• 한국농공학회지
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• 제42권
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• pp.24-30
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• 2000

A system for evaluating streamflow data (KORSAS) was developed, and is operated using PC based Windows to help the hydrological observation practitioner's working in Korea Water Resources Corporation (KOWACO). This system has modules including; DB access and data management, flow measurement arranging, H-Q relation deriving, area rainfall calculating, flow calculating, and flow evaluating modules. Evaluation of observed streamflow is accomplished through the following processes. First, hourly streamflow data is calculated from water level data stored in a DB server by applying the rating relationship between water level and flow rates derived from the past flow measurements. Second, hourly areal rainfal data is calculated from point data stored in the DB server by applying Thiessen networks. Third, hydrographs are displayed on a daily, weekly, monthly, or seasonal duration basis, and are compared to hydrographs of reservoir inflow, hydrographs at water level observation stations and hydrographs derived from simulated results using models.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.488-488
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• 2015

Intermittent streamflow is common phenomenon in arid and semi-arid regions. To manage water resources of intermittent streamflows, stochactic simulation data is essential; however the seasonally stochastic modeling for intermittent streamflow is a difficult task. In this study, using the periodic Markov chain model, we simulate intermittent monthly streamflow for occurrence and the periodic gamma autoregressive and copula models for amount. The copula models were tested in a previous study for the simulation of yearly streamflow, resulting in successful replication of the key and operational statistics of historical data; however, the copula models have never been tested on a monthly time scale. The intermittent models were applied to the Colorado River system in the present study. A few drawbacks of the PGAR model were identified, such as significant underestimation of minimum values on an aggregated yearly time scale and restrictions of the parameter boundaries. Conversely, the copula models do not present such drawbacks but show feasible reproduction of key and operational statistics. We concluded that the periodic Markov chain based the copula models is a practicable method to simulate intermittent monthly streamflow time series.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2004년도 총회 및 춘계학술발표회
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• pp.451-454
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• 2004

The study aims to assess the quality of bank filtrate in relation to streamflow and physico-chemical properties of the stream. Turbidity, pH, temperature and dissolved oxygen (DO) of Nakdong River and riverbank filtrate were statistically analyzed. The physico-chemical properties of riverbank filtrate were measured from irregularly different seven pumping wells every day. Autocorrelation analyses were conducted to the qualities of stream water and bank filtrated water. Temperature, pH and DO of streamflow shows strong linearity and long memory effect, indicating the effect of seasonal air temperature and rainy season. Temperature of riverbank filtrate shows weak linearity and weak memory, indicating differently from the trend of stream temperature. Turbidity of steramflow shows strong linearity and long memory effect, while turbidity of riverbank filtrate indicates weak linearity and weak memory. Cross-correlation analysis shows low relation between turbidity, pH, temperature and DO of riverbank filtrate and those of streamflow. Turbidity of streamflow was largely affected by the streamflow rate, showing a similar trend with autocorrelation function of streamflow rate. The turbidity of riverbank filtrate has a lag time of 25 hours. This indicates that turbidity of streamflow in a dry season has very low effect on the turbidity of riverbank filtrate, and a high turbidity of the stream in a rainy season has a fairly low effect on the turbidity of riverbank filtrate.

• 한국습지학회지
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• 제10권1호
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• pp.1-9
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• 2008

본 연구에서는 융설을 고려할 수 있는 물수지 모형인 WASMOD(Water And Snow MODeling system)에 대하여 기술하였으며, 소양강댐 상류유역에 적용하여 장기 월 유출량을 산정하였다. WASMOD의 장점은 입력자료의 구축이 간단하며 사용자가 쉽게 운영할 수 있다는 점이다. 모형의 매개변수를 최적화하기 위해 자동추적법인 VA05A를 이용하였으며, 관측 월 유출 수문곡선과 모의 월 수문곡선을 비교하였다. 관측 유출량과 계산 유출량간의 상관계수가 0.89이상으로, 이를 통해 WASMOD의 국내 유역에 적용가능성을 확인할 수 있었다.

• 물과 미래
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• 제13권4호
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• pp.41-50
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• 1980

본 연구는 Gamma 분포의 이론적 검토와 이의 수공학에의 적용, 즉 Gamma 분포의 적합성 및 Gamma 모델에 의한 하천유량의 Simulation에 대한 연구와 검토를 행하는데 그 목적을 두고 있다. 분석에 있어서 우리나라 주요하천(낙동강, 한강 및 금강)의 월유량자료를 사용하였으며 분석을 간단하게 하기 위하여 자료를 Modular coefficient로 변환시켰다. 먼저 이변수 Gamma 분포형에 대한 월류량에의 적합성을 검정하였으며 이로부터 Gamma 분포형과 Monto Carlo 기법을 기초로 한 Gamma 모델에 의하여 월류량의 Simulation을 행하였다. 그 결과 기록치와 매우 근접한 Simulation 자료를 얻을 수 있었다.

• 한국측량학회지
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• 제33권3호
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• pp.163-172
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• 2015

This study examined the potential effects of urban growth on streamflow in the Gyungan River watershed, Korea, using urban containment scenarios. First, two scenarios (conservation and development) were established, and SLEUTH model was adapted to predict urban growth into the year 2060 with 20 years interval under two scenarios in the study area. Urban growth was larger under scenario 2, focusing on development, than under scenario 1, focusing on conservation. Most urban growth was predicted to involve the conversion of farmland, forest, and grasslands to urban areas. Streamflow in future periods under these scenarios was simulated by the Soil and Water Assessment Tool (SWAT) model. Each scenario showed distinct seasonal variations in streamflow. Although urban growth had a small effect on streamflow, urban growth may heighten the problems of increased seasonal variability in streamflow caused by other factor, such as climate change. This results obtained in this study provide further insight into the availability of future water resource and can aid in urban containment planning to mitigate the negative effects of urban growth in the study area.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2016년도 학술발표회
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• pp.49-49
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• 2016

The impact of land cover changes on streamflow of the Akaki catchment will be assessed using Soil and Water Assessment Tool (SWAT) model. The study will analyze the historical land cover changes (1993 to 2016) that have taken place in the catchment and its effect on the streamflow of the study area. Arc GIS will be used to analysis the satellite images obtained from the United States Geological Survey (USGS). To investigate the impact of land cover change on streamflow the model set up will be done using readily available spatial and temporal data, and calibrated against measured discharge. Two third of the data will be used for model calibration (1993?2000) and the remaining one-third for model validation (2001?2004). Model performance will be evaluated by using Nash and Sutcliff efficiency (NS) and coefficient of determination (R2). The calibrated model will be used to assess two land cover change (2002 and 2016) scenarios and its likely impacts of land use changes on the runoff will be quantified. The evaluation of the model response to these changes on streamflow will be presented properly. The study will contribute a lot to understand land use and land cover change on streamflow. This enhances the ability of stakeholder to implement sound policies to minimize undesirable future impacts and management alternatives which have a significant role in future flood control of the study area.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.134-134
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• 2022

Streamflow forecasting plays a crucial role in water resource control, especially in highly urbanized areas that are very vulnerable to flooding during heavy rainfall event. In addition to providing the accurate prediction, the evaluation of effects and importance of the input predictors can contribute to water manager. Recently, machine learning techniques have applied their advantages for modeling complex and nonlinear hydrological processes. However, the techniques have not considered properly the importance and uncertainty of the predictor variables. To address these concerns, we applied the GA-BART, that integrates a genetic algorithm (GA) with the Bayesian additive regression tree (BART) model for hourly streamflow forecasting and analyzing input predictors. The Jungrang urban basin was selected as a case study and a database was established based on 39 heavy rainfall events during 2003 and 2020 from the rain gauges and monitoring stations. For the goal of this study, we used a combination of inputs that included the areal rainfall of the subbasins at current time step and previous time steps and water level and streamflow of the stations at time step for multistep-ahead streamflow predictions. An analysis of multiple datasets including different input predictors was performed to define the optimal set for streamflow forecasting. In addition, the GA-BART model could reasonably determine the relative importance of the input variables. The assessment might help water resource managers improve the accuracy of forecasts and early flood warnings in the basin.

• 한국수자원학회논문집
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• 제51권6호
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• pp.523-533
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• 2018

본 연구에서는 충주댐 유역에 대해 앙상블 유량예측기법의 강우-유출 모델 매개변수, 입력자료에 따른 불확실성 분석을 수행하였다. 앙상블 유량예측기법으로는 ESP (Ensemble Streamflow Prediction) 기법과 BAYES-ESP (Bayesian-ESP) 기법을 활용하였으며, 강우-유출 모델로는 ABCD를 활용하였다. 모델 매개변수에 따른 불확실성 분석은 GLUE (Generalized Likelihood Uncertainty Estimation) 기법을 적용하였으며, 입력자료에 따른 불확실성 분석은 유량예측 앙상블에 활용되는 기상시나리오의 기간에 따라 수행하였다. 연구결과 앙상블 유량예측 기법은 입력자료 보다 모델 매개변수의 영향을 크게 받았으며, 20년 이상의 관측 기상자료가 확보되었을 때 활용하는 것이 적절하였다. 또한 BAYES-ESP는 ESP에 비해 불확실성을 감소시킬 수 있는 것으로 나타났다. 본 연구는 불확실성 분석을 통해 앙상블 유량예측기법의 특징을 규명하고 오차의 원인을 분석하였다는 점에서 가치가 있다고 판단된다.

• 한국농공학회지
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• 제26권2호
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• pp.106-124
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• 1984

Monthly streanflow of watersheds is one of the most important elements for the planning, design, and management of water resources development projects, e.g., determination of storage requirement of reservoirs and control of release-water in lowflow rivers. Modeling of longterm runoff is theoretically based on water-balance analysis for a certain time interval. The effect of the casual factors of rainfall, evaporation, and soil-moisture storage on streamflow might be explained by multiple regression analysis. Using the basic concepts of water-balance and regression analysis, it was possible to develop a generalized model called the Regionalized Regression Model for Monthly Streamflow in Korean Watersheds. Based on model verification, it is felt that the model can be reliably applied to any proposed station in Korean watersheds to estimate monthly streamflow for the planning, design, and management of water resources development projects, especially those involving irrigation. Modeling processes and properties are summarized as follows; 1. From a simplified equation of water-balance on a watershed a regression model for monthly streamflow using the variables of rainfall, pan evaporation, and previous-month streamflow was formulated. 2. The hydrologic response of a watershed was represented lumpedly, qualitatively, and deductively using the regression coefficients of the water-balance regression model. 3. Regionalization was carried out to classify 33 watersheds on the basis of similarity through cluster analysis and resulted in 4 regional groups. 4. Prediction equations for the regional coefficients were derived from the stepwise regression analysis of watershed characteristics. It was also possible to explain geographic influences on streamflow through those prediction equations. 5. A model requiring the simple input of the data for rainfall, pan evaporation, and geographic factors was developed to estimate monthly streamflow at ungaged stations. The results of evaluating the performance of the model generally satisfactory.