• Journal of Korea Water Resources Association
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• v.39 no.12 s.173
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• pp.1013-1022
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• 2006

Urban flooding is usually caused by the surcharge of storm sewers. For this reason, previous studies on urban flooding are mainly concentrated on the simulation of urban drainage systems. However these approaches that find the pipes which have insufficient drainage capacity are very approximate and unreasonable ways in establishing both flood prevention and flood-loss reduction planning. In this study, a two-dimensional model linked the existing ILLUDAS model is developed to calculate the accurate and resonable solution about urban flood inundation and it is verified by using the simulation of July 2001 flood in Seoul. In the urban area with a small difference of ground elevations, the two-dimensional flood propagation phases must be considered to make a accurate analysis for inundated area and depth. The result of this study can be used to construct fundamental data for a flood control plan and establish a urban flood forecasting/warning system.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.195-195
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• 2016

Kon - Ha Thanh River basin is the largest and the most important river basin in Binh Dinh, a province in the South Central Coast of Vietnam. In the lower rivers, frequent flooding and inundation caused by heavy rains, upstream flood and or uncontrolled flood released from upstream reservoirs, are very serious, causing damage to agriculture, socio-economic activity, human livelihood, property and lives. The damage is expected to increase in the future as a result of climate change. An advanced flood warning system could provide achievable non-structural measures for reducing such damages. In this study, we applied a modelling system which intergrates a 1-D river flow model and a 2-D surface flow model for simulating hydrodynamic flows in the river system and floodplain inundation. In the model, exchange of flows between the river and surface floodplain is calculated through established links, which determine the overflow from river nodes to surface grids or vice versa. These occur due to overtopping or failure of the levee when water height surpasses levee height. A GIS based comprehensive raster database of different spatial data layers was prepared and used in the model that incorporated detailed information about urban terrain features like embankments, roads, bridges, culverts, etc. in the simulation. The model calibration and validation were made using observed data in some gauging stations and flood extents in the floodplain. This research serves as an example how advanced modelling combined with GIS data can be used to support the development of efficient strategies for flood emergency and evacuation but also for designing flood mitigation measures.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.339-342
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• 2008

Recently the life and property damage caused by urban inundation have increased. In order to prevent the damage by inundation the researches for displaying the flooded areas through integrating SWMM and GIS have been progressed. However most of flood analysis systems only have used the GIS to display the flooded areas, and don't provide the integration disaster information to prevent the inundation. In this paper, we design a prototype for the Map Viewer based Spatial DB for the integrated urban floooded area management system. And we implement the spatial DB conversion module.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.3
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• pp.76-92
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• 2018

This study aimed to establish database of rainfall inundation area by rainfall scenarios and conduct a real time prediction for urban flood mitigation. the data leaded model was developed for the mapping of inundated area with rainfall forecast data provided by korea meteorological agency. for the construction of data leaded model, 1d-2d modeling was applied to Gangnam area, where suffered from severe flooding event including september, 2010. 1d-2d analysis result agree with observed in term of flood depth. flood area and flood occurring report which maintained by NDMS(national disaster management system). The fitness ratio of the NDMS reporting point and 2D flood analysis results was revealed to be 69.5%. Flood forecast chart was created using pre-flooding database. It was analyzed to have 70.3% of fitness in case of flood forecast chart of 70mm, and 72.0% in case of 80mm flood forecast chart. Using the constructed pre-flood area database, it is possible to present flood forecast chart information with rainfall forecast, and it can be used to secure the leading time during flood predictions and warning.

• Journal of Korea Water Resources Association
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• v.51 no.1
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• pp.19-33
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• 2018

This study proposed a rainfall-runoff model for the purpose of real-time flood warning in urban basins. The proposed model was based on the shot noise process, which is expressed as a sum of shot noises determined independently with the peak value, decay parameter and time delay of each sub-basin. The proposed model was different from other rainfall-runoff models from the point that the runoff from each sub-basin reaches the basin outlet independently. The model parameters can be easily determined by the empirical formulas for the concentration time and storage coefficient of a basin and those of the pipe flow. The proposed model was applied to the total of three rainfall events observed at the Jungdong, Guro 1 and Daerim 2 pumping stations to evaluate its applicability. Summarizing the results is as follows. (1) The unit response function of the proposed model, different from other rainfall-runoff models, has the same shape regardless of the rainfall duration. (2) The proposed model shows a convergent shape as the calculation time interval becomes smaller. As the proposed model was proposed to be applied to urban basins, one-minute of calculation time interval would be most appropriate. (3) Application of the one-minute unit response function to the observed rainfall events showed that the simulated runoff hydrographs were very similar to those observed. This result indicates that the proposed model has a good application potential for the rainfall-runoff analysis in urban basins.

• Korean Journal of Agricultural Science
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• v.46 no.4
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• pp.843-856
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• 2019

Real-time flood prediction has an important role in significantly reducing potential damage caused by floods for urban residential areas located downstream of river basins. This paper presents an effective approach for flood forecasting based on the construction of a deep neural network (DNN) model. In addition, this research depends closely on the open-source software library, TensorFlow, which was developed by Google for machine and deep learning applications and research. The proposed model was applied to forecast the flowrate one, two, and three days in advance at the Son Tay hydrological station on the Red River, Vietnam. The input data of the model was a series of discharge data observed at five gauge stations on the Red River system, without requiring rainfall data, water levels and topographic characteristics. The research results indicate that the DNN model achieved a high performance for flood forecasting even though only a modest amount of data is required. When forecasting one and two days in advance, the Nash-Sutcliffe Efficiency (NSE) reached 0.993 and 0.938, respectively. The findings of this study suggest that the DNN model can be used to construct a real-time flood warning system on the Red River and for other river basins in Vietnam.

• Korean Journal of Remote Sensing
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• v.21 no.4
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• pp.317-327
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• 2005

The flood is the most general and frequently occurs among natural disasters. Generally flood by the rainfall which extends superexcellently for the occurrence but flash flood from severe rain storm gets up an absurd drowsiness at grade hour. This paper aims to 1 hour real-time flash flood and predict possibility at the area where is the possible flood will occur from the rainfall hour mountain after acquiring data in GIS(Geographic Information System) base by GcIUH(Geomorphoclimatic Instantaneous Unit Hydrograph). The flash flood occurrence is set up at 0.5m, 0.7m and 1.0m in standard depth. And this study suggests standard flood alarm which designed by probable flood according to duration time. The research result shows real-time flash flood evaluation has the suitable standard in the basin when comparing with the existing official warning announcement system considering topographical information.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.713-723
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• 2019

Due to the climate change and various rainfall pattern, it is difficult to estimate a rainfall criterion which cause inundation for urban drainage districts. It is necessary to examine the result of inundation analysis by considering the detailed topography of the watershed, drainage system, and various rainfall scenarios. In this study, various rainfall scenarios were considered with the probabilistic rainfall and Huff's time distribution method in order to identify the rainfall characteristics affecting the inundation of the Hyoja drainage basin. Flood analysis was performed with SWMM and two-dimensional inundation analysis model and the parameters of SWMM were optimized with flood trace map and GA (Genetic Algorithm). By linking SWMM and two-dimensional flood analysis model, the fitness ratio between the existing flood trace and simulated inundation map turned out to be 73.6 %. The occurrence of inundation according to each rainfall scenario was identified, and the rainfall criterion could be estimated through the logistic regression method. By reflecting the results of one/two dimensional flood analysis, and AWS/ASOS data during 2010~2018, the rainfall criteria for inundation occurrence were estimated as 72.04 mm, 146.83 mm, 203.06 mm in 1, 2 and 3 hr of rainfall duration repectively. The rainfall criterion could be re-estimated through input of continuously observed rainfall data. The methodology presented in this study is expected to provide a quantitative rainfall criterion for urban drainage area, and the basic data for flood warning and evacuation plan.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.565-575
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• 2022

Recently, in the field of water resource engineering, interest in predicting time series water levels and flow rates using deep learning technology that has rapidly developed along with the Fourth Industrial Revolution is increasing. In addition, although water-level and flow-rate prediction have been performed using the Long Short-Term Memory (LSTM) model and Gated Recurrent Unit (GRU) model that can predict time-series data, the accuracy of flow-rate prediction in rivers with rapid temporal fluctuations was predicted to be very low compared to that of water-level prediction. In this study, the Paldang Bridge Station of the Han River, which has a large flow-rate fluctuation and little influence from tidal waves in the estuary, was selected. In addition, time-series data with large flow fluctuations were selected to collect water-level and flow-rate data for 2 years and 7 months, which are relatively short in data length, to be used as training and prediction data for the LSTM and GRU models. When learning time-series water levels with very high time fluctuation in two models, the predicted water-level results in both models secured appropriate accuracy compared to observation water levels, but when training rapidly temporal fluctuation flow rates directly in two models, the predicted flow rates deteriorated significantly. Therefore, in this study, in order to accurately predict the rapidly changing flow rate, the water-level data predicted by the two models could be used as input data for the rating curve to significantly improve the prediction accuracy of the flow rates. Finally, the results of this study are expected to be sufficiently used as the data of flood warning system in urban rivers where the observation length of hydrological data is not relatively long and the flow-rate changes rapidly.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.816-820
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• 2005

본 연구에서는 해안 도시 하천의 범람으로 인한 홍수 재해 발생시 예상될 수 있는 피해에 대해 적절한 홍수예경보 및 피난대책을 수립하고자 대표적인 해안 도시 하천의 특성을 가지는 부산시 온천천 유역을 대상으로 수치지도에서 각종 지형자료를 추출하였고 수문 GIS 자료를 구축하였다. 그리고, 하천 수리 분석을 위한 한계유출량 산정을 위해 HEC-RAS 모형을 이용 조위의 영향을 고려하여 홍수위 및 한계유출량을 산정하였고 수문 분석을 위한 도시 돌발 홍수 기준 우량 산정을 위해 PCSWMM 2002를 이용하여 기준 우량을 산정하였다. 전형적인 해안 도시 지역 유역 특성을 나타내는 부산시 온천천 유역에 대한 경보발령 기준을 설정하기 위하여 선정지점 세 곳의 한계수심 $H_{c1},\;H_{c2},\;H_{c3},\;H_{c4}$가 발생할 수 있는 강우량(위험 홍수량을 유발하는 위험 강우량(Trigger Rainfall))을 산정하였고 PCSWMM을 이용한 모형화 기법으로 해안 도시 돌발 홍수 기준 우량을 산정하였다. 산정 결과 온천천 유역의 홍수예경보 시스템과 이에 따른 홍수예경보 발령흐름도, 운영체계가 결정되어 해안 도시 돌발 홍수예경보 방안이 구축되었다. 해안 도시의 홍수 관리는 도시 우수 시스템, 하천, 해안 특성이 복합된 문제이다. 현재 해안 도시 지역의 홍수예경보 시스템 구축 실적이 전무한 실정임을 볼 때 현실적으로 실용화 할 수 있는 시스템 개발을 해내는 것이 무엇보다도 시급하고 중요한 문제이다. 앞으로 더욱 심도있게 연구하여 주요 하천에 대한 홍수예경보 시스템 구축이 절실히 요구된다.