长江流域资源与环境 >> 2025, Vol. 34 >> Issue (09): 2011-.doi: 10.11870/cjlyzyyhj202509010

• 自然资源 • 上一篇    下一篇

干旱背景下环洞庭湖区水储量组分变化及归因分析

隆院男1,2,蒋沂澄1,2,黄志勇1,2*,朱镇源3,4
  

  1. (1.长沙理工大学水利与海洋工程学院,湖南 长沙 410114;2.洞庭湖水环境治理与
    生态修复湖南省重点实验室,湖南 长沙 410114;3.中国科学院大学,北京 100049;
    4.青海省盐湖地质与环境重点实验室,青海 西宁 810008)
  • 出版日期:2025-09-20 发布日期:2025-09-22

Variations and Attribution of Water Storage Components in the Dongting Lake Surrounding Area Under Drought Conditions

LONG Yuan-nan1,2, JIANG Yi-cheng1,2, HUANG Zhi-yong1,2, ZHU Zhen-yuan3,4   

  1. (1. School of Hydraulic and Ocean Engineering, Changsha University of Science & Technology, Changsha 410114, China;
    2. Key Laboratory of Dongting Lake Aquatic Eco-Environmental Control and Restoration of Hunan Province, Changsha 410114, China;
    3. University of Chinese Academy of Sciences, Beijing 100049, China; 4. Qinghai Provincial Key Laboratory
    of Geology and Environment of Salt Lakes, Xining 810008, China)
  • Online:2025-09-20 Published:2025-09-22

摘要: 利用重力卫星球谐系数反演2003~2022年环洞庭湖区陆地水储量变化,基于正演模拟方法,联合实测湖泊和水库蓄水量数据和WGHM水文模型分离陆地水储量各组分,分析其变化规律及影响因素,探究重力卫星数据在小尺度湖泊湿地的适用性以及环洞庭湖区陆地水储量组分变化与气候因子的响应关系。结果表明:(1)利用重力卫星球谐系数产品分离地下水储量组分时,通过消除洞庭湖与三峡水库蓄水量变化信号泄露的干扰及1个月滞后期影响,与实测值相关系数达0.71,均方根误差为29.1 mm/mo.。(2)总陆地水储量变化由地表水储量主导(~66%),其次是地下水储量(~21%),各组分交换强度较弱。2003年以来,总陆地水储量亏损指数共表征了5场中度及以上干旱事件,总历时26个月,总水储量亏损达到3 551 mm。此外,土壤水亏损量达1 377 mm,地表水亏损量达2 691 mm,地下水亏损量达1 681 mm。(3)降水和气温异常直接调控陆地水储量变化,总陆地水储量和地表水对降水异常的响应无滞后,土壤水存在1个月滞后;气温升高加剧水储量亏损,但地下水对其响应较为迟缓。ENSO通过调控大气环流成为流域气象干旱的重要影响因素,其与地表水亏损指数相关性最强。

Abstract: This study monitored terrestrial water storage (TWS) anomalies in the Dongting Lake Area from 2003 to 2022 using the spherical harmonic coefficients from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On satellite missions. A forward modeling approach was integrated with in-situ lake/reservoir storage data and the WaterGAP Global Hydrology Model (WGHM) simulations to disaggregate TWS components (surface water, groundwater, and soil moisture). The spatiotemporal dynamics and driving factors were also analyzed. This study systematically investigated the applicability of GRACE data in small-scale lake-wetland systems and the response relationships between TWS components and climatic factors. Key findings included: (1) Incorporating leakage corrections for observed water storage variations in the Dongting Lake and the Three Gorges Reservoir significantly improved groundwater component separation accuracy. After eliminating 1-month time lag effects, the correlation coefficient between satellite-based and observed groundwater storage anomalies reached 0.71. (2) TWS anomalies were dominated by surface water storage (~66%), followed by groundwater storage (~21%), with weak inter-component exchange. Since 2003, TWS deficit indices identified five moderate-to-severe drought episodes totaling 26 months, with cumulative deficits reaching 3 551 mm. Deficits of different water storage components were quantified, which included soil moisture (1 377 mm), surface water (2 691 mm), and groundwater (1 681 mm). (3) Precipitation anomalies and temperature extremes directly regulated TWS dynamics. Total TWS and surface water responded instantaneously to precipitation anomalies, while soil moisture exhibited 1-month hysteresis. Warming amplified water storage deficits, though groundwater exhibited delayed temperature sensitivity. ENSO emerged as the primary drought driver via monsoon system perturbations induced by equatorial sea surface temperature gradients, showing the strongest correlation with surface water storage deficit index.

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