Basil Kraft

Dr. Basil Kraft is a Professor at ETH Zürich, affiliated with the Professorship for Land-Climate Dynamics. His research focuses on integrating machine learning with physical models to advance understanding of terrestrial hydrology, carbon cycles, and climate dynamics. Key areas include deep learning applications for water cycle modeling, vegetation phenology, and hybrid system modeling.

His work emphasizes data-driven approaches to reconstruct runoff patterns, estimate ecosystem fluxes, and constrain biospheric CO2 dynamics using satellite observations and atmospheric transport models. Recent contributions include frameworks like FLUXCOM-X for global flux products and H2MV for physically constrained water cycle modeling.

Publications highlight innovations in combining physics-based models with recurrent neural networks to address challenges like drought propagation, evapotranspiration upscaling, and carbon flux estimation under moisture stress. His methodologies bridge gaps between environmental observations and predictive modeling, with applications in flood/drought monitoring and climate change impacts.

Notably, no scientific awards are listed in the provided text. He advises no formal students but leads research teams advancing hybrid modeling techniques. His address is Universitätstrasse 16, Zürich, and he can be reached at basil.kraft@env.ethz.ch.