Integrated risk analysis for urban flooding under changing climates

被引:4
|
作者
Yang, Wenyu [1 ,4 ]
Zhao, Ziyong [3 ,4 ]
Pan, Liping [4 ]
Li, Ruifei [5 ]
Wu, Shixue [4 ,6 ]
Hua, Pei [7 ]
Wang, Haijun [1 ]
Schmalz, Britta [3 ]
Krebs, Peter [4 ]
Zhang, Jin [2 ]
机构
[1] Yunnan Univ, Inst Ecol Res & Pollut Control Plateau Lakes, Yunnan Key Lab Ecol Protect & Resource Utilizat Ri, Kunming 650500, Peoples R China
[2] Hohai Univ, Yangtze Inst Conservat & Dev, Natl Key Lab Water Disaster Prevent, Nanjing 210098, Peoples R China
[3] Tech Univ Darmstadt, Chair Engn Hydrol & Water Management, D-64287 Darmstadt, Germany
[4] Tech Univ Dresden, Inst Urban & Ind Water Management, D-01062 Dresden, Germany
[5] Shanghai Univ, Sch Environm & Chem Engn, Shanghai 200444, Peoples R China
[6] UFZ, Helmholtz Ctr Environm Res, D-04318 Leipzig, Germany
[7] South China Normal Univ, Sch Environm, Guangdong Prov Key Lab Chem Pollut & Environm Safe, Guangzhou 510006, Peoples R China
基金
中国国家自然科学基金;
关键词
Urban flooding; Climate change; GCM downscaling; kNN-based analog method; Gumbel distribution method; UNCERTAINTY; IMPACT;
D O I
10.1016/j.rineng.2024.103243
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Urban flooding poses significant threats to human lives and urban development worldwide, while the impact of climate change on urban flooding remains unclear. To systematically analyze the variabilities of hydrological patterns and urban flooding under changing climates, this study coupled the downscaled general circulation model (GCM) projection with hydrologic-hydraulic modeling, with consideration of both the low-greenhouse gas (GHG) emission scenario of SSP1-2.6 and the high-GHG emission scenario of SSP5-8.5. Results demonstrated that the original GCM projection effectively captured the changing trend of rainfall patterns in the given area, with an overestimation of rainfall peaks. The GCM downscaling through the k-nearest neighbors (kNN)-based analog method significantly improved the model accuracy. Scenario analysis indicated that climate change significantly affected the regional hydrology, with the precipitation, surface runoff, and floods increasing by a maximum value of 17.10%, 12.66%, and 63.26%, respectively. The interannual comparison demonstrated that the temporal variability in precipitation and flood intensified with the increase in GHG emissions during 2025-2100, suggesting the uncertainty of long-term climate forecasts. According to flood risk analysis, long-term and short-term floods exhibit varied changing trends across climate scenarios, despite the strong correlations between precipitation and runoff, implying the complexity of flood generation mechanisms. The methods and findings herein provide valuable insights for policymakers and practitioners, to cope with the increasing urban flood risk within the context of evolving environment.
引用
收藏
页数:11
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