Atmosphere (Jan 2024)

Influencing Mechanism of Tidal Disasters on Locust Breeding Area Evolution in the Eastern Coastal Area of China during the Ming and Qing Dynasties

  • Di Feng,
  • Gang Li,
  • Chenxi Feng,
  • Shuo Wang,
  • Qifan Nie,
  • Xingxing Wang

DOI
https://doi.org/10.3390/atmos15010065
Journal volume & issue
Vol. 15, no. 1
p. 65

Abstract

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Locust plagues and tidal disasters are primary natural hazards in China’s eastern coastal regions, yet their interrelationship remains unclear. This study, drawing on historical documents from the Ming and Qing dynasties (1368–1911 AD), focuses on Zhejiang Province and its Hangzhou Bay coastline, areas typically affected by tidal disasters. Employing advanced quantitative analysis and spatiotemporal models, the research aims to reveal the mechanisms behind tidal disasters and their impact on locust population dynamics. The findings indicate a limited spatiotemporal correlation between locust plagues and tidal or drought disasters but a significant association with flooding. The relationship between locust infestations and floods is notably strong in the unique geographical context of Hangzhou Bay’s northern shore. The ‘hydromarginal’ nature of the north coast creates an ideal habitat for locusts. This study pioneers in identifying flooding as a crucial mediator between tidal disasters and locust plagues, shedding light on the ‘typhoon-tidal-flood-locust’ disaster sequence and offering new insights into understanding and mitigating natural disasters in the region. In this study, we primarily employ a quantitative methodology, utilizing advanced data analysis and sophisticated spatiotemporal modeling to investigate the interplay between locust plagues and tidal disasters. Although some progress has been made in the study of historical natural disasters, systematic studies of the relationship between tidal floods and locust breeding sites along the east coast of China during the Ming and Qing dynasties are still scarce. This study fills this gap by employing advanced GIS and time series analysis techniques, combining traditional historical documentary studies with modern scientific methods and providing a new methodological approach to the analysis of historical disaster patterns.

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