Articles | Volume 26, issue 13
https://doi.org/10.5194/hess-26-3393-2022
© Author(s) 2022. 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-26-3393-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Jul 2022
Research article |
| 05 Jul 2022
| 05 Jul 2022
Diel streamflow cycles suggest more sensitive snowmelt-driven streamflow to climate change than land surface modeling does
Department of Natural Resources and Environmental Science, University of Nevada, Reno, Nevada 89557, USA
Global Water Center, University of Nevada, Reno, Nevada 89557, USA
Water Resources Department, Faculty of Agricultural Engineering,
University of Concepción, Chillán 3780000, Chile
Lucia Scaff
Global Water Futures, Canada First Research Excellence Fund (CFREF), University of Saskatchewan, Saskatoon, SK S7N 3H5, Canada
James W. Kirchner
Department of Environmental Systems Science, ETH Zurich, 8092
Zurich, Switzerland
Mountain Hydrology Research Unit, Swiss Federal Research Institute WSL, 8903 Birmensdorf, Switzerland
Beatrice Gordon
Department of Natural Resources and Environmental Science, University of Nevada, Reno, Nevada 89557, USA
Gary Sterle
Global Water Center, University of Nevada, Reno, Nevada 89557, USA
Adrian Harpold
Department of Natural Resources and Environmental Science, University of Nevada, Reno, Nevada 89557, USA
Global Water Center, University of Nevada, Reno, Nevada 89557, USA
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Gary Sterle, Julia Perdrial, Dustin W. Kincaid, Kristen L. Underwood, Donna M. Rizzo, Ijaz Ul Haq, Li Li, Byung Suk Lee, Thomas Adler, Hang Wen, Helena Middleton, and Adrian A. Harpold
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Nikos Theodoratos and James W. Kirchner
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Short summary
We present a new way to detect snowmelt using daily cycles in streamflow driven by solar radiation. Results show that warmer sites have earlier and more intermittent snowmelt than colder sites, and the timing of early snowmelt events is strongly correlated with the timing of streamflow volume. A space-for-time substitution shows greater sensitivity of streamflow timing to climate change in colder rather than in warmer places, which is then contrasted with land surface simulations.
We present a new way to detect snowmelt using daily cycles in streamflow driven by solar...
