• Water for future
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• v.19 no.2
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• pp.167-180
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• 1986

Disaggregation model has recently become a major technique in the field of synthetic generation and the model is possibly one of the most widely acepted tools in stochastic hydrology. The application of disaggregation model is evaluated with the streamflow data at the Waegwan and Hyunpung stage gaugin station on the main stem of the Nakdong River. The disaggregation process of annual streamflow data and the method of parameter estimation for the model is reviewed and the statistical analysis of the generated monthly streamflows such as a computation of moment estimation of covariance and correlogram analysis is made. The results, disaggregated monthly streamflow, obtained by Disaggregation Basic Model for single site are compared with the historical streamflow data and also with the other model, Thomas-Fiering Model. The generated monthly streamflow data by two models have been investigated and verified by comparision of mean and standard deviation between the historical and generated data.

• 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.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.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.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.719-723
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• 2004

본 연구에서는 일 최고, 최소치 유출량 계열을 확충하기 위해 ARIMA(p,d,q) 모형을 이용하였으며, 분석 자료의 경향성 유무를 파악하기 위해 Mann-Kendal 비모수적 검정을 실시하였다. 분석 결과, 최고 최소 유출량 자료 모두 경향성이 없는 것으로 분석되었다. ARIMA(p,d,q) 모형의 최적 차수를 결정하기 위해 ACF, PACF, AIC, 그리고 SBC(Schwarz Bayesian Criterion) 검사를 실시하였으며 이를 통해 최적의 ARMA 모형을 결정하였다. 일 최대치 자료의 경우 추계학적 경향 보다는 무작위적 특성을 보였으며, 일 최소치 자료계열 경우, ARMA(1,0) 모형이 최적 모형으로 선정되었다.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.5 no.2
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• pp.58-65
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• 1993

The theoretical treatment of statistical properties and distribution relevant to nonlinear random wave field of moderate bandwidth such as peak and trough of wave elevation is an overdue task hampered by the complicated form of nonlinear random waves. In this study, the extreme distribution of nonlinear random waves is derived based on the simplified version of Longuet-Higgins' wave model. It is shown that the band width of wave spectrum has a significant influence on these extreme distribution and the significant wave height is getting larger in an increasing manner as the nonlinearity is getting profound.

• Water for future
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• v.22 no.3
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• pp.331-339
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• 1989

The monthly flows with periodicity and trend were forecasted by multiplicative ARIMA model and then the applicability of the model was tested based on 23 years of the historical monthly flow data at Jindong river stage gauging station in the Nakdong River Basin. The parameter estimation was made with 21 years of data and the remaining two years of monthly data were used to compare the forecasted flows by ARIMA (2,0,0)$\times$$(0,1,1)_{12}$ with the observed. The results of forecast showed a good agreement with the observed, implying the applicability of multiplicative ARIMA model for forecasting monthly river flows at the Jindong site.

• Water for future
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• v.20 no.2
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• pp.107-116
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• 1987

The stochastic model has been developed for synthetic generation of hydrologic series that would be needed in the analysis, planning, design and operation of water resources system. In this study, after generating the yearly streamflows by multisite AR(1) model using the historical data in the Han River Basin, the monthly streamflows is generated by the disaggregation model. The model is verified of its applicability to domestic rivers, which is obtained through the statistical analysis and good ness of fit test using synthetic streamflows generated.

• 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.