• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1037-1051
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• 2021

Biochemical oxygen demand (BOD) concentration, one of important water quality indicators, is treated as the measuring item for the ecological chapter in lakes and rivers. This investigation employed novel two-stage hybrid paradigm (i.e., wavelet-based gated recurrent unit, wavelet-based generalized regression neural networks, and wavelet-based random forests) to predict BOD concentration in the Dosan and Hwangji stations, South Korea. These models were assessed with the corresponding independent models (i.e., gated recurrent unit, generalized regression neural networks, and random forests). Diverse water quality and quantity indicators were implemented for developing independent and two-stage hybrid models based on several input combinations (i.e., Divisions 1-5). The addressed models were evaluated using three statistical indices including the root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), and correlation coefficient (CC). It can be found from results that the two-stage hybrid models cannot always enhance the predictive precision of independent models confidently. Results showed that the DWT-RF5 (RMSE = 0.108 mg/L) model provided more accurate prediction of BOD concentration compared to other optimal models in Dosan station, and the DWT-GRNN4 (RMSE = 0.132 mg/L) model was the best for predicting BOD concentration in Hwangji station, South Korea.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.243-243
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• 2015

Low-flow simulation and forecasting is one of the emerging issues in hydrology due to the increasing demand of water in dry periods. Even though low-flow simulation and forecasting remains a difficult issue for hydrologists better simulation and earlier prediction of low flows are crucial for efficient water management. The UN has never stated that South Korea is in a water shortage. However, a recent study by MOLIT indicates that Korea will probably lack water by 4.3 billion m3 in 2020 due to several factors, including land cover and climate change impacts. The two main situations that generate low-flow events are an extended dry period (summer low-flow) and an extended period of low temperature (winter low-flow). This situation demands the hydrologists to concentrate more on low-flow hydrology. Korea's annual average precipitation is about 127.6 billion m3 where runoff into rivers and losses accounts 57% and 43% respectively and from 57% runoff discharge to the ocean is accounts 31% and total water use is about 26%. So, saving 6% of the runoff will solve the water shortage problem mentioned above. The main objective of this study is to present the hydrological modelling approach for low-flow simulation and forecasting using a model that have a capacity to represent the real hydrological behavior of the catchment and to address the water management of summer as well as winter low-flow. Two lumped hydrological models (GR4J and CAT) will be applied to calibrate and simulate the streamflow. The models will be applied to Seolmacheon catchment using daily streamflow data at Jeonjeokbigyo station, and the Nash-Sutcliffe efficiencies will be calculated to check the model performance. The expected result will be summarized in a different ways so as to provide decision makers with the probabilistic forecasts and the associated risks of low flows. Finally, the results will be presented and the capacity of the models to provide useful information for efficient water management practice will be discussed.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.367-367
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• 2012

기후변화로 인해 기온, 강수량, 습도 등의 기후를 예측하고 변화하는 환경에 적응해가며 생활하고 있다. 또한 여러 가지 외부적인 요인들의 영향을 받아 상수도 시설에서의 에너지 사용량도 영향을 많이 받는다. 하지만 이러한 상수도 시설의 사용량 변화로 인해 상수도 수요량의 변화량을 예측하는데 있어서 국내 연구 및 방법이 많이 부족한 상황이다. 이에 본 연구에서는 다중스케일을 기반으로 하는 비선형 예측 모형을 개발하고자 한다. 다중스케일 분석에서도 가장 우수한 분해 능력을 가지는 Wavelet Transform을 적용하여 시계열을 분해한 후 패턴인식 기반의 비선형 예측모형인 Support Vector Machine(SVM)을 적용하였다. 상수도 수요량의 예측 과정은 다음과 같다. 첫째, 상수도 수요량 자료를 Wavelet Transform 기법을 통하여 단순화 시킨다. 둘째, Global Wavelet Spectrum을 통하여 통계적으로 의미 있는 성분만을 추출하고 이를 해석 대상으로 한다. 셋째, 특정 주기를 갖는 유의한 독립성분들에 대해서 최적 지체시간을 결정한 후 SVM모형을 통해 예측 모형을 구축한다. 넷째, 나머지 성분에 대해서도 SVM 모형을 적용하여 예측을 실시한 후 앞서 예측된 성분과 모두 결합하여 최종적으로 예측시계열을 구성한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.356-356
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• 2019

우리나라는 강우량의 계절적 편기가 심하여 홍수기인 6월부터 9월까지의 년간 총강우량이 2/3을 차지하고 있으며 갈수기의 경우에는 강우량의 부족으로 물 부족현상을 겪고 있다. 이와 같은 현상은 최근 기후변화로 인해 더욱 증가되고 있으며 홍수기에도 국지적인 강우발생이 크게 증가하여 갈수기 가뭄이 더욱 심화되고 있다. 이와 같이 갈수시 가뭄에 대한 대책을 세우기 위해서는 하천에 유입되는 물과 하천 내에서 시간에 따라 유하되거나 조절되는 등 하천 자체 내에서 변화하는 하천유량의 변화 및 하천 외부로 유출되는 용수수요량을 정확히 분석하는 물수지분석이 필요하다. 이에, 본 연구에서는 송강천을 대상유역으로 선정하고 DEM을 통해 3개의 단위유역을 구분하였다. 단위유역별 생활용수, 공업용수, 농업용수 등에 대한 용수수요량 추정을 통해 유역별 용수수요 총량과 장래 수요증가량을 산정하였다. TANK 모형을 활용하여 단위유역별 기준갈수량을 산정하고 물수지분석을 통해 물 부족 여부를 판단하여 단위유역별 하천유지유량을 산정하였다. 분석결과, 단위유역별 하천으로 유입되는 회귀수량이 많아 목표연도별 갈수시 하천유지유량이 평균갈 수량 보다 크게 분석되었으며, 평균갈수시에도 하천의 정상적인 기능 및 상태를 유지하기 위한 최소한의 유량 확보가 가능할 것으로 판단된다.

• Journal of Korean Society of Water and Wastewater
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• v.27 no.6
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• pp.761-770
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• 2013

This study was carried out to forecast the flow rate and water quality at the inlet of the Saemangeum bay in Korea using the SWMM(Storm Water Management Model) and the WASP(Water Analysis Simulation Program), and to analyze the impacts of pollutant loading from non-point source on the water quality of the bay. The calibration and validation of flow rate and water quality were performed using those from two monitoring points in the Mankyeong river administrated by Korean Ministry of Environment as part of the national water quality monitoring network. When the river flow rate was calibrated and validated using the rainfall intensities during 2011-2012, $R^2$ (i.e., coefficient of determination) was ranged from 0.91 to 0.96. For water qualities, it was shown that $R^2$ of BOD(Biochemical Oxygen Demand) was ranged from 0.56 to 0.86, and $R^2$ of T-N(Total Nitrogen) was from 0.64 to 0.75, and $R^2$ of T-P(Total Phosphorus) was from 0.67 to 0.89. The integrated modeling system showed significant advances in the accuracy to estimate the water quality. Finally, further simulations showed that annual average flow of the river running into the bay was estimated to be $1.439{\times}10^9m^3/year$. The discharged load of BOD, T-N, and T-P into the bay were anticipated to be 618.7 ton/year, 331.5 ton/year, and 40.4 ton/year, respectively.

• Journal of Korean Society of Water and Wastewater
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• v.20 no.6
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• pp.799-811
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• 2006

As an alternative measure to replace reactive stance with proactive one, a risk based management scheme has been commonly applied to enhance public satisfaction on water service by providing a higher creditable solution to handle a rehabilitation problem of pipe having high potential risk of leaks. This study intended to examine the feasibility of a simulation model to predict a recurrence probability of pipe leaks. As a branch of the data mining technique, probabilistic neural network (PNN) algorithm was applied to infer the extent of leaking recurrence probability of water network. PNN model could classify the leaking level of each unit segment of the pipe network. Pipe material, diameter, C value, road width, pressure, installation age as input variable and 5 classes by pipe leaking probability as output variable were built in PNN model. The study results indicated that it is important to pay higher attention to the pipe segment with the leak record. By increase the hydraulic pipe pressure to meet the required water demand from each node, simulation results indicated that about 6.9% of total number of pipe would additionally be classified into higher class of recurrence risk than present as the reference year. Consequently, it was convinced that the application of PNN model incorporated with a data base management system of pipe network to manage municipal water distribution network could make a promise to enhance the management efficiency by providing the essential knowledge for decision making rehabilitation of network.

• Journal of Soil and Groundwater Environment
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• v.20 no.2
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• pp.1-9
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• 2015

Groundwater has been a very precious resource for human life and economic development in the world. With increasing population and food demand, the groundwater use especially for agriculture is largely elevated worldwide. The very much large groundwater use results in depletion of major aquifers, land subsidences in many large cities, anthropogenic groundwater contamination, seawater intrusion in coastal areas and accompanying severe conflicts for water security. Furthermore, with the advent of changing climate, securing freshwater supply including groundwater becomes a pressing and critical issue for sustainable societal development in every country because prediction of precipitation is more difficult, its uneven distribution is aggravating, weather extremes are more frequent, and rising sea level is also threatening the freshwater resource. Under these difficulties, can groundwater be sustaining its role as essential element for human and society in the near future? We have to focus our efforts and wisdom on answering the question. Korean government should increase its investment in securing groundwater resources for changing climate.

• Nuclear Engineering and Technology
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• v.36 no.2
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• pp.175-183
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• 2004

For the analysis of a dry process fuel cycle, new modules were implemented into the fuel cycle analysis code DYMOND, which was developed by the Argonne National Laboratory. The modifications were made to the energy demand prediction model, a Canada deuterium uranium (CANDU) reactor, direct use of spent pressurized water reactor (PWR) fuel in CANDU reactors (DUPIC) fuel cycle model, the fuel cycle calculation module, and the input/output modules. The performance of the modified DYMOND code was assessed for the postulated once-through fuel cycle models including both the PWR and CANDU reactor. This paper presents modifications of the DYMOND code and the results of sample calculations for the PWR once-though and DUPIC fuel cycles.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.435-435
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• 2017

최근 태국 짜오프라야강 유역의 물 부족 문제 해결을 위해 한국 정부와 태국 정부간 G2G사업으로 "태국 짜오프라야강 유역과 인근 유역 연계 수자원개발 마스터플랜 수립"이 추진되고 있다. 본 연구에서는 장기간 가뭄 등으로 물 부족 문제가 심각한 태국 짜오프라야강 유역에 대하여 다각적인 추가용수 공급방안을 검토하고 이를 토대로 수자원 장기 종합계획을 수립하기 위한 태국 짜오프라야강 유역의 물수급 현황 및 향후 전망을 분석하고자 한다. 본 연구에서는 ModSim 8.5 모형을 통해 물수급 현황 및 전망을 분석하였으며 대상유역은 짜오프라야강 유역과 인접한 유역 7개 유역(Ping, Wang, Yom, Nan, Sakae Krang, Pasak, Chao Phraya)을 대상으로 하였으며 총 유역면적은 $195,718km^2$로 우리나라 면적의 2배에 달한다. 또한 물수지 분석을 위한 입력자료 구축은 총 30년간(1986년 1월 1일 ~ 2013년 12월 31일)의 소유역별 자연유입량, 용수수요량(생활, 공업, 농업) 및 환경유량으로 구축하였으며 대상유역의 대규모 시설물인 19개소의 댐에 대한 제원도 태국 현지 기관을 통해 확보하여 물수지 분석에 적용하였다. 물수지 분석시 적용된 용수수요량에 대한 공급우선순위는 환경유량, 생할용수, 공업용수, 농업용수순이며 동일 용수의 경우 상류에 위치한 수요량에 우선순위를 우선적으로 부여하였다. 각 수요량에 대한 회귀율은 태국 물수급 해석 조건에 맞춰 환경유량 100%, 생공용수 0%, 농업용수 50%로 적용하였다. 연구결과, 2015년을 대상으로 분석한 불수급 현황은 생공용수의 경우, Ping과 Wang 유역에서만 수요량 대비 10~30%정도 부족량이 발생한데 반해 농업용수의 경우, 전 유역에서 약 20~40% 정도의 부족량이 발생하고 있으며 2025년 및 2035년을 대상으로 분석한 물수급 전망은 2015년 현황과 유사하나 부족량의 심도를 더욱 커지고 범위도 넓어지는 경향을 나타내고 있으며 농업용수의 경우 전유역에서 약 20~50%정도의 부족량이 발생하였으며 가장 극한 부족이 발생한 소유역은 80%까지도 발생될 것으로 전망되었다.

• Journal of The Geomorphological Association of Korea
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• v.23 no.1
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• pp.87-101
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• 2016

This study was conducted to develop a hydrological model of catchment water balance which is able to estimate irrigation return flows, so BROOK90-K (Kongju National University) was developed as a result of the study. BROOK90-K consists of three main modules. The first module was designed to simulate water balance for reservoir and its catchment. The second and third module was designed to simulate hydrological processes in rice paddy fields located on lower watershed and lower watershed excluding rice paddy fields. The models consider behavior of floodgate manager for estimating the storage of reservoir, and modules for water balance in lower watershed reflects agricultural factors, such as irrigation period and, complex sources of water supply, as well as irrigation methods. In this study, the models were applied on Guryangcheon stream watershed. R2, Nash-Sutcliffe efficiency (NS), NS-log1p, and root mean square error between simulated and observed discharge were 0.79, 0.79, 0.69, and 4.27 mm/d respectively in the model calibration period (2001~2003). Furthermore, the model efficiencies were 0.91, 0.91, 0.73, and 2.38 mm/d respectively over the model validation period (2004~2006). In the future, the developed BROOK90-K is expected to be utilized for various modeling studies, such as the prediction of water demand, water quality environment analysis, and the development of algorithms for effective management of reservoir.