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Journal Article

Citation

Li Y, Wu J, Tang R, Wu K, Nie J, Shi P, Li N, Liu L. Sci. Total Environ. 2022; ePub(ePub): ePub.

Copyright

(Copyright © 2022, Elsevier Publishing)

DOI

10.1016/j.scitotenv.2022.156476

PMID

35679942

Abstract

Typhoon disasters have caused casualties, property loss, and other negative impacts to social and economic development. Vulnerability is an important component of typhoon risk. However, little is known about the contributions of vulnerability factors and their interaction effects on typhoon-induced losses at a fine scale. Focusing on the vulnerability measures of Typhoon Hato in 2017 and Typhoon Mangkhut in 2018, this study aims to quantify the contribution and interactive effects of physical and socioeconomic factors on vulnerability based on the GeoDetector method and determine the factors that account for most of the change in vulnerability. The results show that from Typhoon Hato in 2017 to Typhoon Mangkhut in 2018, the vulnerability of the economy and houses decrease on average. Rain intensity and wind intensity are the dominant factors of disaster loss for Typhoon Hato and Typhoon Mangkhut, respectively. Vegetation cover and landform explain vulnerability does better than average slope in most instances. For different loss types, the dominant socioeconomic vulnerability factor is different. For both typhoons, emergency transfer has a higher q ranking for the population vulnerability, while the percentage of the GDP made up of primary industry have higher determining powers (q) for economic vulnerability. The dominant interaction effects between two vulnerability factors differ depending on the typhoon and loss type but show a nonlinear enhancement effect in most cases. Moreover, changes in the maximum 4-hour accumulated rainfall account for most of the change in vulnerability between Hato and Mangkhut. Overall, the results can be conducive to understanding the complexity of vulnerability to typhoons and provide a reference for possible indicators for vulnerability assessment models, and determining the reasons for changes in vulnerability can be constructive to the formulation of specific policies for disaster prevention and mitigation.


Language: en

Keywords

Vulnerability; Direct loss; Emergency transfer; Hazard intensity; Typhoon

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