2025 Vol. 58, No. 1
Article Contents

LIU Yong, ZHANG Xin, WEI Liangshuai, HUANG Anbang, PENG Bo, SHU Qinfeng. 2025. Analysis of Climate Change and Vegetation Change in the Yangtze River Source. Northwestern Geology, 58(1): 257-269. doi: 10.12401/j.nwg.2023127
Citation: LIU Yong, ZHANG Xin, WEI Liangshuai, HUANG Anbang, PENG Bo, SHU Qinfeng. 2025. Analysis of Climate Change and Vegetation Change in the Yangtze River Source. Northwestern Geology, 58(1): 257-269. doi: 10.12401/j.nwg.2023127

Analysis of Climate Change and Vegetation Change in the Yangtze River Source

More Information
  • The source of the Yangtze River is located in the remote and high-altitude Qinghai-Tibet Plateau, where the ecosystem is fragile. Influenced by global climate change and human activities, various elements closely related to the ecological system of the source area, such as glaciers, permafrost, swamps, wetlands, and vegetation, have experienced different degrees of degradation, which has aroused widespread concern from various sectors of society. This article analyzes the spatiotemporal evolution characteristics of the climate and ecological vegetation in the Yangtze River source region using long-term, high spatiotemporal resolution meteorological and MODIS NDVI data, combined with mathematical and statistical methods, and explores the response mechanism of vegetation to climate and soil water. The results show that over the past 40 years, the rainfall and surface temperature in the Yangtze River source region have decreased from southeast to northwest, and the temperature in each region has generally increased. Vegetation growth in the eastern region is better than that in the western region, and since 2000, the overall vegetation growth in the Yangtze River source region has gradually improved. Due to the sensitivity of permafrost to temperature, vegetation growth during the growing season in the Yangtze River source region is more affected by temperature than rainfall. The ecological vegetation in the Yangtze River source region is greatly influenced by soil water content, and the degree of influence gradually weakens from the surface to the deep layers.

  • 加载中
  • [1] 陈婷. 长江源区生态水文学研究[D]. 北京: 中国地质大学(北京), 2009

    Google Scholar

    CHEN Ting. Study on the ecohydrology of the Yangtze River source area [D]. Beijing: China University of Geosciences (Beijing), 2009.

    Google Scholar

    [2] 杜臻, 张茂省, 冯立等. 鄂尔多斯盆地煤炭采动的生态系统响应机制研究现状与展望[J]. 西北地质, 2023, 56(03): 78-88

    Google Scholar

    DU Zhen, ZHANG Maosheng, Feng Li, et al. Research Status and Prospect of Ecosystem Response Mechanism to Coal Mining in Ordos Basin [J]. Northwest Geology, 2023, 56 (03): 78-88.

    Google Scholar

    [3] 方欣, 刘小槺, 岳大鹏. 毛乌素沙地1960-2018年气候变化特征及影响因子分析[J]. 水土保持研究, 2022, 29(02): 163-169

    Google Scholar

    FANG Xin, LIU Xiaokang, YUE Dapeng. Analysis of climate change characteristics and impact factors in the Maowusu Sands from 1960-2018[J]. Soil and water conservation research, 2022, 29(02): 163-169.

    Google Scholar

    [4] 黄荟羽, 李恩键, 安娟, 等. 克拉默法与曼-肯德尔法对降水突变检验的对比分析[J]. 现代农业科技, 2018, 8: 2 doi: 10.3969/j.issn.1007-5739.2018.06.002

    CrossRef Google Scholar

    HUANG Aiyu, LI Enjian, AN Juan, et al. A comparative analysis of the Cramer method and the Mann-Kendall method for precipitation mutation testing[J]. Modern Agricultural Science and Technology, 2018, 8: 2. doi: 10.3969/j.issn.1007-5739.2018.06.002

    CrossRef Google Scholar

    [5] 韩海辉, 李健强, 易欢等. 遥感技术在西北地质调查中的应用及展望[J]. 西北地质, 2022, 55(03): 155-169

    Google Scholar

    HAN Haihui, LI Jianqiang, YI Huan, et al. Application and prospect of remote sensing technology in geological survey of Northwest China [J]. Northwest Geology, 2022, 55 (03): 155-169.

    Google Scholar

    [6] 李雪银, 张志强, 孙爱芝. 1982—2021年黄河流域植被覆盖时空演变及影响因素研究[J]. 地球环境学报, 2022, 13(04), 428–436

    Google Scholar

    LI Xueyin, ZHANG Zhiqiang, SUN Aizhi. Spatial and temporal evolution of vegetation cover in the Yellow River basin from 1982 to 2021 [J]. Journal of Earth Environment, 2022, 13(04), 428-436.

    Google Scholar

    [7] 李元寿, 王根绪, 赵林, 等. 青藏高原多年冻土活动层土壤水分对高寒草甸覆盖变化的响应[J]. 冰川冻土, 2010, 32(1): 157-165

    Google Scholar

    LI Yuanshou, WANG Genxu, ZHAO Lin, et al. Soil moisture response to alpine meadow cover change in the permafrost active layer of the Qinghai-Tibet Plateau[J]. Glacial Permafrost, 2010, 32(1): 157-165.

    Google Scholar

    [8] 钱开铸. 长江源区水文周期特征及其对气候变化的响应[D]. 北京: 中国地质大学(北京), 2013

    Google Scholar

    QIAN Kaizhu. Characteristics of the hydrological cycle in the Yangtze River source area and its response to climate change [D]. Beijing: China University of Geosciences (Beijing), 2013.

    Google Scholar

    [9] 汪柳皓, 魏显虎, 张宗科, 等. 青藏高原地区植被指数变化及其与温湿度因子的关系[J]. 森林与环境学报, 2022, 42(02): 141-148

    Google Scholar

    WANG Liuhao, WEI Xianhu, ZHANG Zongke, et al. Changes in vegetation index and its relationship with temperature and humidity factors in the Qinghai-Tibet Plateau[J]. Journal of Forest and Environment, 2022, 42(02): 141-148.

    Google Scholar

    [10] 强建华. 遥感技术在新疆南部地区矿山环境调查及生态修复中的应用[J]. 西北地质, 2021, 54(03): 253-258 doi: 10.19751/j.cnki.61-1149/p.2021.03.023

    CrossRef Google Scholar

    QIANG Jianhua. Application of remote sensing technology in mine environment investigation and ecological restoration in Southern Xinjiang [J]. Northwest Geology`, 2021, 54 (03): 253-258. doi: 10.19751/j.cnki.61-1149/p.2021.03.023

    CrossRef Google Scholar

    [11] 吴小丽. 近30年来青藏高原多年冻土区与季节性冻土区土壤水分变化差异[D]. 兰州: 兰州交通大学, 2020

    Google Scholar

    WU Xiaoli. Differences in soil moisture changes between perennial and seasonal permafrost areas on the Qinghai-Tibet Plateau over the past 30 years[D]. Lanzhou: Lanzhou Transportation University, 2020.

    Google Scholar

    [12] 阳坤, 何杰. 中国区域地面气象要素驱动数据集(1979-2018)[R]. 国家青藏高原科学数据中心, 2019

    Google Scholar

    YANG Kun, HE Jie. Regional ground meteorological element-driven dataset for China (1979-2018) [R]. National Qinghai-Tibet Plateau Scientific Data Center, 2019.

    Google Scholar

    [13] 朱艺旋, 张扬建, 俎佳星, 等. 基于MODIS NDVI、SPOT NDVI数据的GIMMS NDVI性能评价[J]. 应用生态学报, 2019, 30(2), 536–544

    Google Scholar

    ZHU Yixuan, ZHANG Yangjian, ZU Jiaxing, et al. Performance evaluation of GIMMS NDVI based on MODIS NDVI and SPOT NDVI data[J]. Journal of Applied Ecology, 2019, 30(2), 536-544.

    Google Scholar

    [14] 赵林. 青藏高原新绘制冻土分布图(2017)[R]. 国家青藏高原科学数据中心, 2019.

    Google Scholar

    [15] 赵林, 胡国杰, 邹德富, 等.青藏高原多年冻土综合监测数据集(2002-2018)[R].北京: 国家青藏高原科学数据中心, 2021.

    Google Scholar

    [16] Ba R, Lovallo M, Song W G, et al. Multifractal Analysis of MODIS Aqua and Terra Satellite Time Series of Normalized Difference Vegetation Index and Enhanced Vegetation Index of Sites Affected by Wildfires[J]. Entropy, 2022, 24(12), 1748. doi: 10.3390/e24121748

    CrossRef Google Scholar

    [17] Essaadia A, Abdellah A, Ahmed A, et al. The normalized difference vegetation index (NDVI) of the Zat valley, Marrakech: comparison and dynamics[J]. Heliyon, 2022, 8(12), 12204. doi: 10.1016/j.heliyon.2022.e12204

    CrossRef Google Scholar

    [18] Parmesan C, Yohe G. A globally coherent fingerprint of climate change impacts across natural systems [J]. Nature, 2003, 421(6918), 37–42. doi: 10.1038/nature01286

    CrossRef Google Scholar

  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Figures(15)

Tables(4)

Article Metrics

Article views(211) PDF downloads(26) Cited by(0)

Access History

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint