• Journal of Environmental Science International
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• v.23 no.10
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• pp.1673-1691
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• 2014

Although most natural disaster related studies conducted in Korea recently have been related to typhoons or severe rainstorms, the occurrence frequency of disasters due to windstorms or rainstorms is also high. To reduce the strong wind damage caused by strong windstorms due to climate change, basic studies of strong winds are necessary. Therefore, in this study, the types and representative cases of windstorms that were observed to have been higher than 14 m/s, which is the criterion for strong-wind warnings from the Korea Meteorological Administration, were selected from among those windstorm cases that occurred on the Korean Peninsula for 10 years to conduct a statistical analysis of them and determine their synoptic meteorological characteristics. The cases of windstorms occurring on the Korean Peninsula were divided into six weather patterns according to the locations of the anticyclones/cyclones. Among these types, the SH type, which occurs when Siberian Highs expand into the Korean Peninsula, showed the highest occurrence frequency, accounting for at least the majority of the entire occurrence frequency of windstorms together with that of the EC type, which occurs when cyclones develop on the East Sea, and there was no clear yearly trend of the occurrence frequencies of windstorms. The monthly occurrence frequencies of windstorms were formed mainly by typhoons in the summer and the Siberian Highs in the winter, and the months with the highest windstorm occurrence frequencies were December and January, in which mainly the SH and EC type windstorms occurred. March showed the next highest occurrence frequency with10 times, and SH windstorms occurred the most frequently in March, followed by the CC, SC, and EC types of windstorms, in order of precedence. Therefore, attention to these types of windstorms is required. Countermeasures against storm and flood damage in Korea targeting the summer should be re-reviewed together with pre-disaster prevention plans, because cases of storm and flood damage due to windstorms occur more frequently than those due to typhoons, and they occur throughout the year.

• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.617-625
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• 1999

Global warming has begun since the industrial revolution and it is getting worse recently. Even though the increase of greenhouse gases such as $CO_2$ is thought to be the main cause for global warming, its impact on global climate has not been revealed clearly in rather quantitative manners. However, researches using General Circulation Models(GCMs) has shown the accumulation of greenhouse gases increases the global mean temperature, which in turn impacts on the global water circulation pattern. This changes in global water circulation pattern result in abnormal and more frequent meteorological events such as severe floods and droughts, generally more severe than the normal ones, which are now common around the world and is referred as a indirect proof of global warming. Korean peninsula also cannot be an exception and have had several extremes recently. The main objective of this research is to analyze the impact of global warming on the change of flood and drought frequency. Based on the assumption that now is a point in a continuously changing climate due to global warming, we analyzed the observed daily rainfall data to find out how the increase of annual rainfall amount affects the distribution of daily rainfall. Obviously, the more the annual rainfall depth, the more frequency of much daily rainfall, and vice versa. However, the analysis of the 17 points data of Keum river basin in Korea shows that especially the number of days of under 10mm or over 50mm daily rainfall depth is highly correlated with the amount of annual rainfall depth, not the number of dry days with their correlation coefficients quite high around 0.8 to 0.9.

• Journal of Korea Water Resources Association
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• v.50 no.10
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• pp.661-671
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• 2017

The objective of this study was to analyze the flood stage considering the uncertainty caused by the river roughness coefficients and discharge. The methodology of this study involved the GLUE (Generalized Likelihood Uncertainty Estimation) to quantify the uncertainty bounds applying three different storm events. The uncertainty range of the roughness was 0.025~0.040. In case of discharge, the uncertainty stemmed from parameters in stage-discharge rating curve, if h represents stage for discharge Q, which can be written as $Q=A(h-B)^C$. Parameters in rating curve (A, B and C) were estimated by non-linear regression model and assumed by t distribution. The range of parameters in rating curve was 5.138~18.442 for A, -0.524~0.104 for B and 2.427~2.924 for C. By sampling 10,000 parameter sets, Monte Carlo simulations were performed. The simulated stage value was represented by 95% confidence interval. In storm event 1~3, the average bound was 0.39 m, 0.83 m and 0.96 m, respectively. The peak bound was 0.52 m, 1.36 m and 1.75 m, respectively. The recurrence year of each storm event applying the frequency analysis was 1-year, 10-year and 25-year, respectively.

• Journal of the Korean Society of Hazard Mitigation
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• v.6 no.3 s.22
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• pp.69-76
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• 2006

An hydraulic and hydrologic analysis procedure was proposed to reduce the inundation damage of highway in urban stream, that could contribute the EAP and Traffic control planning of Dongbu highway in the Jungrang stream basin which is one of the representative urban area in Korea. We performed the HEC-HMS runoff analysis, and the UNET unsteady flow modeling to decide the inundation reaches and their characteristics. The high inundation risk areas were of Emoon railway bridge and the Wollueng bridge, which are inundated in the case of 10 year and 20 year frequency flood respectively. We also analyze the inundation characteristics under the various conditions of the accumulation rainfall and the duration. Flood elevation at the Wolgye-1 bridge exceed over Risk Flood Water Level(EL.17.84 m) when the accumulation rainfall is over 250 mm and shorter duration than 7 hr. When neglecting backwater effect from the Han river, inundation risk are highly at the reach C2(Wolgye-1 br. ${\sim}$Jungrang br., left bank), C1(Wolgye-1 br. ${\sim}$Jungrang br., right bank), D(Jungrang br. ${\sim}$Gunja br.) in order, but when consider the effect, the inundation risk are higher than the others at the reach D2(Jungrang br. ${\sim}$Gunja br., left bank) and E(Gunja br. ${\sim}$Yongbi br.), which are located downstream near confluence.

• Journal of Korea Water Resources Association
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• v.48 no.12
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• pp.1011-1021
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• 2015

This study aims to investigate droughts from the magnitude perspective based on the SPI (Standardized Precipitation Index) and the theory of runs applicable to quantitative analysis of drought in South Korea. In addition, the dry spell analysis was conducted on the drought history in the five major river basins of South Korea to obtain the magnitude, duration and severity of drought, and the quantitative evaluation has been made on historical droughts by estimating the return period using the SDF (Severity-Duration-Frequency) curve gained through drought frequency analysis. The analysis results showed that the return periods for droughts at the regional and major river basin scales were clearly identified. The return periods of severe drought that occurred around the major river basins in South Korea turn out to be mostly 30 to 50 years with the years of the worst drought in terms of severity being 1988 and 1994. In particular, South Korea experienced extremely severe droughts for two consecutive years during the period between 1994 and 1995. Drought in 2014 occurred in the Han River basin and was evaluated as the worst one in terms of severity and magnitude.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05a
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• pp.43-50
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• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.

• Journal of Environmental Science International
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• v.25 no.1
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• pp.41-56
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• 2016

In recent localized heavy rainfalls have been arising from abnormal climate change. People are concerning about damages with increasing the frequency of flooding. Therefore, we need to understand river hydraulic characteristics and management to reduce damage from flooding. To study hydraulic characterization of Sincheon experimental catchment HEC-RAS (Hydrologic Engineering Center River Analysis System) model which provided by U.S Army Corps of Engineers (USACE) was applied. This study analyzed and compared water level the frequency flood for 100 years and 200 years by clark unit Hydrography. The change of the water level of Daejeon bridge, Sincheon bridge and Singi bridge showed increased for all conditions. The flow rate for the Daejeon bridge and the Sincheon bridge showed an increase, but the Sinki bridge showed a decreasing flow rate overally, except for 1hour-100 years. The verification result showed that the model was able to simulate the water level with 0.4709 coefficient of determination and error ration ranging from 1 to 3%.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.827-831
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• 2009

Recently, frequency occurring flood and drought has increased the necessity of an effective water resources control and management of river flows. Therefore, the simulation of the flow distribution in natural rivers is great importance to the solution of a wide variety of practical flow problems in water resources engineering. However The serious problem facing two-dimensional hydraulic model is the treatment of wet and dry areas. The objective of this study is to investigate the wet and dry parameters that have direct relevance to model performance in situations where inundation of initially dry areas occurs. Several numerical simulations were carried out, which examined the performance of the marsh porosity method for the purpose of sensitivity analysis. Experimental channel and a variety of channel were performed for model tests. The results were compared with those of the observation data and simulation data of existing model. The RMA-2 model displayed reasonable flow distribution compare to the observation data and simulation data of existing model in dry area for application of natural river flow. As a result of this study, effectively applied marsh porosity method provide a reliable results for flow distribution of wet and dry area, it could be further developed to basis for extending to water quality and sediment transport analysis.

• Journal of Distribution Science
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• v.21 no.7
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• pp.73-82
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• 2023

Purpose: Social networking services have been recognized as an attractive distribution channel at a time when efforts to deliver effective messages to consumers are essential amid a flood of advertisements in the multi-media era. In that sense, this study investigated the effect of the scarcity message type (limited-time vs. limited-quantity) and sender type (corporate vs. consumer) on the intention to purchase golf equipment by Instagram distribution channel. Research design, data and methodology: Data from 108 college students in their 20s and 30s with experience using Instagram were collected online through convenience sampling. A frequency analysis, exploratory factor analysis, reliability analysis, independent sample t-test, and two-way analysis of variance were performed using SPSS 23.0. Results: The results showed that limited-quantity messages induce a higher purchase intention than limited-time messages. Similarly, consumer-sent advertisements induce a higher purchase intention than corporate-sent advertisements. Further, there is no statistically significant interaction effect of the scarcity message type and sender type on the intention to purchase golf equipment. Conclusions: This study is meaningful in verifying consumers' purchase intention depending on the type of scarcity message and the type of sender in Instagram advertisements. The results yield significant implications for marketers and several directions for future research.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1225-1229
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• 2008

본 연구에서는 한강의 중요한 관측지점인 한강대교(구 인도교)지점에서 관측된 연최대치 홍수량을 자료를 이용하여 홍수빈도해석을 수행하였다. 홍수빈도해석을 위하여 확률분포형을 가정해 적합도 검정을 통해 최적 분포형을 선정해 확률홍수량을 산정하는 매개변수적 빈도해석과 원자료에 핵함수를 적용하는 비매개 변수적 빈도해석을 통해 각각 산정한 확률홍수량을 비교하였다. 비매개변수적 빈도해석을 위해서는 변동핵 밀도함수를 적용한 Modified Cauchy 핵밀도함수와 Sheater & Jones Plug-In 광역폭 결정 방법을 이용하였다. 따라서 본 연구에서 분석한 확률홍수량과 한강대교 지점의 계획홍수량의 비교를 통해 현재의 계획홍 수량의 적정성을 평가하였다.