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• W4320888913 endingPage "117495" @default.
• W4320888913 startingPage "117495" @default.
• W4320888913 abstract "Climate change is contributing to an increasing frequency and intensity of floods in Korea. This study predicts areas with a high probability of flooding in coastal areas of South Korea owing to future climate change, which is likely to cause extreme rainfall and sea-level rise, using a spatiotemporal downscaled future climate change scenario with random forest, artificial neural network, and k-nearest neighbor techniques. In addition, the change in coastal flooding risk probability according to the application of different adaptation strategies (green spaces and seawalls) was identified. The results showed a clear difference in the risk probability distribution in the absence and presence of either adaptation strategy. Their effectiveness in moderating future flooding risks is subject to change owing to strategy type, geographic region, and urbanization intensity and the results show that green spaces are slightly more effective than seawalls when forecasting for 2050. This demonstrates the importance of a nature-based strategy. Moreover, this study highlights the need to prepare adaptation measures according to regional characteristics to mitigate the impact of climate change. Korea is surrounded by seas on three sides that have independent geophysical and climate characteristics. The south coast has a higher risk of coastal flooding than the east and west coasts. In addition, a higher urbanization rate is associated with a higher risk probability. This implies that climate change response strategies for coastal cities are necessary as the population and socioeconomic activities of coastal urban areas are likely to increase in the future." @default.
• W4320888913 created "2023-02-16" @default.
• W4320888913 creator A5002041720 @default.
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• W4320888913 date "2023-05-01" @default.
• W4320888913 modified "2023-09-24" @default.
• W4320888913 title "Adaptation strategies for future coastal flooding: Performance evaluation of green and grey infrastructure in South Korea" @default.
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• W4320888913 doi "https://doi.org/10.1016/j.jenvman.2023.117495" @default.
• W4320888913 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36801687" @default.
• W4320888913 hasPublicationYear "2023" @default.
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