Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/90899
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dc.contributorChinese Mainland Affairs Office-
dc.creatorTang, J-
dc.creatorLi, Y-
dc.creatorCui, S-
dc.creatorXu, L-
dc.creatorHu, Y-
dc.creatorDing, S-
dc.creatorNitivattananon, V-
dc.date.accessioned2021-09-03T02:34:59Z-
dc.date.available2021-09-03T02:34:59Z-
dc.identifier.issn1470-160X-
dc.identifier.urihttp://hdl.handle.net/10397/90899-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rights© 2020 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).en_US
dc.rightsThe following publication Tang, J., Li, Y., Cui, S., Xu, L., Hu, Y., Ding, S., & Nitivattananon, V. (2021). Analyzing the spatiotemporal dynamics of flood risk and its driving factors in a coastal watershed of southeastern China. Ecological Indicators, 121, 107134 is available at https://doi.org/10.1016/j.ecolind.2020.107134en_US
dc.subjectContribution analysisen_US
dc.subjectFlood risk assessmenten_US
dc.subjectGISen_US
dc.subjectSpatial multi-criteria analysisen_US
dc.subjectSpatiotemporal variationen_US
dc.titleAnalyzing the spatiotemporal dynamics of flood risk and its driving factors in a coastal watershed of southeastern Chinaen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume121-
dc.identifier.doi10.1016/j.ecolind.2020.107134-
dcterms.abstractRapid urbanization and climate change can cause more extensive flood risk, in the absence of urgent and efficient adaptation measures. As the occurrence of floods varies with time and space, comprehensive and dynamical assessment of the spatiotemporal variability of flood risk and understanding of its drivers is vital for flood risk management. In this study, we developed a spatial multi-criteria analysis (SMCA) framework for quantifying the spatiotemporal dynamics of flood risk through a case study in a coastal watershed of southeastern China from 1990 to 2015. A comprehensive framework for flood risk assessment was constructed from the hazard, exposure, sensitivity and adaptive capacity components with 23 indicators. The results showed that the highest risk happened in the stage of 2006–2010, while the lowest risk stage was 2011–2015, with higher flood risk in the downstream areas of Jiulong River watershed (JRW). The contribution of each indicator reflects the difference in temporal, spatial and quantity aspects. The top 5 driving factors for JRW included: peak discharge, maximum daily rainfall, age structure, wetland, and reservoir. The risk perception showed a continuous growing impact on flood risk. However, some indicators only showed obvious contributions in the specified area: for example, the built-up expansion in Zhangzhou city; the increase of dike length and the improvement of dike standard in Xinluo district; and the increase of government financial investment in Zhangping and Liancheng district. This study demonstrates the well-performance of our proposed novel approach for flood risk assessment. Our results and conclusions are also of significance for policymakers to understand and point out the deficiencies in the current actions of flood adaption, and consequently develop more targeted and spatially-specific strategies for flood adaptation, in the context of climate change and rapid urbanization.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationEcological indicators, Feb. 2021, v. 121, 107134-
dcterms.isPartOfEcological indicators-
dcterms.issued2021-02-
dc.identifier.scopus2-s2.0-85096852556-
dc.identifier.eissn1872-7034-
dc.identifier.artn107134-
dc.description.validate202109 bcvc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.pubStatusPublisheden_US
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