中国农业气象 ›› 2026, Vol. 47 ›› Issue (3): 431-442.doi: 10.3969/j.issn.1000-6362.2026.03.010

• 农业气象灾害栏目 • 上一篇    下一篇

新郑大枣高温干旱灾害风险评估

柳晓庆,李艳,李树岩,周佳布   

  1. 1.中国气象局公共气象服务中心,北京 100081;2.河南省气象科学研究所,郑州 450000;3.成都信息工程大学大气科学学院,成都 610103
  • 收稿日期:2025-01-24 出版日期:2026-03-20 发布日期:2026-03-17
  • 作者简介:柳晓庆,E-mail:616275385@qq.com
  • 基金资助:
    中国气象局农业气象保障与应用技术重点开放实验室基金项目(AMF202208)

Risk Assessment of Heat and Drought Disasters of Xinzheng Jujube

LIU Xiao-qing, LI Yan, LI Shu-yan, ZHOU Jia-bu   

  1. 1. Public Meteorological Service Center, China Meteorological Administration, Beijing 100081, China; 2. Henan Provincial Institute of Meteorological Sciences, Zhengzhou 450000; 3. School of Atmospheric Science, Chengdu University of Information Technology, Chengdu 610103
  • Received:2025-01-24 Online:2026-03-20 Published:2026-03-17

摘要: 河南省新郑市作为黄淮流域重要的大枣生产基地,6−8月高温干旱复合胁迫已成为制约枣产业可持续发展的农业气象灾害之一。本研究基于新郑市1981−2022年6−8月地面气象观测资料和2010−2022年6−8月高分辨率格点实况数据集,采用主成分分析、有序样本聚类方法构建大枣高温干旱指数,运用信息扩散理论建立高温干旱灾害风险评估模型,开展新郑大枣主产区高温干旱灾害的精细化定量评估。结果表明:1981−2022年新郑大枣高温干旱指数呈上升趋势,1996−2007年和2012−2022年两个时段经Mann−Kendall检验上升趋势显著P<0.05)。新郑大枣高温干旱指数EOF分解后,第一模态占总方差贡献的79.3%,空间向量场呈显著的空间一致性特征,表明新郑市高温干旱指数在新郑市全域空间上呈一致升高或降低趋势。新郑市6−8月发生轻度、中度和重度高温干旱风险概率分别为5%46%34%,新郑市北部龙湖镇和孟庄镇北部以及新郑市南部的观音寺镇和梨河镇为重度高温干旱灾害风险概率发生的高值区,新郑市中部以辛店镇、城关乡、新华、新烟、和庄镇、龙王乡和薛店镇等发生中度高温干旱灾害风险概率较大,轻度高温干旱灾害风险概率集中发生于新郑市南部的辛店镇。新郑大枣主要种植区高风险区主要分布在孟庄镇北部,中风险区分布于孟庄镇南部、薛店镇西北部、龙王乡东北部、和庄镇南部。

关键词: 新郑大枣, 高温干旱, 有序样本聚类, 经验正交分解(EOF), 信息扩散

Abstract:

The combination of heat and drought stress during the June-August period has become one of the agrometeorological disasters that are constraining the sustainable development of the jujube industry in Xinzheng city of Henan province, an important jujube production base in the HuangHuai river basin. Based on the ground meteorological observation data from June to August in Xinzheng city from 1981 to 2022 and the high−resolution gridded real−time datasets from June to August in 2010 to 2022, this study used principal component analysis and ordered sample clustering methods to construct the jujube heat and drought index. A heat and drought disaster risk assessment model was developed by applying information diffusion theory to conduct a refined quantitative assessment of heat and drought disasters in the main jujube production area of Xinzheng. The results showed that the heat and drought index of Xinzheng jujube showed an upward trend from 1981 to 2022. The Mann−Kendall trend test showed a significant upward trend in the two periods from 1996 to 2007 and 2012 to 2022 (P<0.05). After the Empirical orthogonal function (EOF) decomposition of the Xinzheng jujube heat and drought index, the first mode accounted for 79.3% of the total variance contribution. Its spatial vector field displayed significant spatial consistency, indicating a consistent upward or downward trend of the heat and drought index across the entire area of Xinzheng city. The probability of mild, moderate and severe heat and drought risk occurring in Xinzheng city during June−August was 5%, 46% and 34%, respectively. Longhu town and the northern part of Mengzhuang town in the north of Xinzheng city, as well as Guanyinsi town and Lihe town in the south of Xinzheng city were high−probability areas for severe heat and drought risk. The probability of moderate heat and drought disaster risk was relatively high in Xindian town, Chengguan, Xinhua, Xinyan, Hezhuang town, Longwang town and Xuedian town in the central part of Xinzheng city, while the probability of mild heat and drought disaster risk was concentrated in Xindian town in the southern part of Xinzheng city. The high−risk areas in the main jujube planting areas of Xinzheng were mainly distributed in the northern part of Mengzhuang town, while the medium−risk areas were distributed in the southern part of Mengzhuang town, the northwest of Xuedian town, the northeast of Longwang town and the southern part of Hezhuang town. 

Key words: Xinzheng jujube, Heat and drought, Ordinal sample clustering, Empirical orthogonal function (EOF), Information diffusion