• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.288-288
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• 2018

점착성 유사는 응집 현상을 겪는 유사로, 응집 현상(Flocculation Process)는 응집 과정(Aggregation Process)와 파괴 과정(Breakup Process)의 경쟁으로 이루어진다고 여겨진다. 응집 현상을 통해 점착성 유사는 물과 점착성을 띠는 작은 입자들의 덩어리인 플럭(Floc)을 형성하여 흐름 내에서는 대부분이 플럭의 형태로 이동한다. 점착성 유사의 응집 모형 중 하나인 플럭 성장모형(Floc Growth Model, FGM)은 상미분 방정식으로 시간에 따른 플럭의 크기를 계산하는 모형이다. 응집과 파괴의 평형 상태에서 평균 입경을 얻는다. 이러한 FGM은 낮은 수치 계산 비용으로 합리적인 계산 결과를 얻을 수 있으며, 유사 이동 모형 혹은 흐름 모형과의 결합이 수월한 장점을 가진다. 또한, 닫힌 계(Closed System)에서 질량이 보존되는 특징이 있다. 반면, 결정론적인 특성을 띠면서 특정 플럭 크기만을 계산하기 때문에 점착성 유사의 입도 분포에 대한 정보를 얻을 수 없다. 결정론적 특성을 띠는 FGM에 추계학적 방법을 적용함으로써 특정 확률 분포형을 가지는 플럭의 입도 분포를 얻을 수 있다. 본 연구에서는 기 개발된 추계학적 FGM과 유사 이동 모형의 결합을 통해 변화하는 유수동역학적 조건에서 플럭의 입도 분포를 산정하고자 한다. 이전의 많은 실험실 실험 결과들은 부유가 발생한 상태를 유지하면서 수행되는 것으로, 특정 난류 특성(난류 소산 매개변수)와 특정 유사 농도 조건에서의 입도 분포를 얻는다. 그러나 하구부 및 하천의 하류는 조류의 영향을 받는 구간으로, 점착성 유사의 특성을 분석하기 위해서는 변화하는 유수동역학적 특성에 관한 고려가 필수적이라 할 수 있다. 결합된 점착성 유사 입도 분포 모형은 플럭의 침강과 재부유를 고려할 수 있는 특징을 가지며, 실측자료와의 비교를 통해 입도 분포를 합리적으로 모의하는 것으로 나타난다. 본 연구에서 개발된 점착성 유사 입도 분포 모형은 나아가 비점착성 유사의 입도 분포 모형과의 결합을 통해 두 종류의 유사가 혼재하는 구간에서도 합리적인 입도분포와 유사의 이동을 모의할 수 있을 것으로 예측된다.

• Journal of Korea Water Resources Association
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• v.36 no.2
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• pp.195-209
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• 2003

Spatial-Stochastic Neural Networks Model(SSNNM) is used to estimate long-term streamflow in the parallel reservoir groups. SSNNM employs two kinds of backpropagation algorithms, based on LMBP and BFGS-QNBP separately. SSNNM has three layers, input, hidden, and output layer, in the structure and network configuration consists of 8-8-2 nodes one by one. Nodes in input layer are composed of streamflow, precipitation, pan evaporation, and temperature with the monthly average values collected from Andong and Imha reservoir. But some temporal differences apparently exist in their time series. For the SSNNM training procedure, the training sets in input layer are generated by the PARMA(1,1) stochastic model and they covers insufficient time series. Generated data series are used to train SSNNM and the model parameters, optimal connection weights and biases, are estimated during training procedure. They are applied to evaluate model validation using observed data sets. In this study, the new approaches give outstanding results by the comparison of statistical analysis and hydrographs in the model validation. SSNNM will help to manage and control water distribution and give basic data to develop long-term coupled operation system in parallel reservoir groups of the Upper Nakdong River.

• Journal of Korea Water Resources Association
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• v.42 no.11
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• pp.953-961
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• 2009

The objective of this study is to develop a stochastic continuous storage function model for enhancement of an event-oriented watershed and channel storage function models which have been used as an official flood forecast model in Korea. For this study, soil moisture accounting component is added to the original storage function model and each hydrologic component, such as surface flow, subsurface flow, groundwater flow and actual evaportranspiration, is simulated as a function of soil water content. And also, ensemble Kalman filtering technique is used for real-time assimilation of measured streamflow from various stream locations in the watershed. Therefore the enhanced model will be able to simulate hydrologic components for long-term period without additional estimation of model parameters and to give more accurate and reliable results than those from the existing deterministic model due to the assimilation of measured streamflow data.

• Water for future
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• v.20 no.4
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• pp.257-266
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• 1987

The existing stochastic models for the data with hydrologic persistence can be classified into two categories; the short-term and long-term models.For the present study, the Hurst coefficients which are the dominant parameter in the Fast Fractional Gaussian Noise(FFGN)model, one of the long-term models. are estimated with historical annual and monthly streamflows. In order to verify the applicability of these estimators the statistical properties of the generated annual streamflows by FFGN model are compared with those of the historical annual streamflows. Then the generated annual streamflows by FFGN model are disaggregated into the monthly streamflows by disaggregation model at two sites, i.e. Waekman and Jindong, in the Nakdong River Basin. On the other hand, the monthly stream flows at the two sites were also generated by the two-site Matalas model which is one of the short-term models. To evaluate the applicability of the above models and to select the better model the statistical properties of the generated monthly streamflows by two models were compared with those of the historicals, respectively.

• Journal of Korea Water Resources Association
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• v.37 no.5
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• pp.353-361
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• 2004

Effective storage in agricultural reservoir has been determined through the reservoir simulation operation based on the water budget analysis. Since each watershed has the native property for runoff, considering the runoff yielding from the basin is feasible to the determination of reservoir effective storage. In this study the stochastic linear programming model considering mainly runoff from watershed has been also formulated to analyze the effective storage of the exiting reservoir. The linear decision rule coupled with chance-constrained model in the linear programming model contributes to reduce the size of linear program model without considering the period of analysis. The Geum-Gang reservoir located in Ansung have been adopted to evaluate the effective storage. It has been shown that the effective storage based on the linear programming model is greater than that based on the water budget analysis. It has been also desired that once the effective storage is obtained through the linear programming model, operation of the reservoir should be performed to check the designed capacity.

• Water for future
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• v.19 no.2
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• pp.149-156
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• 1986

The generated sequences of monthly flows were analyzed based on the range concept. With the optimum operation rule of the reservoirs as the one which maximizes the wateruse downstream the waterrelease from the reservoir was determined and with \ulcorner consideration to the mean inflows and the range of monthly flows the required reservoirs capacity was stochastically determind. It is suggested that the result obtained in this study would be applied to approximately estimate, in the stage of preliminary design, the required capacity of a reservoir in question with the limited information such as the mean monthly inflow and the period of reservoir operation. For the determination of a reservoir capacity Rippl's mass-curve method has been long used with the past river flow data assuming the same flow records will be repeated in the future. This study aims to find out a better method for determining the reservoir capacity by employing the analytical theory based on the stochastic process. For the present study the synthetic generation methods of Thomas-Fiering type was used to synthetically generate 50 years of monthly river inflows to three single-purpose reservoirs and three multi-purpose reservoirs.

• Journal of Korea Water Resources Association
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• v.30 no.2
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• pp.155-163
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• 1997

In this study, drought analysis of annual flows of Jindong, Hyunpoong, and Waekwan stations located at Nakdong River Basins was performed based on multivariate stochastic models. The stochastic models used were multivariate autoregressive model (MAR) and multivariate contemporaneous (MCAR) model. MCAR(1) and MAR(1) models were selected to be a appropriate models for these stations based on skewness test of normality, test of uncorrelated residuals, and correlograms of the residual series of each model. The statistics generated by MCAR(1) model and MAR(1) model resembled very closely those computed from historical series. The drought characteristics such as run len호, run sum, and run intensity were fairly well reproduced for the various lengths of generated annual flows based on the MCAR(1) and MAR(1) models. Thus, these drought characteristics may give the important informations in planning mid or long term water supplying systems.

• Proceedings of the Korea Water Resources Association Conference
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• 1994.02a
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• pp.267-275
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• 1994

• Journal of Korea Water Resources Association
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• v.35 no.3
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• pp.275-284
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• 2002

In this study, a method of random resampling of residuals from stochastic models such as the Monte-Carlo model, the lag-one autoregressive model(AR(1)) and the periodic lag-one autoregressive model(PAR(1)), has been adopted to generate a large number of long traces of annual and monthly steamflows. Main advantage of this resampling scheme called the Bootstrap method is that it does not rely on the assumption of population distribution. The Bootstrap is a method for estimating the statistical distribution by resampling the data. When the data are a random sample from a distribution, the Bootstrap method can be implemented (among other ways) by sampling the data randomly with replacement. This procedure has been applied to the Yongdam site to check the performance of Bootstrap method for the streamflow generation. and then the statistics between the historical and generated streamflows have been computed and compared. It has been shown that both the conventional and Bootstrap methods for the generation reproduce fairly well the mean, standard deviation, and serial correlation, but the Bootstrap technique reproduces the skewness better than the conventional ones. Thus, it has been noted that the Bootstrap method might be more appropriate for the preservation of skewness.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.225-229
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• 2005

이류모형을 이용한 단기예측 레이더 강우자료와 관측 레이더자료의 비교를 통하여 얻어진 예측오차를 분석하였다. 임의 시점까지의 예측오차 장에 나타나는 확률분포 형태와 공간적 상관성을 분석하여 이들 특성을 반영하는 추후의 예측오차 장을 모의할 수 있었다. 모의된 예측오차 장과 합성된 단기예측 강우 장은 이류모형을 이용한 예측에 따른 불확실성 을 추계학적으로 반영한 예측강우를 제공한다.