Zhang, D., Shi, X. , Xu, H., Jing, Q., Pan, X., Liu, T., Wang, H. and Hou, H. (2020) A GIS-based spatial multi-index model for flood risk assessment in the Yangtze River Basin, China. Environmental Impact Assessment Review, 83, 106397. (doi: 10.1016/j.eiar.2020.106397)
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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.
Item Type: | Articles |
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Additional Information: | The research was financially supported by the Chinese National Funding of Social Sciences (No. 18VZL014), Chinese National Major Science and Technology Program for Water Pollution Control and Treatment (No. 2018ZX07301007), and the University of Glasgow CoSS Strategic Research Fund. |
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Shi, Dr John Xiaogang |
Authors: | Zhang, D., Shi, X., Xu, H., Jing, Q., Pan, X., Liu, T., Wang, H., and Hou, H. |
College/School: | College of Social Sciences > School of Social & Environmental Sustainability |
Journal Name: | Environmental Impact Assessment Review |
Publisher: | Elsevier |
ISSN: | 0195-9255 |
ISSN (Online): | 1873-6432 |
Published Online: | 04 April 2020 |
Copyright Holders: | Copyright © 2020 Elsevier Inc. |
First Published: | First published in Environmental Impact Assessment Review 83: 106397 |
Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
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