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Chinese Agricultural Science Bulletin ›› 2025, Vol. 41 ›› Issue (5): 110-118.doi: 10.11924/j.issn.1000-6850.casb2023-0485

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Temporal Characteristics and Impact Differences of Major Agro-meteorological Disasters in Heilongjiang Province Under Climate Change

WANG Qiujing1(), MA Guozhong2, ZHAI Mo1, CHU Zheng1, QU Huihui1, JIANG Lixia1()   

  1. 1 Innovation and Opening laboratory of Regional Eco-Meteorology in Northeast, China Meteorological Administration/Meteorological Academician Workstation of Heilongjiang Province/Heilongjiang Institute of Meteorological Sciences/Wuying National Climatological Observatory, Harbin 150030
    2 Artificial Rainfall Office of Heilongjiang Province, Harbin 150030
  • Received:2023-07-05 Revised:2024-12-18 Online:2025-02-15 Published:2025-02-11

Abstract:

Based on the grain sown area, disaster data, and agro-meteorological disaster data of Heilongjiang Province from 1972 to 2020, this study employed grey correlation analysis and an integrated agro-meteorological disaster loss model to examine the temporal changes in major agro-meteorological disasters over the past five decades. The research also explored the occurrence characteristics and agricultural impacts of different levels of agro-meteorological disasters under the backdrop of climate change. The results indicated that while the total agricultural disaster area exhibited a fluctuating downward trend (P>0.05), the proportion of disaster-affected areas showed a slight upward trend (P>0.05). Among various meteorological disasters, their effects on agriculture were ranked as follows: drought > low temperature c > flood > wind - hail, with drought and low temperature having the most significant impact and causing more severe damage. In Heilongjiang Province, 85% of the years experienced agro-meteorological disasters, with 15% being classified as major or severe disasters. The most severe disaster years were 1976, 2002, and 2003, with comprehensive disaster indices of 5.8173, 5.1791, and 5.3219, respectively. The disaster-affected area was significantly negatively correlated with grain yield (P < 0.05). As the disaster-affected area increased, grain yield decreased. Specifically, for every 100×103 hm2 increase in the disaster-affected area, grain yield per unit area decreased by 26.34 kg. On average, grain yield per unit area decreased by 38.27 kg. However, there was no significant correlation between the affected area and grain yield during mild or minor disaster years. These disaster assessment results align well with historical records of agricultural disasters in Heilongjiang Province and can provide valuable scientific references for mitigating disaster risks and ensuring stable and high grain yields in agricultural production.

Key words: climate change, agro-meteorological disasters, time series analysis, grey correlation degree, disaster loss assessment model, disaster level, Heilongjiang Province