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DOI10.1007/s13280-024-02005-8
Nature-based solutions potential for flood risk reduction under extreme rainfall events
Manes, Stella; Vale, Mariana M.; Pires, Aliny P. F.
发表日期2024
ISSN0044-7447
EISSN1654-7209
英文摘要Climate change will substantially increase extreme rainfall events, especially in the Tropics, enhancing flood risks. Such imminent risks require climate adaptation strategies to endure extreme rainfall and increase drainage systems. Here, we evaluate the potential of nature-based solutions by using an ecosystem service modeling approach, evaluating the impact of extreme rainfall events on flood risks in a large urban area and with a real-world land recovery plan. We evaluate the cost-effectiveness of four different land recovery scenarios and associated co-benefits, based on a gradient increase in area recovered and cost of implementation. Although the scenarios reveal increasing flood risk reduction and co-benefits along with greater proportion of land recovery, the most cost-effective scenario was the one with an intermediate land recovery where 30% of the study area would be reforested. We emphasize the striking benefits of nature-based solutions for flood risk reduction in cities, considering landscape scale and stakeholders' needs.
英文关键词Forest restoration; InVEST urban flood risk mitigation model; Land recovery; Natural regeneration; Rio de Janeiro; Urban ecology
语种英语
WOS研究方向Engineering ; Environmental Sciences & Ecology
WOS类目Engineering, Environmental ; Environmental Sciences
WOS记录号WOS:001197378600002
来源期刊AMBIO
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/292795
作者单位Universidade Federal do Rio de Janeiro
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GB/T 7714
Manes, Stella,Vale, Mariana M.,Pires, Aliny P. F.. Nature-based solutions potential for flood risk reduction under extreme rainfall events[J],2024.
APA Manes, Stella,Vale, Mariana M.,&Pires, Aliny P. F..(2024).Nature-based solutions potential for flood risk reduction under extreme rainfall events.AMBIO.
MLA Manes, Stella,et al."Nature-based solutions potential for flood risk reduction under extreme rainfall events".AMBIO (2024).
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