TY - JOUR
T1 - Economic impacts of multiple natural disasters and agricultural adaptation measures on supply chains in China
AU - Wei, Siyi
AU - Zhou, Qi
AU - Luo, Ziqun
AU - She, Yunlei
AU - Wang, Qianzi
AU - Chen, Jiayang
AU - Qu, Shen
AU - Wei, Yiming
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/9/15
Y1 - 2023/9/15
N2 - Natural disasters frequently occur in China, leading to both substantial direct economic losses in sectors and superimposed indirect losses that spread through the interregional supply chain network. The agricultural sector is particularly vulnerable to disaster response, emphasizing the importance of evaluating the indirect effects of different disasters and measuring the effectiveness of agricultural adaptation measures for coping and recovery. Here, we presented a compiled dataset of multiple disasters and employed an agent-based multiregional input-output model to simulate the day-by-day direct and indirect losses caused by floods, storms, droughts, typhoons, and frosts in China's interregional supply chain network. Our findings revealed that the consecutive 200+ disasters in 2016 resulted in direct losses of $71.7 billion and indirect losses of $45.6 billion, equivalent to 0.67% and 0.42% of China's total GDP, respectively. Floods emerged as the most economically devastating disaster, accounting for over 70% of the total supply chain losses. The agricultural sector played a significant role, accounting for 18.0% of the total indirect losses. Remarkably, agricultural adaptation measures demonstrated the potential to reduce disaster losses by up to 20% across diverse scenarios. Our study enhances understanding of the superimposed economic impacts of multiple natural disasters occurring in China in one whole year rather than merely aggregating the individual impacts of each disaster, which provides a new perspective for exploring the indirect economic losses caused by the frequent occurrence of disasters. Our study also provides valuable insights to develop effective disaster adaptation strategies, enhance supply chain resilience, and promote sustainable economic development in vulnerable sectors and regions within the context of complex climate conditions in the future.
AB - Natural disasters frequently occur in China, leading to both substantial direct economic losses in sectors and superimposed indirect losses that spread through the interregional supply chain network. The agricultural sector is particularly vulnerable to disaster response, emphasizing the importance of evaluating the indirect effects of different disasters and measuring the effectiveness of agricultural adaptation measures for coping and recovery. Here, we presented a compiled dataset of multiple disasters and employed an agent-based multiregional input-output model to simulate the day-by-day direct and indirect losses caused by floods, storms, droughts, typhoons, and frosts in China's interregional supply chain network. Our findings revealed that the consecutive 200+ disasters in 2016 resulted in direct losses of $71.7 billion and indirect losses of $45.6 billion, equivalent to 0.67% and 0.42% of China's total GDP, respectively. Floods emerged as the most economically devastating disaster, accounting for over 70% of the total supply chain losses. The agricultural sector played a significant role, accounting for 18.0% of the total indirect losses. Remarkably, agricultural adaptation measures demonstrated the potential to reduce disaster losses by up to 20% across diverse scenarios. Our study enhances understanding of the superimposed economic impacts of multiple natural disasters occurring in China in one whole year rather than merely aggregating the individual impacts of each disaster, which provides a new perspective for exploring the indirect economic losses caused by the frequent occurrence of disasters. Our study also provides valuable insights to develop effective disaster adaptation strategies, enhance supply chain resilience, and promote sustainable economic development in vulnerable sectors and regions within the context of complex climate conditions in the future.
KW - Adaptation measures
KW - Complex networks
KW - Multiple disasters
KW - Supply chains effect
UR - http://www.scopus.com/inward/record.url?scp=85165931325&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2023.138095
DO - 10.1016/j.jclepro.2023.138095
M3 - Article
AN - SCOPUS:85165931325
SN - 0959-6526
VL - 418
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
M1 - 138095
ER -