• 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.

• Journal of the Earthquake Engineering Society of Korea
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• v.7 no.6
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• pp.59-70
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• 2003

We estimated the spectrum decay parameter $\chi$ and the stress parameter ($\Delta$$\sigma$) in southeastern Korea. Especially, we propose a procedure to compute site-independent $\chi$$_{q}$ and dependent $\chi$$_{s}$ values, separately, This procedure is to use the coda normalization method for the computation of site independent Q or corresponding $\chi$$_{q}$ value as the first step followed by the next step, the computation of $\chi$$_{s}$ values for each site using the given $\chi$$_{q}$ value evaluated at the first step, For the estimation of stress parameter, we used seismic data monitored from three earthquakes occurred near Gyeongju in 1999 with the method of Jo and Baag, In addition, we simulated strong ground motion using the $\chi$ value and the stress parameter, In this case, we calculated the $\chi$ value with conventional method. The $\chi$ value of 0.016+0.000157R and the stress parameter of 92-bar was applied to the stochastic simulation, At last, we derived seismic attenuation equation using results of the stochastic prediction, and compared these results with some others reported previously.ported previously.

• 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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• 2017.05a
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• pp.403-403
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• 2017

기후변화에 따라 도시의 홍수유출이 어떻게 변화할 것인가를 살펴보는 것은 안전한 도시를 설계하는데 매우 중요하다. 이에 본 연구에서는 기후변화 시나리오에 따른 도시홍수유출의 변화를 살펴보고자 하였다. 하지만 기후변화 시나리오 자료는 물리적인 계산량의 한계로 인해 월이나 일 단위의 결과를 갖고 있어 도시홍수유출의 모의에 직접 적용하기 곤란하다. 이를 위해 시단위까지 자료의 상세화가 필요한데 본 연구에서는 기존에 개발된 "K번째 최근접 표본 재추출 방법에 의한 일 강우량의 추계학적 분해" 방법을 기상청의 RCP 기후변화 시나리오에 적용하였다. 이와 같이 추계학적인 방법을 이용해 강우를 시간단위로 분해하면 일단위 강우량은 보존되면서 다양한 시단위의 강우 시나리오를 얻을 수 있으므로 기후변화 시나리오 자료를 시단위로 상세화 하는 동시에 동일한 일단위 강우량을 갖는 많은 시단위 자료를 생성해 낼 수 있다. 본 연구에서는 이러한 방법을 통해 확장된 기후변화 시나리오 자료를 이용해 호우사상을 추출하고 SWMM을 이용하여 도시 홍수유출을 모의함으로써 많은 가상의 홍수유출 자료를 확보할 수 있으며, 이를 통계적으로 분석하여 각 기후변화 시나리오에 따른 도시홍수유출의 변화를 살펴보았다.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.9-9
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• 2018

추계학적 강우생성모형 중 포아송 클러스터(Poisson Cluster) 모형은 단일지점에 대하여 시간강우량의 관측연한 문제점을 해결하기 위한 강우모형으로 강우 단계별 계층적 구조를 이해하는데 유용한 모형이다. 특히 강우 특성을 계절, 지역 등과 같이 비교하는 기준에 따라 5~6개의 비교적 적은 매개변수들로 모의 강우시계열을 생성할 수 있다는 점에서 장기간 강우분석에 필요한 관측연한 문제를 보완할 수 있다. 그러나 매개변수 최적해가 수렴되지 않는 사례가 많고, 매개변수들이 강우의 물리적 특성을 반영하는 것에 비해 내포된 불확실성에 관한 연구는 미흡하다. 본 연구에서는 포아송 클러스터 강우생성모형 중 Neyman-Scott Rectangular Pulse(NSRP) 모형을 Bayesian 모형과 연계한 Bayesian NSRP 모형을 개발하여 매개변수간 물리적 상관성을 고려한 최적화 기법을 개발하였다. Bayesian 모형은 물리적 범위가 다른 매개변수간의 결합확률분포를 산정하여 사후분포(posterior)를 추정하므로 매개변수 최적화와 불확실성 정량화 문제를 동시에 해결할 수 있다. 최종적으로 Bayesian NSRP 모형에 기후변화 시나리오의 통계적 특성을 고려한 시간단위 강우시계열 생성 모의 기법의 활용 가능성을 평가하고자 한다.

• Journal of Korea Water Resources Association
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• v.42 no.10
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• pp.809-824
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• 2009

Hydrological system forecasting, which is the short term runoff historical data during the limited period in dam site, is a conditional precedent of hydrological persistence by stochastic analysis. We have forecasted the monthly hydrological system from Andong dam basin data that is the rainfall, evaporation, and runoff, using the seasonal ARIMA (autoregressive integrated moving average) model. Also we have conducted long term runoff simulations through the forecasted results of TANK model and ARIMA+TANK model. The results of analysis have been concurred to the observation data, and it has been considered for application to possibility on the stochastic model for dam inflow forecasting. Thus, the method presented in this study suggests a help to water resource mid- and long-term strategy establishment to application for runoff simulations through the forecasting variables of hydrological time series on the relatively short holding runoff data in an object basins.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.11 no.4
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• pp.113-119
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• 1991

In the present study, a methodology has been established for water budget analysis of a river basin for which monthyl rainfall and evaporation data are the only available hydrologic data. The monthly rainfall data were first converted into monthyl runoff data by an empirical formula from which long-term runoff data were generated by a stochastic generation mothod. Thomas-Fiering model. Based on the generated long-term data low flow frequency analysis was made for each of the oberved and generated data set, the low flow series of each data set being taken as the water supply for budget analysis. The water demands for various water utilization were projected according to the standard method and the net water consumption computed there of. With the runoff series of the driest year of each generated data set as an input water budget computation was made through the composite reservoirs comprised of small reserviors existing in the basin by deficit-supply method. The water deficit computed through the reservior operation study showed that the deficit radically increases as the return period of low flow becomes large. This indicates that the long-term runoff data generated by stochastic model are a necessity for a reliable water shortage forecasting to cope with the long-term water resourse planning of a river basin. F.E.M. program (ADINA) is also presented herein.

• Journal of Korea Water Resources Association
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• v.42 no.7
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• pp.547-558
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• 2009

General reliability assessment of levees embankment is performed with safety factors for rainfall characteristics and hydrologic and hydraulic parameters, based on the results of deterministic analysis. The safety factors are widely employed in the field of engineering handling model parameters and the diversity of material properties, but cannot explain every natural phenomenon. Uncertainty of flood analysis and related parameters by introducing stochastic method rather than deterministic scheme will be required to deal with extreme weather and unprecedented flood due to recent climate change. As a consequence, stochastic-method-based measures considering parameter uncertainty and related factors are being established. In this study, a variety of dimensionless cumulative rainfall curve for typhoon and monsoon season of July to September with generation method of stochastic temporal variation is generated by introducing Monte Carlo method and applied to the risk assessment of levee embankment using reliability index. The result of this study reflecting temporal and regional characteristics of a rainfall can be used for the establishment of flood defence measures, hydraulic structure design and analysis on a watershed.