• Title/Summary/Keyword: Index flood method

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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.

Analysis of the Applicability of Flood Risk Indices According to Flood Damage Types (홍수피해유형별 홍수 위험 지수 적용성 분석)

  • Kim, Myojeong;Kim, Gwangseob
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.38 no.1
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    • pp.29-39
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    • 2018
  • In this study, the applicabilities of flood risk indices using FVI from IPCC, PSR method from OECD, and DPSIR method from EEA, were analyzed. Normalized values of daily maximum rainfall, hourly maximum rainfall, ten minute maximum rainfall, annual precipitation, total days of heavy rainfall (more than 80mm/day), density of population, density of asset, DEM, road statistics, river maintenance ratio, reservoir capacity, supply ratio of water supply and sewerage, and pumping capacity were constructed from 2000 to 2015 for nationwide 113 watersheds, to estimate flood risk indices. The estimated indices were compared to 4 different types of flood damage such as the number of casualties, damage area, the amount of flood damage, and flood frequency. The relationships between flood indices and different flood damage types demonstrated that the flood index using the PSR method shows better results for the amount of flood damage, the number of casualties and damage area, and the flood index using the DPSIR method shows better results for flood frequency.

Development of Flood Risk Index using causal relationships of Flood Indicators (홍수지표의 인과관계를 이용한 홍수위험지수 개발)

  • Lim, Kwang Suop;Choi, Si Jung;Lee, Dong Ryul;Moon, Jang Won
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.1B
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    • pp.61-70
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    • 2010
  • This research presents a methodology to define and apply appropriate index that can measure the risk of regional flood damage. Pressure-State-Response structure has been used to develop the Flood Risk Index(FRI), which allows for a comparative analysis of flood risk assessment between different sub-basins. FRI is a rational assessment method available to improve disaster preparedness and the prevention of losses. The pressure and state index for flood at 117 sub-basins from the year 1980s until the t 10s showed proportional relations, but state index did not decrease even though response index increased. This shows that pressures for flood damage relatively exceed countermeasure for flood. Thus this means we need to strengthen design criteria for flood countermeasure in the future. The FRI is gradually going down in consequence of continuous flood control projects. Flood risk of Han River and Nakdong River area is relatively lower than that of Geum, Seumjin, and Youngsan River area.

Development of Urban Flood Risk Index for the Cheonggyecheon Watershed Using SWMM (SWMM을 이용한 청계천 유역의 도시홍수 위험도 지수 개발)

  • Yang, Jeong-Seok;Kim, Il-Hwan
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.36 no.3
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    • pp.385-393
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    • 2016
  • In this study, we analyzed th Cheonggyecheon watershed for urban flood risk index. SWMM model configuration based on each watershed data. And it was set as the final index calculated indicators related to the humanities, social and environmental. Each indicator was standardized and weighted using the Delphi method. Finally, select the danger area through urban flood risk index. Determined 12 indices according to the hazard and vulnerability. Vulnerability is selected the index divided by three factors. 21 watersheds were analyzed through urban flood risk index. The top of three areas of index is Jeongneung 1, Majang, Pil-dong, each index is 0.533, 0.494, 0.381. The lowest index is soongin 0.216. Urban flood risk index developed in this study can be applied to other regions in Korea for establishing national water resources management plan.

Development and Application of Vulnerability Analysis Index for River Levee (하천 제방의 취약성 분석 지수 개발 및 적용)

  • Lee, Hoosang;Lee, Jaejoon
    • Journal of Wetlands Research
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    • v.21 no.spc
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    • pp.134-140
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    • 2019
  • In this study, we propose a new method for evaluating the vulnerability to flooding river levee. The purpose of this study is to examine how to apply the factors necessary to calculate the proposed levee flood index. To do this, the safety flood level was analyzed by applying the planned flood level. The levee flood vulnerabilities index was calculated based on seven factors such as freeboard, levee crown section, levee section ratio, safety factor, raised spot length, Seepage line change degree, and critical velocity. The Levee Flood Vulnerability Index(LFVI) of the levee developed in this study was used to levee vulnerability analysis. The results of the analysis were divided into 1 to 7 grades using Levee Flood Vulnerability Index(LFVI).

The Evaluation of TOPLATS Land Surface Model Application for Forecasting Flash Flood in mountainous areas (산지돌발홍수 예측을 위한 TOPLATS 지표해석모델 적용성 평가)

  • Lee, Byong Jua;Choi, Su Mina;Yoon, Seong Sima;Choi, Young Jean
    • Journal of Korea Water Resources Association
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    • v.49 no.1
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    • pp.19-28
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    • 2016
  • The objective of this study is the generation of the gridded flash flood index using the gridded hydrologic components of TOPLATS land surface model and statistic flash flood index model. The accuracy of this method is also examined in this study. The study area is the national capital region of Korea, and 38 flash flood damages had occurred from 2009 to 2012. The spatio-temporal resolutions of land surface model are 1 h and 1 km, respectively. The gridded meteorological data are generated using the inverse distance weight method with automatic weather stations (AWSs) of Korea Meteorological Administration (KMA). The hydrological components (e.g., surface runoff, soil water contents, and water table depth) of cells corresponding to the positions of 38 flood damages reasonably respond to the cell based hourly rainfalls. Under the total rainfall condition, the gridded flash flood index shows 71% to 87% from 4 h to 6 h in the lead time based on the rescue request time and 42% to 52% of accuracy at 0 h which means that the time period of the lead time is in a limited rescue request time. From these results, it is known that the gridded flash flood index using the cell based hydrological components from land surface model and the statistic flash flood index model have a capability to predict flash flood in the mountainous area.

Extraction of water body in before and after images of flood using Mahalanobis distance-based spectral analysis

  • Ye, Chul-Soo
    • Korean Journal of Remote Sensing
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    • v.31 no.4
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    • pp.293-302
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    • 2015
  • Water body extraction is significant for flood disaster monitoring using satellite imagery. Conventional methods have focused on finding an index, which highlights water body and suppresses non-water body such as vegetation or soil area. The Normalized Difference Water Index (NDWI) is typically used to extract water body from satellite images. The drawback of NDWI, however, is that some man-made objects in built-up areas have NDWI values similar to water body. The objective of this paper is to propose a new method that could extract correctly water body with built-up areas in before and after images of flood. We first create a two-element feature vector consisting of NDWI and a Near InfRared band (NIR) and then select a training site on water body area. After computing the mean vector and the covariance matrix of the training site, we classify each pixel into water body based on Mahalanobis distance. We also register before and after images of flood using outlier removal and triangulation-based local transformation. We finally create a change map by combining the before-flooding water body and after-flooding water body. The experimental results show that the overall accuracy and Kappa coefficient of the proposed method were 97.25% and 94.14%, respectively, while those of the NDWI method were 89.5% and 69.6%, respectively.

Development and the Application of Flood Disaster Risk Reduction Index (홍수피해저감지수(FDRRI) 개발 및 시범적용)

  • Moon, Seung-Rok;Yang, Seung-Man;Choi, Seon-Hwa
    • Journal of the Korean Society of Safety
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    • v.29 no.1
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    • pp.64-69
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    • 2014
  • Community-based disaster preparedness approaches are increasingly important elements of vulnerability reduction and disaster strategies. They are associated with a policy trend that values the knowledge and capacities of local people. In this research, we describe the community diagnosis method and develop Flood Disaster Risk Reduction Index(FDRRI) for assessment of flood vulnerability. FDRRI is composed of four indicators such as Flood Exposure Indicator(FEI), Sensitivity Indicator(SI), Risk Reduction Indicator(RRI), and Community Preparedness Indicator(CPI). We anticipate to present the guideline for selection national preparedness projects and uplift community's preparedness capacity.

Uncertainty Assessment of Regional Frequency Analysis for Generalized Logistic Distribution (Generalized Logistic 분포형을 이용한 지역빈도해석의 불확실성 추정)

  • Shin, Hongjoon;Nam, Woosung;Jung, Younghun;Heo, Jun-Haeng
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.6B
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    • pp.723-729
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    • 2008
  • Confidence intervals of growth curves are calculated to assess the uncertainty of index flood method as a regional frequency analysis. The asymptotic variance of quantile estimator for the generalized logistic distribution is introduced to evaluate confidence intervals. In addition, the variances of at-site frequency estimator and regional frequency estimator are used to evaluate an efficiency index. The efficiency indexes for 14 homogeneous regions based on 378 stations show that index flood method estimators are more efficient than at-site frequency estimators. It is shown that the number of sites in a region needs to be limited for regional gain.

Estimation of Flood Quantile in Ungauged Watersheds for Flood Damage Analysis Based on Flood Index of Natural Flow (미계측 유역의 홍수피해분석을 위한 자연유량의 홍수지표 기반 확률홍수량 산정)

  • Chae, Byung Seok;Choi, Si Jung;Ahn, Jae Hyun;Kim, Tae-Woong
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.38 no.1
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    • pp.175-182
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    • 2018
  • In this study, flood quantiles were estimated at ungauged watersheds by adjusting the flood quantiles from the design rainfall - runoff analysis (DRRA) method based on regional frequency analysis. Comparing the flood frequency analysis (FFA) and DRRA, it was found that the flood quantiles estimated by the DRRA method were overestimated by 52%. In addition, a practical method was suggested to make an flood index using natural flows to apply the regional frequency analysis (RFA) to ungauged watersheds. Considering the relationships among DRRA, FFA, and RFA, we derived an adjusting formula that can be applied to estimate flood quantiles at ungauged watersheds. We also employed Leave-One-Out Cross-Validation scheme and skill score to verify the method proposed in this study. As a result, the proposed model increased the accuracy by 23.2% compared to the existing DRRA method.