Articles | Volume 25, issue 5
Research article
27 May 2021
Research article |  | 27 May 2021

The evaluation of the potential of global data products for snow hydrological modelling in ungauged high-alpine catchments

Michael Weber, Franziska Koch, Matthias Bernhardt, and Karsten Schulz

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Cited articles

Abimbola, O. P., Wenninger, J., Venneker, R., and Mittelstet, A. R.: The assessment of water resources in ungauged catchments in Rwanda, J. Hydrol.: Reg. Stud., 13, 274–289,, 2017. a, b
Abrams, M. and Crippen, R.: ASTER GDEM V3 (Aster Global DEM): User Guide, available at: (last access: 25 March 2021), 2019. a
Adams, M. S., Bühler, Y., and Fromm, R.: Multitemporal Accuracy and Precision Assessment of Unmanned Aerial System Photogrammetry for Slope-Scale Snow Depth Maps in Alpine Terrain, Pure Appl. Geophys., 175, 3303–3324,, 2018. a
Arkin, P., Xie, P., and National Center for Atmospheric Research Staff: The Climate Data Guide: CMAP: CPC Merged Analysis of Precipitation, available at:, last access: 24 December 2018. a
Bandyopadhyay, J., Rodda, J. C., Kattelmann, R., Kundzewicz, Z., and Kraemer, D.: Highland waters – a resource of global significance, in: Mountains of the World. A global priority, edited by: Messerli, B. and Ives, J. D., Parthenon Publishing, New York, Carnforth, 131–155,<197::AID-LDR390>3.0.CO;2-U, 1997. a
Short summary
We compared a suite of globally available meteorological and DEM data with in situ data for physically based snow hydrological modelling in a small high-alpine catchment. Although global meteorological data were less suited to describe the snowpack properly, transferred station data from a similar location in the vicinity and substituting single variables with global products performed well. In addition, using 30 m global DEM products as model input was useful in such complex terrain.