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1984—2021年中国高温干旱复合事件特征及标准化经济损失评估

  • 周昱 ,
  • 华丽娟 ,
  • 钟霖浩 ,
  • 杨洋 ,
  • 龚昭荟 ,
  • 周宇欣
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  • 1.中国科学院大学地球与行星科学学院地球系统数值模拟与应用全国重点实验室,北京 101408
    2.应急管理部国家自然灾害防治研究院,北京 100085
E-mail: hualj@ucas.ac.cn

收稿日期: 2024-11-18

  修回日期: 2025-02-27

  网络出版日期: 2025-03-26

基金资助

国家自然科学基金(42275043);国家自然科学基金(42130613);国家自然科学基金(42275183);应急管理部国家自然灾害防治研究院院长基金(J2222816)

Characteristics of compound high temperature and drought events and assessment of standardized economic losses across China from 1984 to 2021

  • Yu ZHOU ,
  • Lijuan HUA ,
  • Linhao ZHONG ,
  • Yang YANG ,
  • Zhaohui GONG ,
  • Yuxin ZHOU
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  • 1.National Key Laboratory of Earth System Numerical Modeling and Application,College of Earth and Planetary Sciences,University of Chinese Academy of Sciences,Beijing 101408,China
    2.National Institute of Natural Hazards,Ministry of Emergency Management of China,Beijing 100085,China

Received date: 2024-11-18

  Revised date: 2025-02-27

  Online published: 2025-03-26

摘要

干旱和高温是常发的灾害性气候事件,可引发不同程度的经济损失。随着社会经济发展,其致灾性与社会经济条件叠加放大了灾害损失。聚焦1984—2021年中国高温干旱复合事件特征及经济损失,基于标准化方法构建干旱强度与灾害损失率关系模型,分析社会经济发展对干旱经济损失的影响,为干旱损失预估和区域防灾策略提供科学依据。结果显示,1984—1990年为干旱高发期,西南、黄淮中部和长江上游为主要干旱中心,经济损失尤为显著。原始损失随时间增加,而剔除人口和经济增长影响后的损失呈下降趋势,且与干旱时空分布高度一致。人口增长和经济发展是中国干旱经济损失显著增加的主要驱动因素,标准化处理能更准确反映干旱事件实际影响。

本文引用格式

周昱 , 华丽娟 , 钟霖浩 , 杨洋 , 龚昭荟 , 周宇欣 . 1984—2021年中国高温干旱复合事件特征及标准化经济损失评估[J]. 中国科学院大学学报, 2026 , 43(4) : 519 -530 . DOI: 10.7523/j.ucas.2025.005

Abstract

As socioeconomic development progresses, the interaction between climatic hazards and socioeconomic conditions amplifies substantial economic losses at varying scales. This study focuses on the characteristics and economic impacts of compound drought-heatwave events in China from 1984 to 2021. Using a standardized methodology, we developed a drought intensity-loss ratio model to isolate the influence of socioeconomic development on drought-related economic losses, providing a scientific basis for loss estimation and regional disaster prevention strategies. The results indicate that 1984 to 1990 was a period of high drought frequency, with the primary drought centers located in Southwest China, the central Huang-Huai region, and the upper Yangtze River, where economic losses were particularly significant. While raw economic losses increased over time, losses adjusted for population and economic growth showed a declining trend, closely aligning with the spatiotemporal distribution of droughts. Population growth and economic development are identified as the main drivers of the significant increase in China’s drought-related economic losses. The standardization approach effectively reveals the actual impacts of drought events. Based on these findings, this study constructed a drought intensity-loss ratio model to better characterize the relationship between natural drought variability and economic losses, offering a robust framework for accurately assessing drought impacts and supporting disaster mitigation strategies.

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