• Title/Summary/Keyword: flash flood

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The big data method for flash flood warning (돌발홍수 예보를 위한 빅데이터 분석방법)

  • Park, Dain;Yoon, Sanghoo
    • Journal of Digital Convergence
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    • v.15 no.11
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    • pp.245-250
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    • 2017
  • Flash floods is defined as the flooding of intense rainfall over a relatively small area that flows through river and valley rapidly in short time with no advance warning. So that it can cause damage property and casuality. This study is to establish the flash-flood warning system using 38 accident data, reported from the National Disaster Information Center and Land Surface Model(TOPLATS) between 2009 and 2012. Three variables were used in the Land Surface Model: precipitation, soil moisture, and surface runoff. The three variables of 6 hours preceding flash flood were reduced to 3 factors through factor analysis. Decision tree, random forest, Naive Bayes, Support Vector Machine, and logistic regression model are considered as big data methods. The prediction performance was evaluated by comparison of Accuracy, Kappa, TP Rate, FP Rate and F-Measure. The best method was suggested based on reproducibility evaluation at the each points of flash flood occurrence and predicted count versus actual count using 4 years data.

Development of real-time program correcting error in radar polarimetric variables (실시간 레이더 편파변수 오차 보정 프로그램 개발)

  • Yoon, Jungsoo;Hwang, Seok-Hwan;Kang, Narae;Lee, Dong-Ryul;Lee, Keon-Haeng
    • Journal of Korea Water Resources Association
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    • v.54 no.12
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    • pp.1329-1338
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    • 2021
  • Rain radar provides high spatio-temporal radar rainfall that can be used as input data to short-term precipitation forecasting models. Korea Institute of Civil Engineering and Building Technology (KICT) has developed a flash flood forecasting system that is providing flash flood forecasting based on short-term rainfall forecasts estimated by the radar rainfall. Accuracy of the radar rainfall as well as the short-term rainfall forecasts, however, can deteriorate when radar polarimetric variables have error. In this study, we develope real-time program that can correct the error inherent in the radar polarimetric variables. First, effect according to the correction of the error was verified using 363 rainfall events on non real-time. The accuracy (1-NE) of the radar rainfall was approximately 70% and correlation coefficient was higher than 0.8 after correcting the error on non real-time. The accuracy (1-NE) using the real-time program was also approximately 70% after correcting the error.

Development of a Comprehensive Flood Index through Standardizing Distributions of Runoff Characteristics (유출특성 분포함수의 표준화를 통한 종합홍수지수의 개발)

  • Wi, Sung-Wook;Chung, Gun-Hui;Kim, Tae-Woong
    • Journal of Korea Water Resources Association
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    • v.41 no.6
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    • pp.605-617
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    • 2008
  • This study developed a flood index which evaluates runoff characteristics. Runoff characteristics expressed in a hydrograph were reflected in the flood index in the form of characteristic factors such as a rising curve gradient, a peak discharge, a flood response time, and a flood discharge volume prior to peak. This study applied the standardization method to estimate the relative severity of the characteristic factors by transforming the distribution of characteristic factors into the standard normal distribution. The flood index developed in this study is a comprehensive flood index (CFI) which makes up for the weak points of a flash flood index (FFI) in determining relative severities. The CFI was applied to Han River basin and Selma River basin, and was compared with the FFI based on the correlation analysis and the regression analysis. The CFI could comprehensively evaluate flood runoff characteristics because the CFI is not dominated by a specific characteristic factor, and the CFI could explain more efficiently the relationship between rainfall and runoff than the FFI.

A study on the search for the shortest evacuation route due to flash floods in the recreation forest (휴양림 내 돌발홍수로 인한 최단 대피 경로 탐색 연구)

  • Jeon, Sungwoo;Kim, Minkyu;Choi, Dongwoo;Lee, Seojun;Jung, Heokyung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.494-497
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    • 2022
  • Recently, the damage caused by flash floods caused by extreme weather due to global warming is increasing. In order to reduce the damage, this paper conducted a study on the search for the shortest route of an evacuation route due to a flash flood. For this, we implemented a route search system using GIS and shape files including buildings and roads and Dijkstra's algorithm. In this study, the location of users close to the point where the flash flood occurs is identified, and the evacuation route is searched from the starting point to the destination point without passing through the dangerous point. Evacuate out of the test bed, or designate a building in the test bed as an evacuation shelter, and search for a route to the nearest evacuation shelter. Accordingly, it is expected that human damage will be reduced by providing the shortest evacuation route.

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A Development of Real-time Flood Forecasting System for U-City (Ubiquitous 환경의 U-City 홍수예측시스템 개발)

  • Kim, Hyung-Woo
    • 한국정보통신설비학회:학술대회논문집
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    • 2007.08a
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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.

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