地球科学进展 doi: 10.11867/j.issn.1001-8166.2025.082

   

基于寒旱指数(CASI)的中国寒旱农业气候资源分布特征
王莺1,3,张强1*,孙芸4,姚玉璧2,冯新媛1,3   
  1. (1. 中国气象局兰州干旱气象研究所,甘肃省干旱气候变化与减灾重点实验室/中国气象局干旱气候变化与减灾重点开放实验室,甘肃 兰州 730020;2. 兰州资源环境职业技术大学,甘肃 兰州 730021;3.张掖国家气候观象台,甘肃 张掖 734000;4.新疆尉犁县铁干里克气象站,新疆 尉犁 841500)
  • 出版日期:2025-08-31
  • 基金资助:
    国家自然科学基金区域创新发展联合基金项目(U24A20604)资助.

Distribution of Cold-Arid Agroclimatic Resources in China using the Cold-Arid Synergy Index (CASI)

WANG Ying1,3, ZHANG Qiang1*, SUN Yun4, YAO Yubi2, FENG Xinyuan1,3   

  1. (1. Institute of Arid Meteorology, China Meteorological Administration, Key Laboratory of Arid Climatic Change and Reducing Disaster of Gansu Province, Key Open Laboratory of Arid Climate Change and Disaster Reduction of CMA, Lanzhou 730020, China; 2. Lanzhou Resources & Environment Voc-Tech University, Lanzhou 730021,China; 3. Zhangye National Climate Observatory, Gansu, Zhangye 734000, China; 4. Tikanlik Meteorological Station, Yuli County, Xinjiang, Yuli 841500, China)
  • Online:2025-08-31 Published:2025-08-31
  • About author:WANG Ying, research areas include climate change impacts on agricultural ecology. E-mail: wangyn924@163.com
  • Supported by:
    Project supported by the National Natural Science Foundation of China Regional Innovation and Development Joint Fund Program (Grant No. U24A20604).
寒旱区占我国国土面积一半以上,其气候条件限制了农业发展。为充分挖掘农业气候资源优势,探索因地制宜的农业发展路径,亟需科学认识寒旱农业气候资源分布特征与内在特质。基于2000—2020 年高分辨率气象数据,融合热量限制与水分胁迫构建了寒旱指数(CASI),量化了中国寒旱农业气候区空间格局及主导因子。研究发现,寒旱农业气候区占国土面积16.42%,呈东北—西南带状分布。依据CASI 可划分为5 个等级,其中青藏高原属极端胁迫区(一级),河西走廊 与内蒙古高原为典型的农牧交错区(二、三级),而东北平原至陇中一带水热配置最优,是适宜规模化发展的核心潜力区(四、五级)。甘肃和内蒙古等省份的寒旱区面积占比超过40%,过渡地带表现出较高的气候敏感性。空间聚集分析进一步揭示,28.52% 的区域为低值聚集区,是核心优势产区;28.24% 的区域属高值聚集区,构成农业气候高风险带。因子贡献量分析显示,水分胁迫主导的区域占73%,热量限制主导的区域占27%,且寒贡献率随海拔升高显著增加。构建的CASI 指数体系为寒旱农业气候区划提供了新方法论工具,其区划成果可为优化农业空间布局、促进资源精准配置及发展特色产业提供科学依据。
Abstract:Cold-arid regions cover more than half of China's land area, but their climatic and environmental conditions have long constrained agricultural development. To fully exploit the advantages of agroclimatic resources, expand the endowment of climatic resources, and explore localized agricultural development pathways, it is essential to scientifically understand the distribution characteristics of agroclimatic resources and study the intrinsic traits of climatic resources in China’s cold-arid regions. Based on 4 km resolution meteorological data from 2000 to 2020, this study constructed a Cold-Arid Synergy Index (CASI), integrating the dual dimensions of thermal limitation (Thermal Restriction Index, TRI) and moisture stress (Hydrological Stress Index, HSI). This index quantifies the spatial differentiation pattern of cold-arid interactive stress and analyzes the contribution mechanisms of its dominant factors. The research found that cold-arid agroclimatic zones in China account for 16.42% of the national land area, exhibiting a northeast-southwest belt-shaped distribution. CASI-based zoning revealed a five-category gradient: Grade I zones (extreme stress) are primarily located on the Tibetan Plateau; Grades II and III zones (Hexi Corridor, Inner Mongolia Plateau) form the main body of the agropastoral ecotone; Grades IV and V zones (Northeast Plain to Central Gansu) have optimal hydrothermal matching and are suitable for large-scale agricultural production. At the provincial scale, provinces such as Gansu and Inner Mongolia have over 40% of their area classified as cold-arid, with CASI standard deviations reaching 0.10–0.18, highlighting the climatic sensitivity of transition zones. LISA spatial autocorrelation analysis indicated that 28.52% of the cold-arid area comprises Low-Low clusters (LL-type), representing core advantageous production areas; 28.24% belongs to High-High clusters areas (HH-type), forming agroclimatic high-risk islands requiring targeted enhancement of climate resilience. Dominant factor analysis revealed that aridity-dominant zones account for 73%, while cold-dominant zones account for 27%, with the contribution of cold stress significantly increasing with elevation. The CASI index system constructed in this study provides a novel methodology for cold-arid agroclimatic zoning, while the zoning results offer a scientific basis for optimizing agricultural spatial layout, enabling precision resource allocation, and developing specialized industries within cold-arid regions under the context of climate change.

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