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Flood disaster industry-linked economic impact and risk assessment: a case study of Yangtze River Economic Zone

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Han Sun at China University of Geosciences
Han Sun
Zhiyun Zha
Zhiyun Zha
Zhiyun Zha
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Chao Huang
Chao Huang
Chao Huang
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Xiaohui Yang
Xiaohui Yang
Xiaohui Yang
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Abstract and Figures

China is an extremely sensitive nation severely impacted by global climate change, with frequent floods in the Yangtze River Economic Zone causing severe socioeconomic losses and ecological and environmental issues. To investigate the potential industry-related economic losses and comprehensive hazards of flooding in the Yangtze River Economic Zone, as well as to investigate the comprehensive improvement of disaster resilience, this paper first uses an input–output model to account for the indirect economic losses caused by floods to various industries in different years. On this basis, a comprehensive flood risk assessment system was constructed from five aspects, including meteorological and geographical conditions, exposure, vulnerability, emergency response and recovery capacity, and disaster losses; the entropy weight method and TOPSIS method were used to rank the flood risks, while ArcGIS was used for visualization and analysis. The results indicate that the most severe economic losses affected by floods in 2020, 2017 and 2012 are in Anhui, Hunan and Sichuan, respectively; manufacturing, agriculture, forestry, animal husbandry and fishery, transportation and storage, and electricity, heat and production and supply are all highly sensitive sectors that are severely impacted by flooding. The risk assessment indicates that the integrated flood risk in the upstream areas of Yunnan and Chongqing has been low and belongs to the low or medium–low risk area, whereas the integrated flood risk in the downstream areas is high, with Shanghai belonging to the high risk area in each of the three years. Lastly, effective regional flood risk management countermeasures are proposed.
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Vol.:(0123456789)
Environment, Development and Sustainability
https://doi.org/10.1007/s10668-024-04556-y
1 3
Flood disaster industry‑linked economic impact andrisk
assessment: acase study ofYangtze River Economic Zone
HanSun1,2· ZhiyunZha1· ChaoHuang1· XiaohuiYang1
Received: 13 June 2023 / Accepted: 21 January 2024
© The Author(s), under exclusive licence to Springer Nature B.V. 2024
Abstract
China is an extremely sensitive nation severely impacted by global climate change, with
frequent floods in the Yangtze River Economic Zone causing severe socioeconomic losses
and ecological and environmental issues. To investigate the potential industry-related
economic losses and comprehensive hazards of flooding in the Yangtze River Economic
Zone, as well as to investigate the comprehensive improvement of disaster resilience, this
paper first uses an input–output model to account for the indirect economic losses caused
by floods to various industries in different years. On this basis, a comprehensive flood risk
assessment system was constructed from five aspects, including meteorological and geo-
graphical conditions, exposure, vulnerability, emergency response and recovery capacity,
and disaster losses; the entropy weight method and TOPSIS method were used to rank the
flood risks, while ArcGIS was used for visualization and analysis. The results indicate that
the most severe economic losses affected by floods in 2020, 2017 and 2012 are in Anhui,
Hunan and Sichuan, respectively; manufacturing, agriculture, forestry, animal husbandry
and fishery, transportation and storage, and electricity, heat and production and supply are
all highly sensitive sectors that are severely impacted by flooding. The risk assessment
indicates that the integrated flood risk in the upstream areas of Yunnan and Chongqing has
been low and belongs to the low or medium–low risk area, whereas the integrated flood
risk in the downstream areas is high, with Shanghai belonging to the high risk area in each
of the three years. Lastly, effective regional flood risk management countermeasures are
proposed.
* Zhiyun Zha
czy597088081@cug.edu.cn
Han Sun
sunhan2004@126.com
Chao Huang
xxchao027@163.com
Xiaohui Yang
1202010704@cug.edu.cn
1 Present Address: School ofEconomics andManagement, China University ofGeosciences
(Wuhan), 388 Lumo Road, Hongshan District, Wuhan, Hubei, China
2 Resource andEnvironmental Economics Research Center, China University ofGeosciences
(Wuhan), Wuhan430074, China
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
... This method has a strong mathematical theoretical foundation, making it more objective and scientifically grounded. Many scholars have employed objective weighting methods to assess risk or vulnerability [23][24][25] . In recent years, machine learning models have also been applied to risk assessments in addition to the entropy weight method 26 . ...
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