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Water 2019, 11(2), 301;

Modelling Snowmelt in Ungauged Catchments

Institute for Hydrology and Water Management (HyWa), University of Natural Resources and Life Sciences, 1190 Vienna, Austria
Department of Civil Engineering, University of Bristol, Bristol BS8 1TR, UK
Received: 20 December 2018 / Revised: 23 January 2019 / Accepted: 29 January 2019 / Published: 11 February 2019
(This article belongs to the Special Issue Study for Ungauged Catchments—Data, Models and Uncertainties)
PDF [2283 KB, uploaded 11 February 2019]


Temperature-based snowmelt models are simple to implement and tend to give good
results in gauged basins. The situation is, however, different in ungauged basins, as the lack of
discharge data precludes the calibration of the snowmelt parameters. The main objective of this
study was therefore to assess alternative approaches. This study compares the performance of
two temperature-based snowmelt models (with and without an additional radiation term) and two
energy-balance models with different data requirements in 312 catchments in the US. It considers
the impact of: (i) the meteorological forcing, by using two gridded datasets (Livneh and MERRA-2),
(ii) different approaches for calibrating the snowmelt parameters (an a priori approach and one
based on Snow Data Assimilation System (SNODAS), a remote sensing-based product) and (iii) the
parameterization and structure of the hydrological model used for transforming the snowmelt signal
into streamflow at the basin outlet. The results show that energy-balance-based approaches achieve
the best results, closely followed by the temperature-based model including a radiation term and
calibrated with SNODAS data. It is also seen that data availability and quality influence the ranking
of the snowmelt models.
Keywords: snowmelt; day-degree approach; SNODAS; hydrological model; a priori parameter estimation; ungauged basins; model performance; data quality snowmelt; day-degree approach; SNODAS; hydrological model; a priori parameter estimation; ungauged basins; model performance; data quality
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Massmann, C. Modelling Snowmelt in Ungauged Catchments. Water 2019, 11, 301.

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