| 2001~2022年长江流域极端气候演变及其对植被NDVI的影响 |
| 摘要点击 254 全文点击 9 投稿时间：2025-04-18 修订日期：2025-07-29 |
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| 中文关键词 植被 归一化差异植被指数（NDVI） 极端气候 时滞和累积效应 长江流域 |
| 英文关键词 vegetation normalized difference vegetation index（NDVI） extreme climate time-lag and accumulation effect Yangtze River Basin |
| DOI 10.13227/j.hjkx.202504233 |
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| 中文摘要 |
| 探究长江流域极端气候对植被生长的影响，对流域生态安全具有重要意义. 基于2001~2022年研究区NDVI数据和气象站点逐日气温和降水量数据，选择气候变化监测和指标专家组（ETCCDI）所定义的16个极端气候指数，运用Theil-Sen Median斜率估计、Mann-Kendall显著性检验及相关性分析等方法，探讨了极端气候的动态特征及其对植被NDVI的影响. 结果表明：①2001~2022年，长江流域极端降水事件和极端高温事件频率增加，而极端低温事件频率减少；雅砻江流域气温回暖现象显著，太湖流域极端降水事件呈显著增加趋势. ②植被NDVI与极端降水指数（除CDD外）和极端高温指数以正相关为主，而与极端低温指数和气温日较差（DTR）以负相关为主；嘉陵江和汉江流域植被生长对R95P、R99P、RX1DAY和RX5DAY敏感，而鄱阳湖、洞庭湖和乌江流域对TN10P、TN90P和DTR敏感；R95P、R99P、TN10P和TN90P是影响不同植被生长的主要因子. ③极端气候指数对植被NDVI的影响以累积效应为主，其中RX1DAY、RX5DAY、TNN、TXN、TNX和TXX以累计1~2个月为主（63.71%~74.27%）；而TN10P、TX10P、TN90P、TX90P和DTR以累计1~3月为主（32.31%~56.67%），其它情景面积占比介于13.48%~25.24%；极端气候指数（除DTR）对不同植被的影响均以累积效应为主，对草地的影响尤为明显. 研究结果不仅对深入理解植被-极端气候的响应机制具有重要意义，同时对开展长江流域生态环境保护具有重要参考价值. |
| 英文摘要 |
| Exploring the impact of extreme climate on vegetation growth in the Yangtze River Basin is of great significance for ecological security in the basin. Based on NDVI data from 2001 to 2022 and the daily temperature and precipitation data from meteorological stations， 16 extreme climate indices defined by the Expert Group on Climate Change Monitoring and Indicators （ETCCDI） were selected. such as Theil-Sen Median slope estimation， Mann-Kendall significance tests， and correlation analysis were used to investigate the dynamic character of extreme climate indices and their effects on vegetation NDVI. The results indicated that： ① From 2001 to 2022， the frequency of extreme precipitation and extreme high temperature events in the Yangtze River Basin had been increasing， while the frequency of extreme low temperature events had been decreasing； the temperature warming phenomenon in the Yalong River Basin was significant， and the extreme precipitation events in the Taihu Lake Basin showed a significant increasing trend. ② Vegetation NDVI was primarily positively correlated with extreme precipitation indices （excluding CDD） and extreme temperature indices， while it was mainly negatively correlated with extreme low temperature indices and daily temperature difference DTR. Vegetation growth was sensitive to R95P， R99P， RX1DAY， and RX5DAY in the Jialing River and Hanjiang River basins， while it was sensitive to TN10P， TN90P， and DTR in the Poyang Lake， Dongting Lake， and Wujiang River basins. Among extreme climate indices， R95P， R99P， TN10P， and TN90P were the main factors influencing the growth of different vegetation. ③ The influence of extreme climate indices on vegetation NDVI was mainly a cumulative effect. Among them， RX1DAY， RX5DAY， TNN， TXN， TNX， and TXX were mainly cumulative for 1 to 2 months （63.71%-74.27%）. However， TN10P， TX10P， TN90P， TX90P， and DTR were mainly an accumulation of 1 to 3 months （32.31%-56.67%）， and the proportion of other scenarios ranged from 13.48% to 25.24%. Extreme climate indices （except DTR） mainly had a cumulative effect on different vegetation types， and the impact on grassland was particularly obvious. The results are not only of great significance for understanding the response mechanism of vegetation to extreme climate but are also of great reference value for ecological environment protection in the Yangtze River Basin. |
