• Journal of Korea Water Resources Association
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• v.35 no.6
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• pp.763-777
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• 2002

The objective of this study is to develop computer simulation model that produces precipitation patterns from stochastic model. The hourly precipitation process consists of the precipitation occurrence and precipitation amounts. In this study, an event cluster model developed by Lee and Lee(2002) is used to describe the occurrence process of events, and the hourly precipitation amounts within each event is described by a nonstationary form of a first-order autoregressive process. The complete stochastic model for hourly precipitation is fitted to historical precipitation data by estimating the model parameters. An analysis of historical and simulated hourly precipitation data for Seoul indicates that the stochastic model preserves many of the features of historical precipitation. The autocorrelation coefficients of the historical and simulated data are nearly identical except for lags more than about 3 hours. The precipitation intensity, duration, marginal distributions, and conditional distributions for event characteristics for the historical and simulated data showed in general good agreement with each other.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.247-247
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• 2015

Global Climate Model (GCM) is too coarse to apply at a basin scale. The spatial downcsaling is needed to used to permit the assessment of the hydrological changes of a basin. Furthermore, temporal downscaling is required to obtain hourly precipitation to analyze a small or medium basin because only few or several hours are used to determine the peak flows after it rains. In the current study, the spariotemporal distribution of downscaled hourly precipitation for RCP4.5 and RCP8.5 scenarios over South Korea is presented as well as its implications over hydrologica responses. Mean hourly precipitation significantly increases over the southern part of South Korea, especially during the morning time, and its increase becomes lower at later times of day in the RCP8.5 scenario. However, this increase cannot be propagated to the mainland due to the mountainous areas in the southern part of the country. Furthermore, the hydrological responses employing a distributed rainfall-runoff model show that there is a significant increase in the peak flow for the RCP8.5 scenario with a slight decrease for the RCP4.5 scenario. The current study concludes that the employed temporal downscaling method is suitable for obtaining the hourly precipitation data from daily GCM scenarios. In addition, the rainfall runoff simulation through the downscaled hourly precipitation is useful for investigating variations in the hydrological responses as related to future scenarios.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.4
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• pp.51-57
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• 2024

This study was conducted on how to simulate runoff, which was done using existing physical models, using an LSTM (Long Short-Term Memory) model based on deep learning. Tancheon, the first tributary of the Han River, was selected as the target area for the model application. To apply the model, one water level observatory and four rainfall observatories were selected, and hourly data from 2020 to 2023 were collected to apply the model. River water level of the outlet of the Tancheon basin was simulated by inputting precipitation data from four rainfall observation stations in the basin and average preceding 72-hour precipitation data for each hour. As a result of water level simulation using 2021 to 2023 data for learning and testing with 2020 data, it was confirmed that reliable simulation results were produced through appropriate learning steps, reaching a certain mean absolute error in a short period time. Despite the short data period, it was found that the mean absolute percentage error was 0.5544~0.6226%, showing an accuracy of over 99.4%. As a result of comparing the simulated and observed values of the rapidly changing river water level during a specific heavy rain period, the coefficient of determination was found to be 0.9754 and 0.9884. It was determined that the performance of LSTM, which aims to simulate river water levels, could be improved by including preceding precipitation in the input data and using precipitation data from various rainfall observation stations within the basin.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.501-504
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• 2008

A non-homogeneous markov model which is able to simulate hourly rainfall series is developed for estimating reliable hydrological variables. The proposed approach is applied to simulate hourly rainfall series in Korea. The simulated rainfall is used to estimate the design rainfall and compared to observations in terms of reproducing underlying distributions of the data to assure model's validation. The model shows that the simulated rainfall series reproduce a similar statistical attribute with observations, and expecially maximum value is gradually increased as number of simulation increase.

• Journal of Korea Water Resources Association
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• v.41 no.3
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• pp.265-276
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• 2008

The observed data of enough period need for design of hydrological works. But, most hydrological data aren't enough. Therefore in this paper, hourly precipitation generated by nonhomogeneous Markov chain model using variable Kernel density function. First, the Kernel estimator is used to estimate the transition probabilities. Second, wet hours are decided by transition probabilities and random numbers. Third, the amount of precipitation of each hours is calculated by the Kernel density function that estimated from observed data. At the results, observed precipitation data and generated precipitation data have similar statistic. Also, rainfall mass curve is derived by calculated transition probabilities for generation of hourly precipitation.

• Journal of Korea Water Resources Association
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• v.41 no.3
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• pp.251-264
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• 2008

In this study, a nonhomogeneous markov model which is able to simulate hourly rainfall series is developed for estimating reliable hydrologic variables. The proposed approach is applied to simulate hourly rainfall series in Korea. The simulated rainfall is used to estimate the design rainfall and flood in the watershed, and compared to observations in terms of reproducing underlying distributions of the data to assure model's validation. The model shows that the simulated rainfall series reproduce a similar statistical attribute with observations, and expecially maximum value is gradually increased as number of simulation increase. Therefore, with the proposed approach, the non-homogeneous markov model can be used to estimate variables for the purpose of design of hydraulic structures and analyze uncertainties associated with rainfall input in the hydrologic models.

• Journal of Korea Water Resources Association
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• v.38 no.8 s.157
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• pp.595-604
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• 2005

Precipitation simulation for making the data size larger is an important task for hydrologic analysis. The simulation can be divided into two major categories which are the parametric and nonparametric methods. Also, precipitation simulation depends on time intervals such as daily or hourly rainfall simulations. So far, Markov model is the most favored method for daily precipitation simulation. However, most models are consist of state transition probability by using the homogeneous Markov chain model. In order to make a state vector, the small size of data brings difficulties, and also the assumption of homogeneousness among the state vector in a month causes problems. In other words, the process of daily precipitation mechanism is nonstationary. In order to overcome these problems, this paper focused on the nonparametric method by using uni-variate and multi-variate when simulating a precipitation instead of currently used parametric method.

• Journal of Korea Water Resources Association
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• v.49 no.11
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• pp.913-922
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• 2016

A long-term precipitation record is typically required for establishing the reliable water resources plan in the watershed. However, the observations in the hourly precipitation data are not always consistent and there are missing values within the time series. This study aims to develop a hourly rainfall simulator for extending rainfall data, based on the well-known Neyman-Scott Rectangular Pulse Model (NSRPM). Moreover, this study further suggests a multisite hourly rainfall simulator to better reproduce areal rainfalls for the watershed. The proposed model was validated with a network of five weather stations in the Uee-stream watershed in Seoul. The proposed model appeared a reasonable result in terms of reproducing most of the statistics (i.e. mean, variance and lag-1 autocovariance) of the rainfall time series at various aggregation levels and the spatial coherence over the weather stations.

• Atmosphere
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• v.17 no.4
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• pp.393-405
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• 2007

Simulation results of WRF for the case of typhoon 'Rusa' were analyzed, comparing with observed data especially forjavascript:confirm_mark('abe', '1'); the Gangneung area around to examine its ability in numerical simulation. From the hourly precipitation time series, two peaks were found at Gangneung and Daegwallyeong, while only one peak was found from those of inland regions else. Especially, for the Yeongdong region, the first peak was directly related to spiral bands generated in front of the typhoon. Convective cells that were developed within the spiral bands moved to the eastern coastal area from the sea so that local heavy rainfall occurred in the Yeongdong region. The second peak was mainly related to the accompanying rain band of typhoon itself, topographic effect and the convergence near Gangneung area. Precipitation in Gangneung was simulated as much as about 30% of observed one. The main reason of this result came from a poor representation of wind directions in Gangneung area of WRF model. Observed wind direction was northwesterly but simulated one was nearly easterly in the area. This might shift a local heavy rainfall area downstream to the mountain area rather than the coastal area.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1235-1239
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• 2008

최근 기상이변 및 이상기후로 인해 예상치 못한 극치사상이 빈번하게 발생하고 있으며, 이로 인한 수자원관리 측면에 있어 많은 어려움을 겪고 있다. 특히 집중호우나 태풍 사상과 같이 단 시간 내에 많은 양의 강수량을 동반한 경우 댐과 같은 대형 수공구조물의 파괴로 인해 인명 및 재산피해의 가능성을 증가시키고 있다. 따라서 본 연구에서는 우리나라에 발생하는 시간강수량에 대한 평가를 하기 위해 우리나라에 발생하는 시간강수량과 수문기상인자인 해수면 온도 및 습윤지수와의 상관관계 분석을 통해 수문기상인자가 우리나라 강수량에 미치는 영향을 평가하였다. 또한, 우리나라에 발생하는 극한강우를 발생 원인별로 태풍 사상과 집중호우 사상으로 구분하여 수문기상인자와의 상관성 분석 결과를 바탕으로 Empirical Simulation Technique 기법을 적용하여 집중호우와 태풍으로 발생하는 강우의 특성을 평가하였다.