Dieses Bild zeigt Wolfgang Nowak

Wolfgang Nowak

Herr Prof. Dr.-Ing.

Leiter
Institut für Wasser- und Umweltsystemmodellierung
Lehrstuhl für Stochastische Simulation und Sicherheitsforschung für Hydrosysteme, Co-Sprecher des Exzellenzclusters EXC 2075 "Data-Integrated Simulation Sciences"
[Foto: SimTech/Max Kovalenko]

Kontakt

Pfaffenwaldring 5a
70569 Stuttgart
Raum: 2.27

Sprechstunde

Nach Vereinbarung per E-Mail

  1. 2024 (submitted)

    1. Ejaz F, Wildt N, Wöhling T, Nowak W. Estimating total groundwater storage and its associated uncertainty through spatiotemporal Kriging of groundwater-level data. Journal of Hydrology.
    2. Xu T, Xiao S, Reuschen S, Wildt N, Franssen HJH, Nowak W. Towards a community-wide effort for benchmarking in subsurface hydrological inversion: benchmarking cases, high-fidelity reference solutions, procedure and a first comparison. Hydrology and Earth System Sciences.
    3. Nowak W, Brünnette T, Schalkers M, Möller M. Overdispersion in gate tomography: Experiments and continuous, two-scale random walk model on the Bloch sphere. ACM Transactions on Quantum Computing.
    4. Kröker I, Brünnette T, Wildt N, Oreamuno MFM, Kohlhaas R, Oladyshkin S, u. a. Bayesian Active Learning for Regularized Multi-Resolution Arbitrary Polynomial Chaos using Information Theory. International Journal for Uncertainty Quantification.
  2. 2024 (accepted)

    1. Hsueh HF, Guthke A, Wöhling T, Nowak W. Optimized Predictive Coverage by Averaging Time-Windowed Bayesian Distributions. Water Resources Research.
  3. 2024

    1. Kröker I, Nißler E, Oladyshkin S, Nowak W, Haslauer C. Data-driven surrogate-based Bayesian model calibration for predicting vadose zone temperatures in drinking water supply pipes. In: Geophys Res Abstr. Vienna: EGU General Assembly 2024; 2024. (Geophys. Res. Abstr.; Bde. 25, EGU2024-7820).
    2. Chen Q, Boxberg MS, Menzel N, Oreamuno MFM, Nowak W, Oladyshkin S, u. a. The site selection data hub: a data-centric approach for integrated simulation workflow management in radioactive waste disposal site selection. In: Geophys Res Abstr. Vienna: EGU General Assembly 2024; 2024. (Geophys. Res. Abstr.; Bde. 26, EGU24-12859).
    3. Zare H, Viswanathan M, Weber TK, Ingwersen J, Nowak W, Gayler S, u. a. Improving winter wheat yield prediction by accounting for weather and model parameter uncertainty while assimilating LAI and updating weather data within a crop model. European Journal of Agronomy. März 2024;156:127149.
    4. Schwindt S, Meisinger L, Negreiros B, and Tim Schneider, Nowak W. Transfer learning achieves high recall for object classification in fluvial environments with limited data. Geomorphology. April 2024;455:109185.
    5. Kurgyis K, Achtziger-Zupančič P, Bjorge M, Boxberg MS, Broggi M, Buchwald J, u. a. Uncertainties and robustness with regard to the safety of a repository for high-level radioactive waste: Introduction of a research initiative. Environmental Earth Sciences. Januar 2024;83(2).
    6. Morales Oreamuno MF, Oladyshkin S, Nowak W. Error-aware surrogate modelling with input dimension reduction for groundwater modelling in heterogenous media. In: Geophys Res Abstr. Vienna: EGU General Assembly 2024; 2024. (Geophys. Res. Abstr.; Bde. 26, EGU24-12586).
    7. Ejaz F, Wildt N, Wöhling T, Nowak W. Estimating catchment-wide total groundwater storage via space-time kriging provides calibration data for catchment-scale groundwater balance models. In: Geophys Res Abstr. Vienna: EGU General Assembly 2024; 2024. (Geophys. Res. Abstr.; Bde. 25, EGU2024-10521).
    8. Martin P, Haas J, Nowak W. Coordinated Optimization of Water-Energy System Operation. In: EURO 2024 Conference Handbook and Abstracts. Copenhagen DK: 33rd European Conference on Operational Research (EURO 2024); 2024. (EURO 2024 Conference Handbook and Abstracts).
    9. Xiao S, Nowak W. Failure probability estimation with failure samples: An extension of the two-stage Markov chain Monte Carlo simulation. Mechanical Systems and Signal Processing [Internet]. Februar 2024;212:111300. Verfügbar unter: https://www.sciencedirect.com/science/article/pii/S0888327024001985
    10. Zare H, Weber TK, Ingwersen J, Nowak W, Gayler S, Streck T. Within-Season crop yield prediction by a multi-model ensemble with integrated data assimilation. Field Crops Research. Februar 2024;308(109293).
    11. Weber TK, Schade A, Rauch R, Ingwersen J, Gayler S, Nowak W, u. a. Bayesian Methods for Parameter Inference, Uncertainty Quantification, Error Modelling, Model Learning and Model Choice in Hydrology. In: Geophys Res Abstr. Vienna: EGU General Assembly 2024; 2024. (Geophys. Res. Abstr.; Bde. 25, EGU2024-2300).
  4. 2023 (submitted)

    1. Banerjee I, Guthke A, Van de Ven CJC, Mumford KG, Nowak W. Comparison of Four Competing Invasion Percolation Models for Gas Flow in Porous Media. Water Resources Research.
  5. 2023

    1. Köse G, Oladyshkin S, Nowak W. Optimizing Pressure Monitoring in a Water Distribution Network through Bayesian Calibration. In: 18th Pipeline Technology Conference 2023 [Internet]. Berlin, Germany: EITEP Institute; 2023. (18th Pipeline Technology Conference 2023). Verfügbar unter: https://www.pipeline-conference.com/abstracts/optimizing-pressure-monitoring-water-distribution-network-through-bayesian-calibration
    2. Kohlhaas R, Kröker I, Oladyshkin S, Nowak W. Gaussian active learning on multi-resolution arbitrary polynomial chaos emulator: concept for bias correction, assessment of surrogate reliability and its application to the carbon dioxide benchmark. Computational Geosciences. 2023;27(3):1–21.
    3. Horuz CC, Karlbauer M, Praditia T, Butz MV, Oladyshkin S, Nowak W, u. a. Physical Domain Reconstruction with Finite Volume Neural Networks. Applied Artificial Intelligence. 2023;37(1):2204261.
    4. Oladyshkin S, Praditia T, Kroeker I, Mohammadi F, Nowak W, Otte S. The Deep Arbitrary Polynomial Chaos Neural Network or how Deep Artificial Neural Networks could benefit from Data-Driven Homogeneous Chaos Theory. Neural Networks. 2023;166:85–104.
    5. Martin P, Haas J, Nowak W. Coordinated Optimization of Water Supply Systems with Evolving Energy Systems. In: Fall Meeting 2023. San Francisco, CA, USA: American Geophysical Union (AGU); 2023. (Fall Meeting 2023).
    6. Bürkner PC, Kröker I, Oladyshkin S, Nowak W. The sparse Polynomial Chaos expansion: a fully Bayesian approach with joint priors on the coefficients and global selection of terms. Journal of Computational Physics. 2023;112210.
    7. Morales Oreamuno MF, Oladyshkin S, Nowak W. Information-Theoretic Scores for Bayesian Model Selection and Similarity Analysis: Concept and Application to a Groundwater Problem. Water Resources Research. Juli 2023;59(7):e2022WR033711.
    8. Ejaz F, Wöhling T, Guthke A, Nowak W. Comprehensive uncertainty analysis for surface water and groundwater forecasts under climate change based on a lumped geo-hydrological model. Journal of Hydrology [Internet]. Oktober 2023;626-B:130323. Verfügbar unter: https://www.sciencedirect.com/science/article/pii/S0022169423012659
    9. Bruennette T, Werneck L, Keip MA, Nowak W. Random Fracture Models - Towards Statistical Realism and Validation. In: Fall Meeting 2023. San Francisco, CA, USA: American Geophysical Union (AGU); 2023. (Fall Meeting 2023).
    10. Wildt N, Scheurer S, Nowak W, Haslauer C. Learning PFAS mechanisms with a FInite Volume Neural Network (FINN). In: Fall Meeting 2023. San Francisco, CA, USA: American Geophysical Union (AGU); 2023. (Fall Meeting 2023).
    11. Dibak C, Nowak W, Dürr F, Rothermel K. Using Surrogate Models and Data Assimilation for Efficient Mobile Simulations. IEEE Transactions on Mobile Computing. 2023;22(3):1856–66.
    12. Zhang L, Nowak W, Oladyshkin S, Wang Y, Cai J. Opportunities and challenges in CO2 geologic utilization and storage. Advances in Geo-Energy Research. Juli 2023;8(3):141–5.
    13. Wagner A, Sonntag A, Reuschen S, Nowak W, Ehlers W. Hydraulically induced fracturing in heterogeneous porous media using a TPM-phase-field model and geostatistics. Proceedings in Applied Mathematics and Mechanics. 2023;23:e202200118.
    14. Mouris K, Acuna Espinoza E, Schwindt S, Mohammadi F, Haun S, Wieprecht S, u. a. Stability criteria for Bayesian calibration of reservoir sedimentation models. Modeling Earth Systems and Environment [Internet]. 2023; Verfügbar unter: https://doi.org/10.1007/s40808-023-01712-7
    15. Schwindt S, Medrano SC, Mouris K, Beckers F, Haun S, Nowak W, u. a. Bayesian calibration points to misconceptions in three-dimensional hydrodynamic reservoir modelling. Water Resources Research. 2023;59:e2022WR033660.
    16. Banerjee I, Walter P, Guthke A, Mumford KG, Nowak W. The Method of Forced Probabilities: A Computation Trick for Bayesian Model Evidence. Computational Geosciences. 2023;27:45–62.
  6. 2022

    1. Ejaz F, Wöhling T, Höge M, Nowak W. Lumped geohydrological modelling for long-term predictions of groundwater storage and depletion. Journal of Hydrology. 2022;606:127347.
    2. González-Nicolás A, Bilgic D, Kröker I, Mayar A, Trevisan L, Steeb H, u. a. Optimal exposure time in Gamma-Ray Attenuation experiments for monitoring time-dependent densities. Transport in Porous Media. 2022;143:463–96.
    3. Hsueh H fang, Guthke A, Wöhling T, Nowak W. Diagnosis of model-structural errors with a sliding time-window Bayesian analysis. Water Resources Research. 2022;58:e2021WR030590.
    4. Xiao S, Nowak W. Reliability sensitivity analysis based on a two-stage Markov chain Monte Carlo simulation. Aerospace Science and Technology. 2022;130:107938.
    5. Schäfer Rodrigues Silva A, Weber TK, Gayler S, Guthke A, Höge M, Streck T, u. a. Diagnosing Similarities in Probabilistic Multi-Model Ensembles - an Application to Soil-Plant-Growth-Modeling. Modeling Earth Systems and Environment. 2022;8:5143–5175.
    6. Zare H, Weber TK, Ingwersen J, Nowak W, Gayler S, Streck T. Combining crop modelling with remote sensing data using a particle filtering technique to produce real-time forecasts of winter wheat yields under uncertain boundary conditions. Remote Sensing. 2022;14:1360.
    7. Cheng K, Z L, Xiao S, Oladyshkin S, Nowak W. Mixed covariance function Kriging model for uncertainty quantification. International Journal for Uncertainty Quantification. 2022;12(3):17–30.
    8. Chavez Rodriguez L, González-Nicolás A, Ingalls B, Nowak W, Xiao S, Pagel H. Optimal design of experiments to improve the characterization of atrazine degradation pathways in soil. European Journal of Soil Science. 2022;73(1):e13211.
    9. Rodriguez-Pretelin A, Morales-Casique E, Nowak W. Optimization-based clustering of random fields for computationally efficient and goal-oriented uncertainty quantification: concept and demonstration for delineation of wellhead protection areas in transient aquifers. Advances in Water Resources. 2022;162:104146.
    10. Horuz CC, Karlbauer M, Praditia T, Butz MV, Oladyshkin S, Nowak W, u. a. Inferring Boundary Conditions in Finite Volume Neural Networks. In: Pimenidis E, Angelov P, Jayne C, Papaleonidas A, Aydin M, Herausgeber. International Conference on Artificial Neural Networks and Machine Learning -- ICANN 2022. Cham: Springer International Publishing; 2022. S. 538–49. (Pimenidis E, Angelov P, Jayne C, Papaleonidas A, Aydin M, Reihenherausgeber. International Conference on Artificial Neural Networks and Machine Learning -- ICANN 2022).
    11. Praditia T, Karlbauer M, Otte S, Oladyshkin S, Butz MV, Nowak W. Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network. Water Resources Research. 2022;58(12).
    12. Galvan A, Haas J, Moreno-Leiva S, Osorio-Aravena JC, Nowak W, Palma-Behnke R, u. a. Exporting sunshine: Planning South America’s electricity transition with green hydrogen. Applied Energy. 2022;325:119569.
    13. Karlbauer M, Praditia T, Otte S, Oladyshkin S, Nowak W, Butz MV. Composing Partial Differential Equations with Physics-Aware Neural Networks. In: Proceedings of the 39th International Conference on Machine Learning. Baltimore, USA; 2022. S. 10773--10801. (Proceedings of the 39th International Conference on Machine Learning).
  7. 2021 (submitted)

    1. Cheng K, Lu Z, Xiao S, Oladyshkin S, Nowak W. Unified Bayesian inference framework for surrogate modelling: connection between existing techniques and their common fundamentals. Reliability Engineering and System Safety.
    2. Moreno-Leiva S, Haas J, Nowak W, Kracht W, Eltrop L, Breyer C. Flexible copper: exploring capacity-based energy demand flexibility in the industry. Applied Energy.
  8. 2021

    1. Praditia T, Oladyshkin S, Nowak W. Finite Volume Neural Networks: a Hybrid Modeling Strategy for Subsurface Contaminant Transport. In: AGU Fall Meeting 2021. 2021. (AGU Fall Meeting 2021).
    2. Galván A, Haas J, Martin P, Nowak W, Palma-Behnke R, Breyer C. Exporting sunshine: Planning South America’s energy transition with hydrogen exports. In: AGU Fall Meeting 2021. 2021. (AGU Fall Meeting 2021).
    3. Scheurer S, Schäfer Rodrigues Silva A, Mohammadi F, Hommel J, Oladyshkin S, Flemisch B, u. a. Surrogate-based Bayesian Comparison of Computationally Expensive Models: Application to Microbially Induced Calcite Precipitation. Computational Geosciences. 2021;25:1899–917.
    4. Bakhshipour AE, Hespen J, Haghighi A, Dittmer U, Nowak W. Integrating structural resilience in the design of urban drainage networks in flat areas using a simplified multi-objective optimization framework. Water. 2021;13:269.
    5. Cheng K, Xiao S, Zhang X, Oladyshkin S, Nowak W. Resampling method for reliability-based design optimization based on thermodynamic integration and parallel tempering. Mechanical Systems and Signal Processing. 2021;156:107630.
    6. González-Inostroza P, Rahmann C, Alvarez R, Haas J, Nowak W, Rehtanz C. The Role of Fast Frequency Response of Energy Storage Systems and Renewables for Ensuring Frequency Stability in Future Low-Inertia Power Systems. Sustainability. 2021;
    7. Praditia T, Karlbauer M, Otte S, Oladyshkin S, Butz M, Nowak W. Finite Volume Neural Network: Modeling Subsurface Contaminant Transport. In: Deep Learning for Simulation ICLR Workshop 2021 [Internet]. 2021. (Deep Learning for Simulation ICLR Workshop 2021). Verfügbar unter: https://arxiv.org/abs/2104.06010
    8. Haas J, Hagen D, Moreno-Leiva S, Nowak W, Kern J, Olivares MA. Updated Perspective on Using Batteries for Mitigating Hydropeaking. In: Conference on Sustainable Development of Energy, Water and Environment Systems (SDEWES). 2021. (Conference on Sustainable Development of Energy, Water and Environment Systems (SDEWES); Bd. 16).
    9. Feldmeyer D, Nowak W, Jamshed A, Birkmann J. An open resilience index: crowdsourced indicators empirically developed from natural hazard and climatic event data. Science of the Total Environment. 2021;774:145734.
    10. Praditia T, Oladyshkin S, Nowak W. Physics Informed Neural Network for porous media modelling. In Stuttgart, Germany: InterPore German Chapter Meeting 2021; 2021.
    11. Keller J, Hendricks Franssen HJ, Nowak W. Investigating the Pilot Point Ensemble Kalman Filter for geostatistical inversion and data assimilation. Water Resources Research. 2021;155:104010.
    12. Xiao S, Xu T, Reuschen S, Nowak W, Franssen HJH. Bayesian inversion of multi-Gaussian log-conductivity fields with uncertain hyperparameters: an extension of preconditioned Crank-Nicolson Markov chain Monte Carlo with parallel tempering. Water Resources Research. 2021;57:e2021WR030313.
    13. Reuschen S, Guthke A, Nowak W. The Four Ways to Consider Measurement Noise in Bayesian Model Selection - And Which One to Choose. Water Resources Research. 2021;57:e2021WR030391.
    14. Praditia T, Oladyshkin S, Nowak W. Universal Differential Equation for Diffusion-Sorption Problem in Porous Media Flow. In online: EGU General Assembly 2021; 2021.
    15. Moreno-Leiva S, Haas J, Nowak W, Kracht W, Eltrop L, Breyer C. Integration of seawater pumped storage and desalination in multi-energy systems planning: the case of a key material for the energy transition. Applied Energy. 2021;299:117298.
    16. Saemiana P, Hosseini-Moghari SM, Fatehi I, Shoarinezhad V, Modiri E, Tourian MJ, u. a. Comprehensive comparison of precipitation datasets over Iran. Journal of Hydrology. 2021;603:127054.
    17. Sinsbeck M, Cook E, Nowak W. Sequential Design of Computer Experiments for the Computation of Bayesian Model Evidence. SIAM/ASA Journal on Uncertainty Quantification. Februar 2021;9(1):260--279.
    18. Chow R, Parker B, Steelman C, Thoms A, Nowak W. How do fractures influence hyporheic exchange in sedimentary rock riverbeds? Water Resources Research. 2021;57(7):e2020WR028476.
    19. Bakhshipour AE, Dittmer U, Haghighi A, Nowak W. Towards sustainable urban drainage infrastructures planning: a combined multiobjective optimization and multicriteria decision-making platform. Journal of Water Resources Planning and Management. 2021;147(8).
    20. Flaig S, Praditia T, Kissinger A, Lang U, Oladyshkin S, Nowak W. Prognosis of water levels in a moor groundwater system influenced by hydrology and water extraction using an artificial neural network. In online: EGU General Assembly 2021; 2021.
    21. Reuschen S, Jobst F, Nowak W. Efficient discretization-independent Bayesian inversion of high-dimensional multi-Gaussian priors using a hybrid MCMC. Water Resources Research. 2021;57(8):e2021WR030051.
    22. González-Nicolás A, Schwientek M, Sinsbeck M, Nowak W. Characterization of export regime in discharge-concentration plots via an advanced time-series model and event-based sampling. Water. 2021;13:1723.
    23. Banerjee I, Guthke A, Van de Ven CJC, Mumford KG, Nowak W. Overcoming the model-data-fit problem in porous media: A quantitative method to compare invasion-percolation models to high-resolution data. Water Resources Research. 2021;57(7):e2021WR029986.
    24. Xiao S, Praditia T, Oladyshkin S, Nowak W. Global sensitivity analysis of a CaO/Ca(OH)2 thermochemical energy storage model for parametric effect analysis. Applied Energy [Internet]. 2021;285:116456. Verfügbar unter: https://www.sciencedirect.com/science/article/pii/S0306261921000222
  9. 2020

    1. Haas J, Moreno-Leiva S, Junne T, Chen PJ, Pamparana G, Nowak W, u. a. Copper mining: 100% solar electricity by 2030? Applied Energy [Internet]. März 2020;262(114506). Verfügbar unter: https://www.sciencedirect.com/science/article/pii/S0306261920300180
    2. Xiao S, Oladyshkin S, Nowak W. Forward-reverse switch between density-based and regional sensitivity analysis. Applied Mathematical Modelling. 2020;84:377–92.
    3. Haas J, Mahmoud M, Yeligeti M, Moreno-Leiva S, Nowak W, Palma-Behnke R. Adaptive Planning: Finding Optimal Energy Pathways In Times Of Deep Uncertainty. In Düsseldorf, Germany: International Renewable Energy Storage (IRES) Conference; 2020.
    4. Höge M, Guthke A, Nowak W. Bayesian Model Weighting: The Many Faces of Model Averaging. Water [Internet]. 2020;12(2):309. Verfügbar unter: https://www.mdpi.com/2073-4441/12/2/309
    5. Xu T, Reuschen S, Nowak W, Franssen HJH. Preconditioned Crank-Nicolson Markov chain Monte Carlo coupled with parallel tempering: An efficient method for Bayesian inversion of multi-Gaussian log-hydraulic conductivity fields. Water Resources Research. 2020;56(8):e2020WR027110.
    6. Beckers F, Heredia A, Noack M, Nowak W, Wieprecht S, Oladyshkin S. Bayesian Calibration and Validation of a Large-scale and Time-demanding Sediment Transport Model. Water Resources Research. 2020;56(7):e2019WR026966.
    7. Erdal D, Xiao S, Nowak W, Cirpka O. Sampling Behavioral Model Parameters for Ensemble-based Sensitivity Analysis using Gaussian Process Emulation and Active Subspaces. Stochastic Environmental Research and Risk Assessment. 2020;34:1813–30.
    8. Xiao S, Oladyshkin S, Nowak W. Reliability analysis with stratified importance sampling based on adaptive Kriging. Reliability Engineering & System Safety. 2020;197:106852.
    9. Rodriguez-Pretelin A, Nowak W, Morales-Casique E. Integrating transient flow conditions into groundwater well protection. In: Annual meeting of InterPore, Chapter Mexico. Mexico City, Mexico: InterPore; 2020. (Annual meeting of InterPore, Chapter Mexico).
    10. Sinsbeck M, Höge M, Nowak W. Exploratory-phase-free estimation of GP hyperparameters in sequential design methods - at the example of Bayesian inverse problems. Frontiers in Artificial Intelligence, section AI in Food, Agriculture and Water. 2020;3(52):1–16.
    11. Gonzalez-Nicolas Alvarez A, Nowak W, Sinsbeck M, Schwientek M. Characterize the catchment regime by applying optimal monitoring strategies. In: EGU General Assembly Conference Abstracts. 2020. S. 4843. (EGU General Assembly Conference Abstracts).
    12. Moreno-Leiva S, Haas J, Junne T, Valencia F, Godin H, Kracht W, u. a. Renewable energy in copper production: a review on systems design and methodological approaches. Journal of Cleaner Production. Februar 2020;246(118978).
    13. Maier R, González-Nicolás A, Leven C, Nowak W, Cirpka OA. Joint optimization of measurement and modeling strategies with application to radial flow in stratified aquifers. Water Resources Research. 2020;56:e2019WR026872.
    14. Allgeier J, González-Nicolás A, Erdal D, Nowak W, Cirpka OA. A stochastic framework to optimize monitoring strategies for delineating groundwater divides. Frontiers in Earth Science. 2020;(8):554845.
    15. Oladyshkin S, Beckers F, Kroeker I, Mohammadi F, Heredia A, Noack M, u. a. Uncertainty quantification using Bayesian arbitrary polynomial chaos for computationally demanding environmental modelling: conventional, sparse and adaptive strategy. In: Computational Methods in Water Resources (CMWR). 2020. (Computational Methods in Water Resources (CMWR)).
    16. Oladyshkin S, Mohammadi F, Kröker I, Nowak W. Bayesian3 active learning for Gaussian process emulator using information theory. Entropy. 2020;22(0890):1–27.
    17. Guthke A, Bakhshipour AE, de Barros F, Class H, Daniell JE, Dittmer U, u. a. A unified framework for quantitative interdisciplinary flood risk assessment. In online: AGU Fall Meeting 2020; 2020.
    18. Banerjee I, Guthke A, Ven CJCVD, Mumford K, Nowak W. Overcoming the Model-to-Experimental Data Fit Problem in Porous Media: a New Quantitative Method to Evaluate and Compare Models. In online: AGU Fall Meeting 2020; 2020.
    19. Gonzalez-Nicolas A, Allgeier J, Erdal D, Nowak W, Cirpka OA. Optimal monitoring strategies for minimal uncertainties about a groundwater divide. In: SIAM Conference on Uncertainty Quantification (UQ20) [Internet]. 2020. (SIAM Conference on Uncertainty Quantification (UQ20)). Verfügbar unter: https://www.events.tum.de/frontend/index.php?page_id=3712&v=List&do=15&day=all&ses=1712#
    20. Allgeier J, Gonzalez-Nicolas A, Erdal D, Nowak W, Cirpka OA. A Stochastic Framework to Optimize the Monitoring Strategy for the Delineation of a Groundwater Divide. In: EGU General Assembly Conference Abstracts. 2020. S. 6907. (EGU General Assembly Conference Abstracts).
    21. Praditia T, Walser T, Oladyshkin S, Nowak W. Improving Thermochemical Energy Storage dynamics forecast with Physics-Inspired Neural Network architecture. Energies [Internet]. 2020;13(15):3873. Verfügbar unter: https://www.mdpi.com/1996-1073/13/15/3873
    22. Moreno-Leiva S, Haas J, Nowak W, Junne T. Flexible energy systems for planning the world’s main copper mines considering geographical conditions. In Vienna, Austria: European Geophysical Union (EGU), General Assembly 2020; 2020.
    23. Jackisch C, Schibalski A, Schröder B, Nowak W, Guthke A. Providing relevant uncertainty information to decision makers: Subjective post-processing of rigorous Bayesian uncertainty assessment of model projections. In online: AGU Fall Meeting 2020; 2020.
    24. Schäfer Rodrigues Silva A, Guthke A, Höge M, Cirpka OA, Nowak W. Strategies for simplifying reactive transport models - a Bayesian model comparison. Water Resources Research. 2020;56:e2020WR028100.
    25. Guisandez I, Perez-Diaz JI, Nowak W, Haas J. Should environmental constraints be considered in linear programming based water value calculators? International Journal of Electrical Power & Energy Systems. Mai 2020;117(105662).
    26. Haas J, Khalighi J, de la Fuente A, Gerbersdorf S, Nowak W, Chen PJ. Floating photovoltaic plants: ecological impacts versus hydropower operation flexibility. Energy Conversion and Management. Februar 2020;206(112414).
    27. Hsueh HF, Guthke A, Wöhling T, Nowak W. Diagnosing Model-structural Errors with a Sliding Time-window Bayesian Analysis. In online: AGU Fall Meeting 2020; 2020.
    28. Reuschen S, Xu T, Nowak W. Bayesian inversion of hierarchical geostatistical models using a parallel-tempering sequential Gibbs MCMC algorithm. Advances in Water Resources. 2020;141:103614.
  10. 2019

    1. Anindito Y, Haas J, Olivares MA, Kern J, Nowak W. A new solution to mitigate hydropeaking? Batteries versus re-regulation reservoirs. Journal of Cleaner Production. Februar 2019;210:477–89.
    2. Junne T, Haas J, Wang J, Moreno S, Naegler T, Buchgeister J, u. a. Considering Ecological Sustainability in Planning the Future Electricity Supply of Chile – How Much More Does it Cost? In Düsseldorf, Germany: International Renewable Energy Storage (IRES) Conference; 2019.
    3. Haas J, Nowak W, Palma-Behnke R. Multi-objective planning of energy storage technologies for a fully renewable system: implications for the main stakeholders in Chile. Energy Policy. März 2019;126:494–506.
    4. Köppel M, Franzelin F, Kröker I, Oladyshkin S, Santin G, Wittwar D, u. a. Comparison of data-driven uncertainty quantification methods for a carbon dioxide storage benchmark scenario. Computational Geosciences. 2019;23(2):339–54.
    5. Bode F, Reed P, Reuschen S, Nowak W. Search Space Representation and Reduction Methods to Enhance Multi-Objective Water Supply Monitoring Design. Water Resources Research. 2019;55(3):2257–78.
    6. Xiao S, Reuschen S, Köse G, Oladyshkin S, Nowak W. Estimation of small failure probabilities based on thermodynamic integration and parallel tempering. Mechanical Systems and Signal Processing. 2019;133:106248.
    7. Pamparana G, Kracht W, Haas J, Ortiz JM, Nowak W, Palma-Behnke R. Studying the integration of solar energy into the operation of a semi-autogenous grinding mill. Part II: effect of ore hardness variability, geometallurgical modeling and demand side management. Minerals Engineering. 2019;137:53–67.
    8. Xiao S, Oladyshkin S, Nowak W. Reliability sensitivity analysis with subset simulation: application to a carbon dioxide storage problem. In: International Conference of Euro Asia Civil Engineering Forum. Stuttgart, Germany: International Conference of Euro Asia Civil Engineering Forum; 2019. (International Conference of Euro Asia Civil Engineering Forum).
    9. Chow R, Hao W, Jeremy B, Jürnjakob D, Wöhling T, Nowak W. Sensitivity of simulated hyporheic exchange to river bathymetry: The Steinlach River Test Site. Groundwater. 2019;57(3):378–91.
    10. Most S, Bolster D, Bijeljic B, Nowak W. Trajectories as training images to simulate advective-diffusive, non-Fickian transport. Water Resources Research. 2019;55:3465–80.
    11. Höge M, Guthke A, Nowak W. The Hydrologist’s Guide to Bayesian Model Selection, Averaging and Combination. Journal of Hydrology [Internet]. Mai 2019;572:96–107. Verfügbar unter: http://www.sciencedirect.com/science/article/pii/S0022169419301532
    12. Haas J, Hagen D, Nowak W. Energy storage and transmission systems to save the fish? Minimizing hydropeaking for little extra-cost. Sustainable Energy Technologies and Assessments. 2019;35:41–7.
    13. Chow R, Jeremy B, Jürnjakob D, Wöhling T, Nowak W. Evaluating subsurface parameterization to simulate hyporheic exchange: The Steinlach River Test Site. Groundwater. 2019;58(7):93–109.
    14. Pamparana G, Kracht W, Haas J, Ortiz JM, Nowak W, Palma-Behnke R. Studying the integration of solar energy into the operation of a semi-autogenous grinding mill. Part I: framework, model development and effect of solar irradiance forecasting. Minerals Engineering. 2019;137:68–77.
    15. Bakhshipour AE, Bakhshizadeh M, Dittmer U, Haghighi A, Nowak W. Hanging Gardens Algorithm to Generate Decentralized Layouts for Urban Drainage Systems Optimization. Journal of Water Resources Planning and Management. Juni 2019;145(9):04019034.
    16. Maier R, Gonzalez-Nicolas A, Leven C, Nowak W, Cirpka OA. Choosing Between Heterogeneity and Anisotropy - What’s in the Data and What Do Your Purposes Require? In: AGU Fall Meeting Abstracts. 2019. S. H21L-1910. (AGU Fall Meeting Abstracts; Bd. 2019).
    17. Praditia T, Walser T, Oladyshkin S, Nowak W. Using physics-based regularization in Artificial Neural Networks to predict thermochemical energy storage systems. In: Fall Meeting 2019, Abstract: IN32B-15. San Francisco, CA, USA: American Geophysical Union (AGU); 2019. (Fall Meeting 2019, Abstract: IN32B-15).
    18. Allgeier J, González-Nicolás A, Cirpka O, Nowak W, Finchel M. Where to draw the line? In: Groundwater quality in the transition between rural and urban environments Conference, Poster. Liege, Belgium; 2019. (Groundwater quality in the transition between rural and urban environments Conference, Poster).
    19. Rodriguez-Pretelin A, Nowak W. Dynamic re-distribution of pumping rates in well fields to counter transient problems in groundwater production. Groundwater for Sustainable Development. April 2019;8:606–16.
    20. Bakhshipour AE, Dittmer U, Haghighi A, Nowak W. Hybrid green-blue-gray decentralized urban drainage systems design, a simulation-optimization framework. Journal of Environmental Management. 2019;249:109364.
    21. Motavita DF, Chow R, Guthke A, Nowak W. The Comprehensive Differential Split-Sample Test: A stress-test for hydrological model robustness under climate variability. Journal of Hydrology. 2019;573:501–15.
    22. Oladyshkin S, Nowak W. The connection between Bayesian Inference and Information Theory for model selection, information gain and experimental design. Entropy. 2019;21:1081.
    23. González-Nicolás A, Nowak W, Sinsbeck M, Schwientek M. Optimal scheduling and event-based sampling: development and demonstration for investigating the nitrate characteristics of a headwater catchment. In: General Assembly 2019, Geophysical Research Abstracts: EGU2019-964, 2019. Vienna, Austria: European Geosciences Union (EGU); 2019. (General Assembly 2019, Geophysical Research Abstracts: EGU2019-964, 2019).
  11. 2018

    1. Most S, Bijeljic B, Bolster D, Nowak W. Simulating three-dimensional non-Fickian transport across arbitrary Péclet regimes using training trajectories. In Saint-Malo, France: XXII. International Conference on Computational Methods in Water Resources (CMWR); 2018.
    2. Haas J, Nowak W. What technical phenomena are relevant when designing the optimal energy storage mix? In Stuttgart, Germany: 2nd International Conference on Simulation Technology; 2018.
    3. Haas J, Nowak W, Hagen D. Energy Storage Systems for a 100\% Renewable Power Supply: a Closer Look on Hydropower. In: 13th SDEWES Conference on Sustainable Development of Energy, Water and Environment Systems. Palermo, Italy: SDEWES; 2018. (13th SDEWES Conference on Sustainable Development of Energy, Water and Environment Systems).
    4. González-Nicolás A, Nowak W. Optimal sampling strategies for river water quality to determine the chemostatic strength of catchments (GRS, Oral Presentation). In: GRS: Flow and Transport in Permeable Media, Understanding Complexity for Prediction in Permeable Media, Oral. Newry, ME, USA: Gordon Research Conferences (GRC); 2018. (GRS: Flow and Transport in Permeable Media, Understanding Complexity for Prediction in Permeable Media, Oral).
    5. 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. Verfügbar unter: http://www.sciencedirect.com/science/article/pii/S0309170817311909
    6. Cebulla F, Haas J, Eichman J, Nowak W, Mancarella P. How much Electrical Energy Storage do we need? A synthesis for the U.S., Europe, and Germany. Journal of Cleaner Production [Internet]. April 2018;181:449–59. Verfügbar unter: https://www.sciencedirect.com/science/article/pii/S0959652618301665
    7. Schäfer-Rodrigues-Silva A, Seitz T, Guthke Anneli, 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.
    8. Haas J, Cebulla F, Nowak W, Rahmann C, Palma R. A multi-service approach for planning the optimal mix of energy storage technologies in a fully renewable power supply. Energy Conversion and Management [Internet]. 2018;178:355–68. Verfügbar unter: https://www.sciencedirect.com/science/article/pii/S0196890418310987
    9. Schäfer-Rodrigues-Silva A, Nowak W. Diagnosing redundancies, gaps and data match in multi-model ensembles. In Saint-Malo, France: XXII. International Conference on Computational Methods in Water Resources (CMWR); 2018.
    10. Höge M, Wöhling T, Nowak W. A Primer for Model Selection: The Decisive Role of  Model Complexity. Water Resources Research [Internet]. 2018; Verfügbar unter: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2017WR021902
    11. 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.
    12. Gosses M, Nowak W, Wöhling T. Explicit treatment for Dirichlet, Neumann and Cauchy      boundary conditions in POD-based reduction of groundwater models. Advances in Water Resources. 2018;115:160–71.
    13. González-Nicolás A, Nowak W. Optimal sampling strategies for river water quality to determine the chemostatic strength of catchments (Integrated Hydrosystem Modelling, Poster Presentation). In: Integrated Hydrosystem Modelling, Poster. Tübingen, Germany: Research Training Group „Integrated Hydrosystem Modelling“; 2018. (Integrated Hydrosystem Modelling, Poster).
    14. Mehne J, Nowak W. Predicting the battery core temperature: explanatory power of  measurement quantities under different uncertainty scenarios. Journal of Energy Storage. 2018;18:476–84.
    15. Thoms A, Chow R, Steelman C, Nowak W, Parker B. Simulating Hyporheic Exchange in Bedrock Rivers - The Eramosa Bedrock River Field Site. In: Fall Meeting 2018. Washington, D.C., USA: American Geophysical Union (AGU); 2018. (Fall Meeting 2018).
    16. Rodriguez-Pretelin A, Nowak W. Integrating transient behavior as a new dimension to WHPA delineation. Advances in Water Resources. 2018;119:178–87.
    17. Höge M, Wöhling T, Nowak W. The Decisive Role of Model Complexity in Model Selection. In: General Assembly 2018, Geophysical Research Abstracts  20: EGU2018-6499, 2018. Vienna, Austria: European Geosciences Union (EGU); 2018. (General Assembly 2018, Geophysical Research Abstracts  20: EGU2018-6499, 2018).
    18. Haas J, Nowak W, Cebulla F, Rahmann C, Palma-Behnke R. A multi-service approach for finding the optimal energy storage mix for renewable systems. In Düsseldorf, Germany: International Renewable Energy Storage (IRES) Conference; 2018.
    19. Schäfer-Rodrigues-Silva A, Nowak W. What is a legitimate model complexity? In Tübingen, Germany: Meeting of the CRC 1253 CAMPOS - Catchments as Reactors: Metabolism of Pollutants on the Landscape Scale; 2018.
    20. 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).
    21. Chow R, Wu H, Bennett J, Dugge J, Wöhling T, Nowak W. Sensitivity of simulated hyporheic exchange residence times to river bathymetry. In: General Assembly 2018, Geophysical Research Abstracts 20: EGU2018-10900, 2018. Vienna, Austria: European Geosciences Union (EGU); 2018. (General Assembly 2018, Geophysical Research Abstracts 20: EGU2018-10900, 2018).
    22. Khan U, Snieder E, R.Shakir, Höge M, Nowak W. Using model complexity to select the optimum architecture  for artificial neural networks. In: General Assembly 2018, Geophysical Research Abstracts 20: EGU2018-17908. Vienna, Austria: European Geosciences Union (EGU); 2018. (General Assembly 2018, Geophysical Research Abstracts 20: EGU2018-17908).
    23. Rodriguez-Pretelin A, Nowak W. A framework for transient behavior restriction in WHPA delineation: A dynamic multiobjective approach. In Saint-Malo, France: XXII. International Conference on Computational Methods in Water Resources (CMWR); 2018.
    24. González-Nicolás A, Nowak W. Optimal sampling strategies for river water quality to determine the chemostatic strength of catchments (GRC, Poster Presentation). In: GRC: Flow and Transport in Permeable Media, From Pore-Scale Physics to Geologic-Scale Processes, Poster. Newry, ME, USA: Gordon Research Conferences (GRC); 2018. (GRC: Flow and Transport in Permeable Media, From Pore-Scale Physics to Geologic-Scale Processes, Poster).
    25. 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.
    26. Oladyshkin S, Nowak W. Incomplete statistical information limits the utility of higher-order polynomial chaos expansions. Reliability Engineering & System Safety. 2018;169:137–48.
    27. Bode F, Ferre T, Zigelli N, Emmert M, Nowak W. Reconnecting Stochastic Methods with Hydrogeological Applications: A Utilitarian Uncertainty Analysis and Risk Assessment Approach for the Design of Optimal monitoring Networks. Water Resources Research. 2018;54:2270–97.
    28. Haas J, Khalighi J, Chen PJ, de la Fuente A, Nowak W. Save the Lake! Floating Solar Photovoltaic to Avoid Algae Blooms? In: Fall Meeting 2018. Washington, DC, USA: American Geophysical Union (AGU); 2018. (Fall Meeting 2018).
    29. Rodriguez-Pretelin A, Nowak W. Unsupervised learning for probabilistic WHPA analysis: A novel approach to identify hydraulic conductivity fields that best approximate geological uncertainties. In: Fall Meeting 2018. Washington, D.C., USA: American Geophysical Union (AGU); 2018. (Fall Meeting 2018).
    30. Schäfer-Rodrigues-Silva A, Guthke Anneli, Nowak W. Quantifying similarity in multi-model ensembles. In Tübingen, Germany: International Conference on Integrated Hydrosystem Modelling; 2018.
    31. 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.
    32. Schäfer-Rodrigues-Silva A, Seitz T, Guthke Anneli, 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.
    33. González-Nicolás A, Nowak W, Shäfer A. Optimization of strategies to collect data of the field. In Tübingen, Germany: 1st Science Meeting within CAMPOS project; 2018.
    34. Rodriguez-Pretelin A, Nowak W. Optimal sampling design for well catchment investigation towards transient analysis of wellhead protection areas. In: Fall Meeting 2018. Washington, D.C., USA: American Geophysical Union (AGU); 2018. (Fall Meeting 2018).
    35. Rodriguez-Pretelin A, Nowak W. Reducing the influence of transient flow for improved Wellhead Protection: An engineered optimal pumping-injection management solution. In Stuttgart, Germany: 2nd International Conference on Simulation Technology; 2018.
    36. Höge M, Wöhling T, Nowak W. Model Selection: Play-It-Safe vs. No-Risk-No-Fun. In: Integrated Hydrosystem Modelling 2018 Conference: How Complex Should Integrated Models Be? Tübingen, Germany: RTG 1829, DFG; 2018. (Integrated Hydrosystem Modelling 2018 Conference: How Complex Should Integrated Models Be?).
    37. 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).
    38. Rodriguez-Pretelin A, Nowak W. A Multi-Objective Optimization formulation for transient flow restriction in Wellhead Protection. In: JpGU 2018. Chiba, Japan: Japan Geoscience Union (JpGU); 2018. (JpGU 2018).
  12. 2017

    1. Sinsbeck M, Nowak W. Sequential Design of Computer Experiments for the Solution of Bayesian Inverse Problems. In Weimar, Germany: 88th GAMM Annual Meeting; 2017.
    2. Chow R, Bennett J, J. Dugge TW, Nowak W. Evaluating Uncertainty in Estimating Groundwater Residence Time through a River Bend –An Integrated Hydrogeologic Modelling Study. In: General Assembly 2017, Geophysical Research Abstracts 19: EGU2017-1881, 2017. Vienna, Austria: European Geosciences Union (EGU); 2017. (General Assembly 2017, Geophysical Research Abstracts 19: EGU2017-1881, 2017).
    3. Wirtz D, Nowak W. The rocky road to extended simulation frameworks covering uncertainty, inversion, optimization and control. Environmental Software and Modelling. 2017;93:180–92.
    4. Rodriguez-Pretelin A, Nowak W. Transient flow conditions change how we should think about WHPA delineation: a joint frequency and probability analysis. In: General Assembly 2017, Geophysical Research Abstracts 19: EGU2017-2660, 2017. Vienna, Austria: European Geosciences Union (EGU); 2017. (General Assembly 2017, Geophysical Research Abstracts 19: EGU2017-2660, 2017).
    5. Chow R, Bennet J, Dugge J, Wöhling T, Nowak W. Evaluating Predictive Uncertainty of Hyporheic Exchange Modelling. In: Fall Meeting 2017, Abstract: H22D-06. New Orleans, LA, USA: American Geophysical Union (AGU); 2017. (Fall Meeting 2017, Abstract: H22D-06).
    6. Wirtz D, Nowak W. The rocky road to universal scientific simulation frameworks. Environmental Software and Modelling. 2017;93:180–92.
    7. Nowak W, Anindito Y, Haas J, Olivares M. Can re-regulation reservoirs and batteries cost-effectively mitigate sub-daily hydropeaking? In: Fall Meeting 2017, Abstract: PA23A-0363. New Orleans, LA, USA: American Geophysical Union (AGU); 2017. (Fall Meeting 2017, Abstract: PA23A-0363).
    8. Haas J, Nowak W. Water-energy nexus: challenges from Chile. In Golden, Colorado: International Conference on Energy Systems Integration (ICESI); 2017.
    9. 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).
    10. Haas J, Cebulla F, Karl-Kiên C, Nowak W, Palma-Behnke R, Rahmann C, u. a. Challenges and trends of energy storage expansion planning for flexibility provision in power systems - a review. Renewable & Sustainable Energy Reviews [Internet]. Dezember 2017;80:603–619. Verfügbar unter: http://www.sciencedirect.com/science/article/pii/S1364032117308377
    11. Haas J, Pamparana G, Kracht W, Nowak W, Chudinzow D, Ortiz J. Powering a Semi-Autogenous Grinding mill with photovoltaic energy including mineral management: the optimal energy storage mix. In Antofagasta, Chile: 3rd Solar Forum; 2017.
    12. Bode F, Nowak W, Emmert M, Zigelli N. Optimale Grundwassermessstellennetze: Multi-kriterielle  Optimierung als Entscheidungshilfe. gwf Wasser+Abwasser. 2017;158(07–08):111–21.
    13. Haas J, Zuniga D, Nowak W, Olivares M, Castelletti A, Tilmant A. The future of hydropower planning modeling. In: Fall Meeting 2017, Abstract: H23J-1805. New Orleans, LA, USA: American Geophysical Union (AGU); 2017. (Fall Meeting 2017, Abstract: H23J-1805).
    14. Schäfer-Rodrigues-Silva A, Nowak W. Model legitimacy - Model complexity in the light of limited data. In Stuttgart, Germany: Meeting of the international doctoral program „Environment Water“; 2017.
    15. Emmert M, Zigelli N, Haakh F, Bode F, Nowak W. Risikobasiertes Grundwassermonitoring für Wasserschutzgebiete. energie | wasser-praxis. 2017;67(8):68–71.
    16. Mehne J, Nowak W. Improving temperature predictions for Li-ion batteries: data assimilation with a stochastic extension of a physically-based, thermo-electrochemical model. Journal of Energy Storage [Internet]. 2017;12:288–96. Verfügbar unter: http://www.sciencedirect.com/science/article/pii/S2352152X16302328
    17. Most S, Bijeljic B, Bolster D, Dentz M, Nowak W. Simulating Non-Fickian Transport across Péclet Regimes by doing Lévy Flights in the Rank Space of Velocity. In: Fall Meeting 2017, Abstract: H31D-1545. New Orleans, LA, USA: American Geophysical Union (AGU); 2017. (Fall Meeting 2017, Abstract: H31D-1545).
    18. Haas J, Nowak W, Palma-Behnke R. Multiple Storage Technologies Offering Multiple Services in Generation Expansion Planning. In Düsseldorf, Germany: International Renewable Energy Storage (IRES) Conference; 2017.
    19. Rodriguez-Pretelin A, Nowak W. Minimizing transient influence in WHPA delineation: An optimization approach for optimal pumping rate schemes. In: Fall Meeting 2017, Abstract: PA53B-0274. New Orleans, LA, USA: American Geophysical Union (AGU); 2017. (Fall Meeting 2017, Abstract: PA53B-0274).
    20. Rodriguez-Pretelin A, Nowak W. And yet it moves! Involving transient flow conditions is the logical next step for WHPA analysis. In: Fall Meeting 2017, Abstract: H31D-1529. New Orleans, LA, USA: American Geophysical Union (AGU); 2017. (Fall Meeting 2017, Abstract: H31D-1529).
    21. Höge M, Illman W, Nowak W. Bayesian Model Selection under Time Constraints. In: Fall Meeting 2017, Abstract: H23C-1661. New Orleans, LA, USA: American Geophysical Union (AGU); 2017. (Fall Meeting 2017, Abstract: H23C-1661).
  13. 2016

    1. Chow R, Frind ME, Frind EO, Jones JP, Sousa MR, Rudolph DL, u. a. Delineating Baseflow Contribution Areas for Streams – A Model and Methods Comparison. Journal of Contaminant Hydrology. 195:11–22.
    2. Vereecken H, Schnepf A, Hopmans JW, Or MJD, Roose T, Vanderborght J, u. a. Modeling Soil Processes: Key challenges and new perspectives. Vadoze Zone Journal. 15(5).
    3. Koch J, Nowak W. Identification of contaminant source architectures - A statistical inversion that emulates multi-phase physics in a computationally practicable manner. Water Resources Research. 2016;52(2):1009–25.
    4. Oladyshkin S, Nowak W. Incomplete statistical information limits the utility of higher-order polynomial chaos expansions. In Lausanne Switzerland: SIAM Conference on Uncertainty Quantification; 2016.
    5. Sinsbeck M, Nowak W. Sequential Design of Computer Experiments for the Solution of Bayesian Inverse Problems. In Lausanne, Switzerland: SIAM Conference on Uncertainty Quantification; 2016.
    6. Haas J, Schradi J, Nowak W. Performance of Optimization Heuristics for the Operational Planning of Multienergy Storage Systems. In: Fall Meeting 2016, Abstract: GC51C-1162. San Francisco, CA, USA: American Geophysical Union (AGU); 2016. (Fall Meeting 2016, Abstract: GC51C-1162).
    7. 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.
    8. T. H. Mai, W. Nowak RK, Oladyshkin S. Uncertainty quantification for a hydro-morphodynamic model of river Rhine. In: General Assembly 2016, Geophysical Research Abstracts 18: EGU2016-5701-3, 2016. Vienna, Austria: European Geosciences Union (EGU); 2016. (General Assembly 2016, Geophysical Research Abstracts 18: EGU2016-5701-3, 2016).
    9. Most S, Bolster D, Bijeljic B, Nowak W. Coarse Graining of Non-Fickian Solute Transport – PTRW on Smoothed Velocity Fields. In: Fall Meeting 2016, Abstract: H51D-1501. San Francisco, CA, USA: American Geophysical Union (AGU); 2016. (Fall Meeting 2016, Abstract: H51D-1501).
    10. Wöhling T, Geiges A, Nowak W. Optimal design of multi-type groundwater monitoring networks using easily accessible tools. Groundwater. 2016;54(6):861–70.
    11. Most S, Bijeljic B, Nowak W. A copula-based analysis of the dependence structure and process memory of anomalous pore-scale transport. In Cincinnati OH, USA: Interpore International Society for Porous Media: 8th International Conference on Porous Media & Annual Meeting; 2016.
    12. Birkmann J, Wenzel F, Greiving S, Garschagen M, Vall’ee D, Nowak W, u. a. Extreme Events, Critical Infrastructures, Human Vulnerability and Strategic Planning: Emerging Research Issues. Journal of Extreme Events. 2016;3(2):1650017(1-25).
    13. Most S, Bijeljic B, Nowak W. Evolution and persistence of cross-directional statistical dependence during finite-P’eclet transport through a real porous medium. Water Resources Research. 2016;52(11):8920–37.
    14. Höge M, Wöhling T, Nowak W. On the Way to Appropriate Model Complexity. In: Fall Meeting 2016, Abstract: NG13A-1683. San Francisco, CA, USA: American Geophysical Union (AGU); 2016. (Fall Meeting 2016, Abstract: NG13A-1683).
    15. Most S, Jia N, Bijeljic B, Nowak W. Simulating Pre-Asymptotic, Non-Fickian Transport Although Doing Simple Random Walks - Supported By Empirical Pore-Scale Velocity Distributions and Memory Effects. In: Fall Meeting 2016, Abstract: H51D-1502. San Francisco, CA, USA: American Geophysical Union (AGU); 2016. (Fall Meeting 2016, Abstract: H51D-1502).
    16. Nowak W, Guthke A. Entropy-based experimental design for optimal model discrimination in the geosciences. Entropy. 2016;18(11):409.
    17. Flemisch B, Nordbotten JM, Nowak W, Raoof A. Special Issue on „‚NUPUS: Non-linearities and Upscaling in PoroUS Media‘“ (Editorial). Transport in Porous Media. 2016;114:237–40.
    18. Most S, Bijeljic B, Nowak W. Let’s move to spheres! Why a spherical coordinate system is rewarding when analyzing particle increment statistics. In: General Assembly 2016, Geophysical Research Abstracts, Volume 18. Vienna, Austria: European Geosciences Union (EGU); 2016. (General Assembly 2016, Geophysical Research Abstracts, Volume 18).
    19. Bode F, Nowak W, Reed PM, Reuschen S. Putting Man in the Machine: Exploiting Expertise to Enhance Multiobjective Design of Water Supply Monitoring Network. In: Fall Meeting 2016, Abstract: H51A-1413. San Francisco, CA, USA: American Geophysical Union (AGU); 2016. (Fall Meeting 2016, Abstract: H51A-1413).
    20. 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).
  14. 2015

    1. 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.
    2. Nowak W, Bode F, Loschko M. A multi-objective optimization concept for risk-based early-warning monitoring networks in well catchments. Procedia Environmental Sciences. 2015;25:191–8.
    3. Enzenhöfer R, Nowak W, Binning PJ. Stakeholder-Objective Risk Model (STORM): Determining the aggregated risk of multiple contaminant hazards in groundwater well catchments. Advances in Water Resources. 2015;83:165–75.
    4. Geiges A, Rubin Y, Nowak W. Interactive design of experiments: A priori global versus sequential optimization, revised under changing states of knowledge. Water Resources Research. 2015;51(10):7915–36.
    5. Bode F, Reuschen S, Nowak W. Never Use the Complete Search Space: A Concept to Enhance the Optimization Procedure for Monitoring Networks. In: Fall Meeting 2015, Abstract: IN11B-1774. San Francisco, CA, USA: American Geophysical Union (AGU); 2015. (Fall Meeting 2015, Abstract: IN11B-1774).
    6. Bode F, Nowak W, Loschko M. Optimization for early-warning monitoring networks in well catchments should be multi-objective, risk-prioritized and robust against uncertainty. Transport in Porous Media. 2015;114:261–81.
    7. Koch J, Nowak W. Predicting DNAPL mass discharge and contaminated site longevity probabilities: Conceptual model and high-resolution stochastic simulation. Water Resources Research. 2015;51(2):806–31.
    8. 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.
    9. 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.
    10. Most S, Bijeljic B, Nowak W. A complete fingerprint of non-Fickian mixing – an empirical statistical analysis. In Padova, Italy: Interpore International Society for Porous Media: 7th International Conference on Porous Media & Annual Meeting; 2015.
    11. 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).
    12. Most S, Bijeljic B, Nowak W. One Hundred Ways to be Non-Fickian - A Rigorous Multi-Variate Statistical Analysis of Pore-Scale Transport. In: General Assembly 2015, Geophysical Research Abstracts 17: EGU2015-11212, 2015. Vienna, Austria: European Geosciences Union (EGU); 2015. (General Assembly 2015, Geophysical Research Abstracts 17: EGU2015-11212, 2015).
    13. Haas J, Nowak W, Palma-Behnke R, Cebulla F. Energy storage opportunities and modelling challenges in Chile. In Concepcion, Chile: Production and Storage of Renewable Energy, KIT Alumni Expert Seminar; 2015.
    14. Gerbersdorf SU, Cimatoribus C, Class H, Engesser KH, Helbich S, Hollert H, u. a. Anthropogenic Trace Compounds (ATCs) in aquatic habitats - research needs on sources, fate, detection and toxicity to ensure timely elimination strategies and risk management. Environment International. 2015;79:85–105.
    15. Bode F, Loschko M, Nowak W. How to Decide? Multi-Objective Early-Warning Monitoring Networks for Water Suppliers. In: General Assembly 2015, Geophysical Research Abstracts 17: EGU2015-9270, 2015. Vienna, Austria: European Geosciences Union (EGU); 2015. (General Assembly 2015, Geophysical Research Abstracts 17: EGU2015-9270, 2015).
    16. Sinsbeck M, Nowak W. An optimal sampling rule for nonintrusive polynomial chaos expansions of expensive models. International Journal for Uncertainty Quantification. 2015;5(3):275–95.
    17. 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).
    18. Most S, Bijeljic B, Nowak W. A Full Empirical Description of Mixing and Dilution - The Fingerprint of Non-Fickian Mixing. In: Fall Meeting 2015, Abstract: H51F-1429. San Francisco, CA, USA: American Geophysical Union (AGU); 2015. (Fall Meeting 2015, Abstract: H51F-1429).
    19. 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.
  15. 2014

    1. Oladyshkin S, Schröder P, Class H, Nowak W. Stochastic model calibration for large-scale applications via Bayesian updating combined with arbitrary polynomial chaos. In Stuttgart, Germany: XX. International Conference on Computational Methods in Water Resources (CMWR); 2014.
    2. Most S, Bijeljic B, Nowak W. Is There a Critical Distance for Fickian Transport? - a Statistical Approach to Sub-Fickian Transport Modelling in Porous Media. In: Fall Meeting 2014, Abstract: H23B-0868. San Francisco, CA, USA: American Geophysical Union (AGU); 2014. (Fall Meeting 2014, Abstract: H23B-0868).
    3. Bode F, Binning PJ, Nowak W. Enhanced Multi-objective Optimization of Groundwater Monitoring Networks. In Denver, CO, USA: NGWA Groundwater Summit 2014; 2014.
    4. Geiges A, Nowak W. A reverse engineering approach to optimize the design of experiments and field campaigns. In Stuttgart, Germany: XX. International Conference on Computational Methods in Water Resources (CMWR); 2014.
    5. Koch J, Nowak W. A method for implementing Dirichlet and third-type boundary conditions in PTRW simulations. Water Resources Research. 2014;50(2):1374–95.
    6. Elsheikh AH, Oladyshkin S, Nowak W, Christie M. Estimating the probability of CO_2 leakage using rare event simulation. In: ECMOR XIV-14th European conference on the mathematics of oil recovery. 2014. S. We B25. (ECMOR XIV-14th European conference on the mathematics of oil recovery).
    7. Kröker I, Nowak W, Rohde C. A stochastically and spatially adaptive parallel scheme for uncertain and non-linear two-phase flow problems. Computational Geosciences. 2014;19:269–84.
    8. Oladyshkin S, de Barros HCRHWNFPJ, Ashraf M. Data-driven polynomial response surfaces as efficient tool for applied tasks under uncertainty. In Research Triangle Park, NC, USA: SAMSI Geosciences Applications Opening Workshop; 2014.
    9. Bode F, Binning P, Nowak W. Multi-Objective Optimization of Groundwater Monitoring Networks: Computational Costs vs. Optimization Accuracy. In Stuttgart, Germany: XX. International Conference on Computational Methods in Water Resources (CMWR); 2014.
    10. 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).
    11. Oladyshkin S, Nowak W. Analyzing the expansion order for polynomial chaos expansions in the light of imprecise information on statistical input distributions. In Boulder, CO, USA: 1st International Conference on Frontiers in Computational Physics: Modeling the Earth System; 2014.
    12. 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).
    13. Schöniger Anneli, 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.
    14. Enzenhöfer R, Bunk T, Nowak W. Nine steps to risk-informed wellhead protection and management: A case study. Groundwater. 2014;52:161–74.
    15. Schröder P, Class H, Nowak W. On combination of strict Bayesian principles with model reduction technique or how stochastic model calibration can become feasible for large-scale applications. In: Fall Meeting 2013, Abstract: H24F-02. San Francisco, CA, USA: American Geophysical Union (AGU); 2014. (Fall Meeting 2013, Abstract: H24F-02).
    16. Bode F, Loschko M, Nowak W. A Risk-Based Multi-Objective Optimization Concept for Early-Warning Monitoring Networks. In: Fall Meeting 2014, Abstract: H23K-1023. San Francisco, CA, USA: American Geophysical Union (AGU); 2014. (Fall Meeting 2014, Abstract: H23K-1023).
    17. Sinsbeck M, Nowak W. Adaptive Sampling for Bayesian Updating with Non-Intrusive Polynomial Chaos Expansions. In Savannah, Georgia, USA: SIAM Conference on Uncertainty Quantification; 2014.
  16. 2013

    1. Geiges A, Nowak W, Rubin Y. Challenges for the sequential interaction between optimal design of field campaign and model calibration for non-linear systems. In: Fall Meeting 2013, Abstract: H24F-03. San Francisco, CA, USA: American Geophysical Union (AGU); 2013. (Fall Meeting 2013, Abstract: H24F-03).
    2. Bode F, Binning P, Nowak W. What Factors Coordinate the Optimal Position of a Single Monitoring Well Down Gradient of a Hazardous Site. In: Fall Meeting 2013, Abstract: H21I-1175. San Francisco, CA, USA: American Geophysical Union (AGU); 2013. (Fall Meeting 2013, Abstract: H21I-1175).
    3. Wöhling T, Geiges A, Nowak W, Gayler S. Towards optimizing experiments for maximum-confidence model selection between different soil-plant models. Procedia Environmental Sciences. 2013;19:514–23.
    4. Grathwohl P, Rügner H, Wöhling T, Osenbrück K, Schwientek M, Gayler S, u. a. Catchments as Reactors: A comprehensive approach for water fluxes and solute turn-over            (Introduction to the Thematic Issue on Catchment Research). Environmental Earth Science. 2013;69(2):317–33.
    5. Oladyshkin S, Class H, Nowak W. Bayesian updating via bootstrap filtering combined with data-driven polynomial chaos expansions:methodology and application to history matching for carbon dioxide storage in geological formations. Computational Geosciences. 2013;17(4):671–87.
    6. Mehne J, Nowak W. Stochastic Extension of a Thermal-Electrochemical Lithium-Ion Battery Model. In San Francisco, CA, USA: 224th ECS meeting; 2013.
    7. Wöhling T, Geiges A, Nowak W, Gayler S. Evaluating experimental design for soil-plant model selection using a Bootstrap Filter and Bayesian model averaging. In: Fall Meeting 2013, Abstract: H33J-03. San Francisco, CA, USA: American Geophysical Union (AGU); 2013. (Fall Meeting 2013, Abstract: H33J-03).
    8. Tanaka N, Mehne J, Nowak W, Danzer M, Döring H, Bessler WG. Numerical Simulation and Experimental Validation for Thermal Runaway on Lithium-ion Cells. In Bad boll, Germany: 10th Symposium for Fuel Cell and Battery Modelling and Experimental Validation; 2013.
    9. Oladyshkin S, Nowak W. On polynomial chaos expansions under incomplete statistical input information. In München, Germany: Euromech colloquium 543; 2013.
    10. Enzenhöfer R, Binning PJ, Nowak W. Challenges & Limitations in Risk Assessment and Aggregation (The STORM Framework. In Freudenstadt, Germany: NUPUS annual Meeting: : Institut für Wasserbau, Lehrstuhl für Hydromechanik und Hydrosystemmodellierung; 2013.
    11. Leube P, de Barros FPJ, Nowak W, Rajagopal R. Towards optimal allocation of computer resources: trade-offs between uncertainty quantification,discretization and model reduction. Environmental Software and Modelling. 2013;50:97–107.
    12. Nowak W, Litvinenko A. Kriging and spatial design accelerated by orders of magnitude: combining low-rank covariance approximations with FFT-techniques. Mathematical Geosciences. 2013;45(4):411–35.
    13. Oladyshkin S, Schröder P, Class H, Nowak W. Chaos Expansion based Bootstrap Filter to Calibrate CO2 Injection Models. Energy Procedia. 2013;40:398–407.
    14. Ashraf M, Oladyshkin S, Nowak W. Geological storage of CO2: global sensitivity analysis and risk assessment using arbitrary polynomial chaos expansion. International Journal of Greenhouse Gas Control. 2013;19:704–19.
    15. 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).
    16. Bode F, Nowak W. Optimization Early-Warning Monitoring Systems for Improved Drinking Water Resource Protection. In NUPUS annual Meeting: Institut für Wasserbau, Lehrstuhl für Hydromechanik und Hydrosystemmodellierung; 2013.
  17. 2012

    1. Leube P, Geiges A, Nowak W. Bayesian assessment of the expected data impact on prediction confidence in optimal sampling design. Water Resources Research. 2012;48(W02501).
    2. Geiges A, Nowak W. A reverse analysis framework for the assessment of data worth in optimal design. In: Fall Meeting 2012, Abstract: H11K-05. San Francisco, CA, USA: American Geophysical Union (AGU); 2012. (Fall Meeting 2012, Abstract: H11K-05).
    3. Oladyshkin S, Nowak W. Analyzing the expansion order for polynomial chaos expansions in the light of imprecise information on statistical input distributions. In Boulder, CO, USA: 1st International Conference on Frontiers in Computational Physics: Modeling the Earth System; 2012.
    4. Nowak W, Rubin Y, de Barros FPJ. A hypothesis-driven approach to optimal site investigation. Water Resources Research. 2012;48(W06509).
    5. 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).
    6. Enzenhöfer R, Rodriguez-Pretelin A, Nowak W. Transient flow conditions in probabilistic wellhead protection: importance and ways to manage spatial and temporal uncertainty in capture zone delineation. In: Fall Meeting 2012, Abstract: H33I-1443. San Francisco, CA, USA: American Geophysical Union (AGU); 2012. (Fall Meeting 2012, Abstract: H33I-1443).
    7. Oladyshkin S, Nowak W. Polynomial Response Surfaces for Probabilistic Risk Assessment and Risk Control via Robust Design (Book). Luo Y, Herausgeber. Novel Approaches and Their Applications in Risk Assessment, ISBN: 978-953-51-0519-0 [Internet]. 2012; Verfügbar unter: /brokenurl#www.intechopen.com/books/
    8. Ashraf M, Oladyshkin S, Nowak W. Geological storage of CO$_2$: sensitivity analysis and risk assessment using arbitrary polynomial chaos expansion. In: General Assembly 2012, Geophysical Research Abstracts 14: EGU2012-9243, 2012. Vienna, Austria: European Geosciences Union (EGU); 2012. (General Assembly 2012, Geophysical Research Abstracts 14: EGU2012-9243, 2012).
    9. Oladyshkin S, Nowak W. Data-driven uncertainty quantification using the arbitrary polynomial chaos expansion. Reliability Engineering and System Safety. 2012;106:179–90.
    10. Nowak W. Recent Advances in Optimizing Field Campaigns. In: General Assembly 2012, Geophysical Research Abstracts 14: EGU2012-9365, 2012. Vienna, Austria: European Geosciences Union (EGU); 2012. (General Assembly 2012, Geophysical Research Abstracts 14: EGU2012-9365, 2012).
    11. de Barros FPJ, Dentz M, Koch J, Nowak W. Flow topology and scalar mixing in heterogeneous porous media. Geophysical Research Letters. 2012;39(L08404).
    12. Cirpka OA, Rolle M, Chiogna G, de Barros FPJ, Nowak W. Stochastic Evaluation of Mixing-Controlled Steady-State Plume Lengths in Two-Dimensional Heterogeneous Domains. Journal of Contaminant Hydrology. 2012;138–139:22–39.
    13. Tartakovsky D, Nowak W, Bolster D. Introduction to the special issue on uncertainty quantification and risk assessment. Advances in Water Resources. 2012;36:1–2.
    14. Mehne J, Nowak W, Danzer M, Döring H, Tanaka N, Bessler WG. Towards Predicting Thermal Runaway of Lithium-Ion Batteries. In Ulm, Germany: 13th Ulmer Electrochemical Talks; 2012.
    15. Enzenhöfer R, Bunk T, Nowak W, Enzenhöfer R, Bunk T, Nowak W. Nine Steps to risk-informed well-head protection and management via probabilistic vulnerability criteria. In Paris, France: Groundwater Vulnerability- Emerging Issues and New Approaches (IMVUL); 2012.
    16. Oladyshkin S, de Barros FPJ, Nowak W. Global sensitivity analysis: a flexible and efficient framework with an example from stochastic hydrogeology. Advances in Water Resources. 2012;37:10–22.
    17. Enzenhöfer R, Nowak W. Well-head Protection: Time matters? But how much? In Mühlheim an der Ruhr, Germany: NUPUS annual Meeting: Institut für Wasserbau, Lehrstuhl für Hydromechanik und Hydrosystemmodellierung; 2012.
    18. Enzenhöfer R, Nowak W, Helmig R. Probabilistic Exposure Risk Assessment with Advective-Dispersive Well Vulnerability Criteria. Advances in Water Resources. 2012;36:121–32.
    19. Troldborg M, Nowak W, Lange I, Santos M, Binning P, Bjerg PL. Application of Bayesian geostatistics for evaluation of mass discharge uncertainty at contaminated sites. Water Resources Research. 2012;48(W09535).
    20. Koch J, Nowak W, de Barros FPJ, Dentz M. Three-dimensional Scalar Mixing in Porous Media - Flow Heterogeneity and Mixing Enhancement. In: General Assembly 2012, Geophysical Research Abstracts 14: EGU2012-12189, 2012. Vienna, Austria: European Geosciences Union (EGU); 2012. (General Assembly 2012, Geophysical Research Abstracts 14: EGU2012-12189, 2012).
    21. Enzenhöfer R, Rodriguez-Pretelin A, Nowak W. Probabilistic well-head protection under transient flow conditions. In Paris, France: Groundwater Vulnerability- Emerging Issues and New Approaches (IMVUL); 2012.
    22. Leube P, Nowak W, Schneider G. Temporal Moments revisited: Why there is there nobetter way for physically-based model reduction in time. Water Resources Research. 2012;48(W11527).
  18. 2011

    1. Hlawatsch M, Leube P, Nowak W, Weiskopf D. Flow Radar Glyphs-Static Visualization of Unsteady Flow with Uncertainty. IEEE Transactions on Visualization and Computer Graphics. 2011;17(12):1949–58.
    2. Mehne J, Nowak W. Optimization of Pilot Point Locations for Conditional Simulation of Heterogeneous Aquifers. In: Fall Meeting 2011, Abstract: H23D-1298. San Francisco, CA, USA: American Geophysical Union (AGU); 2011. (Fall Meeting 2011, Abstract: H23D-1298).
    3. Oladyshkin S, Class H, Helmig R, Nowak W. Efficient Bayesian updating with PCE-based particle filters based on polynomial chaos expansion and CO$_2$ storage. In: Fall Meeting 2011, Abstract: GC51A-0928. San Francisco, CA, USA: American Geophysical Union (AGU); 2011. (Fall Meeting 2011, Abstract: GC51A-0928).
    4. Geiges A, Nowak W. Optimal Design of site investigation: Entropy based Utility functions and efficient implementations. In: Fall Meeting 2011, Abstract: H21H-04. San Francisco, CA, USA: American Geophysical Union (AGU); 2011. (Fall Meeting 2011, Abstract: H21H-04).
    5. de Barros FPJ, Oladyshkin S, Nowak W. An integrative data-adaptive approach for global sensitivity analysis: application to subsurface flow and transport. In: General Assembly 2011, Geophysical Research Abstracts 13: EGU2011-11206, 2011. Vienna, Austria: European Geosciences Union (EGU); 2011. (General Assembly 2011, Geophysical Research Abstracts 13: EGU2011-11206, 2011).
    6. Enzenhöfer R, Geiges A, Koch J, Leube P, Mehne J, Oladyshkin S, u. a. Zurück in die Unsicherheit - Stochastische Modellierung von Hydrosystemen. In Stuttgart, Germany: LH2-Kolloquium; 2011.
    7. de Barros FPJ, Dentz M, Koch J, Nowak W. Vortex Induced-Mixing in Heterogeneous Porous Media. In: Fall Meeting 2011, Abstract: H31E-1212. San Francisco, CA, USA: American Geophysical Union (AGU); 2011. (Fall Meeting 2011, Abstract: H31E-1212).
    8. Nowak W, de Barros FPJ, Rubin Y. A hypothesis-driven approach to optimal site investigation. In Stuttgart, Germany: SimTech 2011 - International Conference on Simulation Technology 2011; 2011.
    9. Cirpka OA, de Barros FPJ, Chiogna G, Rolle M, Nowak W. Stochastic Flux-Related Analysis of Transverse Mixing in Two-Dimensional Heterogeneous Porous Media. Water Resources Research. 2011;47(W06515).
    10. Oladyshkin S, Class H, Helmig R, Nowak W. A concept for data-driven probabilistic risk assessment and application to carbon dioxide storage in geological formations. Advances in Water Resources. 2011;34:1508–18.
    11. Oladyshkin S, Class H, Helmig R, Nowak W. Bayesian updating on arbitrary polynomial chaos expansion: application to carbon dioxide storage in geological formations. In Poitiers, France: Invited lecture: Pprime CNRS, CEAT; 2011.
    12. Enzenhöfer R, Nowak W. Quantitative Aggregierung von Einzelrisiken zum Gesamtrisiko für Brunneneinzugsgebiete. In Mannheim, Germany: F&E-Projekttreffen: W 1/01/10 Risikomanagement für Wasserschutzgebiete; 2011.
    13. Oladyshkin S, Class H, Helmig R, Nowak W. An Integrative Approach to Robust Design and Probabilistic Risk Assessment for CO$_2$ Storage in Geological Formations. Computer Geosciences. 2011;15(3):565–77.
    14. Enzenhöfer R, Nowak W. Optimal designed risk catchment management by means of proabilistic well vulnerability criteria. In Mühlheim an der Ruhr, Germany: Strategic Asset Management of Water and Wastewater Infrastructure; 2011.
    15. Cirpka OA, de Barros FPJ, Chiogna G, Nowak W. Probability Density Function of Steady-State Concentration in Two-Dimensional Heterogeneous Porous Media. Water Resources Research. 2011;47(W11523).
    16. Koch J, Nowak W, Bardossy A. Identification and simulation of contaminant source architecture. In: General Assembly 2011, Geophysical Research Abstracts 13: EGU2011-7522, 2011. Vienna, Austria: European Geosciences Union (EGU); 2011. (General Assembly 2011, Geophysical Research Abstracts 13: EGU2011-7522, 2011).
    17. Oladyshkin S, Class H, Helmig R, Nowak W. Data-driven framework for history matching: application to carbon dioxide storage in geological formations. In: General Assembly 2011, Geophysical Research Abstracts 13: EGU2011-11137, 2011. Vienna, Austria: European Geosciences Union (EGU); 2011. (General Assembly 2011, Geophysical Research Abstracts 13: EGU2011-11137, 2011).
    18. Enzenhöfer R, Geiges A, Nowak W, Helmig R. Optimal risk management support in actively managed well catchments by means of probabilistic vulnerability criteria. In Stuttgart, Germany: SimTech 2011 - International Conference on Simulation Technology 2011; 2011.
    19. Enzenhöfer R, Nowak W, Helmig R. Risk management with probabilistic advective-dispersive well vulnerability criteria. In: General Assembly 2011, Geophysical Research Abstracts 13: EGU2011-7822, 2011. Vienna, Austria: European Geosciences Union (EGU); 2011. (General Assembly 2011, Geophysical Research Abstracts 13: EGU2011-7822, 2011).
    20. Leube P, Nowak W, Schneider G. Temporal Moments revisited: Why there is there no better way for physically-based model reduction in time. In: Fall Meeting 2011, Abstract: H23D-1314. San Francisco, CA, USA: American Geophysical Union (AGU); 2011. (Fall Meeting 2011, Abstract: H23D-1314).
    21. Enzenhöfer R, Nowak W. Risikomanagement im Grundwasserschutzgebiet - ein präventives probabilistisches Trinkwasserschutzkonzept. Stuttgart; 2011.
    22. Enzenhöfer R, Nowak W. Rational risk-based decision support for drinking water well managers by optimized monitoring designs. In: Fall Meeting 2011, Abstract: H13B-1191. San Francisco, CA, USA: American Geophysical Union (AGU); 2011. (Fall Meeting 2011, Abstract: H13B-1191).
    23. Leube P, Nowak W. Temporal Moments revised, or is there a better way for physically-based model reduction in time? In: General Assembly 2011, Geophysical Research Abstracts 13: EGU2011-6756, 2011. Vienna, Austria: European Geosciences Union (EGU); 2011. (General Assembly 2011, Geophysical Research Abstracts 13: EGU2011-6756, 2011).
    24. de Barros FPJ, Bolster D, Sanchez-Vila X, Nowak W. A Divide and Conquer Approach to Cope with Uncertainty, Human Health Risk and Decision Making in Contaminant Hydrology. Water Resources Research. 2011;47(W05508).
    25. Nowak W, Rubin Y, de Barros FPJ. Optimizing field investigation strategies to answer research hypotheses. In: General Assembly 2011, Geophysical Research Abstracts 13: EGU2011-7582, 2011. Vienna, Austria: European Geosciences Union (EGU); 2011. (General Assembly 2011, Geophysical Research Abstracts 13: EGU2011-7582, 2011).
    26. Oladyshkin S, Class H, Helmig R, Nowak W. Modeling of underground carbon dioxide storage: data-driven robust design and probabilistic risk assessment. In Stuttgart, Germany: SimTech 2011 - International Conference on Simulation Technology 2011; 2011.
    27. Enzenhöefer R, Nowak W. Strategic Asset Management of Water and Wastewater Infrastructure. In Mühlheim an der Ruhr, Germany: nternational Water Association (IWA); 2011.
    28. Enzenhöfer R, Nowak W, Helmig R. Probabilistic exposure risk assessment with advective-dispersive well vulnerability criteria. In Freudenstadt, Germany: NUPUS annual Meeting: Institut für Wasserbau, Lehrstuhl für Hydromechanik und Hydrosystemmodellierung; 2011.
    29. Geiges A, Nowak W. A reverse engineering approach to optimal design of site investigation schemes and monitoring networks. In: General Assembly 2011, Geophysical Research Abstracts 13: EGU2011-7612, 2011. Vienna, Austria: European Geosciences Union (EGU); 2011. (General Assembly 2011, Geophysical Research Abstracts 13: EGU2011-7612, 2011).
    30. Koch J, Nowak W, Bardossy A. Contaminant source architecture (CSA) identification and simulation. In: Fall Meeting 2011, Abstract: H33J-08. San Francisco, CA, USA: American Geophysical Union (AGU); 2011. (Fall Meeting 2011, Abstract: H33J-08).
  19. 2010

    1. Troldborg M, Nowak W, Tuxen N, Bjerg PL, Helmig R, Binning PJ. Uncertainty evaluation of mass discharge estimates from a contaminated site using a fully Bayesian framework. Water Resources Research. 2010;46(12).
    2. de Barros FPJ, Nowak W. On the Link Between Contaminant Source Release Conditions and Plume Prediction Uncertainty. Journal of Contaminant Hydrology. 2010;116:24–34.
    3. Kokkinaki A, Sleep BE, Chambers JE, Cirpka OA, Nowak W. On the value of incorporating spatial statistics in large-scale geophysical inversions: the QSABRe case. In: Fall Meeting 2010, Abstract: H11E-0858. San Francisco, CA, USA: American Geophysical Union (AGU); 2010. (Fall Meeting 2010, Abstract: H11E-0858).
    4. Nowak W, de Barros FPJ, Rubin Y. Bayesian Geostatistical Design: Task-Driven Optimal Site Investigation when the Geostatistical Model is Uncertain. Water Resources Research. 2010;46(W03535).
    5. Oladyshkin S, Class H, Helmig R, Nowak W. Probabilistic risk assessment for $CO_2$ storage in geological formations: robust design and support for decision making under uncertainty. In: General Assembly 2010, Geophysical Research Abstracts 12: EGU2010-3559, 2010. Vienna, Austria: European Geosciences Union (EGU); 2010. (General Assembly 2010, Geophysical Research Abstracts 12: EGU2010-3559, 2010).
    6. Sanchez-Vila X, de Barros FPJ, Bolster D, Nowak W. Divide and Conquer: A Valid Approach for Risk Assessment and Decision Making under Uncertainty for Groundwater-Related Diseases. In: Fall Meeting 2010, Abstract: H41L-05. San Francisco, CA, USA: American Geophysical Union (AGU); 2010. (Fall Meeting 2010, Abstract: H41L-05).
    7. Nowak W, de Barros FPJ, Geiges A, Leube P. Optimal Site Investigation: What data to collect so that calibrated models have best prognistic power? In Tübingen, Germany: Invited lecture: FH-DGG Tagung 2010, Grundwasser für die Zukunft; 2010.
    8. de Barros FPJ, Nowak W. Identifying Contaminant Release Conditions to Reduce Uncertainty in Plume Spreading and Dilution in Heterogeneous Aquifers. In: Computational Methods in Water Resources (CMWR). XVIII International Conference on Water Resources; 2010. (Computational Methods in Water Resources (CMWR)).
    9. Oladyshkin S, Class H, Helmig R, Nowak W. Data-driven framework for modeling of CO$_2$ storage: probabilistic risk assessment, robust design and history matching. In Princeton, NJ, USA: Workshop: Scale of resolution, model complexity and solution approaches for CO2 storage problems; 2010.
    10. Enzenhöfer R, Nowak W, Helmig R. Quantification of Uncertainty for Transport-QBased Well Vulnerability Criteria. In Freudenstadt, Germany: NUPUS annual Meeting: Institut für Wasserbau, Lehrstuhl für Hydromechanik und Hydrosystemmodellierung; 2010.
    11. Nowak W, de Barros FPJ, Cirpka OA. Enhanced dilution and transverse mixing due to flow focusing: a stochastic-analytical approach. In: Fall Meeting 2010, Abstract: H54C-06. San Francisco, CA, USA: American Geophysical Union (AGU); 2010. (Fall Meeting 2010, Abstract: H54C-06).
    12. Enzenhöfer R, Helmig R, Nowak W, Binning PJ. Uncertainty in Model parameter Estimates and Impacts on Risk and Decision Making in the Subsurface. In: Fall Meeting 2010, Abstract: H42D-05. San Francisco, CA, USA: American Geophysical Union (AGU); 2010. (Fall Meeting 2010, Abstract: H42D-05).
    13. Oladyshkin S, Class H, Helmig R, Nowak W. Chaos expansion for uncertainty quantification of multiphase flow in CO$_2$ storage reservoirs. In Nancy, France: JEMP 2010; 2010.
    14. Nowak W, de Barros FPJ, Rubin Y. Hypothesis-driven site investigation. In Monte Veritá, Switzerland: Thirty years of stochastic subsurface hydrology: Where do we stand and what are the emerging challenges; 2010.
    15. Nowak W. Measures of Parameter Uncertainty in Geostatistical Estimation and Geostatistical Optimal Design. Mathematical Geosciences. 2010;42(2):199–221.
    16. Enzenhöfer R, Nowak W, Helmig R. Using probabilistic well vulnerability criteria for a risk-based preventive drinking water safety concept. In: Schirmer M, Hoehn E, Vogt T, Herausgeber. Conceptual and Modelling Studies of Integrated Groundwater, Surface Water, and Ecological Systems. Zurich, Switzerland: IAHS Press; 2010. S. (Schirmer M, Hoehn E, Vogt T, Reihenherausgeber. Conceptual and Modelling Studies of Integrated Groundwater, Surface Water, and Ecological Systems; Bd. 342).
    17. Oladyshkin S, Class H, Hofmann R, Nowak W. Highly efficient tool for probabilistic risk assessment of CCS joint with injection design. In Barcelone, Spain: XVIII. International Conference on Computational Methods in Water Resources (CMWR); 2010.
    18. Oladyshkin S, Class H, Helmig R, Nowak W. Data-driven robust design and probabilistic risk assessment: application to underground carbon dioxide storage. In: Fall Meeting 2010, Abstract: H41L-03. San Francisco, CA, USA: American Geophysical Union (AGU); 2010. (Fall Meeting 2010, Abstract: H41L-03).
    19. Troldborg M, Nowak W, Binning PJ, Løgstrup PB, Helmig R. Uncertainty estimation of the mass discharge from a contaminated site using a fully Bayesian framework. In: Schirmer M, Hoehn E, Vogt T, Herausgeber. Seventh International Groundwater Quality Conference: Groundwater Quality Management in a Rapidly Changing World (GQ10). Zurich, Switzerland: IAHS Press; 2010. S. (Schirmer M, Hoehn E, Vogt T, Reihenherausgeber. Seventh International Groundwater Quality Conference: Groundwater Quality Management in a Rapidly Changing World (GQ10); Bd. 342).
    20. Rubin Y, Nowak W, de Barros FPJ. A Task-oriented Approach for Hydrogeological Site Characterization. In: Fall Meeting 2010, Abstract: H41L-06. San Francisco, CA, USA: American Geophysical Union (AGU); 2010. (Fall Meeting 2010, Abstract: H41L-06).
    21. Nowak W. Challenges and demands from the application side: An example from CO$_2$ injection into the subsurface. In Stuttgart, Germany: Workshop: Numerical Analysis of Stochastic PDEs (NASPDE); 2010.
    22. Oladyshkin S, Class H, Helmig R, Nowak W, de Barros FPJ, Ashraf M. Data-driven polynomial response surfaces as efficient tool for applied tasks under uncertainty. In Research Triangle Park, NC, USA: SAMSI Geosciences Applications Opening Workshop; 2010.
    23. Leube P, Geiges A, Nowak W. A flexible Bayesian assessment for the expected impact of data on prediction confidence for optimal sampling designs. In: General Assembly 2010, Geophysical Research Abstracts 12: EGU2010-12375, 2010. Vienna, Austria: European Geosciences Union (EGU); 2010. (General Assembly 2010, Geophysical Research Abstracts 12: EGU2010-12375, 2010).
  20. 2009

    1. Enzenhöfer R, Helmig R, Nowak W, Binning PJ. Risk assessment in fractured porous media with particular reference to water catchments. In: General Assembly 2009, Geophysical Research Abstracts 11: EGU2009-10661-1, 2009. Vienna, Austria: European Geosciences Union (EGU); 2009. (General Assembly 2009, Geophysical Research Abstracts 11: EGU2009-10661-1, 2009).
    2. Nowak W, de Barros FPJ, Rubin Y. Bayesian Geostatistical Design: Optimal Site Investigation When the Geostatistical Model is Uncertain. In: General Assembly 2009, Geophysical Research Abstracts 11: EGU2009-45565, 2009. Vienna, Austria: European Geosciences Union (EGU); 2009. (General Assembly 2009, Geophysical Research Abstracts 11: EGU2009-45565, 2009).
    3. Nowak W. Best unbiased ensemble linearization and the Quasi-Linear Kalman Ensemble Generator. Water Resources Research. 2009;45(W04431).
    4. Nowak W. Stochastic Simulation and Bayesian Principles, with Examples from Stochastic Hydrogeology. In Stuttgart, Germany: ASIM-Workshop: Grundlagen und Methoden der Modellbildung und Simulation; 2009.
    5. Troldborg M, Nowak W, Tuxen N, Bjerg PL, Helmig R, Binning P. Quantifying uncertainty in mass discharge estimates from contaminated sites using a fully Bayesian framework. ModelCARE: Calibration and Reliability in Groundwater Modeling - Managing Groundwater and the Environment (20 - 23 September 2009, Wuhan, China) China University of Geosciences, 9/2009. 2009;
    6. Oladyshkin S, Nowak W, Helmig R. Joint design and probabilistic risk assessment for CO$_2$ storage by integral probabilistic collocation method. In Stuttgart, Germany: International conference on Non-linearities and Upscaling in Porous Media (NUPUS); 2009.
    7. Fritz J, Nowak W, Neuweiler I. Application of FFT-based Algorithms for Large-Scale Universal Kriging Problems. Mathematical Geosciences. 2009;51(5):199–221.
    8. de Barros FPJ, Nowak W, Rubin Y. Uncertainty of human health risk predictions under different site exploration strategies. In: Fall Meeting 2009, Abstract: H13B-0934. San Francisco, CA, USA: American Geophysical Union (AGU); 2009. (Fall Meeting 2009, Abstract: H13B-0934).
    9. Nowak W. Using Ensemble Kalman Filters for Bayesian Geostatistical Inversion. In: Fall Meeting 2009, Abstract: H53N-02. San Francisco, CA, USA: American Geophysical Union (AGU); 2009. (Fall Meeting 2009, Abstract: H53N-02).
    10. Nowak W. Uncertainty analysis in hydrometry: parameter and prediction uncertainty in subsequent modelling. In Vancouver, Canada: 33rd IAHR Congress: Water Engineering for a Sustainable Environment; 2009.
  21. 2008

    1. Schwede RL., Cirpka OA, Nowak W, Neuweiler I. Impact of sampling volume on the probability density function of steady state concentration. Water Resources Research. 2008;44(W12433).
    2. Nowak W, Schwede RL, Cirpka OA, Neuweiler I. Probability density functions of hydraulic head and velocity in three-dimensional heterogeneous porous media. Water Resources Research. 2008;44(W08452).
    3. Nowak W. A hypothesis-driven approach to site investigation. In: Fall Meeting 2008, Abstract: H53F-1485. San Francisco, CA, USA: American Geophysical Union (AGU); 2008. (Fall Meeting 2008, Abstract: H53F-1485).
    4. Vasin M, Lehmann P, Kaestner A, Hassanein R, Nowak W, Neuweiler I. Drainage in Heterogeneous Sand Columns with Different Geometric Structures. Advances in Water Resources. 2008;31(9):1205–20.
    5. Fienen M, Hunt RJ, Clemo T, Nowak W, Doherty J. Implementation of a bayesian geostatistical parameter estimation module into PEST. In Orange Beach, AL, USA: USGS Modeling Conference; 2008.
  22. 2007

    1. Neuweiler I, Nowak W. Relation Between Connected Patterns in Heterogeneous Soil Parameter Fields and Solute Transport Models in the Unsaturated Zone. In: Fall Meeting 2007, Abstract: H34E-02. San Francisco, CA, USA: American Geophysical Union (AGU); 2007. (Fall Meeting 2007, Abstract: H34E-02).
    2. Schwede RL, Nowak W, Cirpka OA. Impact of Sampling Volume on the Probability Density Function of Steady-State Concentration. In: Fall Meeting 2007, Abstract: H14C-02. San Francisco, CA, USA: American Geophysical Union (AGU); 2007. (Fall Meeting 2007, Abstract: H14C-02).
    3. Nowak W, Schwede RL, Cirpka OA, Neuweiler I. Probability Density Functions of Hydraulic Head and Velocity in Three-Dimensional Heterogeneous Porous Media. In: Fall Meeting 2007, Abstract: H23G-1691. San Francisco, CA, USA: American Geophysical Union (AGU); 2007. (Fall Meeting 2007, Abstract: H23G-1691).
  23. 2006

    1. Nowak W, Cirpka OA. Geostatistical Inference of Hydraulic Conductivity and Dispersivities from Hydraulic Heads and Tracer Data. Water Resources Research. 2006;42(W08416).
  24. 2005

    1. Li W, Nowak W, Cirpka OA. Geostatistical inverse modeling of transient pumping tests using temporal moments of drawdown. Water Resources Research. 2005;41(W08403).
    2. Nowak W. Geostatistical Methods for the Identification of Flow and Transport Parameters in Subsurface Flow [Internet] [Doctoral dissertation]. Universität Stuttgart; 2005. Verfügbar unter: https://elib.uni-stuttgart.de/handle/11682/218
    3. Cirpka OA, Nowak W, Bürger CM. Linearized uncertainty propagation, geostatistical inversing, and data-worth analysis in heterogeneous aquifers. In: General Assembly 2005, Geophysical Research Abstracts 7: 01539, 2005. Vienna, Austria: European Geosciences Union (EGU); 2005. (General Assembly 2005, Geophysical Research Abstracts 7: 01539, 2005).
    4. Li W, Nowak W, Cirpka OA. Geostatistical inversing of transient pumping tests using temporal moments of drawdown. In: General Assembly 2005, Geophysical Research Abstracts 7: 02215, 2005. Vienna, Austria: European Geosciences Union (EGU); 2005. (General Assembly 2005, Geophysical Research Abstracts 7: 02215, 2005).
    5. Nowak W, Cirpka OA. Geostatistical Inversion of Conductivity and Dispersivities for Hydraulic Heads and Tracer Data from a Sandbox Experiment. In: Fall Meeting 2005, Abstract: H21G-03. San Francisco, CA, USA: American Geophysical Union (AGU); 2005. (Fall Meeting 2005, Abstract: H21G-03).
    6. Rahman MA, Jose SC, Nowak W, Cirpka OA. Experiments on vertical transverse mixing in a large-scale heterogeneous model aquifer. Journal of Contaminant Hydrology. 2005;80(3):130–48.
  25. 2004

    1. Cirpka OA, Bürger CM, Nowak W, Finkel M. Uncertainty and data worth analysis for the hydraulic design of funnel-and-gate systems in heterogeneous aquifers. Water Resources Research. 2004;40(W11502).
    2. Cirpka OA, Nowak W. First-order variance of travel time in non-stationary formations. Water Resources Research. 2004;40(W03507).
    3. Cirpka OA, Nowak W, Jose SC. Effective Dispersion in Heterogeneous Media: Comparison between Experiments, Inverse Modeling, and First-Order Theory. In: Fall Meeting 2004, Abstract: H13H-06. San Francisco, CA, USA: American Geophysical Union (AGU); 2004. (Fall Meeting 2004, Abstract: H13H-06).
    4. Nowak W, Cirpka OA. A modified Levenberg-Marquardt Algorithm for Quasi-linear Geostatistical Inversing. Advances in Water Resources. 2004;27(7):737–50.
  26. 2003

    1. Cirpka OA, Nowak W. First-order variance of solute travel time in non-stationary media. In: Fall Meeting 2003, Abstract: H11G-0920. San Francisco, CA, USA: American Geophysical Union (AGU); 2003. (Fall Meeting 2003, Abstract: H11G-0920).
    2. Cirpka OA, Nowak W. Dispersion on kriged hydraulic conductivity fields. Water Resources Research. 2003;39(2):1027.
    3. Nowak W, Cirpka OA. Efficient computational methods for iterative cokriging. In: World Water and Environmental Resources Congress (WWER) 2003: Groundwater Quality Modeling an Management Under Uncertainty. Philadelphia, PA, USA: ASCE; 2003. S. 112–21. (World Water and Environmental Resources Congress (WWER) 2003: Groundwater Quality Modeling an Management Under Uncertainty).
    4. Nowak W, Tenkleve S, Cirpka OA. Efficient computation of linearized cross-covariance and auto-covariance matrices of interdependent quantities. Mathematical Geology. 2003;35(1):53–66.
  27. 2002

    1. Cirpka OA, Nowak W. Influence of Geostatistical Interpolation of Log-Hydraulic Conductivity on Dispersion and Mixing. In: Bridging the Gap between Measurement and Modeling in Heterogeneous Media. Lawrence Berkeley Laboratory, University of California, Berkeley, CA. USA: International Groundwater Symposium; 2002. (Bridging the Gap between Measurement and Modeling in Heterogeneous Media).
  28. 2000

    1. Nowak W. Age determination of a TCE source zone using solute transport profiles in an underlying clayey aquitard. 2000.

10/1994 - 06/2000 Umweltschutztechnik (Dipl.-Ing.), Universität Stuttgart
10/1998 - 06/2000 Water Resources Engineering and Management (M.Sc.), Universität Stuttgart
07/1999 - 06/2000 Wissenschaftlicher Mitarbeiter, University of Waterloo, Kanada
10/2000 - 11/2004
PhD, Bau- und Umweltingenieurwesen, Universität Stuttgart 
03/2001 - 06/2001
Visiting Researcher, Stanford University, USA
11/2004 - 08/2007
PostDoc, Universität Stuttgart
09/2008
PostDoc, University California at Berkeley, USA
09/2008 - 08/2014
Junior Professor, Institut für Wasser- und Umweltsystemmodellierung, Universität Stuttgart
Seit 09/2014
Professor und Leiter der Abteilung Stochastische Simulation und Sicherheitsforschung für Hydrosysteme, Institut für Wasser- und Umweltsystemmodellierung, Universität Stuttgart
Seit 11/2021 Sprecher des Exzellenzclusters Data-Integrated Simulation Science, Universität Stuttgart

Zum Seitenanfang