Dr. Dipl.-Ing.

Anneli Guthke (geb. Schöniger)

Postdoc
Institute for Modelling Hydraulic and Environmental Systems (LS3/SimTech)

Contact

+49-711-685 60157

Business card (VCF)

Pfaffenwaldring 5a
D-70569 Stuttgart
Room: 2.29

  1. 2019 (accepted)

    1. Motavita DF, Chow R, Guthke A, Nowak W. Assessing the impact of calibration and validation data choices on hydrological model performance: a model stress-test. Journal of Hydrology. 2019;
  2. 2019

    1. Höge M, Guthke A, Nowak W. The Hydrologist’s Guide to Bayesian Model Selection, Averaging and Combination. Journal of Hydrology [Internet]. 2019;572:96–107. Available from: http://www.sciencedirect.com/science/article/pii/S0022169419301532
  3. 2018

    1. Guthke A, Höge M, Nowak W. How model selection and averaging strategies help us improve hydrological models. In: General Assembly 2018, Geophysical Research Abstracts 20: EGU2018-12797, 2018. Vienna, Austria: European Geosciences Union (EGU); 2018. (General Assembly 2018, Geophysical Research Abstracts 20: EGU2018-12797, 2018).
    2. Guthke A, Nowak W. Entropy-based experimental design for optimal model discrimination in the Geosciences. In Santander, Spain: Second Workshop on Information Theory and the Earth Sciences; 2018.
    3. Oladyshkin S, Guthke A, Mohamadi F, Kopmann R, Nowak W. Model selection under computational time constraints: application to river engineering. In Saint-Malo, France: XXII. International Conference on Computational Methods in Water Resources (CMWR); 2018.
    4. Schäfer-Rodrigues-Silva A, Guthke A, Nowak W. The importance of model similarity in multi-model problems. In Stuttgart, Germany: Meeting of the international doctoral program “Environment Water”; 2018.
    5. Guthke A, Oladyshkin S, Mohammadi F, Kopmann R, Nowak W. Bayesian model selection under computational time constraints: application to river modeling. In: Fall Meeting 2018. Washington, D.C., USA: American Geophysical Union (AGU); 2018. (Fall Meeting 2018).
    6. Darscheid P, Guthke A, Ehret U. A Maximum-Entropy Method to Estimate Discrete Distributions  from Samples Ensuring Nonzero Probabilities. Entropy [Internet]. 2018;20(8). Available from: http://www.mdpi.com/1099-4300/20/8/601
    7. Schäfer-Rodrigues-Silva A, Seitz T, Guthke A, Nowak W. Quantifying and visualizing similarity in multi-model ensembles. In Cargese, France: Summer school on “Flow and Transport in Porous and Fractured media”; 2018.
    8. Guthke A. A Bayesian take on model choice uncertainty: Statistical tools for model evaluation, selection and combination. In Karlsruhe, Germany: KIT, Institut für Wasser und Gewässerentwicklung, Lehrstuhl für Hydrologie; 2018.
    9. Schäfer-Rodrigues-Silva A, Guthke A, Nowak W. Quantifying similarity in multi-model ensembles. In Tübingen, Germany: International Conference on Integrated Hydrosystem Modelling; 2018.
    10. Mohammadi F, Kopmann R, Guthke A, Oladyshkin S, Nowak W. Bayesian selection of hydro-morphodynamic models under computational  time constraints. Advances in Water Resources [Internet]. 2018;117:53–64. Available from: http://www.sciencedirect.com/science/article/pii/S0309170817311909
    11. Schäfer-Rodrigues-Silva A, Seitz T, Guthke A, Nowak W. Working with multi-model ensembles - what makes models differ and how can we visualize ensembles? In Tübingen, Germany: Seminar of the Research Training Group “Integrated Hydrosystem Modelling”; 2018.
  4. 2017

    1. Guthke A. Defensible Model Complexity: A Call for Data-Based and Goal-Oriented Model Choice. Groundwater [Internet]. 2017;55(5). Available from: http://dx.doi.org/10.1111/gwat.12554
    2. Guthke A, Höge M, Nowak W. Bayesian model evidence as a model evaluation metric. In: General Assembly 2017, Geophysical Research Abstracts 19: EGU2017-13390-1, 2017. Vienna, Austria: European Geosciences Union (EGU); 2017. (General Assembly 2017, Geophysical Research Abstracts 19: EGU2017-13390-1, 2017).
  5. 2016

    1. Lötgering-Lin O, Schöniger A, Nowak W, Gross J. 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. 2016;55(38):10191–207.
    2. Nowak W, Guthke A. Entropy-based experimental design for optimal model discrimination in the geosciences. Entropy. 2016;18(11):409.
    3. Schöniger A, Illman WA, Wöhling T, Nowak W. Which level of model complexity is justified by your data? A Bayesian answer. In: General Assembly 2016, Geophysical Research Abstracts 20: EGU2016-12413, 2016. Vienna, Austria: European Geosciences Union (EGU); 2016. (General Assembly 2016, Geophysical Research Abstracts 20: EGU2016-12413, 2016).
  6. 2015

    1. Schöniger A, Wöhling T, Nowak W. A statistical concept to assess the uncertainty in Bayesian model weights and its impact on model ranking. Water Resources Research. 2015;51(9):7524–46.
    2. Nowak W, Wöhling T, Schöniger A. 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. Vienna, Austria: European Geosciences Union (EGU); 2015. (General Assembly 2015, Geophysical Research Abstracts 17: EGU2015-10293-1, 2015).
    3. Wöhling T, Schöniger A, Gayler S, Nowak W. Bayesian model averaging to explore the worth of data for soil-plant model selection and prediction. Water Resources Research. 2015;51(4):2825–46.
    4. Schöniger A, Wöhling T, Samaniego L, Nowak W. On the various (good and bad) ways to evaluate Bayesian model weights. In: General Assembly 2015, Geophysical Research Abstracts 17: EGU2015-2084-2, 2015. Vienna, Austria: European Geosciences Union (EGU); 2015. (General Assembly 2015, Geophysical Research Abstracts 17: EGU2015-2084-2, 2015).
    5. Schöniger A, Illman W, Wöhling T, Nowak W. Finding the Right Balance Between Groundwater Model Complexity and Experimental Effort via Bayesian Model Selection. Journal of Hydrology. 2015;531(1):96–110.
    6. Lötgering-Lin O, Hopp M, Gross J, Schöniger A, Nowak W. Prediction of pure component and mixture viscosities using PCP-SAFT and entropy scaling. In Houston, TX, USA: SAFT 2015; 2015.
    7. Schöniger A. Multi-model approaches to quantify conceptual uncertainty in environmental modelling. In Tübingen, Germany: International Conference on Integrated Hydrosystem Modelling; 2015.
  7. 2014

    1. Schöniger A, Wöhling T, Nowak W. How to address measurement noise in Bayesian model averaging. In: Fall Meeting 2014, Abstract: H23K-1017. San Francisco, CA, USA: American Geophysical Union (AGU); 2014. (Fall Meeting 2014, Abstract: H23K-1017).
    2. Schöniger A, Wöhling T, Nowak W. 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. Vienna, Austria: European Geosciences Union (EGU); 2014. (General Assembly 2014, Geophysical Research Abstracts 16: EGU2014-2211, 2014).
    3. Schöniger A, Wöhling T, Samaniego L, Nowak W. Model selection on solid ground: rigorous comparison of nine ways to evaluate Bayesian evidence. Water Resources Research. 2014;50(12):9484–513.
  8. 2013

    1. Schöniger A, Wöhling WNT. 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. San Francisco, CA, USA: American Geophysical Union (AGU); 2013. (Fall Meeting 2013, Abstract: H33J-02).
  9. 2012

    1. Schöniger A, Nowak W, Franssen HJH. Parameter estimation by ensemble Kalman filters with transformed data: Approach and application to hydraulic tomography. Water Resources Research. 2012;48(W04502).

03/2010 Environmental Engineering, University of Stuttgart
08/2015 PhD., Center for Applied Geosciences, University of Tübingen
Since 07/2010 Project manager, BoSS Consult GmbH, Stuttgart
09/2015- 12/2016 Postdoc, Center for Applied Geosciences, University of Tübingen
Since 01/2017 Postdoc, Institute for Modelling Hydraulic and Environmental Systems, University of Stuttgart

Stochastic modeling of underground flow and transport processes