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Leveraging GNSS tropospheric products for machine learning-based land subsidence prediction

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Spatiotemporal variations in groundwater levels and the impact on land subsidence in CanTho, Vietnam

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Summary: The study in Can Tho, Vietnam from 2000 to 2018 revealed significant land subsidence caused by excessive groundwater exploitation. Most of the wells showed a downward trend in groundwater levels, posing risks of increased flooding and saltwater intrusion due to ongoing subsidence. The findings emphasize the importance of effective policy strategies for sustainable water resource management to mitigate further land subsidence.

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