• Journal of Korea Water Resources Association
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• v.36 no.3 s.134
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• pp.345-363
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• 2003

From the General Circulation Models(GCMs), it is known that the increases of concentrations of greenhouse gases will have significant implications for climate change in global and regional scales. The GCM has an uncertainty in analyzing the meteorologic processes at individual sites and so the 'downscaling' techniques are used to bridge the spatial and temporal resolution gaps between what, at present, climate modellers can provide and what impact assessors require. This paper describes a method for assessing local climate change impacts using a robust statistical downscaling technique. The method facilitates the rapid development of multiple, low-cost, single-site scenarios of daily surface weather variables under current and future regional climate forcing. The construction of climate change scenarios based on spatial regression(transfer function) downscaling and on the use of a local stochastic weather generator is described. Regression downscaling translates the GCM grid-box predictions with coarse resolution of climate change to site-specific values and the values were then used to perturb the parameters of the stochastic weather generator in order to simulate site-specific daily weather values. In this study, the global climate change scenarios are constructed using the YONU GCM control run and transient experiments.

• Journal of Korea Water Resources Association
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• v.36 no.3 s.134
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• pp.399-411
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• 2003

An approach determining a confidence interval of Nash's observed mean instantaneous unit hydrograph is developed. In the approach, both two parameters are treated as correlated gaussian random variables based on the theory of Box-Cox transformation and the regional similarity relation, so that linear statistical parameter estimation is possible. A parametric bootstrap method is adopted to give the confidence interval of the mean observed hydrograph. The proposed methodology is also applicable to estimate the parameters of Nash's model for un-gauged basins. An application to a watershed has shown that the proposed approach is adequate to assess the uncertainty of the Nash's hydrograph and to evaluate parameters for un-gauged basins.

• 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.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2B
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• pp.163-171
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• 2009

Classical linear models have been generally used to analyze and forecast hydrologic time series. However, there is growing evidence of nonlinear structure in natural phenomena and hydrologic time series associated with their patterns and fluctuations. Therefore, the classical linear techniques for time series analysis and forecasting may not be appropriate for nonlinear processes. In recent, the BDS (Brock-Dechert-Scheinkman) statistic instead of conventional techniques has been used for detecting nonlinearity of time series. The BDS statistic was derived from the statistical properties of the correlation integral which is used to analyze chaotic system and has been effectively used for distinguishing nonlinear structure in dynamic system from random structures. DVS (Deterministic Versus Stochastic) algorithm has been used for detecting chaos and stochastic systems and for forecasting of chaotic system. This study showed the DVS algorithm can be also used for detecting nonlinearity of the time series. In this study, the stochastic and hydrologic time series are analyzed to detect their nonlinearity. The linear and nonlinear stochastic time series generated from ARMA and TAR (Threshold Auto Regressive) models, a daily streamflow at St. Johns river near Cocoa, Florida, USA and Great Salt Lake Volume (GSL) data, Utah, USA are analyzed, daily inflow series of Soyang dam and the results are compared. The results showed the BDS statistic is a powerful tool for distinguishing between linearity and nonlinearity of the time series and DVS plot can be also effectively used for distinguishing the nonlinearity of the time series.

• 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.28 no.4
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• pp.191-201
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• 2016

A stochastic process has been used to develop a condition-based model for preventive maintenance of armor units of rubble-mound breakwaters that can make a decision the optimal interval at which some repair actions should be performed under the perfect maintenance. The proposed cost model in this paper based on renewal reward process can take account of the interest rate, also consider the unplanned maintenance cost which has been treated like a constant in the previous studies to be a time-dependent random variable. A function for the unplanned maintenance cost has been mathematically proposed so that the cumulative damage, serviceability limit and importance of structure can be taken into account, by which a age-based maintenance can be extended to a condition-based maintenance straightforwardly. The coefficients involved in the function can also be properly estimated using a method expressed in this paper. Two stochastic processes, Wiener process and gamma process have been applied to armor stones of rubble-mound breakwaters. By evaluating the expected total cost rate as a function of time for various serviceability limits, interest rates and importances of structure, the optimal period of preventive maintenance can easily determined through the minimization of the expected total cost rate. For a fixed serviceability limit, it shows that the optimal period has been delayed while the interest rate increases, so that the expected total cost rate has become lower. In addition, the gamma process tends to estimate the optimal period more conservatively than the Wiener process. Finally, it is found that the more crucial the level of importance of structure becomes, the more often preventive maintenances should be carried out.

• Proceedings of the Korea Water Resources Association Conference
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• 1986.07a
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• pp.23-33
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• 1986

일강우를 여러가지 성분들이 포함된 백색잡음으로 가정하면, 이로부터 기저유출 성분을 분리하기 위하여 선형론이 적용될 수 있다. 선형론에는 단위충격응답이 요구 되어지므로, 본 연구에서는 이를 추계학적 자기회귀모형에 의하여 추정한다. 자기회귀계수는 기지의 기저유출성분과 이에 해당되는 강우의 지하침투량으로부터 모멘트법에 의하여 결정한다. 기지의 기저유출성분은 주 지하수감수곡선에 의하여 추정되어지며, 지하침투량은 $\Phi$-지수 개념하에 전 강우기간에 걸쳐 일정 침투율의 방법으로부터 구한다. 본 연구방법을 금강유역내 용담집수면적(937$\textrm{km}^2$)에 적용한 결과 상당히 미끈한 수문곡선을 얻을 수 있었으며, 각 호우-유출 사상별 회귀계수의 차수는 공히 2차로 나타났다.

• Journal of the Korea institute for structural maintenance and inspection
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• v.8 no.4
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• pp.185-193
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• 2004

Reasonable prediction of bridge deterioration is the most important factor in the determination of repair time or optimized maintenance policy for bridges. To accomplish these purposes, the proposed method is composed of quantitative condition assessment, Markov chains and Bayesian estimates. Example predictions of concrete slab bridges in Korea were illustrated with higher reasonability than those of existing methods such as expert opinion and visual inspection only.

• Journal of Korea Water Resources Association
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• v.31 no.5
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• pp.553-564
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• 1998

For the proper design and management of underground storage cavern, groundwater flow around cavern should be analyzed. Since this flow is influenced by spatial nonuniformity of hudraulic conductivity, the two-dimensional finite element flow model incorporating stochastic concepts was developed to analyze influences due to this nonuniformity. Monte Carlo technique was applied to obtain an approximate solution for two-dimensional, steady flow in a stochastically defined nonuniform medisu. For this purpose, the values of hydraulic conductivity were generated for each element with known mean and standard deviations. The uncertainty in model prediction depends on both the nonuniformity in hydraulic conductivity and the natures of the flow system such as water curtain and boundary condition. Therefore the uncertainties in predicted hydraulic head and gradient are the greatest where the mean hydraulic gradients are relatively large and far from the boundaries. Especially, we relate these uncertainties with well known gas tightness condition.