2016 with a total of 632 rainfall events. As a result, it was found that commercial area needs priority NPS management compared to other landuses because the commercial area has high runoff coefficient and NPS pollutant EMC compared with other landuses. The annual monitoring frequency for each landuse was estimated to be 11 to 14 times for industrial area, 12 to 14 times for transportation area, 11 to 13 times for commercial area and 22 to 25 times for residential area. Even with the use of accumulated monitoring data for several years, there is still high probability of uncertainty due to high error in some pollutant items, and it is necessary to establish monitoring know-how and data accumulation to reduce errors by continuous monitoring.

• Journal of Korea Water Resources Association
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• v.48 no.5
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• pp.409-423
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• 2015

In this study the very short-term rainfall forecasting and storm water forecasting using the weather radar data were implemented in an urban stream basin. As forecasting time increasing, the very short-term rainfall forecasting results show that the correlation coefficient was decreased and the root mean square error was increased and then the forecasting model accuracy was decreased. However, as a result of the correlation coefficient up to 60-minute forecasting time is maintained 0.5 or higher was obtained. As a result of storm water forecasting in an urban area, the reduction in peak flow and outflow volume with increasing forecasting time occurs, the peak time was analyzed that relatively matched. In the application of storm water forecasting by radar rainfall forecast, the errors has occurred that we determined some of the external factors. In the future, we believed to be necessary to perform that the continuous algorithm improvement such as simulation of rapid generation and disappearance phenomenon by precipitation echo, the improvement of extreme rainfall forecasting in urban areas, and the rainfall-runoff model parameter optimizations. The results of this study, not only urban stream basin, but also we obtained the observed data, and expand the real-time flood alarm system over the ungaged basins. In addition, it is possible to take advantage of development of as multi-sensor based very short-term rainfall forecasting technology.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6B
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• pp.709-721
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• 2008

This paper is to test the applicability of ModKIMSTORM (Modified KIneMatic Wave STOrm Runoff Model) by applying it to Namgangdam watershed of $2,293km^2$. Model inputs (DEM, land use, soil related information) were prepared in 500 m spatial resolution. Using five typhoon events (Saomi in 2000, Rusa in 2002, Maemi in 2003, Megi in 2004 and Ewiniar in 2006) and two storm events (May of 2003 and July of 2004), the model was calibrated and verified by comparing the simulated streamflow with the observed one at the outlet of the watershed. The Pearson's coefficient of determination $R^2$, Nash and Sutcliffe model efficiency E, the deviation of runoff volumes $D_v$, relative error of the peak runoff rate $EQ_p$, and absolute error of the time to peak runoff $ET_p$ showed the average value of 0.984, 0.981, 3.63%, 0.003, and 0.48 hr for 4 storms calibration and 0.937, 0.895, 8.08%, 0.138, and 0.73 hr for 3 storms verification respectively. Among the model parameters, the stream Manning's roughness coefficient was the most sensitive for peak runoff and the initial soil moisture content was highly sensitive for runoff volume fitting. We could look into the behavior of hyrologic components from the spatial results during the storm periods and get some clue for the watershed management by storms.