湖北农业科学 ›› 2026, Vol. 65 ›› Issue (8): 170-179.doi: 10.14088/j.cnki.issn0439-8114.2026.08.025

• 信息工程 • 上一篇    下一篇

中国粮食主产区产能演变特征及灾害损失评估模型构建

张晓艳1, 章超斌1, 李永桩2, 殷芳1, 王兆华1, 刘开昌1   

  1. 1.山东省农业科学院农业信息与经济研究所,济南 250100;
    2.内蒙古通辽市科尔沁区林业工作站,内蒙古 通辽 028000
  • 收稿日期:2026-03-23 发布日期:2026-09-02
  • 通讯作者: 王兆华(1971-),山东潍坊人,研究员,主要从事宏观农业及乡村振兴研究,(电子信箱)wangzhaohua1971@163.com。
  • 作者简介:张晓艳(1974-),女,内蒙古通辽人,研究员,博士,主要从事农业监测预警与乡村振兴研究,(电子信箱)239491965@qq.com;刘开昌(1971-),山东济南人,研究员,主要从事玉米栽培生理及耕作制度研究,(电子信箱)liukc1971@126.com
  • 基金资助:
    国家重点研发计划政府间国际科技创新合作专项(2025YFE0111301); 山东省现代耕作制度产业技术体系项目(SDAIT-31-05); 山东省自然科学基金面上项目(ZR2022MC135); 山东省重点研发计划(软科学项目)重大项目(2025RZA0601)

Evolution characteristics of production capacity and construction of a disaster loss assessment model in China's major grain-producing areas

ZHANG Xiao-yan1, ZHANG Chao-bin1, LI Yong-zhuang2, YIN Fang1, WANG Zhao-hua1, LIU Kai-chang1   

  1. 1. Institute of Agricultural Information and Economics, Shandong Academy of Agricultural Sciences, Jinan 250100, China;
    2. Horqin District Forestry Workstation, Tongliao City, Inner Mongolia, Tongliao 028000, Inner Mongolia, China
  • Received:2026-03-23 Online:2026-09-02

摘要: 为了系统揭示中国粮食主产区产能演变规律及气象灾害对粮食生产的影响,并为区域粮食产量预测及防灾减灾策略制定提供科学依据,基于1949—2023年中国13个粮食主产区的粮食生产与农业灾情长序列统计数据,采用主成分分析(PCA)辨识主导灾害类型,利用受灾率和成灾率构建粮食气象产量响应模型,并计算相应年份的模拟产量,将其与实际产量进行对比。结果表明,2023年主产区粮食播种面积和产量较基准年(1949年)分别增长13.27%和5.98倍,种植结构向三大主粮集中,生产重心呈北增南减的特征。水灾和旱灾是主导致灾因子,且北方地区的灾害脆弱度整体高于南方地区。13个主产区的模拟产量与实际产量均呈良好线性关系,决定系数(R2)为0.835 6~0.976 4。综上,中国13个主产区粮食产量稳步提升,但水旱灾害威胁依然严峻,北方地区需重点提升防灾减灾能力;构建的评估模型对粮食产量具有良好预测精度。

关键词: 粮食主产区, 产能, 灾害损失, 评估模型, 中国

Abstract: To systematically reveal the evolution law of production capacity in China's major grain-producing areas and the impact of meteorological disasters on grain production, and to provide a scientific basis for regional grain yield prediction and disaster prevention and mitigation strategy formulation, based on the long-term statistical data of grain production and agricultural disasters in 13 major grain-producing areas of China from 1949 to 2023, principal component analysis (PCA) was used to identify the dominant disaster types, and the disaster-affected rate and disaster-damaged rate were used to construct a grain meteorological yield response model, and the simulated yield for the corresponding years was calculated and compared with the actual yield. The results showed that in 2023, the sown area and grain yield in the major grain-producing areas increased by 13.27% and 5.98 times, respectively, compared with the base year (1949), the planting structure concentrated on the three major staple grains, and the production center exhibited a characteristic of increase in the north and decrease in the south. Flood and drought were the dominant disaster-causing factors, and the disaster vulnerability in the northern regions was generally higher than that in the southern regions. The simulated yield and actual yield in the 13 major grain-producing areas showed a good linear relationship, with coefficients of determination (R2) ranging from 0.835 6 to 0.976 4. In conclusion, the grain yield in the 13 major grain-producing areas of China steadily increased, but the threat of flood and drought disasters remained severe, the northern regions needed to focus on improving disaster prevention and mitigation capabilities, and the constructed assessment model had good prediction accuracy for grain yield.

Key words: major grain-producing areas, production capacity, disaster loss, assessment model, China

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