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Groundwater storage response to extreme hydrological events in Poyang Lake, China’s largest fresh-water lake
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Type
Article
Citation
Yu, X., Lu, C., Park, E., Zhang, Y., Wu, C., Li, Z., Chen, J., Muhammad Hannan, Liu, B., & Shu, L. (2025). Groundwater storage response to extreme hydrological events in Poyang Lake, China’s largest fresh-water lake. Remote Sensing, 17(6), Article 988. https://doi.org/10.3390/rs17060988
Author
Yu, Xilin
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Lu, Chengpeng
•
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Zhang, Yong
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Wu, Chengcheng
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Li, Zhibin
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Chen, Jing
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Muhammad Hannan
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Liu, Bo
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Shu, Longcang
Abstract
Groundwater systems are important for maintaining ecological balance and ensuring water supplies. However, under the combined pressures of shifting climate patterns and human activities, their responses to extreme events have become increasingly complex. As China’s largest freshwater lake, Poyang Lake supports critical water resources, ecological health, and climate adaptation efforts. Yet, the relationship between groundwater storage (GWS) and extreme hydrological events in this region remains insufficiently studied, hindering effective water management. This study investigates the GWS response to extreme events by downscaling Gravity Recovery and Climate Experiment (GRACE) data and validating it with five years of observed daily groundwater levels. Using GRACE, the Global Land Data Assimilation System (GLDAS), and ERA5 data, a convolutional neural network (CNN)–attention mechanism (A)–long short-term memory (LSTM) model was selected to downscale with high resolution (0.1° × 0.1°) and estimate recovery times for GWS to return to baseline. Our analysis revealed seasonal GWS fluctuations that are in phase with precipitation, evapotranspiration, and groundwater runoff. Recovery durations for extreme flood (2020) and drought (2022) events ranged from 0.8 to 3.1 months and 0.2 to 4.8 months, respectively. A strong correlation was observed between groundwater and meteorological droughts, while the correlation with agricultural drought was significantly weaker. These results indicate that precipitation and groundwater runoff are more sensitive to extreme events than evapotranspiration in influencing GWS changes. These findings highlight the significant sensitivity of precipitation and runoff to GWS, despite improved management efforts.
Date Issued
2025
Publisher
MDPI
Journal
Remote Sensing
Description
The open access publication is available at https://doi.org/10.3390/rs17060988
Grant ID
2024YFC3211600
2021YFC3200502
41971027
524032711
Funding Agency
National Key R&D Program of China
National Natural Science Foundation of China