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中国沙漠 ›› 2025, Vol. 45 ›› Issue (5): 289-300.DOI: 10.7522/j.issn.1000-694X.2025.00126

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青海湖流域植被绿度时空变化及影响因素

王明宇1(), 吴成永2,3, 陈克龙1,2()   

  1. 1.青海师范大学 地理科学学院/青海省自然地理与环境过程重点实验室/青藏高原地表过程与生态保护教育部重点实验室,青海 西宁 810008
    2.青海青海湖湿地生态系统国家定位观测研究站,青海 海北 812300
    3.天水师范学院 资源与环境工程学院,甘肃 天水 741001
  • 收稿日期:2025-04-14 修回日期:2025-06-16 出版日期:2025-09-20 发布日期:2025-09-27
  • 通讯作者: 陈克龙
  • 作者简介:王明宇(2001—),男,江西抚州人,硕士研究生,主要从事自然地理与生态环境过程的研究。E-mail: king_qhnu@163.com
  • 基金资助:
    第二次青藏高原综合科学考察研究项目(2019QZK0405);青海省科技计划项目(2023-ZJ-905T);国家自然科学基金项目(42461064);国家自然科学基金项目(42461018)

Spatiotemporal changes of vegetation greenness and their influencing factors in the Qinghai Lake Basin

Mingyu Wang1(), Chengyong Wu2,3, Kelong Chen1,2()   

  1. 1.School of Geographical Sciences / Key Laboratory of Physical Geography and Environmental Processes of Qinghai Province / Key Laboratory of Tibetan Plateau Land Surface Processes and Ecological Conservation,Ministry of Education,Qinghai Normal University,Xining 810008,China
    2.Qinghai Qinghai Lake Wetland Ecosystem National Positioning Observation and Research Station,Haibei 812300,Qinghai,China
    3.School of Resources and Environmental Engineering,Tianshui Normal University,Tianshui 741001,Gansu,China
  • Received:2025-04-14 Revised:2025-06-16 Online:2025-09-20 Published:2025-09-27
  • Contact: Kelong Chen

摘要:

为探究青海湖流域植被绿度时空变化及其对气候变化和人类活动的响应,基于2000—2023年MODIS归一化植被指数(NDVI)数据、气象数据,通过Sen+Mann-Kendall趋势分析、Hurst指数、相关分析以及残差分析等方法,分析青海湖流域植被绿度的时空变化规律和未来发展趋势,并评估气候变化与人类活动对植被绿度影响程度。结果显示:(1)2000—2023年青海湖流域NDVI年均值为0.45,时间上呈显著上升趋势,年变化速率为0.0022,改善区占研究区的86.22%,呈显著上升趋势,空间异质性明显。(2)植被绿度总体变化相对稳定,变异系数为0~1.7,平均值为0.08,展现出积极发展态势。(3)青海湖流域植被绿度与降水和气温均正相关,且与降水(r=0.196,P<0.05)的相关性强于气温(r=0.07,P<0.05),85.5%区域以降水驱动为主。(4)青海湖流域63.6%区域植被绿度受气候变化和人类活动双重影响,其中人类活动的相对贡献率为85.02%。

关键词: 植被绿度, 时空变化, 气候变化, 人类活动, 青海湖流域

Abstract:

To investigate the spatiotemporal changes in vegetation greenness in the Qinghai Lake Basin and their responses to climate change and human activities, this study analyzed MODIS Normalized Difference Vegetation Index (NDVI) data and meteorological data from 2000 to 2023. Methods such as Sen+Mann-Kendall trend analysis, Hurst index, correlation analysis, and residual analysis were employed to examine the spatiotemporal patterns and future trends of vegetation greenness in the basin. The degree of influence of climate change and human activities on vegetation greenness was also assessed. The results show: (1) From 2000 to 2023, the annual average NDVI in the Qinghai Lake Basin was 0.45, with a significant increasing trend over time at a rate of 0.0022 per year. Areas showing improvement accounted for 86.2% of the study region, exhibiting a significant upward trend and distinct spatial heterogeneity. (2) Vegetation greenness generally remained relatively stable, with a coefficient of variation ranging from 0 to 1.7 and an average of 0.08, indicating a positive development trend. (3) Vegetation greenness in the Qinghai Lake Basin was positively correlated with both precipitation (r=0.196, P<0.05) and temperature (r=0.07, P<0.05), with precipitation having a stronger influence than temperature. Precipitation was the dominant driver in 85.5% of the area. (4) Changes in vegetation greenness in 63.6% of the Qinghai Lake Basin were jointly influenced by climate change and human activities, with human activities accounting for a relative contribution rate of 85.02%.

Key words: vegetation greenness, spatiotemporal changes, climate change, human activities, Qinghai Lake Basin

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