长江流域植被与气象干旱的时空关联及归因分析  

Spatiotemporal Association and Attribution Analysis of Vegetation and Drought in the Yangtze River Basin

作　　者：邹丹[1] 周玉科[2] 董秀娟 林金堂[1] 王洪 梁娟珠[3] Dan ZOU;Yuke ZHOU;Xiujuan DONG;Jintang LIN;Hong WANG;Juanzhu LIANG(School of Resource Engineering,Longyan University,Longyan 364012,China;Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic and Nature Re-sources Research,Chinese Academy of Sciences,Beijing 100101,China;The Academy of Digital China,Fuzhou University,Fuzhou 350002,China)

机构地区：[1]龙岩学院资源工程学院,福建龙岩364012 [2]中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室,北京100101 [3]福州大学数字中国研究院(福建),福建福州350002

出　　处：《遥感技术与应用》2024年第5期1183-1195,共13页Remote Sensing Technology and Application

基　　金：福建省自然科学基金项目(2020J01355、2020J01361);福建省教育厅中青年科技类项目(JAT200609)。

摘　　要：全球气候变化和人类活动导致干旱频率和强度持续增加。目前,干旱已经成为影响植被生长及多样性的关键因素,并进一步影响农业产量、生态系统稳定性和社会经济发展。因此,掌握植被动态与干旱的作用关系有助于揭示陆地生态系统的生理机制并制定有效的管理策略。本研究利用长时序日光诱导叶绿素荧光(SIF)和归一化差异植被指数(NDVI)数据集(2001~2020),评估长江流域不同类型植被与气象干旱(SPEI指数)的作用关系。首先采用相关分析法得到SPEI与SIF(NDVI)的最大相关系数,并对比分析不同类型植被SIF和NDVI响应气象干旱的差异。其次应用改进的偏小波相干法,定量分析大尺度气候模式和太阳活动对植被与气象干旱关系的影响。结果表明:(1)2001~2020年间长江流域干旱发生频繁,且夏季的干湿状况对其全年气候影响最大;(2)SIF与SPEI的相关性优于NDVI与SPEI的相关性;(3)基于NDVI的植被响应时间(3~6个月)大于基于SIF的响应时间(1~4个月),其中耕地和草地的响应时间较短,常绿阔叶林和混交林的响应时间较长;(4)干旱与植被之间存在显著正相关性,周期性为4~16个月。太平洋十年涛动(PDO)、厄尔尼诺南方涛动(ENSO)和太阳黑子是影响干旱和植被关系的重要驱动因素,其中太阳黑子的影响最为显著。总体说明干旱严重威胁长江流域陆地生态系统的生长发展,SIF在监测干旱和植被响应中显示出较大的潜力和优势。研究结果对长江流域地区的干旱预测预警和生态系统保护规划具有参考意义。Global climate change and human activities have led to continued increases in the frequency and intensity of droughts.Recently,drought has become a key factor that affects vegetation growth and diversity,which further impacts agricultural production,ecosystem stability,and socioeconomic development.Therefore,mastering the relationship between vegetation dynamics and drought will help to reveal the physiological mechanism of terrestrial ecosystems and formulate effective management strategies.Here,we used long-term datasets of(2001~2020)Solar-Induced chlorophyll Fluorescence(SIF)and Normalized Difference Vegetation Index(NDVI)to explore vegetation changes and their linkage to meteorological drought(SPEI index)across different vegetation types in the Yangtze River Basin(YRB).Firstly,the correlation analysis method was applied to obtain the maximum correlation coefficient between SPEI and SIF(NDVI),and the differences of SIF and NDVI responses to meteorological drought of different vegetation types were compared and analyzed.Then we employed an improved partial wavelet coherence method to quantitatively analyze the influence of large-scale climate models and solar activity on the interaction between vegetation response to meteorological drought.The results show that:(1)from 2001 to 2020,the YRB experienced frequent droughts,with summer dryness and wetness exerting the significant impact on its annual climate;(2)SPEI exhibits a greater association with SIF than NDVI does.(3)NDVI has a longer response time(3~6 months)to drought than SIF(1~4 months),with cropland and grassland displaying shorter response times and evergreen broadleaf and mixed forests showing longer response times.(4)There is a significant positive correlation between drought and vegetation,with a period of 4~16 months.The teleconnection factors of Pacific Decadal Oscillation(PDO),El Niño Southern Oscillation(ENSO),and sunspots are crucial drivers in establishing the interaction between drought and vegetation,with sunspots having the most significant

关 键 词：气候变化 气象干旱 植被动态 SIF NDVI 长江流域 

分 类 号：P42[天文地球—大气科学及气象学] TP79[自动化与计算机技术—检测技术与自动化装置]