Articles | Volume 16, issue 14
Model description paper
19 Jul 2023
Model description paper |  | 19 Jul 2023

An empirical model to calculate snow depth from daily snow water equivalent: SWE2HS 1.0

Johannes Aschauer, Adrien Michel, Tobias Jonas, and Christoph Marty

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Cited articles

Aili, T., Soncini, A., Bianchi, A., Diolaiuti, G., D'Agata, C., and Bocchiola, D.: Assessing water resources under climate change in high-altitude catchments: a methodology and an application in the Italian Alps, Theor. Appl. Climatol., 135, 135–156,, 2019. a
Akaike, H.: Information Theory and an Extension of the Maximum Likelihood Principle, Springer New York, New York, NY,, 199–213, 1998. a
Anderson, E. A.: A point energy and mass balance model of a snow cover, NOAA Technical Report NWS 19, Office of Hydrology, National Weather Service, Silver Spring, Maryland, 1976. a, b, c, d
Aschauer, J.: swe2hs Python package, Zenodo [code],, 2022. a, b
Aschauer, J.: Code to recreate figures in Aschauer, J., Michel, A., Jonas, T., and Marty, C. (2023), Zenodo [code],, 2023a. a
Short summary
Snow water equivalent is the mass of water stored in a snowpack. Based on exponential settling functions, the empirical snow density model SWE2HS is presented to convert time series of daily snow water equivalent into snow depth. The model has been calibrated with data from Switzerland and validated with independent data from the European Alps. A reference implementation of SWE2HS is available as a Python package.