This image shows Anneli Guthke

Anneli Guthke

Dr. Dipl.-Ing.

Independent Junior Research Group Leader for Statistical Model-Data Integration
[Photo: SimTech/Max Kovalenko]

Contact

+49 711 685 60157
Website
Business card (VCF)

Universitätsstraße 32
70569 Stuttgart
Room: 227c

Office Hours

Consultation by appointment

Subject

  • Model evaluation
  • Uncertainty and error quantification
  • Stochastic simulation
  • Information-theoretic concepts
  • Hybrid machine-learning/simulation approaches
  • Hydro(geo)logical modelling
Publications:

  1. 2023 (submitted)

    1. H.-F. Hsueh, A. Guthke, T. Wöhling, and W. Nowak, “Optimized Predictive Coverage by Averaging Time-Windowed Bayesian Distributions,” Water Resources Research.
    2. I. Banerjee, A. Guthke, C. J. C. Van de Ven, K. G. Mumford, and W. Nowak, “Comparison of Four Competing Invasion Percolation Models for Gas Flow in Porous Media,” Water Resources Research.

  2. 2023

    1. I. Banerjee, P. Walter, A. Guthke, K. G. Mumford, and W. Nowak, “The Method of Forced Probabilities: A Computation Trick for Bayesian Model Evidence,” Computational Geosciences, vol. 27, pp. 45–62, 2023, doi: 10.1007/s10596-022-10179-x.

  3. 2022

    1. H. Hsueh, A. Guthke, T. Wöhling, and W. Nowak, “Diagnosis of model-structural errors with a sliding time-window Bayesian analysis,” Water Resources Research, vol. 58, p. e2021WR030590, 2022, doi: doi:10.1029/2021WR030590.

  4. 2021

    1. S. Reuschen, A. Guthke, and W. Nowak, “The Four Ways to Consider Measurement Noise in Bayesian Model Selection - And Which One to Choose,” Water Resources Research, vol. 57, p. e2021WR030391, 2021, doi: 10.1029/2021WR030391.
    2. I. Banerjee, A. Guthke, C. J. C. Van de Ven, K. G. Mumford, and W. Nowak, “Overcoming the model-data-fit problem in porous media: A quantitative method to compare invasion-percolation models to high-resolution data,” Water Resources Research, vol. 57, no. 7, Art. no. 7, 2021, doi: 10.1029/2021WR029986.

  5. 2020

    1. A. Guthke, “The Unified Risk Equation - An Attempt to Unify Risk Assessment across Disciplines,” Munich, Germany: Engineering Risk Analysis Group, Technical University of Munich, Apr. 2020.
    2. M. Höge, A. Guthke, and W. Nowak, “Bayesian Model Weighting: The Many Faces of Model Averaging,” Water, vol. 12, no. 2, Art. no. 2, 2020, doi: 10.3390/w12020309.
    3. A. Guthke et al., “A unified framework for quantitative interdisciplinary flood risk assessment,” online: AGU Fall Meeting 2020, Dec. 2020.
    4. I. Banerjee, A. Guthke, C. J. C. V. D. Ven, K. Mumford, and W. Nowak, “Overcoming the Model-to-Experimental Data Fit Problem in Porous Media: a New Quantitative Method to Evaluate and Compare Models,” online: AGU Fall Meeting 2020, Dec. 2020.
    5. C. Jackisch, A. Schibalski, B. Schröder, W. Nowak, and A. Guthke, “Providing relevant uncertainty information to decision makers: Subjective post-processing of rigorous Bayesian uncertainty assessment of model projections,” online: AGU Fall Meeting 2020, Dec. 2020.
    6. A. Schäfer Rodrigues Silva, A. Guthke, M. Höge, O. A. Cirpka, and W. Nowak, “Strategies for simplifying reactive transport models - a Bayesian model comparison,” Water Resources Research, vol. 56, p. e2020WR028100, 2020, doi: 10.1029/2020WR028100.
    7. H.-F. Hsueh, A. Guthke, T. Wöhling, and W. Nowak, “Diagnosing Model-structural Errors with a Sliding Time-window Bayesian Analysis,” online: AGU Fall Meeting 2020, Dec. 2020.

  6. 2019

    1. A. Guthke, “Justifiability is key - Bayesian analysis of system and model complexity,” Esch-sur-Alzette, Luxembourg: 10th EGU Leonardo Conference on Earth’s hydrological cycle: Global change, landscape ageing and the pulse of catchments, Oct. 2019.
    2. M. Höge, A. Guthke, and W. Nowak, “The Hydrologist’s Guide to Bayesian Model Selection, Averaging and Combination,” Journal of Hydrology, vol. 572, pp. 96–107, May 2019, doi: https://doi.org/10.1016/j.jhydrol.2019.01.072.
    3. D. F. Motavita, R. Chow, A. Guthke, and W. Nowak, “The Comprehensive Differential Split-Sample Test: A stress-test for hydrological model robustness under climate variability,” Journal of Hydrology, vol. 573, pp. 501–515, 2019, doi: 10.1016/j.jhydrol.2019.03.054.

  7. 2018

    1. A. Guthke, “A Bayesian take on model choice uncertainty: Statistical tools for model evaluation, selection and combination,” Karlsruhe, Germany: KIT, Institut für Wasser und Gewässerentwicklung, Lehrstuhl für Hydrologie, Jul. 2018.
    2. A. Schäfer-Rodrigues-Silva, T. Seitz, Anneli. Guthke, and W. Nowak, “Working with multi-model ensembles - what makes models differ and how can we visualize ensembles?,” Tübingen, Germany: Seminar of the Research Training Group “Integrated Hydrosystem Modelling,” Jun. 2018.
    3. P. Darscheid, A. Guthke, and U. Ehret, “A Maximum-Entropy Method to Estimate Discrete Distributions  from Samples Ensuring Nonzero Probabilities,” Entropy, vol. 20, no. 8, Art. no. 8, 2018, doi: 10.3390/e20080601.
    4. S. Oladyshkin, A. Guthke, F. Mohamadi, R. Kopmann, and W. Nowak, “Model selection under computational time constraints: application to river engineering,” Saint-Malo, France: XXII. International Conference on Computational Methods in Water Resources (CMWR), Jun. 2018.
    5. F. Mohammadi, R. Kopmann, A. Guthke, S. Oladyshkin, and W. Nowak, “Bayesian selection of hydro-morphodynamic models under computational  time constraints.,” Advances in Water Resources, vol. 117, pp. 53–64, 2018, doi: 10.1016/j.advwatres.2018.05.007.
    6. Anneli. Guthke, “Model selection on solid ground: rigorous comparison of nine ways to evaluate Bayesian evidence,” Adelaide, Australia: STAHY 2018 Best Paper Award Session, Sep. 2018.
    7. A. Guthke, M. Höge, and W. Nowak, “How model selection and averaging strategies help us improve hydrological models,” in General Assembly 2018, Geophysical Research Abstracts 20: EGU2018-12797, 2018, in General Assembly 2018, Geophysical Research Abstracts 20: EGU2018-12797, 2018. Vienna, Austria: European Geosciences Union (EGU), Apr. 2018.
    8. A. Schäfer-Rodrigues-Silva, A. Guthke, and W. Nowak, “The importance of model similarity in multi-model problems,” Stuttgart, Germany: Meeting of the international doctoral program “Environment Water,” Feb. 2018.
    9. A. Schäfer-Rodrigues-Silva, Anneli. Guthke, and W. Nowak, “Quantifying similarity in multi-model ensembles,” Tübingen, Germany: International Conference on Integrated Hydrosystem Modelling, Apr. 2018.
    10. A. Guthke and W. Nowak, “Entropy-based experimental design for optimal model discrimination in the Geosciences,” Santander, Spain: Second Workshop on Information Theory and the Earth Sciences, May 2018.
    11. A. Schäfer-Rodrigues-Silva, T. Seitz, Anneli. Guthke, and W. Nowak, “Quantifying and visualizing similarity in multi-model ensembles,” Cargese, France: Summer school on “Flow and Transport in Porous and Fractured media,” Jun. 2018.
    12. A. Guthke, S. Oladyshkin, F. Mohammadi, R. Kopmann, and W. Nowak, “Bayesian model selection under computational time constraints: application to river modeling,” in Fall Meeting 2018, in Fall Meeting 2018. Washington, D.C., USA: American Geophysical Union (AGU), Dec. 2018.

  8. 2017

    1. A. Guthke, “Defensible Model Complexity: A Call for Data-Based and Goal-Oriented Model Choice,” Groundwater, vol. 55, no. 5, Art. no. 5, 2017, doi: 10.1111/gwat.12554.
    2. A. Guthke, M. Höge, and W. Nowak, “Bayesian model evidence as a model evaluation metric,” in General Assembly 2017, Geophysical Research Abstracts 19: EGU2017-13390-1, 2017, in General Assembly 2017, Geophysical Research Abstracts 19: EGU2017-13390-1, 2017. Vienna, Austria: European Geosciences Union (EGU), Apr. 2017.

  9. 2016

    1. O. Lötgering-Lin, A. Schöniger, W. Nowak, and J. Gross, “Bayesian Model Selection helps to Choose Objectively between Thermodynamic Models: A Demonstration of Selecting a Viscosity-Model based on Entropy Scaling,” Industrial & Engineering Chemistry Research, vol. 55, no. 38, Art. no. 38, 2016, doi: 10.1021/acs.iecr.6b02671.
    2. W. Nowak and A. Guthke, “Entropy-based experimental design for optimal model discrimination in the geosciences,” Entropy, vol. 18, no. 11, Art. no. 11, 2016, doi: 10.3390/e18110409.
    3. A. Schöniger, W. A. Illman, T. Wöhling, and W. Nowak, “Which level of model complexity is justified by your data? A Bayesian answer,” in General Assembly 2016, Geophysical Research Abstracts 20: EGU2016-12413, 2016, in General Assembly 2016, Geophysical Research Abstracts 20: EGU2016-12413, 2016. Vienna, Austria: European Geosciences Union (EGU), Apr. 2016.

  10. 2015

    1. T. Wöhling, A. Schöniger, S. Gayler, and W. Nowak, “Bayesian model averaging to explore the worth of data for soil-plant model selection and prediction,” Water Resources Research, vol. 51, no. 4, Art. no. 4, 2015, doi: 10.1002/2014WR016292.
    2. A. Schöniger, T. Wöhling, and W. Nowak, “A statistical concept to assess the uncertainty in Bayesian model weights and its impact on model ranking,” Water Resources Research, vol. 51, no. 9, Art. no. 9, 2015, doi: 10.1002/2015WR016918.
    3. A. Schöniger, “Multi-model approaches to quantify conceptual uncertainty in environmental modelling,” Tübingen, Germany: International Conference on Integrated Hydrosystem Modelling, Apr. 2015.
    4. A. Schöniger, W. Illman, T. Wöhling, and W. Nowak, “Finding the Right Balance Between Groundwater Model Complexity and Experimental Effort via Bayesian Model Selection,” Journal of Hydrology, vol. 531, no. 1, Art. no. 1, 2015, doi: 10.1016/j.jhydrol.2015.07.047.
    5. A. Schöniger, T. Wöhling, L. Samaniego, and W. Nowak, “On the various (good and bad) ways to evaluate Bayesian model weights,” in General Assembly 2015, Geophysical Research Abstracts 17: EGU2015-2084-2, 2015, in General Assembly 2015, Geophysical Research Abstracts 17: EGU2015-2084-2, 2015. Vienna, Austria: European Geosciences Union (EGU), Apr. 2015.
    6. W. Nowak, T. Wöhling, and A. Schöniger, “Lessons learned from a past series of Bayesian model averaging studies for soil/plant models,” in General Assembly 2015, Geophysical Research Abstracts 17: EGU2015-10293-1, 2015, in General Assembly 2015, Geophysical Research Abstracts 17: EGU2015-10293-1, 2015. Vienna, Austria: European Geosciences Union (EGU), Apr. 2015.
    7. O. Lötgering-Lin, M. Hopp, J. Gross, A. Schöniger, and W. Nowak, “Prediction of pure component and mixture viscosities using PCP-SAFT and entropy scaling,” Houston, TX, USA: SAFT 2015, May 2015.

  11. 2014

    1. A. Schöniger, T. Wöhling, and W. Nowak, “How reliable is Bayesian model averaging under noisy data? Statistical assessment and implications for robust model selection,” in General Assembly 2014, Geophysical Research Abstracts 16: EGU2014-2211, 2014, in General Assembly 2014, Geophysical Research Abstracts 16: EGU2014-2211, 2014. Vienna, Austria: European Geosciences Union (EGU), 2014.
    2. A. Schöniger, T. Wöhling, and W. Nowak, “How to address measurement noise in Bayesian model averaging,” in Fall Meeting 2014, Abstract: H23K-1017, in Fall Meeting 2014, Abstract: H23K-1017. San Francisco, CA, USA: American Geophysical Union (AGU), Dec. 2014.
    3. Anneli. Schöniger, T. Wöhling, L. Samaniego, and W. Nowak, “Model selection on solid ground: rigorous comparison of nine ways to evaluate Bayesian evidence,” Water Resources Research, vol. 50, no. 12, Art. no. 12, 2014, doi: 10.1002/2014WR016062.

  12. 2013

    1. A. Schöniger and W. N. T. Wöhling, “Do Bayesian model weights tell the whole story? New analysis and optimal design tools for maximum-confidence model selection,” in Fall Meeting 2013, Abstract: H33J-02, in Fall Meeting 2013, Abstract: H33J-02. San Francisco, CA, USA: American Geophysical Union (AGU), Dec. 2013.

  13. 2012

    1. A. Schöniger, W. Nowak, and H. J. H. Franssen, “Parameter estimation by ensemble Kalman filters with transformed data: Approach and application to hydraulic tomography,” Water Resources Research, vol. 48, no. W04502, Art. no. W04502, 2012, doi: 10.1029/2011WR010462 (was the top cited 2012 WRR article in 2013).
  • Since Oct. 2021: Independent Junior Research Group Leader with SimTech, University of Stuttgart/Germany
  • 2017 - 2021: Postdoctoral researcher with the Department of Stochastic Simulation and Safety Research for Hydrosystems (IWS / LS³), University of Stuttgart/Germany
  • 2015 - 2016: Postdoctoral researcher with the Center for Applied Geoscience (ZAG), University of Tübingen/Germany
  • 2012 - 2015: Doctoral researcher within the International Research Training Group "Integrated Hydrosystem Modelling" (GRK 1829), University of Tübingen/Germany and University of Waterloo/ON, Canada
  • 2010 - 2018: Environmental consultant with BoSS Consult Gmbh, Stuttgart/Germany
  • 2004 - 2010: Studies of environmental engineering (Dipl.-Ing.) with a major in hydrosystem modelling, University of Stuttgart/Germany

EXC

  • Participating Researcher
  • Junior Research Group Leader
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