• Journal of The Korean Society of Agricultural Engineers
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• v.48 no.1
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• pp.27-38
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• 2006

In this study, we developed a program to estimate discharge efficiently considering major hydraulic characteristic including water level, river bed, water slope and roughness coefficient in a natural river. Stream discharge was measured at Gongju gauge station located in the down stream of the Daechung Dam during normal and dry seasons from 2003 to 2004. The developed model was compared with the results from the existing rating curve at T/M gage stations, and was used for runoff analyses. Evaluating the developed river discharge estimation program, it was applied during 1983-2004 that base flow separation method and RRFS (Rainfall Runoff Forecasting System) which is based on SSARR (Streamflow Synthesis And Resevoir Regulation). The result presents the stage-discharge curve creator range at the Gong-ju is overestimated by approximately $10-20\%$, especially at the low stage. It is attributed to the hydraulic characteristics at the study. The discharge simulated by the RRFS and base flow separation, which is calibrated using the measurement at the early spring and late fall season during relatively d]v season, shows the least errors. The coefficient of roughness at Gongju station varied with the high and low water level.

• Journal of Korean Society on Water Environment
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• v.24 no.2
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• pp.230-238
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• 2008

This study evaluated the economic aspect of the rainwater harvesting facilities by hydrologically analyzing the inflow, rainwater consumption, rainfall loss, tank storage, and overflow time series to derive the net rainwater consumption and the number of days of rainwater available. This study considers several rainwater harvesting facilities in Seoul National University, Korea Institute of Construction Technology and Daejon World Cup Stadium and the results derived are as follows. (1) Increasing the water consumption decreases the number of days of rainwater available. (2) Due to the climate in Korea, a larger tank storage does not increase the amount and the number of days of water consumption during wet season (June to September), but a little in October. (3) Economic evaluation of the rainwater harvesting facilities considered in this study shows no net benefit (private benefit). (5) Flood reduction effect of rainwater harvesting facilities was estimated very small to be about 1% even in the case that 10% of all the basin is used as the rainwater collecting area.

• Journal of Korea Water Resources Association
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• v.38 no.2
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• pp.97-110
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• 2005

This paper presents a procedure of evaluation of reservoir capacity for additional water storage for dam rehabilitation. One of the techniques on the extension of rainfall has been developed, and the daily stream flows were simulated by the NWS-PC long-term rainfall-runoff model with the input of the extended daily rainfall which was stochastically generated by the nonhomogeneous markov chain model. We peformed a reliability analysis to Guisan dam about the optimal capacity of dam rehabilitation by using performance criteria that Hashimoto et al. (1982) presented. We estimated that the most suitable water level is approximately 155EL.M. suggested that this method can use supplemental methods to estimate optimum dam scale.

• Journal of Korea Water Resources Association
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• v.46 no.1
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• pp.47-58
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• 2013

Recently, an increase in the occurrence of sudden local flooding of great volume and short duration due to global climate changes has occasioned the significant danger and loss of life and property in Korea as well as most parts of the world. Such a local flood that usually occurs as the result of intense rainfall over small regions rises quite quickly with little or no advance warning time to prevent flood damage. To prevent the local flood damage, it is important to quickly predict the flood severity for flood events exceeding a threshold discharge that may cause the flood damage for inland areas. The aim of this study is to develop the NFI (New Flood Index) measuring the severity of floods in small ungauged catchments for use in local flood predictions by the regression analysis between the NFI and rainfall patterns. Flood runoff hydrographs are generated from a rainfall-runoff model using the annual maximum rainfall series of long-term observations for the two study catchments. The flood events above a threshold assumed as the 2-year return period discharge are targeted to estimate the NFI obtained by the geometric mean of the three relative severity factors, such as the flood magnitude ratio, the rising curve gradient, and the flooding duration time. The regression results show that the 3-hour maximum rainfall depths have the highest relationships with the NFI. It is expected that the best-fit regression equation between the NFI and rainfall characteristics can provide the basic database of the preliminary information for predicting the local flood severity in small ungauged catchments.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.12
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• pp.1209-1217
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• 2008

For efficient turbid water management a SWAT model was established for the Imha-Andong watershed where serious turbid water problems have frequently occurred. To evaluate soil loss combined with rainfall runoff process, the analysis focused on comparing the daily runoff discharge and concentration of suspended sediment (SS) using measured data sets. The results of annual SS load analysis for each sub-basin using the calibrated model showed that in the entire target watershed the soil loss ranged from 0.7 to 5.9 tons/ha in year 2005 and from 3.0 to 34.0 tons/ha in year 2003 when the typhoon 'Maemi' severly affected the area. In the future, it is suggest to increase model simulation accuracies supported by a long-term and extensive monitoring to enhance basin-wide suspended sediment estimation and management.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6B
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• pp.597-603
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• 2006

The purpose of this study is to improve the short term rainfall forecast skill using neural network model that can deal with the non-linear behavior between satellite data and ground observation, and minimize the flood damage. To overcome the geographical limitation of Korean peninsula and get the long forecast lead time of 3 to 6 hour, the developed rainfall forecast model took satellite imageries and wide range AWS data. The architecture of neural network model is a multi-layer neural network which consists of one input layer, one hidden layer, and one output layer. Neural network is trained using a momentum back propagation algorithm. Flood was estimated using rainfall forecasts. We developed a dynamic flood inundation model which is associated with 1-dimensional flood routing model. Therefore the model can forecast flood aspect in a protected lowland by levee failure of river. In the case of multiple levee breaks at main stream and tributaries, the developed flood inundation model can estimate flood level in a river and inundation level and area in a protected lowland simultaneously.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.230-230
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• 2023

딥러닝 알고리즘 중 과거의 정보를 저장하는 문제(장기종속성 문제)가 있는 단순 RNN(Simple Recurrent Neural Network)의 단점을 해결한 LSTM(Long short-term memory)이 등장하면서 특정한 유역의 강우-유출 모형을 구축하는 연구가 증가하고 있다. 그러나 하나의 모형으로 모든 유역에 대한 유출을 예측하는 지역화 강우-유출 모형은 서로 다른 유역의 식생, 지형 등의 차이에서 발생하는 수문학적 행동의 차이를 학습해야 하므로 모형 구축에 어려움이 있다. 따라서, 본 연구에서는 국내 12개의 유역에 대하여 LSTM 기반 분포형 지역화 강우-유출 모형을 구축한 이후 강우 이외의 보조 자료에 따른 정확도를 살펴보았다. 국내 12개 유역의 7년 (2012.01.01-2018.12.31) 동안의 49개 격자(4km²)에 대한 10분 간격 레이더 강우, MODIS 위성 이미지 영상을 활용한 식생지수 (Normalized Difference Vegetation Index), 10분 간격 기온, 유역 평균 경사, 단순 하천 경사를 입력자료로 활용하였으며 10분 간격 유량 자료를 출력 자료로 사용하여 LSTM 기반 분포형 지역화 강우-유출 모형을 구축하였다. 이후 구축된 모형의 성능을 검증하기 위해 학습에 사용되지 않은 3개의 유역에 대한 자료를 활용하여 Nash-Sutcliffe Model Efficiency Coefficient (NSE)를 확인하였다. 식생지수를 보조 자료를 활용하였을 경우 제안한 모형은 3개의 검증 유역에 대하여 하천 흐름을 높은 정확도로 예측하였으며 딥러닝 모형이 위성 자료를 통하여 식생에 의한 차단 및 토양 침투와 같은 동적 요소의 학습이 가능함을 나타낸다.

• Journal of Korean Society of Rural Planning
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• v.11 no.4 s.29
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• pp.67-74
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• 2005

The Doam watershed is located at alpine areas and the annual average precipitation, including snow accumulation, is significant higher than other areas. Thus, pollutant laden runoff and sediment discharge from the alpine agricultural fields are causing water quality degradation at the Doam watershed. To estimate soil erosion from the agricultural fields, the Universal Soil Loss Equation (USLE) has been widely used because of its simplicity to use. In the early spring at the Doam watershed, the stream flow increases because of snow melt, which results in erosion of loosened soil experiencing freezing and thaw during the winter. Also, extremely torrential rainfall, such as the typhoons 'RUSA' in 2002 and 'MAEMI' in 2003, caused significant amounts of soil erosion and sediment at the Doam watershed. However, the USLE model cannot simulate impacts on soil erosion of freezing and thaw of the soil. It cannot estimate sediment yield from a single torrential rainfall event. Also, it cannot simulate temporal changes in USLE input parameters. Thus, the Soil and Water Assessment Tool (SWAT) model was investigated for its applicability to estimate soil erosion at the Doam watershed, instead of the widely used USLE model. The SWAT hydrology and erosion/sediment components were validated after calibration of the hydrologic component. The R$^2$ and Nash-Sutcliffe coefficient values are higher enough, thus it is found the SWAT model can be efficiently used to simulate hydrology and sediment yield at the Doam watershed. The effects of snow melt on SWAT estimated stream flow and sediment were investigated using long-term precipitation and temperature data at the Doam watershed. It was found significant amount of flow and sediment in the spring are contributed by melting snow accumulated during the winter. Two typhoons in 2002 and 2003, MAEMI and RUSA, caused 33% and 22% of total sediment yields at the Doam watershed, respectively. Thus, it is recommended that the SWAT model, capable of simulating snow melt, sediment yield from a single storm event, and long-term weather data, needs to be used in estimating soil erosion at alpine agricultural areas to develop successful soil erosion management instead of the USLE.

• Journal of Environmental Science International
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• v.20 no.11
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• pp.1457-1464
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• 2011

In this study, the method of estimating hydrologic information (water depth, submerged period etc.) on the proper selection of construction point and scale as well as vegetation type suggested for the design of natural riparian rehabilitation structure. Long-term comprehensive watershed model SWAT-K(Korea) was applied to this purpose. Flow duration analysis was conducted to analyze the hydrologic characteristics of Pyungchang watershed at which the 'bangtul' construction method was tested. For this purpose 20 years (1989-2008) rainfall runoff analysis was carried out. Based on the simulated daily streamflow data, flow duration curve was made to analyze the flow characteristics, and the water depth hydrograph was made to analyze the water depth distribution at the cross section. Finally, the information for the selection of proper vegetation according to the submerged period is suggested.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.317-317
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• 2012

본 연구에서는 Kwater에서 개발한 RRFS를 기반으로 인도네시아의 Citarum 유역에 대하여 장기유출모형을 구축하여 보았다. Citarum 유역은 전체면적이 $13,600km^2$이며 유역의 중심부에 3개의 다목적 댐(Saguling, Cirata, Juanda)이 운용 중에 있는 대규모 유역으로서 Fig. 1과 같이 크게 3개의 권역(C-region, I-region, J-region)으로 구분하여 살펴볼 수 있다. 중심부의 C-region은 유역전반에 걸쳐 형성된 수지상의 하천망이 한 개의 유출구로 수렴하여 자바해로 배수되는 일반적인 배수구조를 갖는다. 하지만 이의 좌우에 위치한 I-region과 J-region은 병렬적으로 분포된 중소규모 유역들이 각기 개별적인 유출구를 통하여 독립적으로 자바해로 배수하게 된다. 또한 Juanda 댐의 하류부에는 대상유역의 좌우에 위치한 도심지 및 농경지에 대한 용수공급을 위해 3개의 대규모 인공수로(West Tarum Canal, East Tarum Canal, North Tarum Canal)가 연결되어 있다. 따라서 본 연구에서는 Citarum 유역의 이러한 복잡한 배수특성을 고려하여 우선 C-region에 대하여 RRFS를 이용하여 독립적인 유출모형을 구축하고 여기에 3개의 인공수로를 자연하천망의 분기와 같은 형태로 취급하여 해당 시스템을 확장하여 보았다. 이에 따라 I-region과 J-region은 각기 West Tarum Canal과 East Tarum Canal을 본류로 하는 배수구조를 갖게 되며 병렬적으로 위치한 중소유역들은 이들 인공수로에 대한 측방유역과 같이 취급할 수 있었다. Fig. 2는 본 연구에서 구축한 시스템을 이용하여 Saguling 댐의 유입량을 모의한 결과를 예시한다.