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Assessing impacts of global natural disasters on agricultural value chains and adaptation strategies

  • Qianzi Wang
  • , Qi Zhou
  • , Shen Qu*
  • *Corresponding author for this work
  • Beijing Institute of Technology
  • Beijing Laboratory for System Engineering of Carbon Neutrality

Research output: Contribution to journalArticlepeer-review

Abstract

Natural disasters are intensifying under climate change, posing significant threats to globally interconnected agricultural supply chains. However, the cascading impacts of multi hazard events and the performance of adaptation portfolios remain poorly quantified. This study develops a high-resolution agent-based network model that embeds 419 disaster events across 9 hazard categories into a global supply chain framework. Model simulations indicate that direct agricultural losses amounted to 8349 M.USD, while net indirect losses contributed an additional 3314 M.USD, accounting for 28.4% of total losses and exhibiting a delayed temporal pattern. Furthermore, trade-network diagnostics suggest a feed-livestock cascade pathway, wherein upstream crop and feed disruptions propagate through rigid market linkages and jointly accounted for 64.7% of gross positive indirect agricultural losses. Single disaster simulations show that drought generated the largest total loss and the largest absolute adaptation benefits, indicating that adaptation efficacy varies across hazard types. Scenario evaluations reveal that engineering measures yield the most substantial aggregate benefits, whereas combined portfolios provided limited incremental benefits once the strongest individual measure was already included. These findings highlight the heterogeneous propagation of disaster risks and the need for targeted adaptation portfolios across regions, sectors, and hazard types.

Original languageEnglish
Article number108652
JournalEnvironmental Impact Assessment Review
Volume122
DOIs
Publication statusPublished - Jan 2027
Externally publishedYes

Keywords

  • Adaptation measures
  • Agent-based model
  • Natural disasters
  • Supply chain network cascading losses

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