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  • (-) Eawag Authors = Dal Molin, Marco
  • (-) Journal ≠ Water Resources Research
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Application of stochastic time dependent parameters to improve the characterization of uncertainty in conceptual hydrological models
Bacci, M., Dal Molin, M., Fenicia, F., Reichert, P., & Šukys, J. (2022). Application of stochastic time dependent parameters to improve the characterization of uncertainty in conceptual hydrological models. Journal of Hydrology, 612, 128057 (19 pp.). https://doi.org/10.1016/j.jhydrol.2022.128057
SuperflexPy 1.3.0: an open-source Python framework for building, testing, and improving conceptual hydrological models
Dal Molin, M., Kavetski, D., & Fenicia, F. (2021). SuperflexPy 1.3.0: an open-source Python framework for building, testing, and improving conceptual hydrological models. Geoscientific Model Development, 14(11), 7047-7072. https://doi.org/10.5194/gmd-14-7047-2021
Unraveling the riverine antibiotic resistome: the downstream fate of anthropogenic inputs
Lee, J., Ju, F., Maile-Moskowitz, A., Beck, K., Maccagnan, A., McArdell, C. S., … Bürgmann, H. (2021). Unraveling the riverine antibiotic resistome: the downstream fate of anthropogenic inputs. Water Research, 197, 117050 (12 pp.). https://doi.org/10.1016/j.watres.2021.117050
Understanding dominant controls on streamflow spatial variability to set up a semi-distributed hydrological model: the case study of the Thur catchment
Dal Molin, M., Schirmer, M., Zappa, M., & Fenicia, F. (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. https://doi.org/10.5194/hess-24-1319-2020