A non-stationary downscaling and gap-filling approach for GRACE/GRACE-FO data under climatic and anthropogenic influences

A non-stationary downscaling and gap-filling approach for GRACE/GRACE-FO data under climatic and anthropogenic influences

Abstract Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) are being increasingly used as valuable data sources for hydrological monitoring. However, their coarse spatial resolution is considered as a limitation for regional studies, especially in areas with remarkable h...

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Bibliographic Details
Main Authors: Seyed Mojtaba Mousavimehr, Mohammad Reza Kavianpour
Format: Article
Language:English
Published: SpringerOpen 2025-04-01
Series:Applied Water Science
Subjects:
Groundwater level
GRACE
Machine learning
Non-stationary time series
Downscaling
Hodrick–Prescott filter
Online Access:https://doi.org/10.1007/s13201-025-02427-z
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https://doi.org/10.1007/s13201-025-02427-z

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