• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.235-235
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• 2015

This study investigates the impact of event characteristics on runoff dynamics during extreme flood events observed in a $8.5km^2$ experimental watershed located in South Korea. The 37 most extreme flood events with event rainfall in excess of 50 mm were analysed using an event-based rainfall-runoff model; the Revitalised Flood Hydrograph (ReFH) routinely used for design flood estimation in the United Kingdom. The ReFH model was fitted to each event in turn, and links were investigated between each of the two model parameters controlling runoff production and response time, respectively, and event characteristics such as rainfall depth, duration, intensity and also antecedent soil moisture. The results show that the structure of the ReFH model can effectively accommodate any nonlinearity in runoff production, but that the linear unit hydrograph fails to adequately represent a reduction in watershed response time observed for the more extreme events. By linking the unit hydrograph shape directly to rainfall depth, the consequence of the observed nonlinearity in response time is to increase design peak flow by between 50% for a 10 year return period, and up to 80% when considering the probable maximum flood (PMF).

• Journal of Korea Water Resources Association
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• v.55 no.9
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• pp.657-668
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• 2022

With the occurrence of localized heavy rain while river flow has increased, both flow and rainfall cause riverside flood damages. As the degree of damage varies according to the level of social and economic impact, it is required to secure sufficient forecast lead time for flood response in areas with high population and asset density. In this study, the author established a flood risk matrix using ensemble rainfall runoff modeling and evaluated its applicability in order to increase the damage reduction effect by securing the time required for flood response. The flood risk matrix constructs the flood damage impact level (X-axis) using flood damage data and predicts the likelihood of flood occurrence (Y-axis) according to the result of ensemble rainfall runoff modeling using LENS rainfall data and as well as probabilistic forecasting. Therefore, the author introduced a method for determining the impact level of flood damage using historical flood damage data and quantitative flood damage assessment methods. It was compared with the existing flood warning data and the damage situation at the flood warning points in the Taehwa River Basin and the Hyeongsan River Basin in the Nakdong River Region. As a result, the analysis showed that it was possible to predict the time and degree of flood risk from up to three days in advance. Hence, it will be helpful for damage reduction activities by securing the lead time for flood response.

• Water Engineering Research
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• v.3 no.2
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• pp.113-122
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• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict flash floods. In this study, a Quantitative Flood Forecasting (QFF) model was developed by incorporating the evolving structure and frequency of intense weather systems and by using neural network approach. 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 lifetime, 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. All these processes stretched leadtime up to 18 hours. The QFF model will be applied to the mid-Atlantic region of United States in a forthcoming paper.

• Korean Journal of Agricultural Science
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• v.50 no.4
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• pp.799-808
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• 2023

Globally, abnormal climate phenomena have led to an increase in rainfall intensity, consequently causing a rise in flooding-related damages. Agricultural areas, in particular, experience significant annual losses every year due to a lack of research on flooding in these regions. This study presents a comprehensive analysis of the flood event that occurred on July 16, 2017, in the agricultural area situated in Sindaedong, Heungdeok-gu, Cheongju-si. To achieve this, the EPA (United States Environmental Protection Agency) Storm Water Management Model (SWMM) was employed to generate runoff data by rainfall information. The produced runoff data facilitated the identification of flood occurrence points, and the analysis results exhibited a strong correlation with inundation trace maps provided by the Ministry of the Interior and Safety (MOIS). The detailed output of the SWMM model enabled the extraction of time-specific runoff information at each inundation point, allowing for a detailed understanding of the inundation status in the agricultural area over different time frames. This research underscores the significance of utilizing the SWMM model to simulate inundation in agricultural areas, thereby validating the efficacy of flood alerts and risk management plans. In particular, the integration of rainfall data and the SWMM model in flood prediction methodologies is expected to enhance the formulation of preventative measures and response strategies against flood damages in agricultural areas.

• Journal of Korea Water Resources Association
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• v.52 no.10
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• pp.753-761
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• 2019

Localized heavy storm is one of the major causes of flood damage in urban regions. According to the recent disaster statistics in South Korea, the frequency of urban flood is increasing more frequently, and the scale is also increasing. However, localized heavy storm is difficult to predict, making it difficult for local government officials to deal with floods. This study aims to construct a Flood risk matrix (FRM) using ensemble weather prediction data and to assess its applicability as a means of reducing damage by securing time for such urban flood response. The FRM is a two-dimensional matrix of potential impacts (X-axis) representing flood risk and likelihood (Y-axis) representing the occurrence probability of dangerous weather events. To this end, a regional FRM was constructed using historical flood damage records and probability precipitation data for basic municipality in Busan and Daegu. Applicability of the regional FRMs was assessed by applying the LENS data of the Korea Meteorological Administration on past heavy rain events. As a result, it was analyzed that the flood risk could be predicted up to 3 days ago, and it would be helpful to reduce the damage by securing the flood response time in practice.

• Fire Science and Engineering
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• v.30 no.6
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• pp.64-70
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• 2016

This study assessed the flood vulnerability of Jeju-do depending on climate change using VESTAP. The results showed that the flood vulnerability of Jeju-do in the future (2020s, 2030s and 2040s) will increase continuously compared to the present time (2010s). In particular, the flood vulnerability of Jeju-si is expected to be higher than Seogwipo-si prior to 2030s. Conversely, the flood vulnerability of Seogwipo-si is expected to be higher than Jeju-si after 2030. These analysis results confirmed the characteristics of flood vulnerability between Seogwipo-si and Jeju-si and the growth of flood vulnerability entirely within Jeju-do.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.346-349
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• 2010

In this study several unit hydrographs by rainfall storms are derived and moving averaged unit hydrograph is extracted from them based on the rainfall-runoff data in a small basin 8.5 $km^2$ wide. And peak discharges and peak times of the unit hydrographs are investigated and reviewed. And then a representative unit hydrograph of the moving averaged one is applied to the linear convolution integration for obtaining the flood discharge hydrograph and peak discharge and time of its result are researched and inspected. Variance in application of the representative unit hydrograph in a basin on assumption of linearity is appeared and this is given as a counterevidence about that the runoff response from rainfall on a basin has nonlinear characteristics. And As a result of application of derived representative unit hydrograph the errors in peak discharge and time are investigated.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1119-1130
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• 2021

Urban flooding caused by localized heavy rainfall with unstable climate is constantly occurring, but a system that can predict spatial flood information with weather forecast has not been prepared yet. The worst flood situation in urban area can be occurred with difficulties of structural measures such as river levees, discharge capacity of urban sewage, storage basin of storm water, and pump facilities. However, identifying in advance the spatial flood information can have a decisive effect on minimizing flood damage. Therefore, this study presents a methodology that can predict the urban flood map in real-time by using rainfall data of the Korea Meteorological Administration (KMA), the results of two-dimensional flood analysis and random forest (RF) regression model. The Ujeong district in Ulsan metropolitan city, which the flood is frequently occurred, was selected for the study area. The RF regression model predicted the flood map corresponding to the 50 mm, 80 mm, and 110 mm rainfall events with 6-hours duration. And, the predicted results showed 63%, 80%, and 67% goodness of fit compared to the results of two-dimensional flood analysis model. It is judged that the suggested results of this study can be utilized as basic data for evacuation and response to urban flooding that occurs suddenly.

• Journal of Korea Water Resources Association
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• v.41 no.6
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• pp.605-617
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• 2008

This study developed a flood index which evaluates runoff characteristics. Runoff characteristics expressed in a hydrograph were reflected in the flood index in the form of characteristic factors such as a rising curve gradient, a peak discharge, a flood response time, and a flood discharge volume prior to peak. This study applied the standardization method to estimate the relative severity of the characteristic factors by transforming the distribution of characteristic factors into the standard normal distribution. The flood index developed in this study is a comprehensive flood index (CFI) which makes up for the weak points of a flash flood index (FFI) in determining relative severities. The CFI was applied to Han River basin and Selma River basin, and was compared with the FFI based on the correlation analysis and the regression analysis. The CFI could comprehensively evaluate flood runoff characteristics because the CFI is not dominated by a specific characteristic factor, and the CFI could explain more efficiently the relationship between rainfall and runoff than the FFI.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3B
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• pp.269-279
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• 2009

The design flood estimation in a large river basin has a lot of uncertainties in areal reduction factors, time-spatial rainfall distribution, and parameters of rainfall-runoff model. The use of historical concurrent rainfall events for estimating design flood would reduce the uncertainties. This study presents a procedure for estimating design floods using historical rainfall events and storage function model. The design rainfall and time-spatial distribution were determined through analyzing concurrent rainfall events, and the design floods were estimated using storage function model with a non-linear hydrology response. To evaluate the applicability of the procedure of this study, the estimated floods were compared to results of frequency analysis of flood data. Both floods gave very similar results. It shows the applicability of the procedure presented in this study for estimating design floods in practices.