Multitemporal and Multiscale Feature Attribution Methods to Understand the Impact of Climatic and Land Use Features on the Prediction of Groundwater Levels

Michael Engel; Stefan Kunz; Maria Wetzel; Marco Körner

doi:https://doi.org/10.5194/egusphere-egu25-15651

[Back] [Session HS3.3]

EGU25-15651, updated on 15 Mar 2025

https://doi.org/10.5194/egusphere-egu25-15651

EGU General Assembly 2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Oral | Wednesday, 30 Apr, 08:45–08:55 (CEST)

Room 3.16/17

Multitemporal and Multiscale Feature Attribution Methods to Understand the Impact of Climatic and Land Use Features on the Prediction of Groundwater Levels

Michael Engel¹, Stefan Kunz², Maria Wetzel², and Marco Körner¹

Michael Engel et al.

¹Chair of Remote Sensing Technology, Technical University of Munich (TUM)
²Federal Institute for Geosciences and Natural Resources

How to cite: Engel, M., Kunz, S., Wetzel, M., and Körner, M.: Multitemporal and Multiscale Feature Attribution Methods to Understand the Impact of Climatic and Land Use Features on the Prediction of Groundwater Levels, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15651, https://doi.org/10.5194/egusphere-egu25-15651, 2025.

This abstract has been withdrawn on 03 Apr 2025.