EGU22-11393
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Leveraging sap flow data in a catchment-scale hybrid model to improve soil moisture and transpiration estimates

Ralf Loritz1, Maoya Bassiouni2,3, Anke Hildebrandt4, Sibylle Hassler1,5, and Erwin Zehe1
Ralf Loritz et al.
  • 1Karlsruhe Institute of Technology (KIT), Institute for Water and River Basin Management – Hydrology, Karlsruhe, Germany
  • 2Department of Crop Production Ecology, Swedish University of Agricultural Sciences, Uppsala, Sweden
  • 3Department of Environmental Science, Policy and Management, University of California, Berkeley, CA, USA
  • 4Friedrich Schiller University Jena, Institute of Geoscience, Jena, Germany
  • 5Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research – Atmospheric Trace Gases and Remote Sensing, Karlsruhe, Germany

How to cite: Loritz, R., Bassiouni, M., Hildebrandt, A., Hassler, S., and Zehe, E.: Leveraging sap flow data in a catchment-scale hybrid model to improve soil moisture and transpiration estimates, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11393, 2022.

This abstract has been withdrawn on 11 Mar 2022.