Articles | Volume 24, issue 6
https://doi.org/10.5194/hess-24-2895-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-24-2895-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Jun 2020
Research article |
| 03 Jun 2020
| 03 Jun 2020
On the shape of forward transit time distributions in low-order catchments
Department of Hydrogeology, Helmholtz Centre for Environmental
Research – UFZ, 04318 Leipzig, Germany
Department of Hydrogeology, Helmholtz Centre for Environmental
Research – UFZ, 04318 Leipzig, Germany
Andreas Musolff
Department of Hydrogeology, Helmholtz Centre for Environmental
Research – UFZ, 04318 Leipzig, Germany
Peter Troch
Department of Hydrology and Atmospheric Sciences, University of
Arizona, Tucson, 85721, USA
Ty Ferré
Department of Hydrology and Atmospheric Sciences, University of
Arizona, Tucson, 85721, USA
Jan H. Fleckenstein
Department of Hydrogeology, Helmholtz Centre for Environmental
Research – UFZ, 04318 Leipzig, Germany
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Cited
14 citations as recorded by crossref.
- On the interplay between hillslope and drainage network flow dynamics in the catchment travel time distribution A. Zarlenga et al. https://doi.org/10.1002/hyp.14530
- Consistent Modeling of Transport Processes and Travel Times—Coupling Soil Hydrologic Processes With StorAge Selection Functions R. Schwemmle & M. Weiler https://doi.org/10.1029/2023WR034441
- Nitrate Transport and Retention in Western European Catchments Are Shaped by Hydroclimate and Subsurface Properties S. Ehrhardt et al. https://doi.org/10.1029/2020WR029469
- Uncertainty in water transit time estimation with StorAge Selection functions and tracer data interpolation A. Borriero et al. https://doi.org/10.5194/hess-27-2989-2023
- Can the young water fraction reduce predictive uncertainty in water transit time estimations? A. Borriero et al. https://doi.org/10.1016/j.jhydrol.2024.132238
- Modeling Nitrate Export From a Mesoscale Catchment Using StorAge Selection Functions T. Nguyen et al. https://doi.org/10.1029/2020WR028490
- Identifying Baseflow Source Areas Using Remotely Sensed and Ground‐Based Hydrologic Data and Models A. Ahamed et al. https://doi.org/10.1002/hyp.70322
- Key controls on water transit times along a tropical precipitation gradient F. Quichimbo-Miguitama et al. https://doi.org/10.1016/j.jhydrol.2024.132134
- How catchment characteristics influence hydrological pathways and travel times in a boreal landscape E. Jutebring Sterte et al. https://doi.org/10.5194/hess-25-2133-2021
- Spatial aggregation effects on the performance of machine learning metamodels for predicting transit time to baseflow M. Soriano Jr & R. Maxwell https://doi.org/10.1088/2515-7620/ad0744
- Reduction of vegetation-accessible water storage capacity after deforestation affects catchment travel time distributions and increases young water fractions in a headwater catchment M. Hrachowitz et al. https://doi.org/10.5194/hess-25-4887-2021
- Effect of topographic slope on the export of nitrate in humid catchments: a 3D model study J. Yang et al. https://doi.org/10.5194/hess-26-5051-2022
- Groundwater flow paths drive longitudinal patterns of stream dissolved organic carbon (DOC) concentrations in boreal landscapes A. Lupon et al. https://doi.org/10.5194/hess-27-613-2023
- The value of instream stable water isotope and nitrate concentration data for calibrating a travel time‐based water quality model A. Borriero et al. https://doi.org/10.1002/hyp.15154
14 citations as recorded by crossref.
- On the interplay between hillslope and drainage network flow dynamics in the catchment travel time distribution A. Zarlenga et al. https://doi.org/10.1002/hyp.14530
- Consistent Modeling of Transport Processes and Travel Times—Coupling Soil Hydrologic Processes With StorAge Selection Functions R. Schwemmle & M. Weiler https://doi.org/10.1029/2023WR034441
- Nitrate Transport and Retention in Western European Catchments Are Shaped by Hydroclimate and Subsurface Properties S. Ehrhardt et al. https://doi.org/10.1029/2020WR029469
- Uncertainty in water transit time estimation with StorAge Selection functions and tracer data interpolation A. Borriero et al. https://doi.org/10.5194/hess-27-2989-2023
- Can the young water fraction reduce predictive uncertainty in water transit time estimations? A. Borriero et al. https://doi.org/10.1016/j.jhydrol.2024.132238
- Modeling Nitrate Export From a Mesoscale Catchment Using StorAge Selection Functions T. Nguyen et al. https://doi.org/10.1029/2020WR028490
- Identifying Baseflow Source Areas Using Remotely Sensed and Ground‐Based Hydrologic Data and Models A. Ahamed et al. https://doi.org/10.1002/hyp.70322
- Key controls on water transit times along a tropical precipitation gradient F. Quichimbo-Miguitama et al. https://doi.org/10.1016/j.jhydrol.2024.132134
- How catchment characteristics influence hydrological pathways and travel times in a boreal landscape E. Jutebring Sterte et al. https://doi.org/10.5194/hess-25-2133-2021
- Spatial aggregation effects on the performance of machine learning metamodels for predicting transit time to baseflow M. Soriano Jr & R. Maxwell https://doi.org/10.1088/2515-7620/ad0744
- Reduction of vegetation-accessible water storage capacity after deforestation affects catchment travel time distributions and increases young water fractions in a headwater catchment M. Hrachowitz et al. https://doi.org/10.5194/hess-25-4887-2021
- Effect of topographic slope on the export of nitrate in humid catchments: a 3D model study J. Yang et al. https://doi.org/10.5194/hess-26-5051-2022
- Groundwater flow paths drive longitudinal patterns of stream dissolved organic carbon (DOC) concentrations in boreal landscapes A. Lupon et al. https://doi.org/10.5194/hess-27-613-2023
- The value of instream stable water isotope and nitrate concentration data for calibrating a travel time‐based water quality model A. Borriero et al. https://doi.org/10.1002/hyp.15154
Saved (final revised paper)
Latest update: 13 Jun 2026
Short summary
With the help of a 3-D computer model we examined how long the water of different rain events stays inside small catchments before it is discharged and how the nature of this discharge is controlled by different catchment and climate properties. We found that one can only predict the discharge dynamics when taking into account a combination of catchment and climate properties (i.e., there was not one single most important predictor). Our results can help to manage water pollution events.
With the help of a 3-D computer model we examined how long the water of different rain events...
