• Water Engineering Research
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• v.1 no.1
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• pp.49-61
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• 2000

Magnitude-frequency relationships are used in the design of dams, highway bridges, culverts, water supply systems, and flood control structures. In this paper, possible techniques for analyzing flood frequency at a site are presented. A currently used approach to flood frequency analysis is based on the concept of parametric statistical inference. In this analysis, the assumption is make that the distribution function describing flood data in known. However, such an assumption is not always justified. Even though many people have shown that the nonparametric method provides a better fit to the data than the parometric method and gives more reliable flood estimates. the noparpmetric method implies a small probability in extrapolation beyond the highest observed data in the sample. Therefore, a remedy is presented in this paper by introducing an estimator which mixes parametric and nonparametric density estimate.

• Journal of Wetlands Research
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• v.10 no.3
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• pp.125-132
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• 2008

Generally, stationary is considered as a basic assumption in frequency analysis. However, rainfall and flood discharge are changing due to the climate change and climate variability. Therefore, there is a new opinion that changing pattern of rainfall and flood discharge must be considered in frequency analysis. This study suggests the flood frequency analysis methodology using SIR algorithm which was developed from bootstrap could be used for considering climate change. Than is, SIR algorithm is selected for resampling method considering changing pattern of flood discharge and it has been used for resampling method with likelihood function. Resampled flood discharge data considering the increase of flood discharge pattern are used for parametric flood frequency analysis and this results are compared with frequency analysis results by Bootstrap and original observations. As the results, SIR algorithm shows the greatest flood discharge than other methods in all frequencies and this may reflect the increasing pattern of flood discharge due to the climate change and climate variability.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.5
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• pp.87-92
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• 2009

It has been considered only with the concerned regional damage costs whenever the restoration and flood control measures were established in Korea. If the relationship between regional flood frequency and damages is quantitatively analyzed, more resonable and reliable countermeasure for flood protection and restoration can be proposed. Historical data ('70~'07) about flood damage in Korea were utilized and analyzed to present such relationship using the point frequency analysis. Also, the quadrant analysis was employed to divide into 4 categories: high frequency-high damage, high frequency-low damage, low frequency-high damage, and low frequency-low damage. If the results from this study were utilized well in specific cities and counties in Korea, it would be helpful to establish the countermeasures and action plans for flood protection because it was possible to compare with the relationship between flood frequency and damage of each region. And it would be the fundamental data for estimating the effect of future flood protection plan.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.1
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• pp.175-182
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• 2018

In this study, flood quantiles were estimated at ungauged watersheds by adjusting the flood quantiles from the design rainfall - runoff analysis (DRRA) method based on regional frequency analysis. Comparing the flood frequency analysis (FFA) and DRRA, it was found that the flood quantiles estimated by the DRRA method were overestimated by 52%. In addition, a practical method was suggested to make an flood index using natural flows to apply the regional frequency analysis (RFA) to ungauged watersheds. Considering the relationships among DRRA, FFA, and RFA, we derived an adjusting formula that can be applied to estimate flood quantiles at ungauged watersheds. We also employed Leave-One-Out Cross-Validation scheme and skill score to verify the method proposed in this study. As a result, the proposed model increased the accuracy by 23.2% compared to the existing DRRA method.

• Journal of Korea Water Resources Association
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• v.42 no.9
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• pp.725-736
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• 2009

A flood event can be defined by three characteristics; peak discharge, total flood volume, and flood duration, which are correlated each other. However, a conventional flood frequency analysis for the hydrological plan, design, and operation has focused on evaluating only the amount of peak discharge. The interpretation of this univariate flood frequency analysis has a limitation in describing the complex probability behavior of flood events. This study proposed a bivariate flood frequency analysis using a Gumbel mixed model for the flood evaluation. A time series of annual flood events was extracted from observations of inflow to the Soyang River Dam and the Daechung Dam, respectively. The joint probability distribution and return period were derived from the relationship between the amount of peak discharge and the total volume of flood runoff. The applicability of the Gumbel mixed model was tested by comparing the return periods acquired from the proposed bivariate analysis and the conventional univariate analysis.

• Journal of Korea Water Resources Association
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• v.49 no.7
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• pp.599-606
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• 2016

The objective of this study is to estimate the unregulated flood frequency from Chungju dam to Yangpyung gauging station for the region affected by dams based on the peak discharges simulated by storage function routing model. From the flood frequency analyses, the quantiles for the unregulated flood frequency at 6 sites have similar pattern to each other, and their averaged quantile almost matched to the result from the regional flood frequency analysis. The quantile and annual mean discharge for the unregulated flood frequency for the downstream of Chungju dam show the similar behaviour to those for the upstream area. While the quantile and the annual mean discharge for the regulated flood frequency are significantly different from those for the unregulated flood frequency. In particular, the qunatile shows severe difference as the return period increases, and the annual mean discharge has a tendency to approach to the natural flood as the distance from dam increases.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1361-1375
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• 2013

The design flow considering nonstationarity is estimated to determine the design flood related to hydraulic structure quantitatively based on the design process for stream restoration in the Mokgamcheon watershed proposed by Lee et al. (2011). The purpose of this research is to suggest new ways that the design flood was calculated considering nonstationarity at the Mokgamcheon watershed. Storm-unit hydrograph method to calculate design flood and direct frequency analysis were applied and nonstationarity was considered for the frequency analysis through extRemes toolkit developed at NCAR (National Center for Atmospheric Research). Although the method of direct flood frequency analysis due to dealing with flowrates directly has a more reliable than strom-unit hydrograph method, as a result, the method of direct flood frequency analysis underestimated the design flood than strom-unit hydrograph method due to the characteristics of the flow data. Therefore, the flood of storm-unit hydrograph method (100 years frequency) was determined as the design flood in the Mokgamcheon watershed.

• Water Engineering Research
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• v.1 no.1
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• pp.11-23
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• 2000

Regional flood frequency analysis has been developed by employing the nearby site's information to improve a precision in estimating flood quantiles at the site of interest. In this paper, single site and regional flood frequency analyses were compared based of the 2-parameter Weibull model. For regional analysis, two approaches were employed. The First one is to use the asymptotic variances of the quantile estimators derived based of the assumption that all sites including the site of interest are independent each other. This approach may give the maximum regional gain due to the spatial independence assumption among sites. The second one in Hosking's regional L-moment algorithm. These methods were applied to annual flood data. As the results, both methods generally showed the regional gain at the site of interest depending on grouping the sites as homogeneous. And asymptotic formula generally shows smaller variance than those from Hosking's algorithm. If the shape parameter of the site of interest from single site analysis is quite different from that from regional analysis then Hosking's results might be better than the asymptotic ones because the formula was derived based on the assumption that all sites have the same regional shape parameter. Furthermore, in such a case, regional analysis might be worse than single site analysis in the sense of precision of flood quantile estimation. Even though the selected sites may satisfy Hosking's criteria, regional analysis may not give a regional gain for specific and nonexceedance probabilities.

• Journal of Korea Water Resources Association
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• v.55 no.5
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• pp.333-343
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• 2022

For water resource management, the design flood is calculated using the flood frequency analysis technique and the rainfall runoff model. The method by design flood frequency analysis calculates the stochastic design flood by directly analyzing the actual discharge data and is theoretically evaluated as the most accurate method. Actual discharge data frequency analysis of the measured flow was limited due to data limitations in the existing flood flow analysis. In this study, design flood frequency analysis was performed using the measured flow data stably secured through the water level-discharge relationship curve formula. For the frequency analysis of design flood, the parameters were calculated by applying the bayesian inference, and the uncertainty of flood volume by frequency was quantified. It was confirmed that the result of calculating the design flood was close to that calculated by the rainfall-runoff model by applying long-term rainfall data. It is judged that hydrological analysis can be done from various perspectives by using long-term actual flow data through hydrological survey.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1441-1444
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• 2007

It is now widely acknowledged that climate variability modifies the frequency spectrum of hydrological extreme events. Traditional hydrological frequency analysis methodologies are not devised to account for nonstationarity that arises due to variation in exogenous factors of the causal structure. We use Hierarchical Bayesian Analysis to consider the exogenous factors that can influence on the frequency of extreme floods. The sea surface temperatures, predicted GCM precipitation, climate indices and snow pack are considered as potential predictors of flood risk. The parameters of the model are estimated using a Markov Chain Monte Carlo (MCMC) algorithm. The predictors are compared in terms of the resulting posterior distributions of the parameters associated with estimated flood frequency distributions.