Journals

Lehrstuhl für Stochastische Simulation und Sicherheitsforschung für Hydrosysteme

  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

    1. Ahmed W, Ahmed S, Punthakey JF, Dars GH, Ejaz MS, Qureshi AL, u. a. Statistical Analysis of Climate Trends and Impacts on Groundwater Sustainability in the Lower Indus Basin. Sustainability. 2024;16(1):441.
    2. 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).
    3. Fencl M, Nebuloni R, C. M. Andersson J, Bares V, Blettner N, Cazzaniga G, u. a. Data formats and standards for opportunistic rainfall sensors. Open Research Europe. Oktober 2024;3(169).
    4. 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).
    5. 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
  3. 2023 (submitted)

    1. Hsueh HF, Guthke A, Wöhling T, Nowak W. Optimized Predictive Coverage by Averaging Time-Windowed Bayesian Distributions. Water Resources Research.
    2. 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.
    3. El Hachem A, Seidel J, O’Hara T, Villalobos Herrera R, Overeem A, Uijlenhoet R, u. a. Technical note: Overview and comparison of three quality control algorithms for rainfall data from personal weather stations. Hydrology and Earth System Sciences Discussions [Internet]. 2023:1--22. Verfügbar unter: https://hess.copernicus.org/preprints/hess-2023-195/
  4. 2023

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Bürger R, Chowell G, Kröker I, Lara-Díaz LY. A computational approach to identifiability analysis for a model of the propagation and control of COVID-19 in Chile. Journal of Biological Dynamics. 2023;17(1):2256774.
    7. Kröker I, Oladyshkin S, Rybak I. Global sensitivity analysis using multi-resolution polynomial chaos expansion for coupled Stokes-Darcy flow problems. Computational Geosciences [Internet]. 2023; Verfügbar unter: https://rdcu.be/dhL31
    8. Bárdossy A, Seidel J, Anwar F. Interdependenz von extremen Hochwasserabflüssen. Hydrologie und Wasserbewirtschaftung [Internet]. Oktober 2023;67(5). Verfügbar unter: http://doi.bafg.de/HyWa/2023/HyWa_2023.5_5.pdf
    9. 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
    10. Mohammadi F, Eggenweiler E, Flemisch B, Oladyshkin S, Rybak I, Schneider M, u. a. A surrogate-assisted uncertainty-aware Bayesian validation framework and its application to coupling free flow and porous-medium flow. Computational Geosciences. Juli 2023;27(4):663--686.
    11. Hermann F, Michalowski A, Brünnette T, Reimann P, Vogt S, Graf T. Data-Driven Prediction and Uncertainty Quantification of Process Parameters for Directed Energy Deposition. Materials [Internet]. November 2023;16(23). Verfügbar unter: https://www.mdpi.com/1996-1944/16/23/7308
    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. Regev S, Carmel Y, Gal G, Schlabing D. Climate Change Impact on Sub-Tropical Lakes Ecosystem – Lake Kinneret as a Case Study. November 2023;Science of The Total Environment. Verfügbar unter: http://dx.doi.org/10.1016/j.scitotenv.2024.171163
    14. 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.
    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. 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
    17. 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.
  5. 2022

    1. Kröker I, Oladyshkin S. Arbitrary Multi-Resolution Multi-Wavelet-based Polynomial Chaos Expansion for Data-Driven Uncertainty Quantification. Reliability Engineering & System Safety. 2022;222:108376.
    2. 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.
    3. 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.
    4. 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.
    5. Motschmann A, Teutsch C, Huggel C, Seidel J, León CD, Muñoz R, u. a. Current and future water balance for coupled human-natural systems – Insights from a glacierized catchment in Peru. Journal of Hydrology: Regional Studies [Internet]. Juni 2022;41:101063. Verfügbar unter: https://doi.org/10.1016%2Fj.ejrh.2022.101063
    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. 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.
    8. 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.
    9. Xiao S, Nowak W. Reliability sensitivity analysis based on a two-stage Markov chain Monte Carlo simulation. Aerospace Science and Technology. 2022;130:107938.
    10. Mouris K, Schwindt S, Haun S, Morales Oreamuno MF, Wieprecht S. Introducing seasonal snow memory into the RUSLE. Journal of Soils and Sediments. März 2022;22(5):1609--1628.
    11. 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.
    12. 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.
    13. 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).
    14. 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.
  6. 2021 (submitted)

    1. 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.
  7. 2021

    1. Xiao M, Junne T, Haas J, Klein M. Plummeting costs of renewables - Are energy scenarios lagging? Energy Strategy Reviews [Internet]. Mai 2021;35:100636. Verfügbar unter: https://www.sciencedirect.com/science/article/pii/S2211467X21000225
    2. Cao KK, Pregger T, Haas J, Lens H. To Prevent or Promote Grid Expansion? Analyzing the Future Role of Power Transmission in the European Energy System. Frontiers in Energy Research [Internet]. Februar 2021;8. Verfügbar unter: https://www.frontiersin.org/articles/10.3389/fenrg.2020.541495/full
    3. Manjunath S, Yeligeti M, Fyta M, Haas J, Gils HC. Impact of COVID-19 on electricity demand: Deriving minimum states of system health for studies on resilience. Data. 2021;6(76).
    4. Haas J, Prieto L, Ghorbani N, Breyer C. Revisiting the potential of pumped-hydro energy storage: a method to detect economically attractive sites. Renewable Energy. 2021;
    5. 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;
    6. 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.
    7. 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.
    8. Boyle CFH, Haas J, Kern JD. Development of an irradiance-based weather derivative to hedge cloud risk for solar energy systems. Renewable Energy [Internet]. 2021;164:1230–43. Verfügbar unter: http://www.sciencedirect.com/science/article/pii/S0960148120316578
    9. 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.
    10. Bárdossy A, Seidel J, El Hachem A. The use of personal weather station observations to improve precipitation estimation and interpolation. Hydrology and Earth System Sciences [Internet]. Februar 2021;25(2):583--601. Verfügbar unter: https://hess.copernicus.org/articles/25/583/2021/
    11. 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.
    12. 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.
    13. 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.
    14. Müller T, Schüller A, Kieß T, Seidel J, Sienel J. Aufbau eines Hochwasser-, Starkregen- und Betriebspunktemonitorings im Einzugsgebiet der Echaz und in weiteren Gewässersystemen. Aufbau eines Hochwasser-, Starkregen- und Betriebspunktemonitorings im Einzugsgebiet der Echaz und in weiteren Gewässersystemen [Internet]. Juli 2021;2021(7):434–441. Verfügbar unter: https://doi.org/10.3243/kwe2021.07.004
    15. 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.
    16. 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.
    17. 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.
    18. Kiên-Cao K, Haas J, Sperber E, Sasanpour S, Sarfarazi S, Pregger T, u. a. Bridging granularity gaps to decarbonize large-scale energy systems—The case of power system planning. Energy Science & Engineering. März 2021;
    19. Lillo R, Olivares M, Haas J. Grid-wide assessment of varying re-regulation storage capacity for hydropeaking mitigation. Journal of Environmental Management [Internet]. 2021;293:112866. Verfügbar unter: https://www.sciencedirect.com/science/article/pii/S0301479721009282
    20. Graf M, Hachem AE, Eisele M, Seidel J, Chwala C, Kunstmann H, u. a. Rainfall estimates from opportunistic sensors in Germany across spatio-temporal scales. Journal of Hydrology: Regional Studies [Internet]. Oktober 2021;37:100883. Verfügbar unter: https://doi.org/10.1016%2Fj.ejrh.2021.100883
  8. 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. 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.
    3. Xiao S, Oladyshkin S, Nowak W. Reliability analysis with stratified importance sampling based on adaptive Kriging. Reliability Engineering & System Safety. 2020;197:106852.
    4. Bárdossy A, Anwar F, Seidel J. Hydrological Modelling in Data Sparse Environment: Inverse Modelling of a Historical Flood Event. Water [Internet]. November 2020;12(11):3242. Verfügbar unter: https://doi.org/10.3390%2Fw12113242
    5. Manguang G, Zhang L, Miao X, Oladyshkin S, Cheng X, Wang Y, u. a. Application of computed tomography (CT) in geologic CO_2 storage research: a critical review. Journal of Natural Gas Science and Engineering. 2020;103591.
    6. 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.
    7. 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).
    8. 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.
    9. 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.
    10. 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
    11. 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.
    12. 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).
    13. 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).
    14. Gal G, Yael G, Noam S, Moshe E, Schlabing D. Ensemble Modeling of the Impact of Climate Warming and Increased Frequency of Extreme Climatic Events on the Thermal Characteristics of a Sub-Tropical Lake. Water [Internet]. Juli 2020;12(7):1982. Verfügbar unter: http://dx.doi.org/10.3390/w12071982
  9. 2019

    1. 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.
    2. González-Nicolás A, Cihan A, Petrusak R, Zhou Q, Trautz R, Riestenberg D, u. a. Pressure management via brine extraction in geological CO2 storage: Adaptive optimization strategies under poorly characterized reservoir conditions. International Journal of Greenhouse Gas Control. 2019;83:176–85.
    3. 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.
    4. 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.
    5. Seidel J, Trachte K, Orellana-Alvear J, Figueroa R, Célleri R, Bendix J, u. a. Precipitation Characteristics at Two Locations in the Tropical Andes by Means of Vertically Pointing Micro-Rain Radar Observations. Remote Sensing [Internet]. Dezember 2019;11(24):2985. Verfügbar unter: http://dx.doi.org/10.3390/rs11242985
    6. 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.
    7. Ortiz J, Kracht W, Pamparana G, Haas J. Optimization of a SAG mill energy system: integrating rock hardness, solar irradiation, climate change and demand side management. Mathematical Geosciences. Juli 2019;
    8. 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.
    9. J. Salgado, Oladyshkin S, Osmancevic E, Janotte F. Kalibrierung von Rechennetzmodellen anhand probabilistischer Bayes‘scher Verfahren. DWGV energie wasser-praxis. 2019;2:16–21.
    10. 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.
    11. 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.
    12. Schütze M, Seidel J, Chamorro A, León C. Integrated modelling of a megacity water system – The application of a transdisciplinary approach to the Lima metropolitan area. Journal of Hydrology [Internet]. Juni 2019;573:983–993. Verfügbar unter: http://dx.doi.org/10.1016/j.jhydrol.2018.03.045
    13. 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.
    14. 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
    15. Bliefernicht J, Waongo M, Salack S, Seidel J, Laux P, Kunstmann H. Quality and Value of Seasonal Precipitation Forecasts Issued by the West African Regional Climate Outlook Forum. Journal of Applied Meteorology and Climatology [Internet]. März 2019;58(3):621–642. Verfügbar unter: http://dx.doi.org/10.1175/jamc-d-18-0066.1
    16. Tarasova L, Merz R, Kiss A, Basso S, Blöschl G, Merz B, u. a. Causative classification of river flood events. WIREs Water [Internet]. Mai 2019;6(4). Verfügbar unter: http://dx.doi.org/10.1002/wat2.1353
    17. 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.
    18. 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.
    19. 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.
    20. Wang Y, Xiao S, Lu Z. An efficient method based on Bayes’ theorem to estimate the failure-probability-based sensitivity measure. Mechanical Systems and Signal Processing. 2019;115:607–20.
    21. 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.
    22. 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;
    23. 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.
    24. 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.
    25. Auer H, Bliefernicht J, Seidel J, Kunstmann H, Demuth N. Evaluierung hochaufgelöster Ensemble-Niederschlagsvorhersagen für die Hochwasserfrühwarnung in kleinräumigen Flussgebieten am Beispiel der Starkregenperiode 2016 in Deutschland. Juni 2019; Verfügbar unter: http://doi.bafg.de/HyWa/2019/HyWa_2019.3_1.pdf
  10. 2018

    1. Wang Y, Xiao S, Lu Z. A new efficient simulation method based on Bayes’ theorem and importance sampling Markov chain simulation to estimate the failure-probability-based global sensitivity. Aerospace Science and Technology. 2018;79:364–72.
    2. Haas J, Palma-Behnke R, Valencia F, Araya P, D’iaz-Ferrán G, Telsnig T, u. a. Sunset or sunrise? Understanding the barriers and options for the massive deployment of solar technologies in Chile. Energy Policy [Internet]. Januar 2018;112:399–414. Verfügbar unter: http://linkinghub.elsevier.com/retrieve/pii/S0301421517306249
    3. Xu T, G’omez-Hernández JJ. Simultaneous identification of a contaminant source and hydraulic conductivity via the restart normal-score ensemble Kalman filter. Advances in Water Resources. 2018;112:106–23.
    4. Xiao S, Lu Z, Wang P. Global sensitivity analysis based on distance correlation for structural systems with multivariate output. Engineering Structures. 2018;167:74–83.
    5. 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
    6. 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
    7. Darscheid P, Guthke A, Ehret U. A Maximum-Entropy Method to Estimate Discrete Distributions  from Samples Ensuring Nonzero Probabilities. Entropy [Internet]. 2018;20(8). Verfügbar unter: http://www.mdpi.com/1099-4300/20/8/601
    8. 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
    9. 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
    10. 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.
    11. Praditia T, Helmig R, Hajibeygi H. Multiscale formulation for coupled flow-heat equations arising from single-phase flow in fractured geothermal reservoirs. Computational Geosciences [Internet]. Oktober 2018;22(5):1305–22. Verfügbar unter: https://doi.org/10.1007/s10596-018-9754-4
    12. 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.
    13. Rodriguez-Pretelin A, Nowak W. Integrating transient behavior as a new dimension to WHPA delineation. Advances in Water Resources. 2018;119:178–87.
    14. Xiao S, Lu Z, Wang P. Multivariate Global Sensitivity Analysis Based on Distance Components Decomposition. Risk Analysis. Dezember 2018;38(12):2703–21.
    15. Xiao S, Lu Z. Global sensitivity analysis based on Gini’s mean difference. Structural and Multidisciplinary Optimization. 2018;58(4):1523–35.
    16. Oladyshkin S, Nowak W. Incomplete statistical information limits the utility of higher-order polynomial chaos expansions. Reliability Engineering & System Safety. 2018;169:137–48.
    17. 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.
    18. Xiao S, Lu Z. Reliability analysis by combining higher-order unscented transformation and fourth-moment method. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 2018;4(1):04017034.
    19. Wang P, Lu Z, Xiao S. Variance-based sensitivity analysis with the uncertainties of the input variables and their distribution parameters. Communication in Statistics-Simulation and Computation. 2018;47(4):1103–25.
    20. Chen Z, G’omez-Hernández JJ, Xu T, Zanini A. Joint identification of contaminant source and aquifer geometry in a sandbox experiment with the restart ensemble Kalman filter. Journal of Hydrology. 2018;564:1074–84.
    21. Trachte K, Seidel J, Figueroa R, Otto M, Bendix J. Cross-Scale Precipitation Variability in a Semiarid Catchment Area on the Western Slopes of the Central Andes. Journal of Applied Meteorology and Climatology [Internet]. März 2018;57(3):675–694. Verfügbar unter: http://dx.doi.org/10.1175/jamc-d-17-0207.1
    22. Wang P, Lu Z, Zhang K, Xiao S, Yue Z. Copula-based decomposition approach for the derivative-based sensitivity of variance contributions with dependent variables. Reliability Engineering & System Safety. 2018;169:437–50.
    23. Xiao S, Lu Z, Wang P. Multivariate global sensitivity analysis for dynamic models based on energy distance. Structural and Multidisciplinary Optimization. 2018;57(1):279–91.
    24. Rahmann C, Mayol C, Haas J. Dynamic control strategy in partially-shaded photovoltaic power plants for improving the frequency of the electricity system. Journal of Cleaner Production [Internet]. 2018;202C:109–19. Verfügbar unter: https://www.sciencedirect.com/science/article/pii/S0959652618322996?via%3Dihub
    25. Sun AY, González-Nicolás A, Jeong H, Templeton TC. Metamodeling-based approach for risk assessment and cost estimation: Application to geological carbon sequestration planning. Computers & Geosciences [Internet]. 2018;113(https://doi.org/10.1016/j.cageo.2018.01.006):70–80. Verfügbar unter: https://www.sciencedirect.com/science/article/pii/S0098300417305393
    26. Bui MT, Kuzovlev VV, Zhenikov YN, Füreder L, Seidel J, Schletterer M. Water temperatures in the headwaters of the Volga River: Trend analyses, possible future changes, and implications for a pan‐European perspective. River Research and Applications [Internet]. April 2018;34(6):495–505. Verfügbar unter: http://dx.doi.org/10.1002/rra.3275
  11. 2017

    1. Carpentier D, Haas J, Olivares M, de la Fuente A. Modeling the Multi-Seasonal Link between the Hydrodynamics of a Reservoir and Its Hydropower Plant Operation. Water [Internet]. Mai 2017;9(6):367. Verfügbar unter: http://www.mdpi.com/2073-4441/9/6/367
    2. 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.
    3. Moreno-Leiva S, D’iaz-Ferrán G, Haas J, Telsnig T, D’iaz-Alvarado FA, Palma-Behnke R, u. a. Towards solar power supply for copper production in Chile: Assessment of global warming potential using a life-cycle approach. Journal of Cleaner Production [Internet]. Oktober 2017;164:242--249. Verfügbar unter: http://linkinghub.elsevier.com/retrieve/pii/S0959652617312076
    4. González-Nicolás A, Trevisan L, Illangasekare TH, Cihan A, Birkholzer JT. Enhancing capillary trapping effectiveness through proper time scheduling of injection of supercritical CO2 in heterogeneous formations. Greenhouse Gases: Science and Technology [Internet]. 2017;7(2):339–52. Verfügbar unter: http://dx.doi.org/10.1002/ghg.1646
    5. Wirtz D, Nowak W. The rocky road to universal scientific simulation frameworks. Environmental Software and Modelling. 2017;93:180–92.
    6. Xiao S, Lu Z, Qin F. Estimation of the generalized Sobol’s sensitivity index for multivariate output model using unscented transformation. Journal of Structural Engineering. 2017;143(5):06016005.
    7. Namhata A, Zhang L, Dilmore RM, Oladyshkin S, Nakles DV. Modeling Pressure Changes due to Migration of Fluids into the Above Zone Monitoring Interval of a Geologic Carbon Storage Site. International Journal of Greenhouse Gas Control. 2017;56:30–42.
    8. 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
    9. Guthke A. Defensible Model Complexity: A Call for Data-Based and Goal-Oriented Model Choice. Groundwater [Internet]. 2017;55(5). Verfügbar unter: http://dx.doi.org/10.1111/gwat.12554
    10. Bode F, Nowak W, Emmert M, Zigelli N. Optimale Grundwassermessstellennetze: Multi-kriterielle  Optimierung als Entscheidungshilfe. gwf Wasser+Abwasser. 2017;158(07–08):111–21.
    11. Trevisan L, Pini R, Cihan A, Birkholzer JT, Zhou Q, González-Nicolás A, u. a. Imaging and quantification of spreading and trapping of carbon dioxide in saline aquifers using meter-scale laboratory experiments. Water Resources Research [Internet]. 2017;53(1):485–502. Verfügbar unter: http://dx.doi.org/10.1002/2016WR019749
    12. González-Nicolás A, Baú D, Cody BM. Application of binary permeability fields for the study of CO2 leakage from geological carbon storage in saline aquifers of the Michigan Basin,. Mathematical Geosciences [Internet]. 25. Oktober 2017; Verfügbar unter: https://doi.org/10.1007/s11004-017-9706-x
    13. Agada SS, Geiger S, ElSheikh A, Oladyshkin S. Data-driven surrogates for rapid simulation and optimization of WAG injection in fractured carbonate reservoirs. Petroleum Geoscience. 2017;23(2):270–83.
    14. Emmert M, Zigelli N, Haakh F, Bode F, Nowak W. Risikobasiertes Grundwassermonitoring für Wasserschutzgebiete. energie | wasser-praxis. 2017;67(8):68–71.
    15. Xiao S, Lu Z, Xu Liyang. Multivariate sensitivity analysis based on the direction of eigen space through principal component analysis. Reliability Engineering & System Safety. 2017;165:1–10.
    16. Xiao S, Lu Z. Structural reliability sensitivity analysis based on classification of model output. Aerospace Science and Technology. 2017;71:52–61.
    17. 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
    18. Sinsbeck M, Nowak W. Sequential Design of Computer Experiments for the Solution of Bayesian Inverse Problems. SIAM /ASA Journal of Uncertainty Quantification. 2017;5(1):640–64.
    19. Pamparana G, Kracht W, Haas J, D’iaz-Ferrán G, Palma-Behnke R, Román R. Integrating photovoltaic solar energy and a battery energy storage system to operate a semi-autogenous grinding mill. Journal of Cleaner Production [Internet]. November 2017;165:273–80. Verfügbar unter: http://linkinghub.elsevier.com/retrieve/pii/S0959652617315536
    20. Bartels J, Bliefernicht J, Seidel J, Bárdossy A, Kunstmann H, Johst M, u. a. Bewertung von Ensemble-Abflussvorhersagen für die operationelle Hochwasserwarnung. Hydrologie und Wasserbewirtschaftung, im Druck. Juni 2017;
    21. Cihan A, Birkholzer JT, Trevisan L, González-Nicolás A, Illangasekare T. Investigation of representing hysteresis in macroscopic models of two-phase flow in porous media using intermediate scale experimental data. Water Resources Research [Internet]. 2017;53(1):199–221. Verfügbar unter: http://dx.doi.org/10.1002/2016WR019449
    22. Wang P, Lu Z, Xiao S. A generalized separation for the variance contributions of input variables and their distribution parameters. Applied Mathematical Modelling. 2017;47:381–99.
    23. Schäfer Rodrigues Silva A, Noack M, Schlabing D, Wieprecht S. A data-driven fuzzy approach to simulate the critical shear stress of mixed cohesive/non-cohesive sediments. Journal of Soils and Sediments [Internet]. November 2017;18(10):3070–3081. Verfügbar unter: http://dx.doi.org/10.1007/s11368-017-1860-8
  12. 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. Seidel J, Ketzler G, Bechtel B. Mobile measurement techniques for local and micro-scale studies in urban and topo-climatology. DIE ERDE – Journal of the Geographical Society of Berlin [Internet]. März 2016;(1):15–39. Verfügbar unter: https://doi.org/10.12854/erde-147-2
    5. Xiao S, Lu Z. Structural reliability analysis using combined space partition technique and unscented transformation. Journal of Structural Engineering. 2016;142(11):04016089.
    6. Schulte DO, Rühaak W, Oladyshkin S, Welsch B, Sass I. Optimization of Medium Deep Borehole Thermal Energy Storages. Energy Technology. 2016;(4):104–13.
    7. Wöhling T, Geiges A, Nowak W. Optimal design of multi-type groundwater monitoring networks using easily accessible tools. Groundwater. 2016;54(6):861–70.
    8. Namhata A, Oladyshkin S, Dilmore RM, Zhang L, Nakles DV. Probabilistic Assessment of Above Zone Pressure Predictions at a Geologic Carbon Storage Site. Scientific Reports. 2016;6:39536.
    9. Xu T, G’omez-Hernández JJ. Characterization of non-Gaussian conductivities and porosities with hydraulic heads, solute concentrations, and water temperatures. Water Resources Research. 2016;52(8):6111–36.
    10. 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.
    11. Zhang Y, Liu Y, Pau G, Oladyshkin S, Finsterle S. Evaluation of multiple reduced-order models to enhance confidence in global sensitivity analyses. International Journal of Greenhouse Gas Control. 2016;49:217–26.
    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. Xu T, G’omez-Hernández JJ. Joint identification of contaminant source location, initial release time, and initial solute concentration in an aquifer via ensemble Kalman filtering. Water Resources Research. 2016;52(8):6587–95.
    15. Nowak W, Guthke A. Entropy-based experimental design for optimal model discrimination in the geosciences. Entropy. 2016;18(11):409.
    16. 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.
    17. Xiao S, Lu Z, Xu Liyang. A new effective screening design for structural sensitivity analysis of failure probability with the epistemic uncertainty. Reliability Engineering & System Safety. 2016;156:1–14.
  13. 2015

    1. Xu T, G’omez-Hernández JJ. Inverse sequential simulation: Performance and implementation details. Advances in water resources. 2015;86:311–26.
    2. Xu T, G’omez-Hernández JJ. Inverse sequential simulation: A new approach for the characterization of hydraulic conductivities demonstrated on a non-Gaussian field. Water Resources Research. 2015;51(4):2227–42.
    3. Wöhling T, Schöniger A, Gayler S, Nowak W. Bayesian model averaging to explore the worth of data for soil-plant model selection and prediction. Water Resources Research. 2015;51(4):2825–46.
    4. Baú D, Cody BM, González-Nicolás A. An iterative global pressure solution for the semi-analytical simulation of geological carbon sequestration. Computational Geosciences. 2015;19(4):781–9.
    5. 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.
    6. 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.
    7. Cody BM, Baú D, González-Nicolás A. Stochastic injection-strategy optimization for the preliminary assessment of candidate geological storage sites. Hydrogeology Journal. 2015;23(6):1229–45.
    8. González-Nicolás A, Baú D, Cody BM, Alzraiee A. Stochastic and global sensitivity analyses of uncertain parameters affecting the safety of geological carbon storage in saline aquifers of the Michigan Basin. International Journal of Greenhouse Gas Control. 2015;37:99–114.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. González-Nicolás A, Baú D, Alzraiee A. Detection of potential leakage pathways from geological carbon storage by fluid pressure data assimilation. Advances in Water Resources. 2015;86:366–84.
    14. 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.
    15. Drenkhan F, Carey M, Huggel C, Seidel J, Oré MT. The changing water cycle: climatic and socioeconomic drivers of water‐related changes in the Andes of Peru. WIREs Water [Internet]. September 2015;2(6):715–733. Verfügbar unter: http://dx.doi.org/10.1002/wat2.1105
    16. Beck F, Bárdossy A, Seidel J, Müller T, Fernandez Sanchis E, Hauser A. Statistical analysis of sub-daily precipitation extremes in Singapore. Journal of Hydrology: Regional Studies [Internet]. März 2015;3:337–358. Verfügbar unter: http://dx.doi.org/10.1016/j.ejrh.2015.02.001
    17. Xu T, G’omez-Hernández JJ. Probability fields revisited in the context of ensemble Kalman filtering. Journal of Hydrology. 2015;531:40–52.
    18. 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.
    19. 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.
    20. Sinsbeck M, Tartakovsky D. Impact of data assimilation on cost-accuracy tradeoff in multifidelity models. SIAM/ASA Journal of Uncertainty Quantification. 2015;3(1):954–68.
  14. 2014

    1. 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.
    2. 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.
    3. Pfaff T, Engelbrecht A, Seidel J. Detection of the bright band with a vertically pointing k-band radar. Meteorologische Zeitschrift [Internet]. Dezember 2014;23(5):527–534. Verfügbar unter: http://dx.doi.org/10.1127/metz/2014/0605
    4. Bürger R, Kröker I, Rohde C. A hybrid stochastic Galerkin method for uncertainty quantification  applied to a conservation law modelling a clarifier-thickener unit. ZAMM Z Angew Math Mech [Internet]. 2014;94(10):793–817. Verfügbar unter: http://dx.doi.org/10.1002/zamm.201200174
    5. 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.
    6. Karajan N, Otto D, Oladyshkin S, Ehlers M. Application of the polynomial chaos expansion to approximate the homogenised response of the intervertebral disc. Biomechanics and modeling in mechanobiology. 2014;13(5):1065–80.
    7. Enzenhöfer R, Bunk T, Nowak W. Nine steps to risk-informed wellhead protection and management: A case study. Groundwater. 2014;52:161–74.
  15. 2013

    1. 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.
    2. 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.
    3. 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.
    4. Xu T, G’omez-Hernández JJ, Li L, Zhou H. Parallelized ensemble Kalman filter for hydraulic conductivity characterization. Computers & geosciences. 2013;52:42–9.
    5. 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.
    6. 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.
    7. Oladyshkin S, Schröder P, Class H, Nowak W. Chaos Expansion based Bootstrap Filter to Calibrate CO2 Injection Models. Energy Procedia. 2013;40:398–407.
    8. Xu T, G’omez-Hernández JJ, Zhou H, Li L. The power of transient piezometric head data in inverse modeling: An application of the localized normal-score EnKF with covariance inflation in a heterogenous bimodal hydraulic conductivity field. Advances in water resources. 2013;54:100–18.
    9. 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.
    10. 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.
  16. 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. Nowak W, Rubin Y, de Barros FPJ. A hypothesis-driven approach to optimal site investigation. Water Resources Research. 2012;48(W06509).
    3. Oladyshkin S, Panfilov M. Open thermodynamic model for compressible multicomponent two-phase flow in porous media. Journal of Petroleum Science and Engineering. 2012;81:41–8.
    4. Walter L, Binning PJ, Oladyshkin S, Flemisch B, Class H. Brine migration resulting from CO$_2$ injection into saline aquifers - An approach to risk estimation including various levels of uncertainty. International Journal of Greenhouse Gas Control. 2012;9:495–506.
    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. 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/
    7. Oladyshkin S, Nowak W. Data-driven uncertainty quantification using the arbitrary polynomial chaos expansion. Reliability Engineering and System Safety. 2012;106:179–90.
    8. de Barros FPJ, Dentz M, Koch J, Nowak W. Flow topology and scalar mixing in heterogeneous porous media. Geophysical Research Letters. 2012;39(L08404).
    9. 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.
    10. 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.
    11. 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.
    12. Enzenhöfer R, Nowak W, Helmig R. Probabilistic Exposure Risk Assessment with Advective-Dispersive Well Vulnerability Criteria. Advances in Water Resources. 2012;36:121–32.
    13. 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).
    14. 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).
  17. 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. 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.
    3. 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.
    4. Oladyshkin S, Panfilov M. Hydrogen penetration in water through porous medium: application to a radioactive waste storage site. Environmental Earth Sciences. 2011;64(4):989–99.
    5. 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).
    6. 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).
    7. Cirpka OA, de Barros FPJ, Chiogna G, Nowak W. Probability Density Function of Steady-State Concentration in Two-Dimensional    Heterogeneous Porous Media. Water Resour Res. 2011;47(W11523).
    8. 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).
    9. Cheng T, Wang Q, Ji X, Huang L, Xu T. Parallel computing method for groundwater flow simulation in porous media. Jisuanji Gongcheng yu Yingyong(Computer Engineering and Applications). 2011;47(20):234–7.
    10. Walter L, Oladyshkin S, Class H, Darcis M, Helmig R. A study on pressure evolution in a channel system during CO$_2$ injection. Energy Procedia. 2011;4:3722–9.
  18. 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. 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).
    4. Nowak W. Measures of Parameter Uncertainty in Geostatistical Estimation and Geostatistical Optimal Design. Mathematical Geosciences. 2010;42(2):199–221.
  19. 2009

    1. Nowak W. Best unbiased ensemble linearization and the Quasi-Linear Kalman Ensemble Generator. Water Resources Research. 2009;45(W04431).
    2. 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;
    3. Seidel J, Imbery F, Dostal P, Sudhaus D, Bürger K. Potential of historical meteorological and hydrological data for the  reconstruction of historical flood events – the example of the 1882 flood in  southwest Germany. Natural Hazards and Earth System Sciences [Internet]. Februar 2009;9(1):175–183. Verfügbar unter: http://dx.doi.org/10.5194/nhess-9-175-2009
    4. Fritz J, Nowak W, Neuweiler I. Application of FFT-based Algorithms for Large-Scale Universal Kriging Problems. Mathematical Geosciences. 2009;51(5):199–221.
  20. 2008

    1. Oladyshkin S, Royer JJ, Panfilov M. Effective solution through the streamline technique and HT-splitting for the $3$D dynamic analysis of the compositional flows in oil reservoirs. Transport in Porous Media. 2008;74(3):311–29.
    2. Sudhaus D, Seidel J, Bürger K, Dostal P, Imbery F, Mayer H, u. a. Discharges of past flood events based on historical river profiles. Hydrology and Earth System Sciences [Internet]. Oktober 2008;12(5):1201–1209. Verfügbar unter: http://dx.doi.org/10.5194/hess-12-1201-2008
    3. 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).
    4. 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).
    5. 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.
  21. 2007

    1. Oladyshkin S, Panfilov M. Limit thermodynamic model for compositional gas-liquid systems moving in a porous medium. Transport in Porous Media. 2007;70(2):147–65.
    2. Oladyshkin S, Skachkov S, Panfilova I, Panfilov M. Upscaling fractured media and streamline HT-splitting in compositional reservoir simulation. Oil & Gas Science and Technology. 2007;62(2):137–46.
    3. Hoffmann T, Erkens G, Cohen KM, Houben P, Seidel J, Dikau R. Holocene floodplain sediment storage and hillslope erosion within the Rhine catchment. The Holocene [Internet]. Januar 2007;17(1):105–118. Verfügbar unter: http://dx.doi.org/10.1177/0959683607073287
    4. Oladyshkin S, Panfilov M. Streamline splitting between thermodynamics and hydrodynamics in compositional gas-liquid flow through porous media. Comptes rendus de l’Academie des sciences Mecanique. 2007;335(1):7–12.
    5. Seidel J, Mäckel R. Holocene sediment budgets in two river catchments in the Southern Upper Rhine Valley, Germany. Geomorphology [Internet]. Dezember 2007;92(3–4):198–207. Verfügbar unter: http://dx.doi.org/10.1016/j.geomorph.2006.07.041
  22. 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).
    2. Bürger K, Dostal P, Seidel J, Imbery F, Barriendos M, Mayer H, u. a. Hydrometeorological reconstruction of the 1824 flood event in the Neckar River basin (southwest Germany). Hydrological Sciences Journal [Internet]. Oktober 2006;51(5):864--877. Verfügbar unter: https://doi.org/10.1623%2Fhysj.51.5.864
  23. 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. S. Oladyshkin MP. Modeling of two-phase macroflow with phase transitions and contract properties. Transactions of the Russian Academy of Engineering Sciences. 2005;5:34–6.
    3. 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.
  24. 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. Nowak W, Cirpka OA. A modified Levenberg-Marquardt Algorithm for Quasi-linear Geostatistical Inversing. Advances in Water Resources. 2004;27(7):737–50.
  25. 2003

    1. Cirpka OA, Nowak W. Dispersion on kriged hydraulic conductivity fields. Water Resources Research. 2003;39(2):1027.
    2. 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.
    3. S. Oladyshkin, N.N. Bobkov YuPG, Kozyrev OR. Invariant immersing method applied to the problem to thermocapillary convection a viscous fluid in the plane channel. Transactions of the Russian Academy of Engineering Sciences Ser Applied Mathematics and Mechanics. 2003;4:26–31.
  26. 2002

    1. S. Oladyshkin, N.N. Bobkov YuPG, Kozyrev OR. Modeling of temperature and velocity field inside viscous fluid of finite thermoconductivity, moving inside a corner with free surface, under the action of Marangoni forces. Transactions of the Russian Academy of Engineering Sciences Ser Applied Mathematics and Mechanics. 2002;79–88.
  27. 2001

    1. S. Oladyshkin, N.N. Bobkov YuPG, Kozyrev OR. The numerical algorithm development in the problem of thermocapillary convection under the Marangoni forces action. Transactions of the Russian Academy of Engineering Sciences. 2001;2:28–39.
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