Sustainability 2016, 8(2), 134; doi:10.3390/su8020134
Author
1
Interdisciplinary Program in Landscape Architecture, Seoul National University, Seoul 08826, Korea
2
Department of Landscape Architecture and Rural Systems Engineering, Seoul National University, Seoul 08826, Korea
*
Authors to whom correspondence should be addressed.
Academic Editor: Tan Yigitcanlar
Received: 28 November 2015 / Revised: 27 January 2016 / Accepted: 27 January 2016 / Published: 30 January 2016
(This article belongs to the Section Sustainable Urban and Rural Development)
Abstract
Countermeasures to urban flooding should consider long-term perspectives, because climate change impacts are unpredictable and complex. Urban green spaces have emerged as a potential option to reduce urban flood risks, and their effectiveness has been highlighted in notable urban water management studies. In this study, flooded areas in Seoul, Korea, were divided into four flooded area types by cluster analysis based on topographic and physical characteristics and verified using discriminant analysis. After division by flooded area type, logistic regression analysis was performed to determine how the flooding probability changes with variations in green space area. Type 1 included regions where flooding occurred in a drainage basin that had a flood risk management infrastructure (FRMI). In Type 2, the slope was steep; the TWI (Topographic Wetness Index) was relatively low; and soil drainage was favorable. Type 3 represented the gentlest sloping areas, and these were associated with the highest TWI values. In addition, these areas had the worst soil drainage. Type 4 had moderate slopes, imperfect soil drainage and lower than average TWI values. We found that green spaces exerted a considerable influence on urban flooding probabilities in Seoul, and flooding probabilities could be reduced by over 50% depending on the green space area and the locations where green spaces were introduced. Increasing the area of green spaces was the most effective method of decreasing flooding probability in Type 3 areas. In Type 2 areas, the maximum hourly precipitation affected the flooding probability significantly, and the flooding probability in these areas was high despite the extensive green space area. These findings can contribute towards establishing guidelines for urban spatial planning to respond to urban flooding. View Full-Text
Keywords: urban flood; green space area; flooding probability; flooded area type; logistic regression analysis; cluster analysis
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