• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.146-146
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• 2022

A flash flood is one of the most hazardous natural events caused by heavy rainfall in a short period of time in mountainous areas with steep slopes. Early warning of flash flood is vital to minimize damage, but challenges remain in the enhancing accuracy and reliability of flash flood forecasts. The forecasters can easily determine whether flash flood is occurred using the flash flood guidance (FFG) comparing to rainfall volume of the same duration. In terms of this, the hydrological model that can consider the basin characteristics in real time can increase the accuracy of flash flood forecasting. Also, the predicted radar rainfall has a strength for short-lead time can be useful for flash flood forecasting. Therefore, using both hydrological models and radar rainfall forecasts can improve the accuracy of flash flood forecasts. In this study, FFG was applied to simulate some flash flood events in the Taehwa river basin by using of SURR model to consider soil moisture, and applied to the flash flood forecasting using predicted radar rainfall. The hydrometeorological data are gathered from 2011 to 2021. Furthermore, radar rainfall is forecasted up to 6-hours has been used to forecast flash flood during heavy rain in August 2021, Wulsan area. The accuracy of the predicted rainfall is evaluated and the correlation between observed and predicted rainfall is analyzed for quantitative evaluation. The results show that with a short lead time (1-3hr) the result of forecast flash flood events was very close to collected information, but with a larger lead time big difference was observed. The results obtained from this study are expected to use for set up the emergency planning to prevent the damage of flash flood.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2006년도 학술발표회 논문집
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• pp.1145-1149
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• 2006

The typhoon Rusa passed through the Korean peninsula from the west-southern part to the east-northern part in the summer season of 2002. The flash flood due to the Rusa was occurred over the Korean peninsula and especially the damage was concentrated in Kangnung, Yangyang, Kosung, and Jeongsun areas of Kangwon-Do. Since the latter half of the 1990s the flash flood has became one of the frequently occurred natural disasters in Korea. Flash floods are a significant threat to lives and properties. The government has prepared against the flood disaster with the structural and nonstructural measures such as dams, levees, and flood forecasting systems. However, since the flood forecasting system requires the rainfall observations as the input data of a rainfall-runoff model, it is not a realistic system for the flash flood which is occurred in the small basins with the short travel time of flood flow. Therefore, the flash flood forecasting system should be constructed for providing the realistic alternative plan for the flash flood. To do so, firstly, Flash Flood Monitoring and Prediction (FFMP) Model must be developed suitable to Korea terrain. In this paper, We develop the FFMP model which is based on GIS, Radar techniques and hydro-geomorphologic approaches. We call it the F2MAP model. F2MAP model has three main components (1) radar rainfall estimation module for the Quantitative Precipitation Forecasts (QPF), (2) GIS Module for the Digital terrain analysis, called TOPAZ(Topographic PArametiZation), (3) hydrological module for the estimation of threshold runoff and Flash Flood Guidance(FFG). For the performance test of the model developed in this paper, F2MAP model applied to the Kangwon-Do, Korea, where had a severe damage by the Typhoon Rusa in August, 2002. The result shown that F2MAP model is suitable for the monitoring and the prediction of flash flood.

• 한국수자원학회논문집
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• 제53권3호
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• pp.225-236
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• 2020

유역 상류의 소규모 산지 유역 또는 도시 배수분구 정도의 도시 유역은 지체시간이 수 십 여분에 불과하기 때문에 우량계만으로는 대응에 필요한 충분한 예측 선행시간을 확보하기 어렵다. 도시 및 소규모 산지 유역에서와 같이 지체시간이 짧은 유역에서 발생하는 돌발홍수는 더 이상 우량계만으로 예보가 불가능하다. 도달시간이 짧은 도시 및 산지에서는 지체시간 외에 강수 예측을 통한 홍수예보 선행시간을 확보하는 것이 매우 중요하다. 한강홍수통제소에서는 강우레이더 강우강도를 초단기 예측 모델인 Mcgill Algorithm for Precipitation-nowcast by Lagrangian Extrapolation(MAPLE) 알고리즘의 입력 자료로 활용하여 초단기 예측 강수 자료를 생산하고 있다. 한국건설기술연구원의 돌발홍수연구센터는 한강홍수통제소에서 생산하고 있는 초단기 예측 강수 자료를 입력 자료로 하여 돌발홍수 예측 시스템을 구축하였고 2019년부터 동네규모의 1시간 전 돌발홍수정보를 제공하고 있다. 본 연구에서는 돌발홍수연구센터에서 구축한 돌발홍수 예측 시스템을 설명하고 2019년도에 발생한 수재해 사례를 분석하여 전국 도시·산지·소하천 돌발홍수 예측 시스템의 예측 정확도를 검증하였다. 돌발홍수 예측 시스템의 정확도 검증에는 총 31개의 수재해 사례를 적용하였고 예측 정확도는 Probability of Detection (POD) 기준으로 90.3%로 매우 높게 나타났다.

• Water Engineering Research
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• 제3권2호
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• pp.123-134
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• 2002

A developed Quantitative Flood Forecasting (QFF) model was applied to the mid-Atlantic region of the United States. The model incorporated the evolving structure and frequency of intense weather systems of the study area 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 associated with synoptic atmospheric conditions as Input. Here, we present results from the application of the Quantitative Flood Forecasting (QFF) model in 2 small watersheds along the leeward side of the Appalachian Mountains in the mid-Atlantic region. Threat scores consistently above 0.6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 40% and up to 55 % were obtained.

• Water Engineering Research
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• 제3권2호
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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.

• 한국방재학회:학술대회논문집
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• 한국방재학회 2008년도 정기총회 및 학술발표대회
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• pp.405-408
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• 2008

Up to now, a lot of houses, roads and other urban facilities have been damaged by natural disasters such as flash floods and landslides. It is reported that the size and frequency of disasters are growing greatly due to global warming. In order to mitigate such disaster, flood forecasting and alerting systems have been developed for the Han river, Geum river, Nak-dong river and Young-san river. These systems, however, do not help small municipal departments cope with the threat of flood. In this study, a real-time urban flood forecasting service (U-FFS) is developed for ubiquitous computing city which includes small river basins. A test bed is deployed at Tan-cheon in Gyeonggido to verify U-FFS. It is found that U-FFS can forecast the water level of outlet of river basin and provide real-time data through internet during heavy rain. Furthermore, it is expected that U-FFS presented in this study can be applied to ubiquitous computing city (u-City) and/or other cities which have suffered from flood damage for a long time.

• 한국정보통신설비학회:학술대회논문집
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• 한국정보통신설비학회 2007년도 학술대회
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• pp.181-184
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• 2007

Up to now, a lot of houses, roads and other urban facilities have been damaged by natural disasters such as flash floods and landslides. It is reported that the size and frequency of disasters are growing greatly due to global warming. In order to mitigate such disaster, flood forecasting and alerting systems have been developed for the Han river, Geum river, Nak-dong river and Young-san river. These systems, however, do not help small municipal departments cope with the threat of flood. In this study, a real-time urban flood forecasting service (U-FFS) is developed for ubiquitous computing city which includes small river basins. A test bed is deployed at Tan-cheon in Gyeonggido to verify U-FFS. Wireless sensors such as rainfall gauge and water lever gauge are installed to develop hydrologic forecasting model and CCTV camera systems are also incorporated to capture high definition images of river basins. U-FFS is based on the ANFIS (Adaptive Neuro-Fuzzy Inference System) that is data-driven model and is characterized by its accuracy and adaptability. It is found that U-FFS can forecast the water level of outlet of river basin and provide real-time data through internet during heavy rain. It is revealed that U-FFS can predict the water level of 30 minutes and 1 hour later very accurately. Unlike other hydrologic forecasting model, this newly developed U-FFS has advantages such as its applicability and feasibility. Furthermore, it is expected that U-FFS presented in this study can be applied to ubiquitous computing city (U-City) and/or other cities which have suffered from flood damage for a long time.

• 한국수자원학회논문집
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• 제35권5호
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• pp.553-561
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• 2002

본 연구의 목적은 돌발홍수예경보 시스템의 개념을 국내에 도입하고 미소유역 규모의 한계유출량을 산정할 수 있는 시스템을 개발하는데 있다. 입력자료 설정에서 돌발홍수예보 입력파일 생성 등 총 9단계로 구성된 한계유출량 산정 GUI 시스템은 약 5 $\textrm{km}^2$ 규모로 소유역을 구분하며, 구분된 각 미소유역별 수문특성인자, 제방월류유량, 단위도 첨두유량 및 한계유출량을 산정한다. 개발된 시스템을 평창강 유역에 적용한 결과, 지속시간 1시간의 토양이 포화된 상태에서 소하천이 범람하는데 요구되는 유효강우량을 나타내는 한계유출량은 18.72~81.96 mm의 범위를 갖으며, 평균값은 46.39 mm인 것으로 나타났다. 평창강 유역의 미소유역별 산정된 한계유출량을 국외의 타 연구 사례와 비교한 결과 평창강 유역에서 산정된 결과는 적절한 것으로 판단된다. 본 연구에서 구축된 ArcView/Avenue 기반의 한계유출량 산정 GUI 시스템은 국내 타 유역에도 적용 가능할 것으로 판단되어 향후 국내 돌발 홍수예경보 시스템의 일부로 활용될 수 있을 것으로 판단된다.

• 한국방재학회 논문집
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• 제10권4호
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• pp.81-88
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• 2010

최근 들어 기상 이변에 따라 단시간 동안에 특정 소유역에 집중하는 호우 또는 초과우량에 의한 국지성 돌발홍수가 빈번히 발생함에 따라, 이로 인한 인명과 재산의 상당한 위험과 손실은 전 세계적인 것으로서 우리나라도 증가일로에 있다. 돌발홍수는 일반적으로 급경사 소유역에서 집중적인 강우에 의해 발생하여 빠른 유출과 토석류를 동반하기 때문에, 홍수피해를 대비하기 위한 사전 홍수예보시간이 부족할 정도로 급격히 빠른 홍수의 특성을 보인다. 본 연구의 목적은 대상유역의 확률강우량으로부터 돌발홍수지수(flash flood index, FFI)를 산정하여 돌발홍수의 심각성 정도를 정량적으로 분석하고자 한다. 특히 미계측 유역하천에서의 지역 홍수예 경보를 위한 기초자료를 제공할 수 있도록, 대상유역에 대하여 상대적인 돌발홍수심도를 제시할 수 있는 FFI-D-F(돌발홍수지수-지속시간-빈도) 관계곡선을 개발하였다. 또한 FFI-D-F 관계곡선은 현존 및 계획 방재시설물의 돌발홍수 대응능력 및 잔여홍수위험 평가에 활용될 수 있을 것으로 기대된다.

• 한국습지학회지
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• 제12권3호
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• pp.155-163
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• 2010

돌발홍수는 짧은 지속기간, 급격한 경사와 불투수층에 대해 강한 강우로 인하여 피해를 유발하는 홍수를 말한다. 돌발홍수는 강우가 돌발홍수기준(Flash Flood Guidance)을 초과하는 경우에 발생하게 되며, 따라서 돌발홍수기준을 정확히 산정하는 것이 돌발홍수예보의 정확성에 크게 기여한다. 즉, 강우-유출관계가 갖고 있는 불확실성(uncertainty)을 최소화 할수록 돌발홍수기준을 정확하게 산정할 수 있으며, 강우-유출 모형은 각각 고유의 매개변수와 특성을 갖고 있으므로 어떠한 강우-유출 모형을 사용하여 강우-유출관계를 도출하느냐에 따라 불확실성의 정도가 크게 좌우된다. 본 연구에서는 4개의 강우-유출모형(HEC-HMS 모형, 저류함수모형, SSARR 모형, TANK 모형)의 모의값에 Monte Carlo 모의 방법을 적용하여 95%신뢰수준에 대한 신뢰한계를 추정하여 제시하였다.