• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.733-745
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• 2010

Seasonality of hydrologic extreme variable is a significant element from a water resources managemental point of view. It is closely related with various fields such as dam operation, flood control, irrigation water management, and so on. Hydrological frequency analysis conjunction with partial duration series rather than block maxima, offers benefits that include data expansion, analysis of seasonality and occurrence. In this study, nonstationary frequency analysis based on the Bayesian model has been suggested which effectively linked with advantage of POT (peaks over threshold) analysis that contains seasonality information. A selected threshold that the value of upper 98% among the 24 hours duration rainfall was applied to extract POT series at Seoul station, and goodness-fit-test of selected GEV distribution has been examined through graphical representation. Seasonal variation of location and scale parameter ($\mu$ and $\sigma$) of GEV distribution were represented by Fourier series, and the posterior distributions were estimated by Bayesian Markov Chain Monte Carlo simulation. The design rainfall estimated by GEV quantile function and derived posterior distribution for the Fourier coefficients, were illustrated with a wide range of return periods. The nonstationary frequency analysis considering seasonality can reasonably reproduce underlying extreme distribution and simultaneously provide a full annual cycle of the design rainfall as well.

• Journal of the Korean Society of Hazard Mitigation
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• v.3 no.3 s.10
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• pp.125-132
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• 2003

In this study, safety analysis of river in flash flood due to local extraordinary rainfall was conducted for the Hong-Je river, which was selected as a representative sample basin because it is one of the most urbanized rivers in Seoul. The rainfall data of precipitation 310.1 mm and probable maximum precipitation (PMP) 740.0 mm in July $14{\sim}15$, 2001 was used to perform safety analysis. Resulting of safety analysis of the flood control in Hong-Je river, case of the 50 year of design frequency, safety section, management section, and danger section were represented to be 85%, 15%, and 0% respectively. For the 200 year of design frequency, safety section decreased by 6% and management section and danger section increment by 4% and 2%, respectively, The variation of management section was not observed with respect to 200 year of frequency. Little variation of safety value for management section for 300 and 500 of frequency increased by 8% and 12% relative to 50 year of frequency, respectively. management section and danger section for 1000 year of frequency increased by 19% and 13% relative to 50 year of frequency.

• Journal of Korea Water Resources Association
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• v.51 no.9
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• pp.747-759
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• 2018

Multivariate regional frequency analysis has advantages of regional and multivariate framework as adopting a large number of regional dataset and modeling phenomena that cannot be considered in the univariate frequency analysis. To the best of our knowledge, the multivariate regional frequency analysis has not been employed for hydrological variables in South Korea. Applicability of the multivariate regional frequency analysis should be investigated for the hydrological variable in South Korea in order to improve our capacity to model the hydrological variables. The current study focused on estimating parameters of regional copula and regional marginal models, selecting the most appropriate distribution models, and estimating regional multivariate growth curve in the multivariate regional frequency analysis. Annual maximum rainfall and duration data observed at 71 stations were used for the analysis. The results of the current study indicate that Frank and Gumbel copula models were selected as the most appropriate regional copula models for the employed regions. Several distributions, e.g. Gumbel and log-normal, were the representative regional marginal models. Based on relative root mean square error of the quantile growth curves, the multivariate regional frequency analysis provided more stable and accurate quantiles than the multivariate at-site frequency analysis, especially for long return periods. Application of regional frequency analysis in bivariate rainfall-duration analysis can provide more stable quantile estimation for hydraulic infrastructure design criteria and accurate modelling of rainfall-duration relationship.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.257-266
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• 2022

Inundation damage is increasing every year due to localized heavy rain and an increase of rainfall exceeding the design frequency. Accordingly, the importance of hydraulic structures for flood control and defense is also increasing. The hydraulic structures are designed according to its purpose and performance, and the amount of flood is an important calculation factor. However, in Korea, design rainfall is used as input data for hydrological analysis for the design of hydraulic structures due to the lack of sufficient data and the lack of reliability of observation data. Accurate probability rainfall and its temporal distribution are important factors to estimate the design rainfall. In practice, the regression equation of temporal distribution for the design rainfall is calculated using the cumulative rainfall percentage of Huff's quartile method. In addition, the 6^th order polynomial regression equation which shows high overall accuracy, is uniformly used. In this study, the optimized regression equation of temporal distribution is derived using the variable selection method according to the principle of parsimony in statistical modeling. The derived regression equation of temporal distribution is verified through the significance test. As a result of this study, it is most appropriate to derive the regression equation of temporal distribution using the stepwise selection method, which has the advantages of both forward selection and backward elimination.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.581-585
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• 2010

This study introduced a Bayesian based frequency analysis in which the statistical trend seasonal analysis for hydrologic extreme series is incorporated. The proposed model employed Gumbel and GEV extreme distribution to characterize extreme events and a fully coupled bayesian frequency model was finally utilized to estimate design rainfalls in Seoul. Posterior distributions of the model parameters in both trend and seasonal analysis were updated through Markov Chain Monte Carlo Simulation mainly utilizing Gibbs sampler. This study proposed a way to make use of nonstationary frequency model for dynamic risk analysis, and showed an increase of hydrologic risk with time varying probability density functions. In addition, full annual cycle of the design rainfall through seasonal model could be applied to annual control such as dam operation, flood control, irrigation water management, and so on. The proposed study showed advantage in assessing statistical significance of parameters associated with trend analysis through statistical inference utilizing derived posterior distributions.

• Journal of Wetlands Research
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• v.15 no.1
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• pp.125-137
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• 2013

Global warming and climate change have influence on abnormal weather pattern and the rainstorm has a localized and intensive tendency in Korea. IPCC(2007) also reported the rainstorm and typhoon will be more and more stronger due to temperature increase during the 21st century. Flood Estimation Handbook(Institute of Hydrology, 1999) published in United Kingdom, in the case that the data period is shorter than return period, recommends the regional frequency analysis rather than point frequency analysis. This study uses Regional Climate Model(RCM) of Korea Meteorological Administration(KMA) for obtaining the rainfall and for performing the regional frequency analysis. We used the rainfall data from 58 stations managed by KMA and used L-moment algorithm suggested by Hosking and wallis(1993) for the regional frequency analysis considering the climate change. As the results, in most stations, the rainfall amounts in frequencies have an increasing tendency except for some stations. According to the A1B scenario, design rainfall is increased by 7~10% compared with the reference period(1970-2010).

• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.37-53
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• 2024

In this study, flood records from 79 sites across Thailand were analyzed to estimate flood indices using the regional frequency analysis based on the L-moments method. Observation sites were grouped into homogeneous regions using k-means and Ward's clustering techniques. Among various distributions evaluated, the generalized extreme value distribution emerged as the most appropriate for certain regions. Regional growth curves were subsequently established for each delineated region. Furthermore, 20- and 100-year return values were derived to illustrate the recurrence intervals of maximum rainfall across Thailand. The predicted return values tend to increase at each site, which is associated with growth curves that could describe an increasing long-term predictive pattern. The findings of this study hold significant implications for water management strategies and the design of flood mitigation structures in the country.

• Journal of Korea Multimedia Society
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• v.17 no.4
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• pp.478-489
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• 2014

Recently, flood damage by frequent localized downpours in cities are on the increase on account of abnormal climate phenomena and growth of impermeable area by urbanization. In this study, we are focused on flooding on roads which is the basis of all means of transportation. To calculate real-time accumulated rainfall on a road link, we use the Coefficient of Correlation Weighting method (CCW) which is one of the revised methods of missing rainfall as we consider a road link as a unobserved rainfall site. CCW and real-time accumulated rainfall entered through the Internet are used to estimate the real-time rainfall on a road link. Together with the real-time accumulated rainfall, flooding history, rainfall range causing flooding of a road link and frequency probability precipitation for road design are used as factors to determine the Flood Risk Index on roads. We simulated two cases in the past, July, 7th, 2009 and July, 15th, 2012 in Busan. As a result, all of road links included in the actual flooded roads at that time got the high level of flood risk index.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.5
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• pp.617-626
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• 2022

In Korea, annual precipitation and its variability have gradually increased since modern meteorological observations began, and the risk of disasters has also been increasing due to significant regional variations and recent abnormal climate conditions. Given that damage from storms and floods mainly occurs around rivers, it is crucial to determine the appropriate design frequency for river-related projects. This study examined existing design practices used to determine hydrological design frequencies and suggested a new method to determine appropriate design frequencies. The study collected available data pertaining to seven evaluation factors, specifically the basin areas, shape parameters, channel slopes, stream orders, backwater effect reaches, extreme rainfall frequencies, and urbanized flood inundation areasfor 413 local rivers in Chungcheongnam-do in Korea. The estimated weights for areas of extreme rainfall frequencies and urbanized flood inundation were found to be 18, having a great effect on determining the design frequency. Compared with the established design frequency in previous government reports, the estimated design frequency increased for 255 rivers and decreased for 158 rivers.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.121-121
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• 2020

Varying dominant processes, including Tropical Cyclone (TC) and non-TC rainfall events, have been known to drive the occurrence of precipitation in South Korea. With the changes in the pattern of the Earth's climate due to anthropogenic activities, nonstationarity or changes in the magnitude and frequency of these dominant processes have been separately observed for the past decades and are expected to continue in the coming years. These changes often cause unprecedented hydrologic events such as extreme flooding which pose a greater risk to the society. This study aims to take into account a more reliable future climate condition with two dominant processes. Diverse statistical models including the hidden markov chain, K-nearest neighbor algorithm, and quantile mappings are utilized to mimic future rainfall events based on the recorded historical data with the consideration of the varying effects of TC and non-TC events. The data generated is then utilized to the hydrologic model to conduct a flood frequency analysis. Results in this study emphasize the need to consider the nonstationarity of design rainfalls to fully grasp the degree of future flooding events when designing urban water infrastructures.