• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.4
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• pp.303-312
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• 2007

There is still a controversy going on about how to model energy dissipation due to breaking over frequency domain. In this study, we unveil the exact structure of energy dissipation using stochastic wave breaking model. It turns out that contrary to our present understanding, energy dissipation is cubically distributed over frequency domain. The verification of proposed model is conducted using the acquired data during SUPERTANK Laboratory Data Collection Project (Krauss et al., 1992). For further verification, we numerically simulate the nonlinear shoaling process of Conoidal wave over a beach of uniform slope, and obtain very promising results from the viewpoint of a skewness and asymmetry of wave field, usually regarded as the most fastidious parameter to satisfy.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.54-54
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• 2017

본 연구에서는 배수분구를 기준으로 서울특별시의 총 239개 지역 배수관망의 네트워크 특성을 깁스모형(Gibbs' model)을 이용하여 분석하였다. 깁스모형은 추계학적 하천망 모형으로 배수관망 네트워크의 특성을 검토하는데 사용된다. 또한 추계학적 모형이므로 같은 특성을 가지는 배수관망의 모의에도 이용된다. 분석결과 배수분구를 기준으로 서울시 총 239개 중 배수관망이 미 발단된 2개 지역을 제외한 237개를 값에 따라 총 8단계로 구분하여 분석하였다. ${\beta}$값이 $10^{-4}{\sim}10^{-1}$으로 비교적 비효율적인 배수관망은 전체 배수관망의 약 68%를 차지하는 것으로 나타났고, ${\beta}$값이 $10^0{\sim}10^3$으로 비교적 효율적인 배수관망은 전체 배수관망의 약 32%를 차지하는 것으로 나타났다. 따라서 서울시의 배수관망 특성은 비효율적인 관망이 지배적인 것으로 나타났다. 2010년과 2011년의 침수 흔적도와 ${\beta}$ 값의 상관분석을 수행한 결과 비효율적인 네트워크 특성을 가진 유역보다 상대적으로 효율적인 네트워크 특성을 가진 유역이 침수가 발생할 확률이 높다는 것을 밝혀냈다. 이러한 결과는 지속가능한 도시지역 배수관망 설계에 도움을 주고, 방재 관련 사업수립 및 침수원인 분석을 위한 연구에 기여할 것으로 판단된다.

• 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.30 no.3
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• pp.269-278
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• 1997

Operating rules, the basic principle of reservoir operation, are mostly developed from maximum or minimum, mean inflow series so that those rules cannot be used in practical operating situations to estimate the expected benefits or provide the operating policies for uncertainty conditions. Many operating rules based on the deterministic method that considers all operation variables including inflows as known variables can not reflect to uncertainties of inflow variations. Explicit operating rules can be developed for improving the weakness. In this method, stochastic trend of inflow series, one of the reservoir operation variables, can be directly method, the stochastic technique was applied to develop reservoir operating rule. In this study, stochastic dynamic programming using the concepts was applied to develop optimal operating rule for the Chungju reservoir system. The developed operating rules are regarded as a practical usage because the operating policy is following up the basic concept of Lag-1 Markov except for flood season. This method can provide reservoir operating rule using the previous stage's inflow and the current stage's beginning storage when the current stage's inflow cannot be predicted properly.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.2
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• pp.52-62
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• 2013

A stochastic Markov process (MP) model has been developed for evaluating the probability of failure of the armor unit of rubble-mound breakwaters as a function of time. The mathematical MP model could have been formulated by combining the counting process or renewal process (CP/RP) on the load occurrences with the damage process (DP) on the cumulative damage events, and applied to the armor units of rubble-mound breakwaters. Transition probabilities have been estimated by Monte-Carlo simulation (MCS) technique with the definition of damage level of armor units, and very well satisfies some conditions constrained in the probabilistic and physical views. The probabilities of failure have been also compared and investigated in process of time which have been calculated according to the variations of return period and safety factor being the important variables related to design of armor units of rubble-mound breakwater. In particular, it can be quantitatively found how the prior damage levels can effect on the sequent probabilities of failure. Finally, two types of methodology have been in this study proposed to evaluate straightforwardly the repair times which are indispensable to the maintenance of armor units of rubble-mound breakwaters and shown several simulation results including the cost analyses.

• Journal of Korea Water Resources Association
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• v.47 no.8
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• pp.693-701
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• 2014

In this study a stochastic rainfall generation model is used to analyze the structural variability of rainfall events since it has limitations in the traditional approach of measuring rainfall variability according to different durations. The NSRPM(Neyman-Scott Rectangular Pulse Model) is a stochastic rainfall generation model using a point process with 5 model parameters which is widely used in hydrologic fields. The five model parameters have physical meaning associated with rainfall events. The model parameters were estimated using hourly rainfall data from 1973 to 2011 at Seoul stations. The variability of model parameter estimates was analyzed and compared with results of traditional analysis.

• Journal of Korea Water Resources Association
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• v.35 no.5
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• pp.631-638
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• 2002

Stochastic model has been widely used for the forecasting of time series. However, this study tries to perform the precipitation forecasting by fuzzy time series model using fuzzy concept. The published fuzzy based models are used for the forecasting of time series and also we suggest that the combination of fuzzy time series models and neuro-fuzzy system can increase the forecastibility of the models. The precipitation time series in illinois, USA is analyzed for the forecasting by the known fuzzy time series models and the suggested methodology in this study. As a result, we know that the suggested methodology shows more exact results than the known models.

• Water for future
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• v.25 no.4
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• pp.109-119
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• 1992

The purpose of this study is to develop real-time streamflow forecasting models in order to manage effectively the flood warning system and water resources during the storm. The stochastic system models of the rainfall-runoff process using in this study are constituted and applied the Recursive Least Square and the Instrumental Variable-Approximate Maximum Likelihood algorithm which can estimate recursively the optimal parameters of the model. Also, in order to improve the performance of streamflow forecasting, initial values of the model parameter and covariance matrix of parameter estimate errors were evaluated by using the observed historical data of the hourly rainfall-runoff, and the accuracy and applicability of the models developed in this study were examined by the analysis of the I-step ahead streamflow forecasts.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.610-614
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• 2010

지구온난화에 따른 이상기후 현상으로 불확실성에 대한 고려가 더욱 중요해진 지금 설계빈도의 무조건적인 상향조정에 의존하기보다는 추계학적 방법을 도입한 수문량의 확충 및 매개변수의 불확실성을 고려하기 위한 연구가 활발히 진행중이다. 본 연구에서는 강우발생의 불확실성을 반영하여 제내지에서의 침수 범위를 GIS상에서 검토하기 위해 log-ratio 방법, Johnson 시스템, 직교변환을 활용한 다변량 Monte Carlo 기법으로 추계학적 시간에 따른 강우변동을 생성하였다. 생성된 강우변동 결과를 토대로 수문분석, 홍수위 분석 등을 실시하고 FLUMEN 모형을 적용하여 해당유역에 대한 홍수범람시 침수범위를 산정하였다. 본 연구결과는 실제 강우의 불확실성을 반영하고 있어 시 공간적 강우특성이 반영된 유역별 주민대피지도, 홍수위험지도 등을 제작하는데 활용될 수 있을 것으로 기대된다.

• Journal of Korea Water Resources Association
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• v.42 no.6
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• pp.433-443
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• 2009

For the better understanding of the temporal characteristics of soil water, this study is to suggest a stochastic soil water model and to apply it for impact assessment of climate change. The loss function is divided into 3 stages for more specified comprehension of the probabilistic behavior of soil water, and especially, the soil water model considering the stochastic characteristics of precipitation is developed in order to consider the variation of climatic factors. The simulation result of soil water model confirms that the proposed soil water model can re-generate the observation properly, and it also proves that the soil water behaves with consistent cycle based on the precipitation pattern. Moreover, with the simulation results with a climate change scenario, it can be predicted that the future soil water will have higher variations than present soil water.