• 제목/요약/키워드: extreme rainfall events

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강우의 비정상성을 고려한 청미천 유역의 미래 침수특성 분석 (Future Inundation Characteristics Analysis for the Cheongmi Stream Watershed Considering Non-stationarity of Precipitation)

  • 류정훈;강문성;전상민;박지훈;이경도
    • 한국농공학회논문집
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    • 제59권1호
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    • pp.81-96
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    • 2017
  • Along with climate change, it is reported that the scale and the frequency of extreme climate events (e.g. heavy rain, typhoon, etc.) show unstable tendency of increase. In case of Korea, also, the frequency of heavy rainfall shows increasing tendency, thus causing natural disaster damage in downtown and agricultural areas by rainfall that exceeds the design criteria of hydraulic structures. In order to minimize natural disaster damage, it is necessary to analyze how extreme precipitation event changes under climate change. Therefore a new design criteria based on non-stationarity frequency analysis is needed to consider a tendency of future extreme precipitation event and to prepare countermeasures to climate change. And a quantitative and objective characteristic analysis could be a key to preparing countermeasures to climate change impact. In this study, non-stationarity frequency analysis was performed and inundation risk indices developed by 4 inundation characteristics (e.g. inundation area, inundation depth, inundation duration, and inundation radius) were assessed. The study results showed that future probable rainfall could exceed the existing design criteria of hydraulic structures (rivers of state: 100yr-200yr, river banks: 50yr-100yr) reaching over 500yr frequency probable rainfall of the past. Inundation characteristics showed higher value in the future compared to the past, especially in sections with tributary stream inflow. Also, the inundation risk indices were estimated as 0.14 for the past period of 1973-2015, and 0.25, 0.29, 1.27 for the future period of 2016-2040, 2041-2070, 2071-2100, respectively. The study findings are expected to be used as a basis to analyze future inundation damage and to establish management solutions for rivers with inundation risks.

차량용 강우센서와 강우관측소 관측자료 비교분석 (Comparison and Analysis of Observation Data of Rainfall Sensor for Vehicle and Rainfall Station)

  • 이충대;이병현;조형제;김병식
    • 대한토목학회논문집
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    • 제38권6호
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    • pp.783-791
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    • 2018
  • 낮은 밀도의 강우관측망과 레이더 강우의 편향적인 추정은 좁은 지역에서 발생하는 돌발홍수에 대한 적용에는 한계가 있다. 이를 개선하기 위해서는 더 많은 강우정보의 생산이 필요하다. 본 연구에서는 최근에 개발되어 활용되고 있는 차량용 강우센서를 이용하여 적용성을 분석하였다. 개발된 강우센서를 차량에 부착하여 차량의 이동에 따른 강우 관측을 수행하였다. 분석 방법은 강우센서와 인근 강우관측소의 관측값에 대하여 시계열 및 평균 강수량을 이용하였다. 차량별로 부착된 센서(1~10번)의 관측 강우를 분석한 결과 전체적으로 센서별로 상대적으로 차이가 발생하고 있으나 강우 사상에 따른 관측값의 경향은 일정한 패턴을 나타내고 있는 것을 알 수 있었다. 이는 강우센서의 관측위치와 인근 강우관측소와의 거리 차이, 차량의 이동 속도, 강우관측 방법 등 다양한 원인에 의해 발생하는 것으로 분석되었다. 이 결과는 차량용 강우센서를 이용한 강우관측의 가능성을 보여주었으며 향후 다양한 조건에서의 실험 및 강우센서 개선을 통하여 보다 정밀한 강우관측이 가능할 것으로 검토되었다.

Quantitative Flood Forecasting Using Remotely-Sensed Data and Neural Networks

  • Kim, Gwangseob
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2002년도 학술발표회 논문집(I)
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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.

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분포형 수문모형을 이용한 침식 및 퇴적의 시.공간 변동성 분석 (Analysis on Spatiotemporal Variability of Erosion and Deposition Using a Distributed Hydrologic Model)

  • 이기하;유완식;장창래;정관수
    • 한국수자원학회논문집
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    • 제43권11호
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    • pp.995-1009
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    • 2010
  • 기후변화에 의해 집중호우의 빈도 및 강도가 증가하고 지속적인 유역개발에 따른 토지이용의 증가는 토양침식 및 토사유출로 인한 재해 및 환경문제를 야기한다. 현재 광범위하게 사용되고 있는 토양침식량 산정기법은 대부분 대상유역내의 평균 토양침식량을 산출하는 총량적 개념의 경험식이므로 호우기간동안의 침식 및 퇴적의 시 공간적 변화양상을 모의할 수 없다는 한계를 지니고 있다. 따라서 보다 합리적인 유역규모의 강우-유사-유출 메카니즘 해석을 위해서는 기존의 집중형 모의기법을 대체하고 다양한 기상학적/지형학적 정보를 활용할 수 있는 물리적 기반의 분포형 모형이 요구된다. 본 연구에서는 사면의 지표 및 지표하 흐름을 고려한 유출모의 모듈과 단위수류력 이론을 기반으로 하는 유사유출 모의모듈을 결합한 분포형 강우-유사-유출 모형을 확장개발하고, 용담댐 상류부의 천천유역에 적용하여 모형의 재현성 평가를 수행하였다. 수문곡선의 모의 결과 모형의 재현성은 우수하였으며, 유사량곡선의 경우 첨두부분에서 과소선정되는 경향이 나타났다. 또한, 지표면 유동거리 및 국부경사에 따른 침식 및 퇴적의 공간분포를 분석한 결과, 침식된 토사는 비교적 경사가 완만한 하천주변에 퇴적되었으며, 강우량과 침식 및 퇴적의 공간분포의 분석결과, 강우량의 증가에 따라 침식량이 증가하였으며, Thiessen망 유역별로 침식 및 퇴적 분포는 상이하게 나타났다.

Floods and Flood Warning in New Zealand

  • Doyle, Martin
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2012년도 학술발표회
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    • pp.20-25
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    • 2012
  • New Zealand suffers from regular floods, these being the most common source of insurance claims for damage from natural hazard events in the country. This paper describes the origin and distribution of the largest floods in New Zealand, and describes the systems used to monitor and predict floods. In New Zealand, broad-scale heavy rainfall (and flooding), is the result of warm moist air flowing out from the tropics into the mid-latitudes. There is no monsoon in New Zealand. The terrain has a substantial influence on the distribution of rainfall, with the largest annual totals occurring near the South Island's Southern Alps, the highest mountains in the country. The orographic effect here is extreme, with 3km of elevation gained over a 20km distance from the coast. Across New Zealand, short duration high intensity rainfall from thunderstorms also causes flooding in urban areas and small catchments. Forecasts of severe weather are provided by the New Zealand MetService, a Government owned company. MetService uses global weather models and a number of limited-area weather models to provide warnings and data streams of predicted rainfall to local Councils. Flood monitoring, prediction and warning are carried out by 16 local Councils. All Councils collect their own rainfall and river flow data, and a variety of prediction methods are utilized. These range from experienced staff making intuitive decisions based on previous effects of heavy rain, to hydrological models linked to outputs from MetService weather prediction models. No operational hydrological models are linked to weather radar in New Zealand. Councils provide warnings to Civil Defence Emergency Management, and also directly to farmers and other occupiers of flood prone areas. Warnings are distributed by email, text message and automated voice systems. A nation-wide hydrological model is also operated by NIWA, a Government-owned research institute. It is linked to a single high resolution weather model which runs on a super computer. The NIWA model does not provide public forecasts. The rivers with the greatest flood flows are shown, and these are ranked in terms of peak specific discharge. It can be seen that of the largest floods occur on the West Coast of the South Island, and the greatest flows per unit area are also found in this location.

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A Model to Identify Expeditiously During Storm to Enable Effective Responses to Flood Threat

  • Husain, Mohammad;Ali, Arshad
    • International Journal of Computer Science & Network Security
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    • 제21권5호
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    • pp.23-30
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    • 2021
  • In recent years, hazardous flash flooding has caused deaths and damage to infrastructure in Saudi Arabia. In this paper, our aim is to assess patterns and trends in climate means and extremes affecting flash flood hazards and water resources in Saudi Arabia for the purpose to improve risk assessment for forecast capacity. We would like to examine temperature, precipitation climatology and trend magnitudes at surface stations in Saudi Arabia. Based on the assessment climate patterns maps and trends are accurately used to identify synoptic situations and tele-connections associated with flash flood risk. We also study local and regional changes in hydro-meteorological extremes over recent decades through new applications of statistical methods to weather station data and remote sensing based precipitation products; and develop remote sensing based high-resolution precipitation products that can aid to develop flash flood guidance system for the flood-prone areas. A dataset of extreme events has been developed using the multi-decadal station data, the statistical analysis has been performed to identify tele-connection indices, pressure and sea surface temperature patterns most predictive to heavy rainfall. It has been combined with time trends in extreme value occurrence to improve the potential for predicting and rapidly detecting storms. A methodology and algorithms has been developed for providing a well-calibrated precipitation product that can be used in the early warning systems for elevated risk of floods.

북한강 수계 대규모 탁수사상 발생에 의한 댐 저수지의 탁수 영향 분석 (Analyzing the Effect of an Extreme Turbidity Flow Event on the Dam Reservoirs in North Han River Basin)

  • 박형석;정세웅;정선아
    • 한국물환경학회지
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    • 제33권3호
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    • pp.282-290
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    • 2017
  • A long-term resuspension of small particles, called persistent turbidity, is one of the most important water quality concerns in the dam reservoirs system located in North Han River. Persistent turbidity may incur aesthetic nuisance and harmful effect on the ecosystem health, in addition to elevated water treatment costs for the drinking water supply to the Seoul metropolitan area. These sufferings have been more intensified as the strength and frequency of rainfall events increase by climate change in the basin. This study was to analyze the effect of an extreme turbidity flow event that occurred in 2006 on the serial reservoirs system (Soyang-Uiam-Cheongpyung-Paldang) in North Han River. The CE-QUAL-W2 model was set up and calibrated for the river and reservoirs system using the field data obtained in 2006 and 2007. The results showed that Soyang Reservoir released turbid water, which was classified as the TSS concentration is greater than 25 mg/L, for 334 days with peak TSS of 264.1 mg/L after the extreme flood event (592.7 mm) occurred between July 10 and 18 of 2006. The turbid water departed from Soyang Reservoir reached at the most downstream Paldang Reservoir after about 20 days and sustained for 41 days, which was validated with water treatment plant data. Since the released water from Soyang Reservoir had low water temperature and high TSS, an underflow formed in the downstream reservoirs and vertically mixed at Paldang Reservoir due to dilution by the sufficient inflow from South Han River.

Spatiotemporal distribution of downscaled hourly precipitation for RCP scenarios over South Korea and its hydrological responses

  • Lee, Taesam;Park, Taewoong;Park, Jaenyoung
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2015년도 학술발표회
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    • pp.247-247
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    • 2015
  • Global Climate Model (GCM) is too coarse to apply at a basin scale. The spatial downcsaling is needed to used to permit the assessment of the hydrological changes of a basin. Furthermore, temporal downscaling is required to obtain hourly precipitation to analyze a small or medium basin because only few or several hours are used to determine the peak flows after it rains. In the current study, the spariotemporal distribution of downscaled hourly precipitation for RCP4.5 and RCP8.5 scenarios over South Korea is presented as well as its implications over hydrologica responses. Mean hourly precipitation significantly increases over the southern part of South Korea, especially during the morning time, and its increase becomes lower at later times of day in the RCP8.5 scenario. However, this increase cannot be propagated to the mainland due to the mountainous areas in the southern part of the country. Furthermore, the hydrological responses employing a distributed rainfall-runoff model show that there is a significant increase in the peak flow for the RCP8.5 scenario with a slight decrease for the RCP4.5 scenario. The current study concludes that the employed temporal downscaling method is suitable for obtaining the hourly precipitation data from daily GCM scenarios. In addition, the rainfall runoff simulation through the downscaled hourly precipitation is useful for investigating variations in the hydrological responses as related to future scenarios.

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Synthetic storm sewer network for complex drainage system as used for urban flood simulation

  • Dasallas, Lea;An, Hyunuk;Lee, Seungsoo
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2021년도 학술발표회
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    • pp.142-142
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    • 2021
  • An arbitrary representation of an urban drainage sewer system was devised using a geographic information system (GIS) tool in order to calculate the surface and subsurface flow interaction for simulating urban flood. The proposed methodology is a mean to supplement the unavailability of systematized drainage system using high-resolution digital elevation(DEM) data in under-developed countries. A modified DEM was also developed to represent the flood propagation through buildings and road system from digital surface models (DSM) and barely visible streams in digital terrain models (DTM). The manhole, sewer pipe and storm drain parameters are obtained through field validation and followed the guidelines from the Plumbing law of the Philippines. The flow discharge from surface to the devised sewer pipes through the storm drains are calculated. The resulting flood simulation using the modified DEM was validated using the observed flood inundation during a rainfall event. The proposed methodology for constructing a hypothetical drainage system allows parameter adjustments such as size, elevation, location, slope, etc. which permits the flood depth prediction for variable factors the Plumbing law. The research can therefore be employed to simulate urban flood forecasts that can be utilized from traffic advisories to early warning procedures during extreme rainfall events.

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Expert Team on Climate Change Detection and Indices (ETCCDI)를 이용한 강원지역 극한기상특성의 변화 분석 (Analysis of Extreme Weather Characteristics Change in the Gangwon Province Using ETCCDI Indices)

  • 강건국;이동섭;황석환;김병식
    • 한국수자원학회논문집
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    • 제47권12호
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    • pp.1107-1119
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    • 2014
  • 전 세계적으로 기후변화로 인한 이상기후에 대한 관심이 높아지고 있으며 이로 인한 부정적 영향에 대한 우려가 증가되고 있다. 우리나라도 기후변화로 연평균 강수량이 1910년대 1,155mm에서 2000년대 1,375mm로 약 19% 증가했으며 21세기말에는 약 17%가 증가할 것으로 전망하고 있다. 특히, 최근 10년간 1일 100mm 이상 집중호우의 발생빈도는 총 385회로, 70~80년대 222회에 비해 1.7배나 증가하는 등 기후변화로 인해 극한기상의 변화가 심해지는 것으로 보고되고 있다. 강원지방의 경우 대부분 지역이 산악으로 구성되어 있어 다른 어느 지역보다 기후변화로 인한 영향을 크게 받을 것으로 예상되며, 높은 태백산맥으로 인해 영서 및 영동으로 구분되어 산악 및 해양성기후를 모두 가지고 있는 특이한 지역이라고 할 수 있다. 이에 본 논문에서는 강원지방의 기후가 최근 어떤 특성변화가 있는지 ETCCDI (Expert Team on Climate Change Detection and Indices) 지수를 이용하여 정량화하고자 한다.