About Me

Group Leader in Hydrological Modeling

RESEARCH INTERESTS

Fabrizio Fenicia works on hydrology and water quality modeling at the catchment scale. His research interests include:

• Flexible hydrological models to facilitate the model building process
• Hybrid hydrological models combining machine learning and process based models
  
• Approaches that guide model building and selection
• Advancing the understanding and prediction of catchment scale hydrological behavior
• Water quality modeling including isotopes or pesticides concentrations in streams
• Assessing modeling uncertainties
  

ONLINE RESOURCES

• SuperflexPy, an open-source Python framework for constructing conceptual hydrological models for lumped and semi-distributed applications SuperflexPy.
  

TEACHING ACTIVITIES

• Short course on “Principles of catchment-scale hydrological models”. The course is organized every year together with Prof. Dmitri Kavetski, and it includes lectures, exercises and fieldwork activities that cover the fundamental principles of horological modelling. The main focus is on conceptual hydrological models, including numerical methods, calibration, uncertainty, flexible models, semi-distributed models. The fieldwork activity includes visiting experimental catchments that are modeled in the exercises. The course is currently suspended due to Covid restrictions.
• Guest lecture at TU-Delft within the "hydrological modelling" course. The guest lecture focuses on flexible hydrological models and normally takes place once a year.

EDITORIAL ACTIVITIES

Editor of the "Hydrology and Earth System Sciences" journal

Gao, H., F. Fenicia, and H. H. G. Savenije (2023), HESS Opinions: Are soils overrated in hydrology?, Hydrol. Earth Syst. Sci., 27(14), 2607-2620, doi: 10.5194/hess-27-2607-2023.

Höge, M., et al. (2023), CAMELS-CH: hydro-meteorological time series and landscape attributes for 331 catchments in hydrologic Switzerland, Earth Syst. Sci. Data, 15(12), 5755-5784, doi:10.5194/essd-15-5755-2023.

Shen, C., et al. (2023), Differentiable modelling to unify machine learning and physical models for geosciences, Nature Reviews Earth & Environment, 4(8), 552-567, doi: 10.1038/s43017-023-00450-9.

Dal Molin, M., D. Kavetski, C. Albert, and F. Fenicia (2023), Exploring Signature-Based Model Calibration for Streamflow Prediction in Ungauged Basins, Water Resour Res, 59(7), e2022WR031929, doi: https://doi.org/10.1029/2022WR031929.

Chow, R., S. Spycher, R. Scheidegger, T. Doppler, A. Dietzel, F. Fenicia, and C. Stamm (2023), Methods comparison for detecting trends in herbicide monitoring time-series in streams, Sci Total Environ, 891, 164226, doi: https://doi.org/10.1016/j.scitotenv.2023.164226.

Fabre, C., T. Doppler, R. Chow, F. Fenicia, R. Scheidegger, A. Dietzel, and C. Stamm (2023), Challenges of spatially extrapolating aquatic pesticide pollution for policy evaluation, Sci Total Environ, 875, 162639, doi: https://doi.org/10.1016/j.scitotenv.2023.162639.

Prieto, C., N. Le Vine, D. Kavetski, F. Fenicia, A. Scheidegger, and C. Vitolo (2022), An Exploration of Bayesian Identification of Dominant Hydrological Mechanisms in Ungauged Catchments, Water Resour Res, 58(3), e2021WR030705, doi: https://doi.org/10.1029/2021WR030705.

Höge, M., A. Scheidegger, M. Baity-Jesi, C. Albert, and F. Fenicia (2022), Improving hydrologic models for predictions and process understanding using neural ODEs, Hydrol. Earth Syst. Sci., 26(19), 5085-5102, doi: 10.5194/hess-26-5085-2022.

Zhang, X., H. Yang, W. Zhang, F. Fenicia, H. Peng, and G. Xu (2022), Hydrologic impacts of cascading reservoirs in the middle and lower Hanjiang River basin under climate variability and land use change, Journal of Hydrology: Regional Studies, 44, 101253, doi: https://doi.org/10.1016/j.ejrh.2022.101253.

Gao, H., C. Han, R. Chen, Z. Feng, K. Wang, F. Fenicia, and H. Savenije (2022), Frozen soil hydrological modeling for a mountainous catchment northeast of the Qinghai–Tibet Plateau, Hydrol. Earth Syst. Sci., 26(15), 4187-4208, doi: 10.5194/hess-26-4187-2022.

Fenicia, F., and J. J. McDonnell (2022), Modeling streamflow variability at the regional scale: (1) perceptual model development through signature analysis, J Hydrol, 605, 127287, doi: https://doi.org/10.1016/j.jhydrol.2021.127287.

Fenicia, F., D. Meißner, and J. J. McDonnell (2022), Modeling streamflow variability at the regional scale: (2) Development of a bespoke distributed conceptual model, J Hydrol, 605, 127286, doi: https://doi.org/10.1016/j.jhydrol.2021.127286.

David, P. C., P. L. B. Chaffe, V. B. P. Chagas, M. Dal Molin, D. Y. Oliveira, A. H. F. Klein, and F. Fenicia (2022), Correspondence Between Model Structures and Hydrological Signatures: A Large-Sample Case Study Using 508 Brazilian Catchments, Water Resour Res, 58(3), e2021WR030619, doi: https://doi.org/10.1029/2021WR030619.

Bacci, M., M. Dal Molin, F. Fenicia, P. Reichert, and J. Šukys (2022), Application of stochastic time dependent parameters to improve the characterization of uncertainty in conceptual hydrological models, J Hydrol, 612, 128057, doi: https://doi.org/10.1016/j.jhydrol.2022.128057.

Fenicia, F., and D. Kavetski (2021), Behind every robust result is a robust method: Perspectives from a case study and publication process in hydrological modelling, Hydrological Processes, 35(8), e14266, doi:10.1002/hyp.14266.

Fenicia, F., and D. Kavetski (2021), Behind every robust result is a robust method: Perspectives from a case study and publication process in hydrological modelling, Hydrological Processes, 35(8), e14266, doi: https://doi.org/10.1002/hyp.14266.

Ammann, L., C. Stamm, F. Fenicia, and P. Reichert (2021), Quantifying the Uncertainty of a Conceptual Herbicide Transport Model With Time-Dependent, Stochastic Parameters, Water Resources Research, 57(8), e2020WR028311, doi:10.1029/2020WR028311.

Bouaziz, L. J. E., F. Fenicia, . . . M. Hrachowitz (2021), Behind the scenes of streamflow model performance, Hydrology and Earth System Sciences, 25(2), 1069-1095, doi:10.5194/hess-25-1069-2021.

Dal Molin, M., D. Kavetski, and F. Fenicia (2021), SuperflexPy 1.2.0: an open source Python framework for building, testing and improving conceptual hydrological models, Geosci. Model Dev., 2020, 1-39, doi:10.5194/gmd-2020-409.

Gharari, S., H. V. Gupta, M. P. Clark, M. Hrachowitz, F. Fenicia, P. Matgen, and H. H. G. Savenije (2021), Understanding the Information Content in the Hierarchy of Model Development Decisions: Learning From Data, Water Resources Research, 57(6), e2020WR027948, doi:10.1029/2020WR027948.

Lee, J., F. Ju, A. Maile-Moskowitz, K. Beck, A. Maccagnan, C. S. McArdell, M. Dal Molin, F. Fenicia, . . . H. Bürgmann (2021). Unraveling the riverine antibiotic resistome: The downstream fate of anthropogenic inputs. Water Research, 197, 117050, doi:10.1016/j.watres.2021.117050.

McDonnell, J. J., C. Gabrielli, A. Ameli, J. Ekanayake, F. Fenicia, J. Freer, . . . R. Woods (2021), The Maimai M8 experimental catchment database: Forty years of process-based research on steep, wet hillslopes, Hydrological Processes, 35(5), e14112, doi:10.1002/hyp.14112.

Reichert, P., L. Ammann, and F. Fenicia (2021), Potential and Challenges of Investigating Intrinsic Uncertainty of Hydrological Models With Stochastic, Time-Dependent Parameters, Water Resources Research, 57(3), e2020WR028400, doi:10.1029/2020WR028400.

Ammann, L., T. Doppler, C. Stamm, P. Reichert, and F. Fenicia (2020), Characterizing fast herbicide transport in a small agricultural catchment with conceptual models, J Hydrol, 586, 124812, doi:10.1016/j.jhydrol.2020.124812.

Chow, R., R. Scheidegger, T. Doppler, A. Dietzel, F. Fenicia and C. Stamm (2020), A review of long-term pesticide monitoring studies to assess surface water quality trends, Water Research X, 9, 100064, doi:10.1016/j.wroa.2020.100064.

Dal Molin, M., M. Schirmer, M. Zappa, and F. Fenicia (2020), Understanding dominant controls on streamflow spatial variability to set up a semi-distributed hydrological model: the case study of the Thur catchment, Hydrology and Earth System Sciences, 24(3), 1319-1345, doi:10.5194/hess-24-1319-2020.

Ammann, L., F. Fenicia, and P. Reichert (2019), A likelihood framework for deterministic hydrological models and the importance of non-stationary autocorrelation, Hydrology and Earth System Sciences, 23(4), 2147-2172, doi:10.5194/hess-23-2147-2019.

Fenicia, F., D. Kavetski, P. Reichert, and C. Albert (2018), Signature-Domain Calibration of Hydrological Models Using Approximate Bayesian Computation: Empirical Analysis of Fundamental Properties, Water Resources Research, 54(6), 3958-3987, doi:10.1002/2017WR021616.

Kavetski, D., F. Fenicia, P. Reichert, and C. Albert (2018), Signature-Domain Calibration of Hydrological Models Using Approximate Bayesian Computation: Theory and Comparison to Existing Applications, Water Resources Research, 54(6), 4059-4083, doi:10.1002/2017WR020528.

Moser, A., D. Wemyss, R. Scheidegger, F. Fenicia, M. Honti, and C. Stamm (2018), Modelling biocide and herbicide concentrations in catchments of the Rhine basin, Hydrology and Earth System Sciences, 22(8), 4229-4249, doi:10.5194/hess-22-4229-2018.

Scaini, A., C. Hissler, F. Fenicia, J. Juilleret, J. F. Iffly, L. Pfister, and K. Beven (2018), Hillslope response to sprinkling and natural rainfall using velocity and celerity estimates in a slate-bedrock catchment, Journal of Hydrology, 558, 366-379, doi:10.1016/j.jhydrol.2017.12.011.

Scaini, A., M. Audebert, C. Hissler, F. Fenicia, L. Gourdol, L. Pfister, and K. J. Beven (2017), Velocity and celerity dynamics at plot scale inferred from artificial tracing experiments and time-lapse ERT, Journal of Hydrology, 546, 28-43, doi:10.1016/j.jhydrol.2016.12.035.

de Boer-Euser, T., L. Bouaziz, J. De Niel, C. Brauer, B. Dewals, G. Drogue, F. Fenicia, B. Grelier, J. Nossent, F. Pereira, H. Savenije, G. Thirel, and P. Willems (2017), Looking beyond general metrics for model comparison – lessons from an international model intercomparison study, Hydrology and Earth System Sciences, 21(1), doi:10.5194/hess-21-423-2017.

Fenicia, F., D. Kavetski, H. H. G. Savenije, and L. Pfister (2016), From spatially variable streamflow to distributed hydrological models: Analysis of key modeling decisions, Water Resources Research(52), 1-36,  doi:10.1002/2015WR017398.

Gao, H. K., M. Hrachowitz, N. Sriwongsitanon, F. Fenicia, S. Gharari, and H. H. G. Savenije (2016), Accounting for the influence of vegetation and landscape improves model transferability in a tropical savannah region, Water Resources Research, 52(10), 7999-8022, doi:10.1002/2016WR019574.

Ley, R., H. Hellebrand, M. C. Casper, and F. Fenicia (2016), Comparing classical performance measures with signature indices derived from flow duration curves to assess model structures as tools for catchment classification, Hydrology Research, 47(1), 1-14, doi:10.2166/nh.2015.221.

Wrede, S., F. Fenicia, N. Martínez-Carreras, J. Juilleret, C. Hissler, A. Krein, H. H. G. Savenije, S. Uhlenbrook, D. Kavetski, and L. Pfister (2015), Towards more systematic perceptual model development: a case study using 3 Luxembourgish catchments, Hydrological Processes, 29(12), 2731-2750, 10.1002/hyp.10393.

Gao, H., M. Hrachowitz, S. J. Schymanski, F. Fenicia, N. Sriwongsitanon, and H. H. G. Savenije (2014), Climate controls how ecosystems size the root zone storage capacity at catchment scale, Geophysical Research Letters, 41(22), 2014GL061668, doi:10.1002/2014GL061668.

Gao, H., M. Hrachowitz, F. Fenicia, S. Gharari, and H. H. G. Savenije (2014), Testing the realism of a topography-driven model (FLEX-Topo) in the nested catchments of the Upper Heihe, China, Hydrology and Earth System Sciences, 18(5), 1895-1915, doi:10.5194/hess-18-1895-2014.

Gharari, S., M. Hrachowitz, F. Fenicia, H. Gao, and H. H. G. Savenije (2014), Using expert knowledge to increase realism in environmental system models can dramatically reduce the need for calibration, Hydrology and Earth System Sciences, 18(12), 4839-4859,  10.5194/hess-18-4839-2014.

Gharari, S., M. Shafiei, M. Hrachowitz, R. Kumar, F. Fenicia, H. V. Gupta, and H. H. G. Savenije (2014), A constraint-based search algorithm for parameter identification of environmental models, Hydrology and Earth System Sciences, 18(12), 4861-4870, 10.5194/hess-18-4861-2014.

Euser, T., H. C. Winsemius, M. Hrachowitz, F. Fenicia, S. Uhlenbrook, and H. H. G. Savenije (2013), A framework to assess the realism of model structures using hydrological signatures, Hydrology and Earth System Sciences, 17(5), 1893-1912, 10.5194/hess-17-1893-2013.

Gharari, S., M. Hrachowitz, F. Fenicia, and H. H. G. Savenije (2013), An approach to identify time consistent model parameters: sub-period calibration, Hydrology and Earth System Sciences, 17(1), 149-161, 10.5194/hess-17-149-2013.

Hrachowitz, M., et al. (2013), A decade of Predictions in Ungauged Basins (PUB)a review, Hydrological Sciences Journal-Journal Des Sciences Hydrologiques, 58(6), 1198-1255, 10.1080/02626667.2013.803183.

Kayastha, N., J. Ye, F. Fenicia, V. uzmin, and D. P. Solomatine (2013), Fuzzy committees of specialized rainfall-runoff models: further enhancements and tests, Hydrology and Earth System Sciences, 17(11), 4441-4451, 10.5194/hess-17-4441-2013.

van Esse, W. R., C. Perrin, M. J. Booij, D. C. M. Augustijn, F. Fenicia, D. Kavetski, and F. Lobligeois (2013), The influence of conceptual model structure on model performance: a comparative study for 237 French catchments, Hydrology and Earth System Sciences, 17(10), 4227-4239, 10.5194/hess-17-4227-2013.

Clark, M. P., D. Kavetski, and F. Fenicia (2012), Reply to comment by K. Beven et al. on "Pursuing the method of multiple working hypotheses for hydrological modeling", Water Resources Research, 48, W11802, 10.1029/2012wr012547.

Fenicia, F., L. Pfister, D. Kavetski, P. Matgen, J. F. Iffly, L. Hoffmann, and R. Uijlenhoet (2012), Microwave links for rainfall estimation in an urban environment: Insights from an experimental setup in Luxembourg-City, Journal of Hydrology, 464, 69-78, 10.1016/j.jhydrol.2012.06.047.

Matgen, P., F. Fenicia, S. Heitz, D. Plaza, R. de Keyser, V. R. N. Pauwels, W. Wagner, and H. Savenije (2012), Can ASCAT-derived soil wetness indices reduce predictive uncertainty in well-gauged areas? A comparison with in situ observed soil moisture in an assimilation application, Advances in Water Resources, 44, 49-65, 10.1016/j.advwatres.2012.03.022.

Clark, M. P., D. Kavetski, and F. Fenicia (2011), Pursuing the method of multiple working hypotheses for hydrological modeling, Water Resources Research, 47(9), W09301, 10.1029/2010wr009827.

Fenicia, F., D. Kavetski, and H. H. G. Savenije (2011), Elements of a flexible approach for conceptual hydrological modeling: 1. Motivation and theoretical development, Water Resources Research, 47(11), W11510, 10.1029/2010wr010174.

Kavetski, D., and F. Fenicia (2011), Elements of a flexible approach for conceptual hydrological modeling: 2. Application and experimental insights, Water Resources Research, 47(11), W11511, 10.1029/2011wr010748.

Gharari, S., F. Fenicia, M. Hrachowitz, and H. H. G. Savenije (2011), Land classification based on hydrological landscape units, Hydrology and Earth System Sciences Discussion, 8, 4381–4425,  10.5194/hess-15-3275-2011.

Hellebrand, H., C. Muller, P. Matgen, F. Fenicia, and H. Savenije (2011), A process proof test for model concepts: Modelling the meso-scale, Physics and Chemistry of the Earth, 36(1-4), 42-53, 10.1016/j.pce.2010.07.019.

Kavetski, D., F. Fenicia, and M. P. Clark (2011), Impact of temporal data resolution on parameter inference and model identification in conceptual hydrological modeling: Insights from an experimental catchment, Water Resources Research, 47(5), W05501, 10.1029/2010WR009525.

Fenicia, F., S. Wrede, D. Kavetski, L. Pfister, L. Hoffmann, H. H. G. Savenije, and J. J. McDonnell (2010), Assessing the impact of mixing assumptions on the estimation of streamwater mean residence time, Hydrological Processes, 24(12), 1730-1741, 10.1002/Hyp.7595.

Schoups, G., J. A. Vrugt, F. Fenicia, and N. C. V. de Giesen (2010), Corruption of accuracy and efficiency of Markov chain Monte Carlo simulation by inaccurate numerical implementation of conceptual hydrologic models, Water Resources Research, 46, W10530, 10.1029/2009wr008648.

Fenicia, F., H. H. G. Savenije, and Y. Avdeeva (2009), Anomaly in the rainfall-runoff behaviour of the Meuse catchment. Climate, land-use, or land-use management? Hydrology and Earth System Sciences, 13(9), 1727-1737, 10.5194/hess-13-1727-2009.

Pfister, L., J. J. McDonnell, S. Wrede, D. Hlubikova, P. Matgen, F. Fenicia, L. Ector, and L. Hoffmann (2009), The rivers are alive: on the potential for diatoms as a tracer of water source and hydrological connectivity, Hydrological Processes, 23(19), 2841-2845, 10.1002/Hyp.7426.

Fenicia, F., J. J. McDonnell, and H. H. G. Savenije (2008), Learning from model improvement: On the contribution of complementary data to process understanding, Water Resources Research, 44(6), W06419, 10.1029/2007wr006386.

Fenicia, F., H. H. G. Savenije, and H. C. Winsemius (2008), Moving from model calibration towards process understanding, Physics and Chemistry of the Earth, 33(17-18), 1057-1060, 10.1016/j.pce.2008.06.008.

Fenicia, F., H. H. G. Savenije, P. Matgen, and L. Pfister (2008), Understanding catchment behavior through stepwise model concept improvement, Water Resources Research, 44(1), W01402, 10.1029/2006wr005563.

Fenicia, F., H. H. G. Savenije, P. Matgen, and L. Pfister (2007), A comparison of alternative multiobjective calibration strategies for hydrological modeling, Water Resources Research, 43(3), W03434, 10.1029/2006wr005098.

Fenicia, F., D. P. Solomatine, H. H. G. Savenije, and P. Matgen (2007), Soft combination of local models in a multi-objective framework, Hydrology and Earth System Sciences, 11(6), 1797-1809, 10.5194/hess-11-1797-2007.

Fenicia, F., H. H. G. Savenije, P. Matgen, and L. Pfister (2006), Is the groundwater reservoir linear? Learning from data in hydrological modelling, Hydrology and Earth System Sciences, 10(1), 139-150, 10.5194/hess-10-139-2006.

Fenicia, F., G. P. Zhang, T. Rientjes, L. Hoffmann, L. Pfister, and H. H. G. Savenije (2005), Numerical simulations of runoff generation with surface water-groundwater interactions in the Alzette river alluvial plain (Luxembourg), Physics and Chemistry of the Earth, 30(4-5), 277-284 10.1016/j.pce.2004.11.001.

Zhang, G. P., H. H. G. Savenije, F. Fenicia, and L. Pfister (2006), Modelling subsurface storm flow with the Representative Elementary Watershed (REW) approach: application to the Alzette River Basin, Hydrology and Earth System Sciences, 10(6), 937-955, 10.5194/hess-10-937-2006.

Zhang, G. P., F. Fenicia, T. H. M. Rientjes, P. Reggiani, and H. H. G. Savenije (2005), Modeling runoff generation in the Geer river basin with improved model parameterizations to the REW approach, Physics and Chemistry of the Earth, 30(4-5), 285-296, 10.1016/j.pce.2004.11.002.

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Projects

Hypothesis testing using controlled experiments to characterize diffuse pollution in small agricultural catchments

Herbicide transport modelling

Flexible framework for conceptual hydrological modeling.

SUPERFLEX

Calibrating stochastic rainfall-runoff models to scaling laws, for improved predictions of extreme events.

New hydrological signatures from scaling laws in rainfall and runoff time seriesn und Abflusszeitreihen

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