干旱气象 ›› 2025, Vol. 43 ›› Issue (2): 163-175.

• 论文 • 上一篇    

1963—2022年西北地区中西部干旱演变特征及植被响应研究

苏天鑫1 ,孟宪红2,3 ,杨显玉1 ,安颖颖2,3 ,赵采玲4   

  1. 1. 成都信息工程大学大气科学学院/高原大气与环境四川省重点实验室,四川 成都 610225; 2. 中国科学院西北生态环境资源研究院/冰冻圈科学与冻土工程重点实验室,甘肃 兰州 730000; 3. 甘肃省黄河源区气候与环境野外科学观测研究站,甘肃 兰州 730000; 4. 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实验室,甘肃 兰州 730020
  • 出版日期:2025-04-30 发布日期:2025-05-13
  • 作者简介:苏天鑫(2001—),男,湖北襄阳人,硕士研究生,主要从事区域气候变化及其影响研究。E-mail:sutianxin2001@163. com。

Drought evolution characteristics and vegetation response in the midwestern region of northwest China from 1963 to 2022

SU Tianxin1, MENG Xianhong2,3, YANG Xianyu1, AN Yingying2,3, ZHAO Cailing4
  

  1. 1. College of Atmospheric Sciences, Chengdu University of Information Technology/ Sichuan Key Laboratory of
    Plateau Atmosphere and Environment, Chengdu 610225, China;
    2. Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences / Key Laboratory of
    Cryosphere Science and Frozen Soil Engineering, Lanzhou 730000, China;
    3. Field Scientific Observatory for Climate and Environment in the Yellow River Source Region, Lanzhou 730000, China;
    4. Key Laboratory for Arid Climate Change and Disaster Reduction of Gansu Province, Lanzhou Institute of Arid Meteorology/ Key Laboratory for Arid Climate Change and Disaster Reduction of the China Meteorological Administration , Lanzhou 730020, China
  • Online:2025-04-30 Published:2025-05-13

摘要:

系统研究干旱演变特征及植被对干旱的响应,对防旱减灾、水资源管理和策略制定具有重要意义。本研究以新疆、青海和甘肃三省为研究区域,基于1963—2022年CN05.1数据计算标准化降水蒸散指数(Standardized Precipitation Evapotranspiration Index,PEI),结合2003—2022年植被归一化指数NDVI,应用游程理论、Theil-Sen趋势检验、Mann-Kendall显著性检验、回归分析等方法,分析西北地区中西部不同时间尺度的干旱演变特征,并探讨干旱对植被的影响。结果表明,近60 a来,研究区在年代际和年际尺度上呈现干旱化趋势,1998年为干旱突变年;新疆东部和南部、柴达木盆地及河西走廊的干旱化趋势更为明显,干旱程度以轻旱和中旱为主,河西走廊中旱发生频率(大于 15.00%)明显高于其他地区。干旱变化具有12 a、30 a和46 a的周期特征并具有明显的季节差异。春、夏、秋季西北地区中西部具有明显干旱化趋势,其中秋季SPEI减小速率为-0.034 a-1,干旱化趋势最突出;尤其是河西走廊,春、夏、秋季 SPEI减小速率均小于-0.030 a-1,表明该地区连旱可能性较高,同时干旱历时、烈度峰值和平均干旱烈度均较高。塔里木盆地春秋季的干旱程度亦较为突出。干旱对植被变化具有一定的影响。与 2003—2012 年相比,2013—2022 年 NDVI 退化面积增加约 3.52%。近 20 a 来植被退化区域主要分布在新疆西部、青海东部和南部,NDVI与SPEI呈正相关。

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Abstract:

Systematically investigating drought evolution characteristics and vegetation responses to drought is crucial for drought prevention, disaster mitigation, water resource management, and policy formulation. Our study focuses on Xinjiang, Qinghai, and Gansu provinces in mid-western Northwest China. Using the CN05.1 dataset from 1963 to 2022 to calculate the standardized precipitation evapotranspiration index (SPEI), combined with the normalized difference vegetation index (NDVI) from 2003 to 2022, we applied run theory, Theil-Sen slope estimator, Mann-Kendall trend test, and regression analysis to analyze drought evolution across multiple temporal scales and explore drought impacts on vegetation. The results indicate that over the past 60 years, the study area exhibited a drying trend on decadal and interannual scales, with 1998 identified as a significant drought mutation year. Pronounced drying trends were observed in eastern and southern Xinjiang, the Qaidam Basin, and the Hexi Corridor, where light and moderate droughts were predominant. The Hexi Corridor experienced a significantly higher frequency of moderate droughts (greater than 15.00%) than other regions. Drought variability exhibited periodic characteristics of 12-year, 30-year, and 46-year cycles, with notable seasonal differences. In spring, summer, and autumn, the mid-western Northwest China showed significant drying trends, with the most rapid decline in autumn (SPEI rate: −0.034 yr⁻¹). The Hexi Corridor exhibited SPEI decline rates below −0.030 yr⁻¹ across all three seasons, indicating high risks of consecutive droughts, alongside prolonged duration, higher peak intensity, and mean drought intensity. The Tarim Basin also faced severe drought conditions in spring and autumn. Drought exerted measurable impacts on vegetation dynamics. Compared to 2003-2012, NDVI degradation areas increased by approximately 3.52% during 2013-2022. Over the past two decades, vegetation degradation was concentrated in western Xinjiang, eastern and southern Qinghai, where NDVI and SPEI were positively correlated.

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