环洞庭湖区植被覆盖变化及其影响因素分析

蒋沂澄 ,  隆院男 ,  黄志勇 ,  黄草 ,  朱镇源

水利水电技术(中英文) ›› 2026, Vol. 57 ›› Issue (6) : 181 -194.

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水利水电技术(中英文) ›› 2026, Vol. 57 ›› Issue (6) : 181 -194. DOI: 10.13928/j.cnki.wrahe.2026.06.013
水利新质生产力驱动下的水生态修复技术创新专栏

环洞庭湖区植被覆盖变化及其影响因素分析

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Analysis of vegetation cover changes and their influencing factors in area surrounding Dongting Lake

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摘要

【目的】环洞庭湖区作为长江中下游典型的湖区湿地生态系统,其湿地植被在维持区域生态安全、防洪缓冲等方面具有重要功能。探讨环洞庭湖区植被覆盖时空变化特征,进一步分析其影响因素,旨在为湖区生态系统的动态监测与综合调控提供科学依据。【方法】以归一化植被指数(NDVI)为植被覆盖变化的核心指标,结合重力卫星球谐系数产品反演的陆地水储量变化(TWSA)数据及多源气象数据,系统分析2003—2022年环洞庭湖区植被覆盖变化的时空特征,探讨归一化植被指数影响因素的驱动机制。【结果】(1)2003—2022年环洞庭湖区NDVI年均值在0.49~0.56之间,年际变化速率约为0.002 4/yr。(2)空间格局上呈现出西北地区和东南地区有明显上升趋势,NDVI变化速率由西北地区和东南地区向中部地区递减的特征。(3)水储量亏损指数在研究期间共监测到5场中度及以上水文干旱事件,总历时26个月,总水储量亏损达到3551 mm。在五次水文干旱事件中,NDVI异常均为负值,说明水储量亏损抑制了植被生长。NDVI对降水变化响应迅速,对气温的响应存在约1个月滞后,却先于TWSA1个月发生变化。而厄尔尼诺-南方涛动(ENSO)通过调控大气环流间接影响植被,植被对ENSO的响应存在显著的长期滞后效应。【结论】2003—2022年环洞庭湖区年均NDVI整体呈波动上升趋势,表明生态保护政策推动下,区域植被覆盖整体改善。降水和气温是决定植被生长的主要气候因子,TWSA作为综合反映地表水、地下水和土壤水的关键指标,对植被动态同样具有重要调控作用。

Abstract

[Objective] As a typical wetland ecosystem in the middle and lower reaches of the Yangtze River, the area surrounding Dongting Lake plays a vital role in regional ecological security and flood mitigation. The spatiotemporal variation characteristics of vegetation cover in the area surrounding Dongting Lake are investigated, and the influencing factors are further analyzed, aiming to provide a scientific basis for the dynamic monitoring and integrated management of ecosystems in lake areas. [Methods] The normalized difference vegetation index(NDVI) was used as the primary indicator of vegetation cover changes. Combined with terrestrial water storage anomaly(TWSA) data derived from spherical harmonic products from the Gravity Recovery and Climate Experiment(GRACE) satellites and multi-source meteorological data, the spatiotemporal characteristics of vegetation change in the area surrounding Dongting Lake from 2003 to 2022 were systematically analyzed. The driving mechanisms behind the influencing factors of NDVI were investigated. [Results] (1) From 2003 to 2022, the annual average NDVI in the area surrounding Dongting Lake ranged between 0.49 and 0.56, with an interannual increase rate of approximately 0.002 4/yr.(2) Spatially, NDVI showed significant increases in the northwest and southeast, with NDVI change rates gradually decreasing from these regions toward the central region of the lake area.(3) During the study period, five moderate or more severe hydrological drought events were identified based on water storage deficit index(WSDI), with a total duration of 26 months and a cumulative terrestrial water storage deficit of 3551 mm. During the five hydrological drought events, NDVI anomalies were all negative, indicating that water storage deficits suppressed vegetation growth. NDVI responded rapidly to precipitation variations. NDVI responded to temperature variations with a lag of about one month, yet it occurred one month earlier than its response to TWSA. El Ni1o-Southern Oscillation(ENSO) indirectly affected vegetation by modulating atmospheric circulation, and vegetation showed a significant long-term lagged response to ENSO. [Conclusion] The annual average NDVI in the area surrounding Dongting Lake exhibited an overall fluctuating upward trend from 2003 to 2022, indicating improved regional vegetation cover under ecological conservation policies. Precipitation and temperature are identified as the primary climatic factors of vegetation growth. Notably, TWSA, as a comprehensive indicator reflecting surface water, groundwater, and soil moisture, plays a significant regulatory role in vegetation dynamics.

关键词

植被覆盖变化 / 环洞庭湖区 / NDVI / 陆地水储量变化 / 水文干旱 / ENSO / 时滞响应 / 影响因素

Key words

vegetation cover change / area surrounding Dongting Lake / NDVI / terrestrial water storage anomaly / hydrological drought / ENSO / time-lagged response / influencing factors

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蒋沂澄,隆院男,黄志勇,黄草,朱镇源. 环洞庭湖区植被覆盖变化及其影响因素分析[J]. 水利水电技术(中英文), 2026, 57(6): 181-194 DOI:10.13928/j.cnki.wrahe.2026.06.013

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基金资助

国家自然科学基金项目(42301404)

湖南省水利科技项目(XSKJ2023059-06)

湖南省水利科技项目(XSKJ2024064-3)

湖南省自然科学基金(2022J40480)

长沙理工大学2023年研究生科研创新项目(CSLGCX23054)

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