• Journal of Korea Water Resources Association
• /
• v.40 no.9
• /
• pp.709-722
• /
• 2007

The floods of Korea happens periodically during summer. The cause of heavy rain that provokes floods can be classified into typhoon and localized downpour. The typhoon happens in the tropical region. It causes one of the worst damage to Korea by extreme rainfall and strong wind. Usually, it is known that the flood damage by the typhoon is larger than that by the localized downpour. Therefore, this study classified rainfall events into typhoon events and localized downpour events based on the cause. Through statistical analyses of the rainfall data, this study investigated special quality of the rainfall during the time of typhoon. In analysis results, probability Precipitation calculated by the typhoon events were exposed bigger than that calculated by all rainfall events.

• Journal of Korea Water Resources Association
• /
• v.56 no.12
• /
• pp.955-967
• /
• 2023

Climate change is expected to amplify the future flooding risks in rural areas which could have devastating implications for the sustainability of the agricultural sector and food security in South Korea. In this study, spatially disaggregated and statistically bias-corrected outputs from three global circulation models (GCMs) archived in the Coupled Model Intercomparison Project Phases 5 and 6 (CMIP5 and 6) were used to project the future climate by 2100 under medium and extreme scenarios. A hydrological model was developed to simulate the flood phenomena at the Shindae experimental site located in the Chungcheongbuk Province, South Korea. Hourly rainfall, inundation depth, and discharge data collected during the two extreme events that occurred in 2021 and 2022 were used to calibrate and validate the hydrological model. Probability analysis of extreme rainfall data suggested a higher likelihood of intense and unprecedented extreme rainfall events, which would be particularly notable during 2051-2100. Consequently, the flooded area under an inundation depth of >700 mm increased by 13-36%, 54-74%, and 71-90% during 2015-2030, 2031-2050, and 2051-2100, respectively. Severe flooding probability was notably higher under extreme CMIP6 scenarios than under their CMIP5 counterparts.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.38 no.5
• /
• pp.655-669
• /
• 2018

In this study, we developed a hybrid forecasting model based on a four-parameter distribution which allows a simultaneous season-ahead forecasting for both seasonal rainfall and sub-daily rainfall in Han-River and Geum-River basins. The proposed model is mainly utilized a set of time-varying predictors and the associated model parameters were estimated within a Bayesian nonstationary rainfall frequency framework. The hybrid forecasting model was validated through an cross-validatory experiment using the recent rainfall events during 2014~2017 in both basins. The seasonal precipitation results showed a good agreement with the observations, which is about 86.3% and 98.9% in Han-River basin and Geum-River basin, respectively. Similarly, for the extreme rainfalls at sub-daily scale, the results showed a good correspondence between the observed and simulated rainfalls with a range of 65.9~99.7%. Therefore, it can be concluded that the proposed model could be used to better consider climate variability at multiple time scales.

• 한국방재학회:학술대회논문집
• /
• 2008.02a
• /
• pp.497-500
• /
• 2008

The typhoon is provoking huge damage attacking in Korea periodically every year. Therefore, in this study, the analysis of 24 hourly maximum precipitation change related to typhoon events achieved based on Mann-Whitney U test, T test, Modified T test, Sign test, F test, and Modified F test. At the results, the 24 hourly maximum precipitation was expose that average and standard deviation are increasing recently. Therefore, hydorlogical structures have to be prepared of extreme rainfall events by typhoons.

• Journal of Korea Water Resources Association
• /
• v.52 no.11
• /
• pp.895-904
• /
• 2019

It has been well recognized that extreme rainfall process often features a nonstationary behavior, which may not be effectively modeled within a stationary frequency modeling framework. Moreover, extreme rainfall events are often described by a two (or more)-component mixture distribution which can be attributed to the distinct rainfall patterns associated with summer monsoons and tropical cyclones. In this perspective, this study explores a Mixture Distribution based Nonstationary Frequency (MDNF) model in a changing rainfall patterns within a Bayesian framework. Subsequently, the MDNF model can effectively account for the time-varying moments (e.g. location parameter) of the Gumbel distribution in a two (or more)-component mixture distribution. The performance of the MDNF model was evaluated by various statistical measures, compared with frequency model based on both stationary and nonstationary mixture distributions. A comparison of the results highlighted that the MDNF model substantially improved the overall performance, confirming the assumption that the extreme rainfall patterns might have a distinct nonstationarity.

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

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

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.42 no.3
• /
• pp.76-88
• /
• 2000

AGNPS model is applied in this study to analyze the changes of non-point source pollutant according to AMC condition using probable rainfall. Probable rainfall of H-dam area by Gumber's extreme value distribution is computed through frequency analysis for each return period. 35 coarse grids are subdivided into 134 find grids of finite differential network to analyze peak flow soil loss quantity and nutrients of study area and the modified CN estimation equation shows good result about rainfall events-peak flow relationship. And as the consequence of estimation of soil loss quantity for each rainfall event soil loss quantity shows 120%-170% of actual soil loss quantity Regression analysis for the observed and calculated values of flow T-P AMC has an important effect on nutrients concentration of outflow and it if found that the excessive fertilization under AMC III condition may cause eutrophication by nutrients because the range of increase of outflow concentration appears relatively high.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.58 no.1
• /
• pp.39-51
• /
• 2016

Extreme floods occur more often recently as the frequency of extreme storm events increase due to the climate change. Because the extreme flood exceeding the design flood can cause large-scale disasters, it is important to predict and prepare for the future extreme flood. Flood flow is affected by two main factors; rainfall and land use. To predict the future extreme flood, both changes in rainfall due to the climate change and land use should be considered. The objective of this study was to simulate the future design flood in the Hwangguji river watershed, South Korea. The climate and land use change scenarios were derived from the representative concentration pathways (RCP) 4.5 and 8.5 scenarios. Conversion of land use and its effects (CLUE) and hydrologic modelling system (HEC-HMS) models were used to simulate the land use change and design flood, respectively. Design floods of 100-year and 200-year for 2040, 2070, and 2100 under the RCP4.5 and 8.5 scenarios were calculated and analyzed. The land use change simulation described that the urban area would increase, while forest would decrease from 2010 to 2100 for both the RCP4.5 and 8.5 scenarios. The overall changes in design floods from 2010 to 2100 were similar to those of probable rainfalls. However, the impact of land use change on design flood was negligible because the increase rate of probable rainfall was much larger than that of curve number (CN) and impervious area.

• Journal of the Korean Geographical Society
• /
• v.39 no.5 s.104
• /
• pp.711-721
• /
• 2004

The aim of this study is to clarify whether frequency and/or severity of extreme climate events have changed significantly in Korea during recent years. Using the best available daily data, spatial and temporal aspects of ten climate change indicators are investigated on an annual and seasonal basis for the periods of 1954-1999. A systematic increase in the $90^{th}$ percentile of daily minimum temperatures at most of the analyzed areas has been observed. This increase is accompanied by a similar reduction in the number of frost days and a significant lengthening of the thermal growing season. Although the intra-annual extreme temperature range is based on only two observations, it provides a very robust and significant measure of declining extreme temperature variability. The five precipitation-related indicators show no distinct changing patterns for spatial and temporal distribution except for the regional series of maximum consecutive dry days. Interestingly, the regional series of consecutive dry days have increased significantly while the daily rainfall intensity index and the fraction of annual total precipitation due to events exceeding the $95^{th}$ percentile for 1901-1990 normals have insignificantly increased.