• Journal of Korea Water Resources Association
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• v.33 no.1
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• pp.99-110
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• 2000

In this study we proposed a simple method for generating multi-site daily rainfall based on the 1-order Markov chain and considering the spatial correlation. The occurrence of rainfall is simulated by a simple 1st-order Markov chain and its intensity to be chosen randomly from the observed data. The spatial correlation between sites could be conserved as the rainfall intensity at each site is to be chosen consistently with the target site in time through generation. It is found that the generated daily rainfall data reproduce genera] characteristics of the observed data such as average, standard deviation, average number of wet and dry days, but the clustering level in time is somewhat loosened. Thus, the lag-I correlation coefficient of the generated data gave smaller value than the observed, also the average lengths of wet run and dry run and the wet-to-wet and dry-to-dry probabilities were a bit less than the observed. This drawback seems to be overcome somewhat by choosing a proper site representing overall basin characteristics or by use of more detailed states of rainfall occurrence.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.4 no.1
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• pp.103-112
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• 1984

This study is an effort to develop a series of empirical procedure for the determination of design flood for a small watershed based on the unit hydrograph theory. It is shown that a flood discharge of a watershed with a specific return period can be expressed as a product of its watershed area, rainfall factor, runoff factor and flood peak reduction factor. Since the procedures for the determination of rainfall factor and runoff factor were already developed in the previous study (13) a series of step-by-step procedure is devised to empirically determine the flood peak reduction factor in the present study. Using the methodology developed herein the 50-year design flood, which is of concern in the drainage of agricultural lands, is estimated for a watershed on upper Kyungan River and compared with the design floods by the existing methods now in use. The flood peak reduction factor was correlated with the dimensionless parameter consisted of the rainfall duration divided by the basin lag time, which was computed from the derived unit hydrographs by the method of moment. The unit hydrographs of various durations were synthesized by the method of build up and S-curve. A multiple correlation was also made between the basin lag time and the physiographic parameters of the watershed, i.e., the stream length and the average stream slope.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.171-171
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• 2011

상수도의 합리적인 운용과 관리를 위해서는 급수량 예측이 매우 중요하다. 기존 급수량 예측은 신경망과 칼만 필터법을 사용한 연구들이 대부분이었다. 이러한 연구결과들은 높은 상관결과를 갖고 있지만 이는 자기상관계수에 대한 높은 의존도에 따른 결과로 볼 수 있다. 즉, 예측의 결과가 전날 수요량을 거의 그대로 따라오는 경향을 띄어, 급수량 예측 그래프가 기존 그래프를 오른쪽으로 이동시킨 것과 같이 나타난다. 본 연구에서는 이러한 문제점들을 해결하기 위해서 물수요량을 예측하는데 있어서 효과적인 예측인자를 도출하는 것이 우선되어야 할 것으로 판단되었다. 이에, 물수요량 특성을 효과적으로 나타내어 줄 수 있는 예측인자로서 강수량, 최저온도, 최고온도, 평균온도 등을 1차적으로 선정하였다. 이들 예측인자들과 서울시 물수요량과의 상관성을 평가하여 최적의 예측인자 Set과 지체시간 등을 산정하였다. 이렇게 선정된 예측인자와 Bayesian 통계기법 기반의 회귀분석 모형을 구축하여 물수요량을 예측하였다. 본 연구에서 적용하고자 하는 계층적 Bayesian 모형은 유사한 특성을 가지는 자료계열들 사이에서 서로 보완이 될 수 있는 정보들을 추출함으로써 모형이 갖는 불확실성을 상당히 줄일 수 있는 방법이다. 이러한 모형적 특징은 생산량 예측에 대한 불확실성 저감 측면에서 장점이 있을 것으로 판단된다. 본 연구에서는 광암, 암사, 구의, 뚝도, 영등포, 강북 정수장을 대상으로 모형의 적합성을 평가하였다. 이러한 연구결과는 향후 정수장 운영계획 및 동일한 시스템을 갖는 상수도 급수량 예측 시 유용하게 사용할 수 있을 것이다.

• Journal of Korean Society of Transportation
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• v.21 no.4
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• pp.67-77
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• 2003

The purpose of this study is to provide the criteria for implementing unprotected left turn at intersections with variation of traffic volume on a cross road approach. Using Transyt-7F model, the delays calculated from permissive and protected left turn signal system were compared by gradually increasing the left turn volume for a certain opposing through volume up to the volume limits to which permissive left turn is more effective, Average stopped delay of the intersection was used as the measure of effectiveness in this study. The major conclusions are (1) the lighter the traffic gets in a cross road, the more the allowable left turn volume increases. The allowable left turn volume when the ratio of cross traffic to the concerned approach traffic is 0.6 appears about 50% more than the volume when the ratio is 1.0. (2) Comparing to the criteria of the manual of traffic safety facility, the results when the traffic ratio is 0.6 seem to be most similar the criteria of manual and the results when the traffic ratio are 0.8 and 1.0 appears to be lower than the criteria of manual. (3) The possible amount of making a left turn that is inversely proportional to the opposing through traffic, decreases as the number of opposing through lanes increases. The products of volume need to be used as the criteria of permissive left turn with considerable cautions because of its low consistency.

• Journal of Korean Society of Transportation
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• v.32 no.4
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• pp.410-420
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• 2014

This research suggests a new tram signal priority model which determines signal timings and tram intersection waiting time using analytical method. This model can calculate the signal timings for Early Green and Green Extension among the active tram signal priority techniques by tram detection time of upstream detector. Moreover, it can determine the tram intersection waiting time that means tram intersection travel time delay from a vantage point of tram travel. Under the active tram signal priority condition, priority phases can bring additional green time from variable green time of non-priority phases. In this study, the signal timing and tram intersection waiting time calculation model was set up using analytical methods. In case studies using an isolated intersection, this study checks tram intersection waiting time ranged 12.7 to 29.4 seconds when variable green times of non-priority phases are 44 to 10 seconds under 120 seconds of cycle length.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.2
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• pp.22-34
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• 2011

This paper presents the investigation results of a research on how engineers can analyze the economic effect of the ETCS(Electronic Toll Collection System) installed to minimize the vehicle delays on freeway tollgates during toll payments. This research considered this economic effect to occur in the form of vehicle passing time reductions at the ETCS, and the multi-service queuing theory was applied to estimate these values. This research found: 1) When vehicles approaching tollgates show Poisson distribution and the service time of the ETCS shows Exponential distribution, the multi-service queuing theory would be applicable for estimating vehicle passing times at toll-gates, 2) Despite the ETCS placement, exit sections of tollgates give a greater reduction of vehicle passing times than entering sections due to more delays at conventional toll payments, and 3)The ETCS would not guarantee vehicle passing time reductions all the time, because in such a case as many vehicles were queuing at the ETCS, the total delay level for a toll gate would increase greatly. In addition, in order to examine the accuracy of the estimated vehicle passing values, this research compared the values from the multi-service queuing theory with the observed values from a set of field survey values at freeway toll-gates, and found that the two values were in a good agreement with a very low error range of 1-3 seconds per vehicle. Based on this result, the multi-service queuing theory was recommended for practice.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.358-358
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• 2023

본 연구에서는 그동안 수자원분야 강우유출 해석분야에 활용되었던 대표적인 머신러닝&딥러닝(ML&DL) 모델을 활용하여 모델의 하이퍼파라미터 튜닝뿐만 아니라 모델의 특성을 고려한 기상 및 수문데이터의 조합과 전처리(lag-time, 이동평균 등)를 통하여 데이터 특성과 ML&DL모델의 조합시나리오에 따른 일 유입량 예측성능을 비교 검토하는 연구를 수행하였다. 이를 위해 소양강댐 유역을 대상으로 1974년에서 2021년까지 축적된 기상 및 수문데이터를 활용하여 1) 강우, 2) 유입량, 3) 기상자료를 주요 영향변수(독립변수)로 고려하고, 이에 a) 지체시간(lag-time), b) 이동평균, c) 유입량의 성분분리조건을 적용하여 총 36가지 시나리오 조합을 ML&DL의 입력자료로 활용하였다. ML&DL 모델은 1) Linear Regression(LR), 2) Lasso, 3) Ridge, 4) SVR(Support Vector Regression), 5) Random Forest(RF), 6) LGBM(Light Gradient Boosting Model), 7) XGBoost의 7가지 ML방법과 8) LSTM(Long Short-Term Memory models), 9) TCN(Temporal Convolutional Network), 10) LSTM-TCN의 3가지 DL 방법, 총 10가지 ML&DL모델을 비교 검토하여 일유입량 예측을 위한 가장 적합한 데이터 조합 특성과 ML&DL모델을 성능평가와 함께 제시하였다. 학습된 모형의 유입량 예측 결과를 비교·분석한 결과, 소양강댐 유역에서는 딥러닝 중에서는 TCN모형이 가장 우수한 성능을 보였고(TCN>TCN-LSTM>LSTM), 트리기반 머신러닝중에서는 Random Forest와 LGBM이 우수한 성능을 보였으며(RF, LGBM>XGB), SVR도 LGBM수준의 우수한 성능을 나타내었다. LR, Lasso, Ridge 세가지 Regression모형은 상대적으로 낮은 성능을 보였다. 또한 소양강댐 댐유입량 예측에 대하여 강우, 유입량, 기상계열을 36가지로 조합한 결과, 입력자료에 lag-time이 적용된 강우계열의 조합 분석에서 세가지 Regression모델을 제외한 모든 모형에서 NSE(Nash-Sutcliffe Efficiency) 0.8이상(최대 0.867)의 성능을 보였으며, lag-time이 적용된 강우와 유입량계열을 조합했을 경우 NSE 0.85이상(최대 0.901)의 더 우수한 성능을 보였다.

• Spatial Information Research
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• v.8 no.2
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• pp.257-274
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• 2000

Recently, natural environment is being forced by the quick increasing of population and industrialization, and especially, capacity and pollution of water resource is being come to the front. It needs to extract the accurate topological and hydrological parameters of watershed in order to manage water resource efficiently. But, these data are processed yet by manual work and simple operation in hydrological fields. In this paper, we presented algorithm that could extract topological any hydrological parameters over Sumjin watershed using GIS and RS and it gives the saving of data processing time and the confidency of data. The extraction procedure of topological characteristics and hydrological parameters is as below. First, watershed and stream are extracted by DEM and curve number is extracted throughout the overlay of landcov map and soil map. Also, we extracted surface parameters like watershed length and the slope of watershed length by Grid computation into watershed and stream. And we gave the method that could extract hydrologic parameters like Muskingum K and sub-basin lag time by executing computation into surface parameters and average SCS curve number being extracted.

• Journal of Korea Water Resources Association
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• v.50 no.1
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• pp.65-73
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• 2017

This study analyzed the peak drought severity and drought duration of the Cheongmicheon watershed from 1985 to 2015 to assess the lag time of peak drought severity between several drought indices. Standardized Precipitation Index (SPI) based on precipitation and Standardized Precipitation Evapotranspiration Index (SPEI) based on precipitation and evapotranspiration were applied as meteorological drought indices. Streamflow Drought Index (SDI) based on runoff data was applied as hydrological drought index. In case of SDI, we used Soil and Water Assessment Tool (SWAT) model for simulation of daily runoff data. As a result, the time of peak drought severity of SDI occurred after the occurrence of SPI and SPEI. The lag time for the peak drought severity, on average, between SDI and SPI was 0.59 months while SDI and SPEI was 0.79 months. As compared with SDI, the maximum delay was 2 months for both SPI and SPEI. This study results also shows that even though the rainfall events were able to cope with meteorological droughts, they were not always available to solve the hydrological droughts in the same time.

• Journal of Korea Water Resources Association
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• v.42 no.4
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• pp.297-307
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• 2009

For reliable water quality simulation by semi distributed model, accurate daily runoff simulation should have preceded. In this study, newly developed channel routing method which is nonlinear storage method is combination of Muskingum routing method and variable storage routing method and temporally weighted average curve number method were applied for effect analysis of water quality simulation. Developed modules, which are added in SWAT models and simulation, were conducted for the Chungju dam watershed. The simulation result by each module applied effect. As a result of analysis contribute water quality modeling, nonlinear storage method is more effective than temporally weighted average curve number method. Nutrient loading discharge was affected by development of runoff delaying from improvement of channel routing, because of characteristics of nonpoint source pollution.