Assessing Differences in Groundwater Hydrology Dynamics Between In Situ Measurements and GRACE-Derived Estimates via Machine Learning: A Test Case of Consequences for Agroecological Relationships Within the Yazoo–Mississippi Delta (USA)

Assessing Differences in Groundwater Hydrology Dynamics Between In Situ Measurements and GRACE-Derived Estimates via Machine Learning: A Test Case of Consequences for Agroecological Relationships Within the Yazoo–Mississippi Delta (USA)

In situ groundwater monitoring is critical for irrigated agroecosystems and informs land cover changes. Yet, such data can pose management challenges and confound agroecological relationships. Correspondingly, satellite-based approaches, including the GRACE-constellation, are increasing. Although in...

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Bibliographic Details
Main Authors: Lucas J. Heintzman, Zahra Ghaffari, Abdel R. Awawdeh, Damien E. Barrett, Lance D. Yarbrough, Greg Easson, Matthew T. Moore, Martin A. Locke, Hakan I. Yasarer
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Hydrology
Subjects:
irrigation
landscape change
artificial intelligence
GRACE mascon
Online Access:https://www.mdpi.com/2306-5338/11/11/186
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