• Water Engineering Research
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• 제1권2호
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• pp.107-117
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• 2000

Streamflow patterns at two gauging stations in Korea, An-Dong dam and Chung-Ju dam, are statistically analyzed in relation to EI Nino/Southern Oscillation (ENSO). As a measure of ENSO, the Southern Oscillation Index (SOI) is used on a monthly and seasonal basis. The traditional correlation analysis shows that cross correlations of the SOI with the seasonal streamflow are generally weak. To investigate the relationship between the extreme values of the SOI, which represent the EI Nino and La Nina events, and the corresponding streamflow patterns, the composite analysis is employed in this study. The composite analysis demonstrates that when EI Nino occurs, seasonal streamflows at An-Dong and Chung-Ju dams during the period from September of the EI Nino year to February of the following year appear to be drier than their means.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.317-317
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• 2018

Baseflow which is one of the unmeasurable components of streamflow and slowly flows through underground is important for water resource management. Despite various separation methods from researches preceded, it is difficult to find a significant separation method for baseflow separation. This study applied the MRC method and developed the improved approach to separate baseflow from total streamflow hydrograph. Previous researchers utilized the whole streamflow data of study period at once to derive synthetic MRCs causing unreliable results. This study has been proceeded with total nine areas with gauging stations. Each three areas are selected from 3 domestic major watersheds. Tool for drawing MRC had been used to draw MRCs of each area. First, synthetic MRC for whole period and two other MRCs were drawn following two different criteria. Two criteria were set by different conditions, one is flow condition and the other is seasonality. The whole streamflow was classified according to seasonality and flow conditions, and MRCs had been drawn with a specialized program. The MRCs for flow conditions had low R2 and similar trend to recession segments. On the other hand, the seasonal MRCs were eligible for the baseflow separation that properly reflects the seasonal variability of baseflow. Comparing two methods of assuming MRC for baseflow separation, seasonal MRC was more effective for relieving overestimating tendency of synthetic MRC. Flow condition MRCs had large distribution of the flow and this means accurate MRC could not be found. Baseflow separation using seasonal MRC is showing more reliability than the other one however, if certain technique added up to the flow condition MRC method to stabilize distribution of the streamflow, the flow conditions method could secure reliability as much as seasonal MRC method.

• 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 2018년도 학술발표회
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• pp.326-326
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• 2018

The study will assess the seasonal effect of hydrological models on performance and parameters for streamflow simulation. TPHM, GR4J, CAT, and TANK-SM hydrological models will be applied for simulating streamflow in ten small and large watersheds located in South Korea. The readily available hydrometeorological data will be applied as an input to the four hydrological models and the potential evapotranspiration will be computed using the Penman-Monteith equation. The SCE-UA algorithm implemented in PEST will be used to calibrate the models considering similar objective functions bedside the calibration will be renewed to capture the seasonal effects on the model performance and parameters. The seasonal effects on the model performance and parameters will be presented after assessing the four hydrologic models results. The conventional approach and season-based results will be evaluated for each model in the tested watersheds and a conclusion will be made based on the finding of the results.

• 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.

• 한국수자원학회논문집
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• 제47권5호
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• pp.491-500
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• 2014

하천수 가뭄을 평가하기 위하여 임계수준 방법을 이용한 하천수 가뭄지수 (streamflow drought index)를 소개하고 섬진강댐의 유입량을 대상으로 적용하였다. 사용한 임계수준은 고정, 월별 및 일별로써 연도별 가뭄의 1~3순위 분석결과, 1984년, 1988년과 1995년이 수문학적 가뭄의 크기도 컸고 오랫동안 지속되었다. 총 물 부족량과 지속기간의 극한값을 연도별로 비교해 본 바, 1984년, 1988년, 1995년과 2001년에 발생하였던 사상이 심각한 수준이었다. 또한 고정 임계수준은 계절 변동성을 반영하지못하는 단점이 있어서 최소한계절 이하의 임계수준 사용이 요구되었지만 월별과 일별로 정해진 임계수준은 적정한 것으로 판단되었다. 본 연구에서 제안한 방법론은 갈수예보 및 저수지 용량결정에 활용될 수 있겠다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.118-118
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• 2020

This study investigates the change of flow characteristics over 10 Asian river basins in the past 30 years (1976-2005). The variation is estimated from The Soil and Water Assessment Tool (SWAT) model outputs based on reanalysis data which was bias-corrected for Asian monsoon reagion. The model was firstly calibrated and validated using observed data for daily streamflow. Four statistical criteria were applied to evaluate the model performance, including Coefficient of determination (R2), Nash - Sutcliffe model efficiency coeffi cient (NSE), Root mean square error-observations standard deviation ratio (RSR), and Percentage Bias (PBIAS). Then parameters of the model were applied for the historical period 1976-2005. The estimates show a temporal non-considerable increasing rate of daily streamflow in most of the basins over the past 30 years. The difference of monthly discharge becomes more significant during the months in the wet season (June to September) in all basins. The seasonal runoff shows significant difference in Summer and Autumn, when the rainfall intensity is higher. The line showing averaged runoff/rainfall ratio in all basins is sharp, presenting high variation of seasonal runoff/rainfall ratio from season to season.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.149-149
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• 2022

Accurate quantitative evaluation of baseflow contribution to streamflow is imperative to address seasonal drought vulnerability, flood occurrence and groundwater management concerns for efficient and sustainable water resources management in watersheds. Several baseflow separation algorithms using recursive filters, graphical method and tracer or chemical balance have been developed but resulting baseflow outputs always show wide variations, thereby making it hard to determine best separation technique. Therefore, the current global shift towards implementation of artificial intelligence (AI) in water resources is employed to compare the performance of deep learning models with conventional hydrograph separation techniques to quantify baseflow contribution to streamflow of Piney River watershed, Tennessee from 2001-2021. Streamflow values are obtained from the USGS station 03602500 and modeled to generate values of Baseflow Index (BI) using Web-based Hydrograph Analysis (WHAT) model. Annual and seasonal baseflow outputs from the traditional separation techniques are compared with results of Long Short Term Memory (LSTM) and simple Gated Recurrent Unit (GRU) models. The GRU model gave optimal BFI values during the four seasons with average NSE = 0.98, KGE = 0.97, r = 0.89 and future baseflow volumes are predicted. AI offers easier and more accurate approach to groundwater management and surface runoff modeling to create effective water policy frameworks for disaster management.