• Title/Summary/Keyword: Flood Management

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Application of AHP in GIS-based Decision Analysis - with emphasis in Flood Hazard management (GIS 기반 의사결정 분석에 AHP의 적용 - 홍수재해관리 중심으로)

  • 김수정;염재홍;이동천
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2004.11a
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    • pp.423-428
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    • 2004
  • Flooding is one of the main causes of loss of lives and properties among various natural disasters in Korea. Flood risk maps are currently being produced in Korea but the progress is slow considering the necessity to map at nationwide scale. In this study, GIS-based multi-criteria decision making process which is normally used for resource management and site analysis was applied to locate flood vulnerable areas. Past records of flooding maps were analysed to extract topographic characteristics of flooded areas. The extracted characteristics were then set as criteria for flooding analysis using the Fuzzy and Analytic Hierarchy Process(AHP) methodology. Results from this study showed that an improved phased action plan was possible, because the flood vulnerable areas are shown in varying degrees of uncertainty unlike the conventional Boolean type GIS layer superimposition analysis.

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Regional flood frequency analysis of extreme rainfall in Thailand, based on L-moments

  • Thanawan Prahadchai;Piyapatr Busababodhin;Jeong-Soo Park
    • Communications for Statistical Applications and Methods
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    • v.31 no.1
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    • pp.37-53
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    • 2024
  • In this study, flood records from 79 sites across Thailand were analyzed to estimate flood indices using the regional frequency analysis based on the L-moments method. Observation sites were grouped into homogeneous regions using k-means and Ward's clustering techniques. Among various distributions evaluated, the generalized extreme value distribution emerged as the most appropriate for certain regions. Regional growth curves were subsequently established for each delineated region. Furthermore, 20- and 100-year return values were derived to illustrate the recurrence intervals of maximum rainfall across Thailand. The predicted return values tend to increase at each site, which is associated with growth curves that could describe an increasing long-term predictive pattern. The findings of this study hold significant implications for water management strategies and the design of flood mitigation structures in the country.

Improvement and evaluation of flood control safety utilizing a flood risk map - Yeong-Seomjin River Basin - (홍수위험지도를 활용한 치수안전도 방법 개선 및 평가 - 영·섬진강 유역중심으로 -)

  • Eo, Gyu;Lee, Sung Hyun;Lim In Gyu;Lee, Gyu Won;Kim, Ji Sung
    • Journal of Korea Water Resources Association
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    • v.57 no.1
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    • pp.21-33
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    • 2024
  • Recently, the patterns of climate change-induced disasters have become more diverse and extensive. To develop an effective flood control plan, Korea has incorporated the concept of Potential Flood Damage (PFD) into the Long-Term Comprehensive Water Resources Plan to assess flood risk. However, concerns regarding the PFD have prompted numerous studies. Previous research primarily focused on modifying and augmenting the PFD index or introducing new indices. This study aims to enhance the existing flood control safety evaluation method by utilizing a flood risk map that incorporates risk indices, specifically focusing on the Yeong-Seomjin river basin. The study introduces three main evaluation approaches: risk and potential analysis, PFD and flood management level analysis, and flood control safety evaluation. The proposed improved evaluation method is expected to be instrumental in evaluating various flood control safety measures and formulating flood control plans.

Machine Learning for Flood Prediction in Indonesia: Providing Online Access for Disaster Management Control

  • Reta L. Puspasari;Daeung Yoon;Hyun Kim;Kyoung-Woong Kim
    • Economic and Environmental Geology
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    • v.56 no.1
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    • pp.65-73
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    • 2023
  • As one of the most vulnerable countries to floods, there should be an increased necessity for accurate and reliable flood forecasting in Indonesia. Therefore, a new prediction model using a machine learning algorithm is proposed to provide daily flood prediction in Indonesia. Data crawling was conducted to obtain daily rainfall, streamflow, land cover, and flood data from 2008 to 2021. The model was built using a Random Forest (RF) algorithm for classification to predict future floods by inputting three days of rainfall rate, forest ratio, and stream flow. The accuracy, specificity, precision, recall, and F1-score on the test dataset using the RF algorithm are approximately 94.93%, 68.24%, 94.34%, 99.97%, and 97.08%, respectively. Moreover, the AUC (Area Under the Curve) of the ROC (Receiver Operating Characteristics) curve results in 71%. The objective of this research is providing a model that predicts flood events accurately in Indonesian regions 3 months prior the day of flood. As a trial, we used the month of June 2022 and the model predicted the flood events accurately. The result of prediction is then published to the website as a warning system as a form of flood mitigation.

Re-evaluation of comprehensive flood management plan for the Yeongsan river basin using Robust Decision Making (로버스트 의사결정을 이용한 영산강유역 종합치수계획 재평가)

  • Kang, Dong-Heon;Kim, Young-Oh;Park, Junehyeong
    • Journal of Korea Water Resources Association
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    • v.50 no.2
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    • pp.99-109
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    • 2017
  • This research adopted a Robust Decision Making framework to re-evaluate four alternative strategies proposed by the Comprehensive Flood Management Plan for the Yeongsan River Basin report (MLTM, 2005) considering uncertainties of future floods under condition of climate change. To reflect the uncertainties, multiple sets of future flood scenarios were used with three uncertainty factors: the change in rainfall intensity based on the RCP climate change scenarios and the changes in the temporal and the spatial flood distributions. With combinations of these factors, 216 plausible flood scenario sets were generated and the performances of the four alternatives under different future states were evaluated. From the results, the most robust alternative among the strategies was identified. Moreover, the key factors which made the tested alternatives poor were discovered through assessment of the uncertainty factors. This information can provide detailed insights to decision makers and can be utilized to overcome alternatives' potential vulnerabilities by modifying the strategy to be more robust.

Development of Decision Support System for Flood Forecasting and Warning in Urban Stream (도시하천의 홍수예·경보를 위한 의사결정지원시스템 개발)

  • Yi, Jaeeung
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.6B
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    • pp.743-750
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    • 2008
  • Due to unusual climate change and global warming, drought and flood happen frequently not only in Korea but also in all over the world. It leads to the serious damages and injuries in urban areas as well as rural areas. Since the concentration time is short and the flood flows increase urgently in urban stream basin, the chances of damages become large once heavy storm occurs. A decision support system for flood forecasting and warning in urban stream is developed as an alternative to alleviate the damages from heavy storm. It consists of model base management system based on ANFIS (Adaptive Neuro Fuzzy Inference System), database management system with real time data building capability and user friendly dialog generation and management system. Applying the system to the Tanceon river basin, it can forecast and warn the stream flows from the heavy storm in real time and alleviate the damages.

Causes and Measures of Flood Damage ('99.8) in Imjin River Basin (임진강 유역 대홍수 ('99,8)의 피해 원인과 대책)

  • 김현영;이용직
    • Proceedings of the Korean Society of Agricultural Engineers Conference
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    • 1999.10c
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    • pp.454-458
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    • 1999
  • This study is to analyze the causes of flood damage in Imjin river basin inAugust , 1999. and to propose the measure to reudce such flood damage. The northern part of Kyonggin Province in the basin was severely damaged by flood due to the heavy rainfall for 4 days from 31 July to 3 August, whioch was recordedas 1,032mm. The heavy rainfall worth recording was one of main cuasese of such damage, but unsuitable river improvement and basin management were also important causes. The flood proptection works such as flood control reservoir and riverlevee were not contructed or sufficient in spite of the unflavorable geographical conditions of Imjin reiver. In case of irrigatiion faciliteis, 43 pumping stations in 3 FIAs were severely damaged due to inundation of the pump and switch boxes. The protection works for pump room should be improved to reduce the damage due to inundation.

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Forecasting Model for Flood Risk at Bo Region (보 지역 홍수 위험도 예측모형 연구)

  • Kwon, S.H.;Oh, H.S.
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.37 no.1
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    • pp.91-95
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    • 2014
  • During a flood season, Bo region could be easily exposed to flood due to increase of ground water level and the water drain difficulty even the water amount of Bo can be managed. GFI for the flood risk is measured by mean depth to water during a dry season and minimum depth to water and tangent degree during a flood season. In this paper, a forecasting model of the target variable, GFI and predictors as differences of height between ground water and Bo water, distances from water resource, and soil characteristics are obtained for the dry season of 2012 and the flood season of 2012 with empirical data of Gangjungbo and Hamanbo. Obtained forecasting model would be used for keep the value of GFI below the maximum allowance for no flooding during flooding seasons with controlling the values of significant predictors.

Analyzing on the cause of downstream submergence damages in rural areas with dam discharge using dam management data

  • Sung-Wook Yun;Chan Yu
    • Korean Journal of Agricultural Science
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    • v.50 no.3
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    • pp.331-347
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    • 2023
  • The downstream submergence damages caused during the flood season in 2020, around the Yongdam-dam and five other sites, were analyzed using related dam management data. Hourly- and daily-data were collected from public national websites and to conduct various analyses, such as autocorrelation, partial-correlation, stationary test, trend test, Granger causality, Rescaled analysis, and principal statistical analysis, to find the cause of the catastrophic damages in 2020. The damage surrounding the Yongdam-dam in 2020 was confirmed to be caused by mis-management of the flood season water level. A similar pattern was found downstream of the Namgang- and Hapcheon-dams, however the damage caused via discharges from these dams in same year is uncertain. Conversely, a different pattern from that of the Yongdam-dam was seen in the areas downstream of Sumjingang- and Daecheongdams, in which the management of the flood season water level appeared appropriate and hence, the damages is assumed to have occurred via the increase in the absolute discharge amount from the dams and flood control capacity leakage of the downstream river. Because of the non-stationarity of the management data, we adapted the wavelet transform analysis to observe the behaviors of the dam management data in detail. Based on the results, an increasing trend in the discharge amount was observed from the dams after the year 2000, which may serve as a warning about similar trends in the future. Therefore, additional and continuous research on downstream safety against dam discharges is necessary.