Unravelling the spatiotemporal variation in the water levels of Poyang Lake with the variational mode decomposition model

IF 3.2 3区 地球科学 Q1 Environmental Science Hydrological Processes Pub Date : 2024-07-15 DOI:10.1002/hyp.15239
Min Gan, Xijun Lai, Yan Guo, Zhao Lu, Yongping Chen, Shunqi Pan, Haidong Pan, Ao Chu
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Abstract

Poyang Lake is a dynamic floodplain lake system that exhibits complex water level fluctuations and experiences significant regime changes over space and time, which remains to be further explored. This study used the variational mode decomposition (VMD) model to decompose the Poyang Lake's water levels from 1960 to 2022 at four key stations into six intrinsic mode functions (IMFs), namely IMF1–IMF6, representing variations on different time scales. The results present significant spatiotemporal heterogeneity. The multi-year variation (IMF1) accounts for 5.6%–12.4% of the total variation and displays a northward decreasing trend, reflecting the lake's river-like characteristics. The spectrum of IFM1 also reveals a significant 3.6-year fluctuation mainly attributed to the tributary inflow, especially the Ganjiang River. The IMF1 differences between stations show abrupt decreases since the 2000s, indicating the impact of concentrated sand mining activities on the northern and central regions. The annual variation (IMF2) is the most prominent, contributing 76.1%–88.4% of the total variation, and shows a southward attenuation trend, likely due to the weakening influence of the Yangtze River flow. The intra-annual scale (IMF3–IMF6) represents 6.0%–11.5% of the total variation and exhibits less spatial difference compared to the multi-year and annual variations. The VMD model effectively separates the water level signals into different frequency bands, providing insights into the complex interactions between the lake, tributaries, and Yangtze River, as well as the impacts of human activities like sand mining, enhancing understanding of floodplain lake dynamics. The results also imply the importance of coping with the water level decline of Poyang Lake.

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用变异模式分解模型揭示鄱阳湖水位的时空变化
鄱阳湖是一个动态的洪泛湖泊系统,水位波动复杂,水系时空变化显著,有待进一步探索。本研究利用变异模态分解(VMD)模型,将鄱阳湖 1960~2022 年四个关键站点的水位分解为六个本征模态函数(IMFs),即 IMF1-IMF6,代表不同时间尺度上的变化。结果呈现出明显的时空异质性。多年变化(IMF1)占总变化的 5.6%-12.4%,呈向北递减趋势,反映了湖泊的河流特征。IFM1 的频谱也显示出显著的 3.6 年波动,这主要归因于支流的流入,尤其是赣江。自 2000 年代以来,各站间的 IMF1 差异突然减小,表明北部和中部地区受到集中采砂活动的影响。年变异(IMF2)最为显著,占总变异的 76.1%-88.4%,并呈现出向南衰减的趋势,这可能是由于长江流量的影响减弱所致。年内尺度(IMF3-IMF6)占总变化的 6.0%-11.5%,与多年变化和年变化相比,空间差异较小。VMD 模型有效地将水位信号分成了不同的频段,有助于深入了解湖泊、支流和长江之间复杂的相互作用,以及采砂等人类活动的影响,从而加深对洪泛平原湖泊动力学的理解。研究结果还暗示了应对鄱阳湖水位下降的重要性。
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来源期刊
Hydrological Processes
Hydrological Processes 环境科学-水资源
CiteScore
6.00
自引率
12.50%
发文量
313
审稿时长
2-4 weeks
期刊介绍: Hydrological Processes is an international journal that publishes original scientific papers advancing understanding of the mechanisms underlying the movement and storage of water in the environment, and the interaction of water with geological, biogeochemical, atmospheric and ecological systems. Not all papers related to water resources are appropriate for submission to this journal; rather we seek papers that clearly articulate the role(s) of hydrological processes.
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