• Journal of The Geomorphological Association of Korea
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• v.20 no.4
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• pp.51-70
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• 2013

The characteristics of deposits formed by the Daejon-cheon and Soobuk-cheon, dissecting the mountains such as Byungpung Mt. and Samin Mt. in western part of Damyang county, Jeonmam province. Results from field survey and bore hole logging by KIGAM are used in interpreting depositional environment, in this study. By the result of deposits near of the channels Daejon-cheon and Soobuk-cheon, and main channel of Youngsan River, the depth of sediment layers in this area is 4~7m, far thinner than formerly estimated. Weathered material of local rocks forms the base of the sedimentary layers. It can be assumed that the location channel of the Youngsan river has been stable ever since the start of the sedimentary events. Sediment particles of tributaries are angular than those of Youngsan River. Particles are larger and sorting is poor. It is interpreted as mount flash flood deposits. Main sources of sediments at the valley bottom or deposition dominated area are the terrace deposits or slope deposits over the gentle foot-slope or front of surrounding mountains. Some particles show polygonal cracking on the surface originated from the strong chemical weathering, while most of these has high angularity. It means various geomorphic processes operate to produce and transport the particles in this area.Isolated hills within the sedimentary plains are made with weathered materials of local bedrock. In the case of foot-slope of the hills, thin sedimentary layers are found. So it can be concluded that surface features of deposition zone of the Daejon-cheon and Soobuk-cheon is formed by the filling of lower part of the valley and its feature partly controlled by the relief of the weathering front.

• Journal of Korean Society of Disaster and Security
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• v.7 no.1
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• pp.17-25
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• 2014

Due to the recent climate change impact, natural disasters occur due to sea surface rising, typhoon attacks, flash floods, local heavy rainfalls, landslides, and coastal area erosion, continuing to cause human and property damage. These impacts, coupled with urbanization and industrialization activities, are turning the previously safe areas into disaster-vulnerable areas, increasing human and economic damage. This paper aimed to prepare measures designed to minimize human damage in natural disaster vulnerable parts of South Korea in summer. Toward that end, how vulnerable areas were managed and what the damage was like were studied. Also, cases of human damage and statistics there of were reviewed and analyzed, relevant problems were derived, and thus structural and non-structural measures designed to minimize human damage were presented.

• 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 Korean Society of Water and Wastewater
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• v.24 no.3
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• pp.351-359
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• 2010

Recently, there have been flood damages due to the climate change and the flash flood continuously in Korea and there are several flood disaster mitigation plans that are normally most of management plan for water related disasters even though drought disasters are as important as flood disasters. In this study, it is underlined that the research on solution of water shortness due to the drought disasters is currently required since the frequency of drought damage is not very many but continuously increasing. There was big drought damage in TaeBaek City of Kangwon province due to the serious lack of water during autumn, 2008 to spring, 2009. This study therefore analyses the characteristics of hydrometeorological conditions by rainfall frequency analysis and the operations of Gwangdong dam that is a source of multi-regional water supply by analysing water demand. As results of study, there was a drought with 20 years returning period which is not really available to fill the reservoir as usual and which could only filled 52% of reservoir. The rainfall during the dry season was less than normal, however, the water demand from the TaeBaek City was higher than normal. As researching several reasons of water shortness including the reasons described above, this study might be useful for drought mitigation plan.

• Journal of the Korean Society of Hazard Mitigation
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• v.4 no.4 s.15
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• pp.13-19
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• 2004

The tremendous flood damage caused by Typhoon Rusa(2002) was occurred at GangNeung City in GangWon Province. Almost of the city region was inundated and most of the stream channel facilities were damaged by flash flood with heavy rainfalls. We have investigated seriously damaged parts of stream bank and tried to analyze the causes of damages focused on flow characteristics in curved channel. We analyzed the damage aspects of curved channel by examining geomorphological survey and hydrographical characteristics. Strong correlation was shown according to the regression analysis between length of stream and meander wave length, and meander belt and length of stream. Furthermore, enveloped curve was presented between bottom slope of channel and meander belt, and meander ratio and channel width. As a result, special consideration about stream flow characteristics are needed for engineers who design stream banks and channels.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.259-259
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• 2016

This study examined Artificial Neurons Networks model (ANNs) for forecast flash discharge at Southern part of Thailand by using rainfall data and discharge data. The Sungai Kolok River Basin has meant the border crossing between Thailand and Malaysia which watershed drains an area lies in Thailand 691.88 square kilometer from over all 2,175 square kilometer. The river originates in mountainous area of Waeng district then flow through Gulf of Thailand at Narathiwat Province, which the river length is approximately 103 kilometers. Almost every year, flooding seems to have increased in frequency and magnitude which is highly non-linear and complicated phenomena. The purpose of this study is to forecast runoff on Sungai Kolok at X.119A gauge station (Sungai Kolok district, Narathiwat province) for 3 days in advance by using Artificial Neural Networks model (ANNs). 3 daily rainfall stations and 2 daily runoff station have been measured by Royal Irrigation Department and Meteorological Department during flood period 2000-2014 were used as input data. In order to check an accuracy of forecasting, forecasted runoff were compared with observed data by pursuing Coefficient of determination ($R^2$). The result of the first day gets the highest accuracy and then decreased in day 2 and day 3, consequently. $R^2$values for first day, second day and third day of runoff forecasting is 0.71, 0.62 and 0.49 respectively. The results confirmed that the ANNs model can be used when the range of collected dataset is short and real-time operated. In conclusion, the ANNs model is suitable to runoff forecasting during flood incident of Sungai Kolok river because it is straightforward model and require with only a few parameters for simulation.

• Atmosphere
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• v.25 no.2
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• pp.283-294
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• 2015

For urban flash flood simulation, we need the higher resolution radar rainfall than radar rainfall of KMA, which has 10 min time and 1km spatial resolution, because the area of subbasins is almost below $1km^2$. Moreover, we have to secure the high quantitative accuracy for considering the urban hydrological model that is sensitive to rainfall input. In this study, we developed the quantitative precipitation estimation (QPE), which has 250 m spatial resolution and high accuracy using KMA AWS and SK Planet stations with Mt. Gwangdeok radar data in Seoul area. As the results, the rainfall field using KMA AWS (QPE1) is showed high smoothing effect and the rainfall field using Mt. Gwangdeok radar is lower estimated than other rainfall fields. The rainfall field using KMA AWS and SK Planet (QPE2) and conditional merged rainfall field (QPE4) has high quantitative accuracy. In addition, they have small smoothed area and well displayed the spatial variation of rainfall distribution. In particular, the quantitative accuracy of QPE4 is slightly less than QPE2, but it has been simulated well the non-homogeneity of the spatial distribution of rainfall.

• Journal of the Korean Society of Safety
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• v.33 no.5
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• pp.78-83
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• 2018

Recently, due to the rapid industrialization and urbanization, a great number of infrastructure and population were concentrated in urban areas. These changes have resulted in unprecedent runoff characteristics in urban basins, and the increase in impermeable areas leads to the growth of the runoff and the peak flow rate. Although many cities have made a lot of efforts to check and expand the stormwater network, the flash flood or the local torrential rain caused a growing number of casualty and property damage. This study analyzed the stormwater passage rate in a target area using SWMM. By incorporating the flow quantity surpassing the storm sewer capacity, a 2D inland flooding analysis model was applied to route the inundated area and velocity.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.2258-2263
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• 2008

최근 이상기후로 인하여 국지성 집중호우의 형태를 띠는 강우가 많이 발생하고 있다. 이러한 강우는 돌발 홍수가 발생하는데 중요한 요소로 작용하게 된다. 이에 본 연구에서는 돌발홍수지수산정을 위한 강우-유출모형 적용시, 집중형모형과 분포형모형의 장단점을 비교하였다. 이를 위하여 안양천 유역을 대상으로 HEC-HMS모형의 Clark 및 ModClack방법을 이용하여 돌발홍수지수를 산정하여 보았다. 2003년, 2004년, 2005년 각 연도별로 하나씩의 호우를 선정하여 이들을 대상으로 분석을 하였다. 집중형 모형에 대해서는 유역면적평균강우량을, 준분포형 모형에 대해서는 Kriging 기법을 통하여 공간분포된 강우량을 이용하였다. 돌발홍수는 상대적으로 크기가 작은 유역에 많이 발생하므로 소유역 분할시 결정한 소유역의 크기가 돌발홍수 지수에 큰 영향을 줄 수 있다. 따라서 돌발홍수지수의 산정은 유역의 크기에 따라 집중형 모형, 준분포형 모형 모형을 적절하게 선택하여 강우-유출관계를 유도해야 할 것으로 판단된다. 또한 돌발홍수지수의 산정이 돌발홍수예보를 위한 기준이 되는 것을 감안할 때 준분포 모형이 강우레이더에 의한 강우예측자료를 활용하는 데에 유리할 것으로 생각된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.180-180
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• 2019

본 연구의 목표는 돌발홍수 예 경보시스템(Flash Flood Warning System, FFWS)의 효용성 극대화를 위한 레이더 자료의 품질향상 기법을 개발하는 것이다. 지금까지 사용되어온 레이더 자료의 품질향상 기법들은 모두 자료의 평균값에 맞추어져 개발되었다. 그러나 돌발홍수 예 경보시스템에서 사용되는 강우강도 임계값은 평균값과 큰 차이가 난다. 따라서 레이더 자료를 이용하여 추정하는 큰 강우강도의 신뢰도는 떨어지게 된다. 이에 본 연구에서는 돌발홍수 예 경보시스템에 사용되는 목표 강우량에 대한 강우추정 관계식의 매개변수 추정 기법을 개발하고자 한다. 이를 위해 비슬산 레이더 반사도 자료와 비슬산 레이더 관측반경 내 위치한 AWS 지점의 강우자료를 이용하였다. 먼저, 강수입자분포(Drop Size Distribution, DSD)를 지수분포로 가정하여 유도한 레이더 강우추정 관계식을 재검토하였다. 다음으로 관측된 비슬산 레이더 반사도 자료를 10dBZ 단위로 구분하여 레이더 반사도 구간별로 레이더 반사도 자료와 강우자료 쌍에 대한 DSD 매개변수를 산정하였다. DSD 매개변수를 산정하기 위해 비슬산 레이더 반사도 자료와 AWS 지점의 강우자료를 지수분포로 가정하여 유도한 강우추정 관계식에 적용하였다. 다음으로 목표 강우량에 대한 강우추정 관계식의 매개변수 추정을 위해 레이더 반사도 구간별로 DSD 매개변수의 대푯값을 결정하였다. 마지막으로 지수분포로 가정하여 유도한 레이더 강우추정 관계식에 레이더 반사도 구간별 DSD 매개변수의 대푯값을 적용함으로써 목표 강우량에 대한 강우추정 관계식의 매개변수를 추정하였다.