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Development for rainfall classification based on local flood vulnerability using entropy weight in Seoul metropolitan area
  • Lee, Seonmi ;
  • Choi, Youngje ;
  • Lee, Eunkyung ;
  • Ji, Jungwon ;
  • Yi, Jaeeung
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Publication Year
2022-04-01
Publisher
Korea Water Resources Association
Citation
Journal of Korea Water Resources Association, Vol.55, pp.267-278
Keyword
Entropy methodFlood vulnerabilityRainfall classificationUrban flood
All Science Classification Codes (ASJC)
Civil and Structural EngineeringEnvironmental Science (miscellaneous)Ecological Modeling
Abstract
Recently Flood damage volume has increased as heavy rain has frequently occurred. Especially urban areas are a vulnerability to flooding damage because of densely concentrated population and property. A local government is preparing to mitigate flood damage through the heavy rain warning issued by Korea Meteorological Administration. This warning classification is identical for a national scale. However, Seoul has 25 administrative districts with different regional characteristics such as climate, topography, disaster prevention state, and flood damage severity. This study considered the regional characteristics of 25 administrative districts to analyze the flood vulnerability using entropy weight and Euclidean distance. The rainfall classification was derived based on probability rainfall and flood damage rainfall that occurred in the past. The result shows the step 2 and step 4 of rainfall classification was not significantly different from the heavy rain classification of the Korea Meteorological Administration. The flood vulnerability is high with high climate exposure and low adaptability to climate change, and the rainfall classification is low in the northern region of Seoul. It is possible to preemptively respond to floods in the northern region of Seoul based on relatively low rainfall classification. In the future, we plan to review the applicability of rainfall forecast data using the rainfall classification of results from this study. These results will contribute to research for preemptive flood response measures.
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/33411
DOI
https://doi.org/10.3741/jkwra.2022.55.4.267
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Article
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