A GIS-based spatial multi-index model for flood risk assessment in the Yangtze River Basin,China |
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| Affiliation: | 1. Department of Land Management, School of Public Affairs, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China;2. School of Politics and Public Administration, Soochow University, 199 Ren''ai Road, SIP, Suzhou 215123, China;3. Collaborative Innovation Center for New-type Urbanization and Social Governance of Jiangsu Province, 188 Ren''ai Road, SIP, Suzhou 215123, China;1. Department of Economics, University Ca'' Foscari of Venice, Venice, Italy;2. Venice Centre for Climate Studies (VICCS), Venice, Italy;3. DFD German Aerospace Center (DFD-DLR), Wessling, Germany;4. International Research Institute for Climate and Society (IRI), Columbia University, New York, USA;1. State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean, and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;2. Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration (CISSE), Shanghai Jiao Tong University, Shanghai 200240, China;3. Department of Civil and Environmental Engineering, Lehigh University, Bethlehem, PA 18015, USA;4. Department of Civil and Construction Engineering, Swinburne University of Technology, Hawthorn, Victoria 3122, Australia |
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| Abstract: | This paper developed a GIS-based spatial multi-index model for large basin-scale flood risk assessment. In terms of the risk definition proposed by the IPCC, the flood risk in the Yangtze River Basin (YRB) was classified into indexes of hazard, vulnerability, and exposure. The model systematically accounts for various flood risk indicators related to the economic, social and ecological environment of the YRB. Using the robust data space analysis and processing capabilities of ArcGIS, these flood risk indicators were superimposed and analyzed to generate an integrated flood risk spatial distribution map for the YRB. The modeling results were verified reasonably well using observation data from the YRB floods in 1998, 2008, and 2016. We found that 24.90% of the study area was at very high and high risk in 1998, and the risk in these areas decreased to 15.95% and 17.61% in 2008 and 2016, respectively. We believe that the GIS-based spatial multi-index model can be applied to other areas where basin-scale flood risk assessment is desired and contribute to further scientific research on flood forecasting and mitigation. |
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