Tina Trautmann

Doctoral Researcher
BGI Team
Global diagnostic models
Intern. Max Planck Research School for Global Biogeochemical Cycles (IMPRS-gBGC)
+49 3641 57-6229

Main Focus

 My main focus is on improving our understanding of the large-scale water cycle by combining simple conceptual hydrologic modelling approaches and multiple Earth-observation based data products.

  • large scale hydrological modelling
  • variations of terrestrial water storages
  • the interaction between vegetation and the hydrological cycle
  • earth-observation based products
  • model-data fusion techniques and multi-criteria model calibration

Curriculum Vitae

  • since Feb 2017: PhD Researcher, Max-Planck-Institute for Biogeochemistry Jena, Department of Biogeochemical Integration, and University of Potsdam, Institute of Environmental Science & Geography
    • Topic: Understanding global Water Storage Variations using Model-Data Integration
    • supervised by Dr. Martin Jung (MPI-BGC Jena) and Prof. Dr. Andreas Güntner (GFZ Potsdam)
    • associated member of the International Max Planck Research School for Biogeochemical Cycles (IMPRS-gBGC)
  • Sep 2019 - Dec 2019: Research Stay with Prof. Dr. Hyungjun Kim, Institute of Industrial Science, University of Tokyo, Japan
  • Aug 2016 - Dec 2016: Scientist, Max-Planck-Institute for Biogeochemistry Jena, Department of Biogeochemical Integration

  • Oct 2013 - Jul 2016: Master of Science in Geoinformatics, Friedrich-Schiller University Jena
    • Focus: (hydrological) modelling, spatial analysis using geographic information systems, processing and analysis of optical satellite data
    • Thesis: Macroscopic diagnostic modeling of the hydrological cycle: Understanding the dynamics of water pools in snow affected regions
  • Oct 2010 - Sep 2013: Bachelor of Science in Geography, Friedrich-Schiller University Jena
    • Focus: Geoinformatics, Remote Sensing, Soil Science, Geoecology
    • Thesis: Monthly hydrological modeling and process analysis of the Cuito River upstream of Cuito Cuanavale, Angola, using the model JAMS/J2000g

    • Exam Award 2017 of the Faculty of Chemistry and Earth Science for Master Thesis, Friedrich Schiller University Jena

    • Trautmann, T., Koirala, S., Güntner, A., Kim, H., Jung, M., Implications of river storage for integrating GRACE TWS observations into a global hydrological model, submitted to Geophysical Research Letters.
    • Trautmann, T., Koirala, S., Carvalhais, N., Güntner, A., Jung, M., The importance of vegetation in understanding terrestrial water storage variations, Hydrology and Earth System Sciences, 26, 4, 1089-1109, 2022, doi:10.5194/hess-26-1089-2022
    • Trautmann, T., Koirala, S., Carvalhais, N., Eicker, A., Fink, M., Niemann, C., Jung, M., Understanding terrestrial water storage variations in northern latitudes across scales, Hydrology and Earth System Sciences, 22, 7, 4061-4082, 07, 2018, doi:10.5194/hess-22-4061-2018
    • AGU Fall Meeting 2021, New Orleans, USA; Talk: Implications of river storage on assimilating GRACE TWS variations into a simple hydrological modeling framework
    • EGU General Assembly 2020, online conference; PICO/Display: Using Earth Observation Data of Vegetation to improve global hydrological Simulations, doi.org/10.5194/egusphere-egu2020-9951
    • AGU Fall Meeting 2019, San Francisco, USA; Talk: Improving the Representation of Vegetation in Global Hydrological Models using Earth Observation Data
    • ESA CCI Soil Moisture User Workshop 2018, TU Wien, Vienna, Austria; Talk: Improving a hydrological model with global (soil moisture) data
    • 8th GEWEX Open Science Conference: Extremes and Water on the Edge, Canmore, Canada; Poster & Lightning Talk: Understanding spatio-temporal variations of the Terrestrial Water Storage
    • EGU General Assembly 2017, Vienna, Austria; PICO: Understanding the spatio-temporal composition of Terrestrial Water Storage variations using a model-data fusion approach

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