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Abstract
Nature-based solutions (NbS), including China's Sponge City Program (SCP), can address the challenges urban communities face due to surface runoff and flooding. The current capacity of SCP facilities in urban environments falls short of meeting the demands placed on communities by climate change. Bioswales are a form of SCP facility that plays an important role in reducing surface runoff by promoting infiltration. This study assesses the potential of SCP facilities to reduce runoff in urban communities under climate change using the storm water management model. The study site in Ningbo, China, was used to evaluate the potential role of bioswales in reducing runoff risks from climate change. We found that bioswales were most effective in scenarios when rainfall peaks occurred early and were less effective in right-skewed rainfall events. The overall performance of SCP facilities was similar across all climate scenarios. To maintain the current protection level of SCP facilities, bioswales would need to cover at least 4% of the catchment area. These findings from Ningbo provide a useful method for assessing NbS in other regions and indicative values for the increase in the bioswale coverage needed to adapt to climate change.
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Details
1 University of Nottingham Ningbo China, School of Geographical Sciences, Faculty of Science and Engineering, Ningbo, China (GRID:grid.50971.3a) (ISNI:0000 0000 8947 0594); Chinese Academy of Sciences (CAS), Key Laboratory of Urban Environment and Health, Ningbo Observation and Research Station, Institute of Urban Environment, Xiamen, China (GRID:grid.9227.e) (ISNI:0000000119573309)
2 University of Nottingham, School of Geography, Nottingham, UK (GRID:grid.4563.4) (ISNI:0000 0004 1936 8868)
3 University of Nottingham Ningbo China, Department of Civil Engineering, Faculty of Science and Engineering, Ningbo, China (GRID:grid.50971.3a) (ISNI:0000 0000 8947 0594)
4 Chinese Academy of Sciences (CAS), Key Laboratory of Urban Environment and Health, Ningbo Observation and Research Station, Institute of Urban Environment, Xiamen, China (GRID:grid.9227.e) (ISNI:0000000119573309); CAS Haixi Industrial Technology Innovation Centre in Beilun, Zhejiang Key Laboratory of Urban Environmental Processes and Pollution Control, Ningbo, China (GRID:grid.9227.e)
5 Chinese Academy of Sciences (CAS), Key Laboratory of Urban Environment and Health, Ningbo Observation and Research Station, Institute of Urban Environment, Xiamen, China (GRID:grid.9227.e) (ISNI:0000000119573309)
6 University of Nottingham Ningbo China, School of Geographical Sciences, Faculty of Science and Engineering, Ningbo, China (GRID:grid.50971.3a) (ISNI:0000 0000 8947 0594); University of Leeds, Water@Leeds Research Institute, Leeds, UK (GRID:grid.9909.9) (ISNI:0000 0004 1936 8403)