The deadline to submit a session, town hall, or pre-conference workshop proposal for AGU25 has passed. Please search for and review proposed sessions below. Please note this site is frozen as of 4/29/25 and will not reflect any changes to proposals made after this date.


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Abstract: Hydrological Back-casting in Data-Scarce Regions: A Physics-Guided Machine Learning Approach for Historical Groundwater Level Reconstruction (AGU25)

Hydrological Back-casting in Data-Scarce Regions: A Physics-Guided Machine Learning Approach for Historical Groundwater Level Reconstruction

Dolon Banerjee, Indian Institute of Technology Ropar, Civil Engineering Department, Rupnagar, India and Sayantan Ganguly Dr, Indian Institute of Technology Ropar, Civil Engineering Department, Ropar, India
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