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第一作者:Haibin Wang
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通讯作者:Jiahong Liu
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第一作者单位:State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
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原位连接:https://doi.org/10.1016/j.ejrh.2024.102168
研究区域:青海湖流域( QLB ):
研究重点:青藏高原湖泊系统是全球生态系统的重要组成部分。全球气候变暖显著改变了其水位。为全面分析青海湖水位变化并预测其未来变化趋势,本研究采用水热耦合平衡理论量化各气候变化因子的影响。此外,结合CMIP6全球气候模式,利用数字流域模型对未来径流进行模拟。本研究利用多元回归模型对青海湖未来水位变化趋势进行预测,从而可以对其未来淹没面积进行估算。
为该地区提供新的水文见解:结果表明,降水、蒸发和下垫面因素对青海湖入湖水量的贡献分别为76.52 %、13.97 %和9.51 %。值得注意的是,青海湖经历了逐渐增温和增湿的过程,预计到2050年湖泊水位将上升到3202.64 m。这种上升将导致淹没范围的扩大,主要集中在靠近冲积平原的地方。此外,还将对青藏铁路约2.8 km的轨道产生影响。这项研究揭示了湖泊对气候变化的水文响应,并预测了未来的水位趋势,为区域演变和相关的环境影响提供了有价值的见解。
Fig. 1.
Cartographic Representation of Qinghai Lake (a) Digital Elevation Map (b) Spatial Distribution of Hydrometric, Rain Gauging, and Mete
orological Stations (c) Temporal Variations in Water Level.
Fig. 2.
Conceptual Framework of the Study
Fig. 3.
Digital Watershed Model Yield Flow.
Fig. 4.
Annual trends in hydrological elements variation (1969
–
2020). (a) temperature(
℃
), (b) evaporation(mm), (c) precipitation(mm), (d) runoff
(mm), (e) aridity Index.
Fig. 5.
Time series of the lake water level and cumulative anomaly curve (1969
–
2020). (a)temperature(
℃
), (b)evaporation(mm), (c)precipitation
(mm), (d) runoff(mm).
Fig. 6.
Scatter plot comparing actual water volume changes with regression model.
Fig. 7.
Comparison of actual water changes and regression model.
Fig. 8.
Time series of CMIP6 model simulated annual mean precipitation and observed precipitation (1995
–
2014) (a) comparison of time series for
mean annual precipitation and observed precipitation (b) comparison of time series for observed precipitation after bias correction.
Fig. 9.
Temporal evolution of Qinghai Lake water level estimates.
Fig. 10.
Remote sensing map of Qinghai Lake water levels: present annual water level and projected average water level in 2050.
Fig. 11.
Remote sensing map of submerged areas in Qinghai Lake due to water level changes.
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