Articles | Volume 30, issue 3
https://doi.org/10.5194/hess-30-779-2026
https://doi.org/10.5194/hess-30-779-2026
Research article
 | 
10 Feb 2026
Research article |  | 10 Feb 2026

Uncertainty, temporal variability, and influencing factors of empirical streamflow sensitivities

Sebastian Gnann, Bailey J. Anderson, and Markus Weiler

Data sets

CAMELS: Catchment Attributes and MEteorology for Large-sample Studies A. J. Newman et al. https://doi.org/10.5065/D6MW2F4D

Catchment attributes and hydro-meteorological timeseries for 671 catchments across Great Britain (CAMELS-GB) G. Coxon et al. https://doi.org/10.5285/8344e4f3-d2ea-44f5-8afa-86d2987543a9

CAMELS-AUS v2: updated hydrometeorological timeseries and landscape attributes for an enlarged set of catchments in Australia K. Fowler et al. https://doi.org/10.5281/zenodo.14289037

CAMELS-DE: hydrometeorological time series and attributes for 1582 catchments in Germany A. Dolich et al. https://doi.org/10.5281/zenodo.13837553

Caravan - A global community dataset for large-sample hydrology F. Kratzert et al. https://doi.org/10.5281/zenodo.7944025

Model code and software

SebastianGnann/Streamflow_sensitivities: First release Sebastian Gnann https://doi.org/10.5281/zenodo.18302902

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Short summary
The extent to which streamflow varies in response to variability in precipitation and potential evaporation is essential for understanding climate change impacts on water resources. This so-called streamflow sensitivity is often estimated directly from observational data, but the robustness of these estimates remains unclear. Through systematic examination of existing approaches, we highlight uncertainties inherent in all approaches and discuss their origins.
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