• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.3
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• pp.385-393
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• 2016

In this study, we analyzed th Cheonggyecheon watershed for urban flood risk index. SWMM model configuration based on each watershed data. And it was set as the final index calculated indicators related to the humanities, social and environmental. Each indicator was standardized and weighted using the Delphi method. Finally, select the danger area through urban flood risk index. Determined 12 indices according to the hazard and vulnerability. Vulnerability is selected the index divided by three factors. 21 watersheds were analyzed through urban flood risk index. The top of three areas of index is Jeongneung 1, Majang, Pil-dong, each index is 0.533, 0.494, 0.381. The lowest index is soongin 0.216. Urban flood risk index developed in this study can be applied to other regions in Korea for establishing national water resources management plan.

• Journal of Korea Water Resources Association
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• v.35 no.4 s.129
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• pp.359-366
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• 2002

The damages from the natural disasters, especially from the floods, have been increasing. Therefore, it is imperative to establish a BMP to diminish the damages from the floods and to enhance the welfare of the nation. Developed countries have been generating and utilizing flood risk maps to raise the alertness of the residents, and thereby achieving efficient flood management. The major objectives of this research were to develop a prototype management system for flood risk map to forecast the boundaries oi the inundation and to plot them through the integration of geographic and hydrologic database. For more efficient system development, the user requirement analysis was made. The GIS database design was done based on the results from the research work of river information standardization. A GIS database for the study area was built by using topographic information to support the hydrologic modeling. The developed prototype include several modules; river information edition module, map plotting module, and hydrologic modeling support module. Each module enabled the user to edit graphic and attribute data, to analyze and to represent the modeling results visually. Subjects such as utilization of the system and suggestions for future development were discussed.

• Journal of Korea Society of Waste Management
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• v.35 no.8
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• pp.777-784
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• 2018

Since climate change increases the risk of extreme rainfall events, concerns on flood management have also increased. In order to rapidly recover from flood damages and prevent secondary damages, fast collection and treatment of flood debris are necessary. Therefore, a quick and precise estimation of flood debris generation is a crucial procedure in disaster management. Despite the importance of debris estimation, methodologies have not been well established. Given the intrinsic heterogeneity of flood debris from local conditions, a regional-scale model can increase the accuracy of the estimation. The objectives of this study are 1) to identify significant damage variables to predict the flood debris generation, 2) to ascertain the difference in the coefficients, and 3) to evaluate the accuracy of the debris estimation model. The scope of this work is flood events in Ulsan city region during 2008-2016. According to the correlation test and multicollinearity test, the number of damaged buildings, area of damaged cropland, and length of damaged roads were derived as significant parameters. Key parameters seems to be strongly dependent on regional conditions and not only selected parameters but also coefficients in this study were different from those in previous studies. The debris estimation in this study has better accuracy than previous models in nationwide scale. It can be said that the development of a regional-scale flood debris estimation model will enhance the accuracy of the prediction.

• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.41-52
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• 2005

The high density of population and building; can cause catastrophe in urban areas when natural or artificial disasters break out. The aim of this paper is to assess comprehensive disasters risk of urban areas by Geospatial Information System. For this purpose, we classified disasters risk of urban areas into low categories: flood, fire, building-collapse, and shelter, and then determined factors for hazard risk assessment respectively. The results of hazard assessment can be applied to minimize the demage of disasters in establishing the urban management planning. For more systematic and professional approach the further research is need to consider more disaster assessment factors and join with related experts.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.335-337
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• 2021

Flood damage is occurring all over the world, and the number of people living in flood-prone areas reached 86 million, a 25% increase compared to 2000. These floods cause enormous damage to life and property, and it is essential to decide on an appropriate evacuation in order to reduce the damage. Evacuation in anticipation of a flood also incurs a lot of cost, and if an evacuation is not performed due to an error in the flood prediction, a greater cost is incurred. Therefore, in this paper, we propose a flood risk determination model using the CNN model to enable evacuation at an appropriate time by using the time series data of precipitation and water level. Through this, it is thought that it can be utilized as an initial study to determine the time of flood evacuation to prevent unnecessary evacuation and to ensure that evacuation can be carried out at an appropriate time.

• Journal of Korea Water Resources Association
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• v.40 no.4
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• pp.345-357
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• 2007

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.410-413
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• 2008

We constructed the regional flood risk and damage magnitude using hazard and vulnerabilities which are climatic, hydrological, socio-economic, countermeasure, disaster probability components for DB construction on the GIS system. Also we developed the Excess Flood Vulnerability index estimation System(EFVS). By the construction of the System, we can perform the scientific flood management for the flood prevention and optional extreme flood defenses according to regional characteristics. In order to evaluate the performance of system, we applied EFVS to Anseong-chen in Korea, and the system's stabilization is appropriate to flood damage analysis.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.6
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• pp.389-403
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• 2021

In this study, dual drainage system based runoff model was established for W-drainage area in G-si, and considering the various rainfall characteristics determined using Huff and Mononobe methods, the degree of flooding in the target area was analyzed and the risk was compared and analyzed through the risk matrix method. As a result, the Monobe method compared to the Huff method was analyzed to be suitable analysis for flooding of recent heavy rain, and the validity of the dynamic risk assessment considering the weight of the occurrence probability as the return period was verified through the risk matrix-based analysis. However, since the definition and estimating criteria of the flood risk matrix proposed in this study are based on the return period for extreme rainfall and the depth of flooding according to the results of applying the dual drainage model, there is a limitation in that it is difficult to consider the main factors which are direct impact on inland flooding such as city maintenance and life protection functions. In the future, if various factors affecting inland flood damage are reflected in addition to the amount of flood damage, the flood risk matrix concept proposed in this study can be used as basic information for preparation and prevention of inland flooding, as well as it is judged that it can be considered as a major evaluation item in the selection of the priority management area for sewage maintenance for countermeasures against inland flooding.

• Journal of Korean Society for Geospatial Information Science
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• v.12 no.1 s.28
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• pp.21-29
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• 2004

Floods are disastrous natural phenomena which result in numerous losses of life and property. It is possible to minimize the potential risk by adopting a disaster management system. Nowadays, Geo-Spatial Information System(GSIS) and computer-modelling techniques have assisted scientists and engineers with determining flood disaster assessments, GIS technologies especially have the advantage of performing spatial analysis as well as generating the model for a flood hazard. Therefore, this paper presents the flood management system based on 3D GSIS that can cope with natural disasters actively and manage flood hazard systematically by constructing the database using hydrological data, digital map, DEM, and high-resolution satellite images.

• 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.